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1
Rana, Abdul Qayyum, and Mohamad Saleh. "Relationship between resting and action tremors in Parkinson’s disease." Journal of Neurosciences in Rural Practice 07, no. 02 (April 2016): 232–37. http://dx.doi.org/10.4103/0976-3147.176192.
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ABSTRACT Objective: To determine the relationship between resting tremor (RT) and action tremor (AT) in Parkinson’s disease (PD) patients. Methods: A retrospective study of RT and AT severity was conducted in 100 PD patients. The severity rating for each type of tremor in the upper extremities was assessed. The disparity in tremor severity between extremities for each tremor type was compared to that of the other two to identify commonalities in the laterality of the tremor manifestation. Results: Overall, RT is predictive of AT on the same side, but not the opposing side of the body. Patients with less intense resting right upper limb (RRU) tremor and moderately intense RRU tremor were significantly more likely to have an action right upper limb (ARU) tremor (−1.53, P = 0.020; −1.88, P = 0.005, respectively). Similarly, patients with less intense resting left upper limb (RLU) tremor and moderately intense RLU tremors were significantly more likely to have an action left upper limb (ALU) tremor (−3.49, P = 0.000; −1.86, P = 0.017, respectively). In addition, RRU and ALU tremors were associated with an increase in RLU and ARU tremors, respectively. Conclusion: Tremors are common findings in PD patients, and often impair quality of life. By identifying and classifying the relationship between resting and ATs in PD patients, our study sheds light onto the importance of better understanding and future management of this debilitating symptomology.
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Louis, Elan D. "Essential tremor: a nuanced approach to the clinical features." Practical Neurology 19, no. 5 (July 4, 2019): 389–98. http://dx.doi.org/10.1136/practneurol-2018-002183.
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Essential tremor is the most common form of tremor in humans. Given neurologists’ high exposure to this condition, and its seemingly straightforward phenotype, it might seem easy to diagnose. However, 30%–50 % of patients labelled as having ‘essential tremor’ have other diagnoses, mostly Parkinson’s disease and dystonia. The tremor of essential tremor is neither non-descript nor featureless but is multifaceted and highly patterned. This review focuses on its clinical features, beginning with a discussion of tremors and then briefly discussing its additional motor features, and presents several aids to help distinguish essential tremor from Parkinson’s disease and dystonia. Careful attention to certain clinical nuances will aid the diagnosis and care of patients with essential tremor.
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Brindha, A., K. A. Sunitha, and S. Robert Wilson. "TREMOR CLASSIFICATION USING WEARABLE IOT BASED SENSORS." IOP Conference Series: Materials Science and Engineering 1219, no. 1 (January 1, 2022): 012024. http://dx.doi.org/10.1088/1757-899x/1219/1/012024.
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Abstract Tremors, a significant symptom of movement disorder, affects a part of the body ranging from slight to severe. These Tremors are symptoms of various neurological diseases such as Parkinson’s disease (PD), Essential tremors (ET), Physiological tremors (PT), Cerebellar tremor, Dystonic tremor, Psychogenic tremor, and many more. Tremor features and types differ for various neurological disorders. During the early stages of the disease, clinical examination of tremors plays a significant role in diagnose management. This work aims to develop a wearable assistive system with an Inertial Measurement Unit (IMU) sensor to classify the tremor of three different neurological disorders based on the tremor position and frequency. This research has been carried out in SRM Medical college and Research Centre with 15 patients. The type of neurodegenerative disease of the subject with tremor is evaluated based on the tremor position and tremor frequency level. The data is collected, transmitted, and processed using the IMU sensor with Internet of things (IoT) and Node MCU board. The decision tree algorithm is used for the classification of tremors. ET, PD, and PT tremors are classified based on the tremor frequency and tremor position. A high rate of accuracy is achieved for the developed system when compared with the Neurologist results. The proposed device quantitatively classified the tremor based on the frequency and position among the three different neurological disorders, i.e., ET, PD, and PT tremors.
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Persad, A., and K. Meguro. "P.123 Normal pressure hydrocephalus with associated tremor." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 46, s1 (June 2019): S45—S46. http://dx.doi.org/10.1017/cjn.2019.215.
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Background: Normal pressure hydrocephalus is a frequent cause of cognitive and functional impairment. Many symptoms are shared between Parkinson’s disease and normal pressure hydrocephalus. Only few studies examine extrapyramidal signs in NPH, and only one case report exists describing tremor improvement with shunting. Methods: We performed a retrospective chart review of our NPH database. We selected patients who had both NPH and question of Parkinsonism due to tremor. Results: Six patients with both NPH diagnosis and tremor were identified. Three patients were treated for Parkinson’s disease and followed by neurology. After shunting, all three improved and attempt was made to wean medications, which led to functional decline. The other three patients improved with shunting and after titration of the shunt had resolution of tremor. Conclusions: We provide evidence that NPH can result in tremor, treatable by shunting. We also emphasize that those patients do exist who have both diseases. This likely exists along a continuum. Careful consideration of NPH should be undertaken in those patients with suspected Parkinson’s disease and imaging findings reminiscent of NPH.
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He, Ya-Chao, Pei Huang, Qiong-Qiong Li, Qian Sun, Dun-Hui Li, Tian Wang, Jun-Yi Shen, et al. "Mutation Analysis ofHTRA2Gene in Chinese Familial Essential Tremor and Familial Parkinson’s Disease." Parkinson's Disease 2017 (2017): 1–6. http://dx.doi.org/10.1155/2017/3217474.
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Background.HTRA2has already been nominated as PARK13 which may cause Parkinson’s disease, though there are still discrepancies among these results. Recently, Gulsuner et al.’s study found thatHTRA2p.G399S is responsible for hereditary essential tremor and homozygotes of this allele develop Parkinson’s disease by examining a six-generation family segregating essential tremor and essential tremor coexisting with Parkinson’s disease. We performed this study to validate the condition ofHTRA2gene in Chinese familial essential tremor and familial Parkinson’s disease patients, especially essential tremor.Methods. We directly sequenced all eight exons, exon-intron boundaries, and part of the introns in 101 familial essential tremor patients, 105 familial Parkinson’s disease patients, and 100 healthy controls.Results. No exonic variant was identified, while one exon-intron boundary variant (rs2241028) and one intron variant (rs2241027) were detected, both with no clinical significance and uncertain function. There was no difference in allele, genotype, and haplotype between groups.Conclusions.HTRA2exonic variant might be rare among Chinese Parkinson’s disease and essential tremor patients with family history, andHTRA2may not be the cause of familial Parkinson’s disease and essential tremor in China.
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Vivar, Guillermina, Dora-Luz Almanza-Ojeda, Irene Cheng, Juan Carlos Gomez, J. A. Andrade-Lucio, and Mario-Alberto Ibarra-Manzano. "Contrast and Homogeneity Feature Analysis for Classifying Tremor Levels in Parkinson’s Disease Patients." Sensors 19, no. 9 (May 4, 2019): 2072. http://dx.doi.org/10.3390/s19092072.
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Early detection of different levels of tremors helps to obtain a more accurate diagnosis of Parkinson’s disease and to increase the therapy options for a better quality of life for patients. This work proposes a non-invasive strategy to measure the severity of tremors with the aim of diagnosing one of the first three levels of Parkinson’s disease by the Unified Parkinson’s Disease Rating Scale (UPDRS). A tremor being an involuntary motion that mainly appears in the hands; the dataset is acquired using a leap motion controller that measures 3D coordinates of each finger and the palmar region. Texture features are computed using sum and difference of histograms (SDH) to characterize the dataset, varying the window size; however, only the most fundamental elements are used in the classification stage. A machine learning classifier provides the final classification results of the tremor level. The effectiveness of our approach is obtained by a set of performance metrics, which are also used to show a comparison between different proposed designs.
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Perez Akly, Manuel S., Carla V. Stefani, Lucía Ciancaglini, José S. Bestoso, Jorge A. Funes, Diego J. Bauso, and Cristina H. Besada. "Accuracy of nigrosome-1 detection to discriminate patients with Parkinson’s disease and essential tremor." Neuroradiology Journal 32, no. 6 (May 31, 2019): 395–400. http://dx.doi.org/10.1177/1971400919853787.
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Purpose The use of susceptibility weighted imaging in high field magnetic resonance imaging scanners can detect the nigrosome-1 area located in the caudo-lateral region of the pars compacta in the substantia nigra. This structure comprises a significant amount of dopaminergic neurons and degenerates in the early stages of Parkinson’s disease. Essential tremor is a neurological condition that in some cases could be confused with the early stages of Parkinson’s disease with a possible error in clinical diagnosis. Our purpose is to evaluate the accuracy of nigrosome-1 detection by high resolution magnetic resonance imaging to discriminate Parkinson’s disease from essential tremor. Methods A case–control study compared patients with a clinical diagnosis of Parkinson’s disease and essential tremor. Magnetic resonance imaging studies were performed using a 3T magnetic resonance imaging scanner. The susceptibility weighted imaging sequence was obtained in the axial plane with an isotropic voxel of 0.75 mm. Two independent neuroradiologists evaluated the images without access to clinical patient data. Results Sixteen patients were included in each group (Parkinson’s disease and essential tremor). Average age: Parkinson’s disease group: 71.3 (SD 6.3) and essential tremor group: 68.3 (SD 12.3). For the first evaluator, the nigrosome-1 area was absent in 15 patients with Parkinson’s disease and in two with essential tremor and for the second evaluator was absent in 15 patients with Parkinson’s disease and four with essential tremor. The sensitivity/specificity for the diagnosis of Parkinson’s disease was 93.75%/87.5% for the first evaluator and 93.75%/75% for the second evaluator. Conclusion The detection of the nigrosome-1 area is a useful tool in the differential diagnosis between Parkinson’s disease and essential tremor, with high sensitivity and specificity.
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Luft, Frauke, Sarvi Sharifi, Winfred Mugge, Alfred C. Schouten, Lo J. Bour, Anne-Fleur van Rootselaar, Peter H. Veltink, and Tijtske Heida. "A Power Spectral Density-Based Method to Detect Tremor and Tremor Intermittency in Movement Disorders." Sensors 19, no. 19 (October 4, 2019): 4301. http://dx.doi.org/10.3390/s19194301.
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There is no objective gold standard to detect tremors. This concerns not only the choice of the algorithm and sensors, but methods are often designed to detect tremors in one specific group of patients during the performance of a specific task. Therefore, the aim of this study is twofold. First, an objective quantitative method to detect tremor windows (TWs) in accelerometer and electromyography recordings is introduced. Second, the tremor stability index (TSI) is determined to indicate the advantage of detecting TWs prior to analysis. Ten Parkinson’s disease (PD) patients, ten essential tremor (ET) patients, and ten healthy controls (HC) performed a resting, postural and movement task. Data was split into 3-s windows, and the power spectral density was calculated for each window. The relative power around the peak frequency with respect to the power in the tremor band was used to classify the windows as either tremor or non-tremor. The method yielded a specificity of 96.45%, sensitivity of 84.84%, and accuracy of 90.80% of tremor detection. During tremors, significant differences were found between groups in all three parameters. The results suggest that the introduced method could be used to determine under which conditions and to which extent undiagnosed patients exhibit tremors.
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van Nuland, Annelies J., Rick C. Helmich, Michiel F. Dirkx, Heidemarie Zach, Ivan Toni, Roshan Cools, and Hanneke E. M. den Ouden. "Effects of dopamine on reinforcement learning in Parkinson’s disease depend on motor phenotype." Brain 143, no. 11 (November 2020): 3422–34. http://dx.doi.org/10.1093/brain/awaa335.
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Abstract Parkinson’s disease is clinically defined by bradykinesia, along with rigidity and tremor. However, the severity of these motor signs is greatly variable between individuals, particularly the presence or absence of tremor. This variability in tremor relates to variation in cognitive/motivational impairment, as well as the spatial distribution of neurodegeneration in the midbrain and dopamine depletion in the striatum. Here we ask whether interindividual heterogeneity in tremor symptoms could account for the puzzlingly large variability in the effects of dopaminergic medication on reinforcement learning, a fundamental cognitive function known to rely on dopamine. Given that tremor-dominant and non-tremor Parkinson’s disease patients have different dopaminergic phenotypes, we hypothesized that effects of dopaminergic medication on reinforcement learning differ between tremor-dominant and non-tremor patients. Forty-three tremor-dominant and 20 non-tremor patients with Parkinson’s disease were recruited to be tested both OFF and ON dopaminergic medication (200/50 mg levodopa-benserazide), while 22 age-matched control subjects were recruited to be tested twice OFF medication. Participants performed a reinforcement learning task designed to dissociate effects on learning rate from effects on motivational choice (i.e. the tendency to ‘Go/NoGo’ in the face of reward/threat of punishment). In non-tremor patients, dopaminergic medication improved reward-based choice, replicating previous studies. In contrast, in tremor-dominant patients, dopaminergic medication improved learning from punishment. Formal modelling showed divergent computational effects of dopaminergic medication as a function of Parkinson’s disease motor phenotype, with a modulation of motivational choice bias and learning rate in non-tremor and tremor patients, respectively. This finding establishes a novel cognitive/motivational difference between tremor and non-tremor Parkinson’s disease patients, and highlights the importance of considering motor phenotype in future work.
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Raihan, Md Zahid, and Tipu Zahed Aziz. "Deep Brain Stimulation in Sub-Thalamic Nucleus in idiopathic Parkinson’s disease – our initial experience in four cases." Bangladesh Journal of Neurosurgery 9, no. 1 (August 30, 2019): 78–83. http://dx.doi.org/10.3329/bjns.v9i1.42931.
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Parkinson’s Disease ( PD ) is a chronic neurodegenerative disease . It’s cardinal features are resting tremor, Rigidity, Akinesia and postural instability. Idiopathic Parkinson’s disease develops mainly due to degeneration of Dopaminergic neurons of Substantia Nigra. The role of Subthalamic Nucleus ( STN ) in the development of Parkinsonian Tremmor and other cardinal features is not completely understood yet. However previous studies in monkeys , administration of MPTP ( 1-methyl-4-phenyl- 1.2.3.6.-tetrahydropyridine ) proved that sub thalamic nucleus has a direct role in the development of Parkinsonian tremor and other features. We used no Micro Electrode Recording (MER) system,only studied clinically that Parkinsonian tremor stopped immediately after placement of electrode and same thing happened after micro stimulation of the sensorymotor region of the sub thalamic nucleus .Then high frequency deep brain stimulation ( DBS ) of these same four patients were assessed six months after surgery which led to a significant reduction of Parkinsonian tremor as well as other cardinal features of PD ( p< 0.001 ) . Both postural and resting tremor disappeared completely in three cases and significantly reduced in one case
Bang. J Neurosurgery 2019; 9(1): 78-83
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Cichaczewski, Ederson, Renato P. Munhoz, Joaquim M. Maia, Percy Nohama, Edison M. Nóvak, and Helio A. Teive. "Electrophysiologic characteristics of tremor in Parkinson?s disease and essential tremor." Arquivos de Neuro-Psiquiatria 72, no. 4 (April 2014): 301–6. http://dx.doi.org/10.1590/0004-282x20140006.
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Tremor in essential tremor (ET) and Parkinson’s disease (PD) usually present specific electrophysiologic profiles, however amplitude and frequency may have wide variations. Objective: To present the electrophysiologic findings in PD and ET. Method: Patients were assessed at rest, with posture and action. Seventeen patients with ET and 62 with PD were included. PD cases were clustered into three groups: predominant rest tremor; tremor with similar intensity at rest, posture and during kinetic task; and predominant kinetic tremor. Results: Patients with PD presented tremors with average frequency of 5.29±1.18 Hz at rest, 5.79±1.39 Hz with posture and 6.48±1.34 Hz with the kinetic task. Tremor in ET presented with an average frequency of 5.97±1.1 Hz at rest, 6.18±1 Hz with posture and 6.53±1.2 Hz with kinetic task. Seven (41.2%) also showed rest tremor. Conclusion: The tremor analysis alone using the methodology described here, is not sufficient to differentiate tremor in ET and PD.
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HEO, JAE-HOON, HYEONG-MIN JEON, EUI-BUM CHOI, DO-YOUNG KWON, and GWANG-MOON EOM. "EFFECT OF SENSORY ELECTRICAL STIMULATION ON RESTING TREMORS IN PATIENTS WITH PARKINSON’S DISEASE AND SWEDDs." Journal of Mechanics in Medicine and Biology 19, no. 07 (November 2019): 1940033. http://dx.doi.org/10.1142/s0219519419400335.
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Patients with scans without evidence of dopaminergic deficits (SWEDDs) show symptoms (e.g., tremors) similar to those of Parkinson’s disease (PD) patients, so they are often misdiagnosed. Sensory electrical stimulation (SES) was reported to suppress essential tremor in patients, but SES was never applied to patients with PD and SWEDDs. As the pathophysiological mechanisms of PD and SWEDDs are likely to be different, we hypothesized that the effect of SES would also be different in the two patient groups. This study aimed to test that hypothesis. Fourteen patients with PD and nine with SWEDDs participated in this study. Three wrist muscles were stimulated for 15[Formula: see text]s using SES with a stimulation intensity lower than the motor threshold. Angular motion of the index finger was measured via a triaxial gyrosensor before, during, and after stimulation. Outcome measures included the amplitude and peak frequency of the angular motion of the index finger. Tremor amplitude decreased during and after SES in patients with PD ([Formula: see text]). However, tremor amplitudes during and after SES were not different from the base level in SWEDDs patients. The peak frequency of tremors temporarily decreased during stimulation in PD patients, but not in SWEDDs patients. SES suppressed tremors in patients with PD, but not with SWEDDs. The results could help understand the pathophysiological differences of tremors between PD and SWEDDs.
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Belokoskova, Svetlana G., and Sergei G. Tsikunov. "Activation of V2 vasopressin receptors induces recovery of motor function in patients with stroke, Parkinson’s disease and parkinsonism of different nature." Reviews on Clinical Pharmacology and Drug Therapy 14, no. 4 (December 15, 2016): 52–60. http://dx.doi.org/10.17816/rcf14452-60.
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In clinical trials have studied effectiveness of agonist of V2 vasopressin receptors, 1-dezamino-8-D-arginine-vasopressin (DDAVP) in correction of movement disorders in patients with stroke, Parkinson’s disease and parkinsonism. Therapy received 15 patients with the stroke and 21 patients with the Parkinson’s disease and parkinsonism. Positive effect of therapy was observed in 67% of cases of stroke and in 73% cases of parkinsonian syndrome. After therapy of DDAVP movement disorders were regressed in patients with light hemiparesis after stroke. In patients with a tremor-rigid shape and akinetic-rigid form of the disease major movement disorders: tremor, rigidity, bradykinesia and hypokinesia were regressed. Except the disorders of movements affective and cognitive abnormalities were decreased. There was established that DDAVP effective in correction of disorders of voluntary and involuntary component of movements function in patients with the focal vascular and neurodegenerative diseases.
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Colosimo, Carlo. "Psychogenic tremor in Parkinson’s disease." Acta Neurologica Belgica 115, no. 4 (April 9, 2015): 829–30. http://dx.doi.org/10.1007/s13760-015-0464-6.
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Bhatia, Lokpal, and Delphine R. Turner. "Parkinson’s tremor mimicking ventricular tachycardia." Age and Ageing 34, no. 4 (July 1, 2005): 410–11. http://dx.doi.org/10.1093/ageing/afi097.
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Bruno, Federico, Alessia Catalucci, Francesco Arrigoni, Alessio Gagliardi, Elena Campanozzi, Antonella Corridore, Emanuele Tommasino, et al. "Comprehensive Evaluation of Factors Affecting Tremor Relapse after MRgFUS Thalamotomy: A Case-Control Study." Brain Sciences 11, no. 9 (September 9, 2021): 1183. http://dx.doi.org/10.3390/brainsci11091183.
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Objective: To identify possible relevant factors contributing to tremor relapse after MRgFUS thalamotomy in patients with essential tremor (ET) and Parkinson’s disease (PD). Methods: We identified patients with tremor relapse from a series of 79 treatments in a single institution. The demographic and clinical characteristics of the study group patients were compared to those of patients who did not relapse in the same follow-up period. Imaging and procedural factors were compared using a control group matched for clinical and demographic characteristics. Results: Concerning clinical and demographic characteristics, we did not find statistically significant differences in gender and age. Seventy-three percent of patients with tremor relapse were Parkinson’s disease patients. Using MRI, we found larger thalamotomy lesions at the 1-year follow-up in the control group with stable outcomes, compared to patients with tremor relapse. In the tractography evaluation, we found a more frequent eccentric position of the DRTt in patients with tremor relapse. Conclusions: The most relevant determining factors for tremor relapse after MRgFUS thalamotomy appear to be tremor from Parkinson’s disease and inaccurate thalamic targeting. Size of the thalamotomy lesion can also influence the outcome of treatment.
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Hossen, A., G. Deuschl, S. Groppa, U. Heute, and M. Muthuraman. "Discrimination of physiological tremor from pathological tremor using accelerometer and surface EMG signals." Technology and Health Care 28, no. 5 (September 18, 2020): 461–76. http://dx.doi.org/10.3233/thc-191947.
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BACKGROUND AND OBJECTIVE: Although careful clinical examination and medical history are the most important steps towards a diagnostic separation between different tremors, the electro-physiological analysis of the tremor using accelerometry and electromyography (EMG) of the affected limbs are promising tools. METHODS: A soft-decision wavelet-based decomposition technique is applied with 8 decomposition stages to estimate the power spectral density of accelerometer and surface EMG signals (sEMG) sampled at 800 Hz. A discrimination factor between physiological tremor (PH) and pathological tremor, namely, essential tremor (ET) and the tremor caused by Parkinson’s disease (PD), is obtained by summing the power entropy in band 6 (B6: 7.8125–9.375 Hz) and band 11 (B11: 15.625–17.1875 Hz). RESULTS: A discrimination accuracy of 93.87% is obtained between the PH group and the ET & PD group using a voting between three results obtained from the accelerometer signal and two sEMG signals. CONCLUSION: Biomedical signal processing techniques based on high resolution wavelet spectral analysis of accelerometer and sEMG signals are implemented to efficiently perform classification between physiological tremor and pathological tremor.
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Bange, Manuel, Sergiu Groppa, and Muthuraman Muthuraman. "Nonlinear irregularities in Parkinson’s disease tremor and essential tremor." Clinical Neurophysiology 132, no. 9 (September 2021): 2255–56. http://dx.doi.org/10.1016/j.clinph.2021.06.002.
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Dirkx, Michiel F., Heidemarie Zach, Annelies J. van Nuland, Bastiaan R. Bloem, Ivan Toni, and Rick C. Helmich. "Cognitive load amplifies Parkinson’s tremor through excitatory network influences onto the thalamus." Brain 143, no. 5 (May 1, 2020): 1498–511. http://dx.doi.org/10.1093/brain/awaa083.
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Abstract Parkinson’s tremor is related to cerebral activity in both the basal ganglia and a cerebello-thalamo-cortical circuit. It is a common clinical observation that tremor markedly increases during cognitive load (such as mental arithmetic), leading to serious disability. Previous research has shown that this tremor amplification is associated with reduced efficacy of dopaminergic treatment. Understanding the mechanisms of tremor amplification and its relation to catecholamines might help to better control this symptom with a targeted therapy. We reasoned that, during cognitive load, tremor amplification might result from modulatory influences onto the cerebello-thalamo-cortical circuit controlling tremor amplitude, from the ascending arousal system (bottom-up), a cognitive control network (top-down), or their combination. We have tested these hypotheses by measuring concurrent EMG and functional MRI in 33 patients with tremulous Parkinson’s disease, OFF medication, during alternating periods of rest and cognitive load (mental arithmetic). Simultaneous heart rate and pupil diameter recordings indexed activity of the arousal system (which includes noradrenergic afferences). As expected, tremor amplitude correlated with activity in a cerebello-thalamo-cortical circuit; and cognitive load increased tremor amplitude, pupil diameter, heart rate, and cerebral activity in a cognitive control network distributed over fronto-parietal cortex, insula, thalamus and anterior cingulate cortex. The novel finding, obtained through network analyses, indicates that cognitive load influences tremor by increasing activity in the cerebello-thalamo-cortical circuit in two different ways: by stimulating thalamic activity, likely through the ascending arousal system (given that this modulation correlated with changes in pupil diameter), and by strengthening connectivity between the cognitive control network and the cerebello-thalamo-cortical circuit. We conclude that both the bottom-up arousal system and a top-down cognitive control network amplify tremor when a Parkinson’s patient experiences cognitive load. Interventions aimed at attenuating noradrenergic activity or cognitive demands may help to reduce Parkinson’s tremor.
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Zach, Heidemarie, Michiel F. Dirkx, Dominik Roth, Jaco W. Pasman, Bastiaan R. Bloem, and Rick C. Helmich. "Dopamine-responsive and dopamine-resistant resting tremor in Parkinson disease." Neurology 95, no. 11 (July 10, 2020): e1461-e1470. http://dx.doi.org/10.1212/wnl.0000000000010316.
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ObjectiveWe tested the hypothesis that there are 2 distinct phenotypes of Parkinson tremor, based on interindividual differences in the response of resting tremor to dopaminergic medication. We also investigated whether this pattern is specific to tremor by comparing interindividual differences in the dopamine response of tremor to that of bradykinesia.MethodsIn this exploratory study, we performed a levodopa challenge in 76 tremulous patients with Parkinson tremor. Clinical scores (Movement Disorders Society–sponsored version of the Unified Parkinson’s Disease Rating Scale part III) were collected “off” and “on” a standardized dopaminergic challenge (200/50 mg dispersible levodopa-benserazide). In both sessions, resting tremor intensity was quantified using accelerometry, both during rest and during cognitive coactivation. Bradykinesia was quantified using a speeded keyboard test. We calculated the distribution of dopamine-responsiveness for resting tremor and bradykinesia. In 41 patients, a double-blinded, placebo-controlled dopaminergic challenge was repeated after approximately 6 months.ResultsThe dopamine response of resting tremor, but not bradykinesia, significantly departed from a normal distribution. A cluster analysis on 3 clinical and electrophysiologic markers of tremor dopamine-responsiveness revealed 3 clusters: dopamine-responsive, intermediate, and dopamine-resistant tremor. A repeated levodopa challenge after 6 months confirmed this classification. Patients with dopamine-responsive tremor had greater disease severity and tended to have a higher prevalence of dyskinesia.ConclusionParkinson resting tremor can be divided into 3 partially overlapping phenotypes, based on the dopamine response. These tremor phenotypes may be associated with different underlying pathophysiologic mechanisms, requiring a different therapeutic approach.
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Yuan, Han, Sen Liu, Jiali Liu, Hai Lin, Cuiwei Yang, Xiaodong Cai, Lepeng Zeng, and Siman Li. "Detection and Quantification of Resting Tremor in Parkinson’s Disease Using Long-Term Acceleration Data." Mathematical Problems in Engineering 2021 (October 11, 2021): 1–12. http://dx.doi.org/10.1155/2021/5669932.
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Long-term monitoring of resting tremor is key to assess the status of patients suffering from Parkinson’s disease (PD), which is of vital importance for reasonable medication. The detection and quantification of resting tremor in reported works rely heavily on specified movements and are not appropriate for long-term monitoring in real-life condition. The purpose of this study is to develop a detection model for long-term monitoring of resting tremor and explore an effective indicator for tremor quantification. This study included long-term acceleration data from PD patients and proposed a resting tremor detection model based on machine learning classifiers and Synthetic Minority Oversampling Technique (SMOTE). Four machine learning classifiers, K-Nearest Neighbor (KNN), Random Forest (RF), Adaptive Boosting (AdaBoost), and Support Vector Machine (SVM), were compared. Furthermore, an indicator called tremor timing ratio (TTR) was defined and calculated for tremor quantification. The detection model with RF classifier achieved the highest overall accuracy of 94.81%. The sample entropy of the acceleration signal was proved most influential in the classification by exploring the feature importance. Through the Kruskal-Wallis test and the Mann-Whitney U test, the TTR had a strong correlation with the subscore of resting tremor in Unified Parkinson Disease Rating Scale (UPDRS). Such two-step evaluation process for resting tremor can detect the tremor effectively and is expected to be applied in long-term monitoring of PD patients in daily life to realize a more comprehensive assessment of PD.
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Ferenčík, Norbert, Miroslav Jaščur, Marek Bundzel, and Filippo Cavallo. "The Rehapiano—Detecting, Measuring, and Analyzing Action Tremor Using Strain Gauges." Sensors 20, no. 3 (January 24, 2020): 663. http://dx.doi.org/10.3390/s20030663.
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We have developed a device, the Rehapiano, for the fast and quantitative assessment of action tremor. It uses strain gauges to measure force exerted by individual fingers. This article verifies the device’s capability to measure and monitor the development of upper limb tremor. The Rehapiano uses a precision, 24-bit, analog-to-digital converter and an Arduino microcomputer to transfer raw data via a USB interface to a computer for processing, database storage, and evaluation. First, our experiments validated the device by measuring simulated tremors with known frequencies. Second, we created a measurement protocol, which we used to measure and compare healthy patients and patients with Parkinson’s disease. Finally, we evaluated the repeatability of a quantitative assessment. We verified our hypothesis that the Rehapiano is able to detect force changes, and our experimental results confirmed that our system is capable of measuring action tremor. The Rehapiano is also sensitive enough to enable the quantification of Parkinsonian tremors.
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Lukšys, Donatas, Gintaras Jonaitis, and Julius Griškevičius. "Quantitative Analysis of Parkinsonian Tremor in a Clinical Setting Using Inertial Measurement Units." Parkinson's Disease 2018 (June 21, 2018): 1–7. http://dx.doi.org/10.1155/2018/1683831.
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Background. Parkinson’s disease (PD) is a neurodegenerative disorder that affects human voluntary movements. Tremor is one of the most common symptoms of PD and is expressed as involuntary oscillation of the body. Tremors can be analysed in the frequency domain. Objective. The aim of the current study was to examine selected tremor parameters (frequency, root mean square, and approximated entropy) in order to quantify the characteristics of patients diagnosed with PD, compared to a healthy control group, and to compare the parameters by dividing the subjects according to UPDRS assessment. Methods. The subjects were divided into two groups: a group of people diagnosed with PD (n = 19) and a control group consisting of healthy volunteers (CO = 12). Each subject performed motor tasks specific to certain tremors: the finger-to-nose test. Each subject performed a motor task three times. A nine degree of freedom (DOF) wireless inertial measurement unit was used for the measurement of upper limb motor tasks. For the quantitative estimation of kinetic and postural tremors, dominant frequency, root means square, and approximation entropy were selected and calculated from the measured angular velocity and linear acceleration signals. A one-way ANOVA with a significance level of α = 0.05 was used to test the null hypothesis that the means of the tremor metrics were the same between the PD and CO groups. Results. Statistically significant differences between PD patients and control groups were observed in ApEn acceleration signal of kinetic tremor, ApEn angular velocity signal of kinetic tremor, ApEn angular velocity of postural tremor, frequency acceleration signal of postural tremor, and RMS angular speed kinetic tremor. Conclusion. Application of inertial measurement units for clinical research of patients and PD tremor evaluation allows providing quantitative information for diagnostic purposes, during screening in a clinical setting that differentiates between PD patients and controls.
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Griškevičius, Julius, and Jurgita Žižienė. "RESEARCH OF UPPER LIMB BIOMECHANICS OF SUBJECTS WITH PARKINSON‘S DISEASE AND ESSENTIAL TREMMOR / SERGANČIŲJŲ PARKINSONO IR ESENCIALINIO TREMORO LIGA VIRŠUTINĖS GALŪNĖS BIOMECHANIKOS TYRIMAS." Mokslas - Lietuvos ateitis 5, no. 6 (December 31, 2013): 587–90. http://dx.doi.org/10.3846/mla.2013.93.
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Parkinson’s disease (PD) is a common neurodegenerative diseasewith symptoms of bradykinesia, rest tremor, rigidity and posturalinstability. PL is diagnosed by a clinician who qualitativelyevaluates patient’s visible symptoms during a physical exam. Inaddition, differentiating PD from essential tremor (ET) can bechallenging because their clinical symptoms are similar. Oncediagnosed, only qualitative tools such as the UPDRS are availableto monitor symptom severity and disease progression. Thepurpose of this study is to evaluate the changes of biomechanicalparameters of upper limb of subjects diagnosed either PD or ET,estimate differences and compare them with healthy subjectsin facilitate a creation of an additional instrumental clinical assessmentof PD subjects via biomechanical evaluation of motorfunction tool and develop methods and indices for differentiatingPD from ET. Santrauka Parkinsono liga (PL) yra lėtinė progresuojanti neurologinė liga, kuri išoriškai pasireiškia galvos bei galūnių drebėjimu, judesių sulėtėjimu, sukaustymu ir eisenos pasikeitimu. Esencialinis tremoras – laipsniškai progresuojanti liga, kuriai būdingas nevalingas kūno dalies drebėjimas. Tai daug dažnesnė būklė negu PL judėjimo sutrikimas. Neretai ankstyvoje ligos stadijoje šios abi patologinės būklės yra painiojamos. Šio straipsnio tikslas yra įvertinti žmonių, sergančių Parkinsono liga ir esencialiniu tremoru, viršutinės galūnės biomechanikos parametrų pokyčius, skirtumus ir palyginti juos su sveiko žmogaus viršutinės galūnės biomechanika.
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Samotus, Olivia, Jack Lee, and Mandar Jog. "Developing a Consistent, Reproducible Botulinum Toxin Type A Dosing Method for Upper Limb Tremor by Kinematic Analysis." Toxins 13, no. 4 (April 8, 2021): 264. http://dx.doi.org/10.3390/toxins13040264.
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Botulinum toxin type A (BoNT-A) injection patterns customized to each patient’s unique tremor characteristics produce better efficacy and lower adverse effects compared to the fixed-muscle-fixed-dose approach for Essential Tremor (ET) and Parkinson’s disease (PD) tremor therapy. This article outlined how a kinematic-based dosing method to standardize and customize BoNT-A injections for tremors was developed. Seven ET and eight PD participants with significant tremor reduction and minimal perceived weakness using optimized BoNT-A injections determined by clinical and kinematic guidance were retrospectively selected to develop the kinematic-based dosing method. BoNT-A dosages allocated per joint were paired to baseline tremor amplitudes per joint. The final kinematic-based dosing method was prospectively utilized to validate BoNT-A injection pattern selection without clinical/visual assessments in 31 ET and 47 PD participants with debilitating arm tremors (totaling 122 unique tremor patterns). Whole-arm kinematic tremor analysis was performed at baseline and 6-weeks post-injection. Correlation and linear regression analyses between baseline tremor amplitudes and the change in tremor amplitude 6-weeks post-injection, with BoNT-A dosages per joint, were performed. Injection patterns determined using clinical assessment and interpretation of kinematics produced significant associations between baseline tremor amplitudes and optimized BoNT-A dosages in all joints. The change in elbow tremor was only significantly associated with the elbow total dose as the change in the wrist and shoulder tremor amplitudes were not significantly associated with the wrist and shoulder dosages from the selected 15 ET and PD participants. Using the kinematic-based dosing method, significant associations between baseline tremor amplitudes and the change (6-weeks post-first treatment) in tremor at each joint with BoNT-A dosages for all joints was observed in all 78 ET and PD participants. The kinematic-based dosing method provided consistency in dose selection and subsequent tremor reduction and can be used to standardize tremor assessments for whole-arm tremor treatment planning.
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Sinai, Alon, Maria Nassar, Elliot Sprecher, Marius Constantinescu, Menashe Zaaroor, and Ilana Schlesinger. "Focused Ultrasound Thalamotomy in Tremor Dominant Parkinson’s Disease: Long-Term Results." Journal of Parkinson's Disease 12, no. 1 (January 21, 2022): 199–206. http://dx.doi.org/10.3233/jpd-212810.
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Background: MRI-guided focused ultrasound (FUS) has established short-term efficacy in tremor relief. Objective: We report our long-term experience of treating tremor with unilateral FUS unilateral VIM-thalamotomy in tremor dominant Parkinson’s disease (TDPD) patients. Methods: We report outcome of FUS thalamotomy in TDPD patients with 1–5 years of follow-up. Outcomes: tremor reduction assessed with Clinical Rating Scale for Tremor (CRST) and Unified Parkinson’s Disease Rating Scale (UPDRS part III) overall and in the treated hemibody and safety. Results: Twenty-six TDPD patients completed 1–5 years of follow-up (median follow-up 36 months, range 12–60 months). Median age was 60 years (range 46–79), with median disease duration of 6 years (range 2–16). Immediately, treatment resulted in 100%improvement in tremor in the treated arm in 23 patients and 90%improvement in 3 patients. In 15 patients with leg tremor, 2 patients with chin tremor and 1 patient with head tremor, tremor was significantly improved. Up to 5 years, median CRST score, median UPDRS score, overall and in treated hemibody, decreased significantly as compared with baseline (p < 0.0001). In 2 patients tremor returned completely and in 8 patients there was partial return of tremor. Adverse events were mild and resolved within 3 months. At baseline 4 patients were not receiving any medication vs. 3 at last follow-up and 15 were not taking levodopa vs.9 at last follow-up. Conclusion: Unilateral FUS VIM-thalamotomy in TDPD patients was effective and safe and provided long-term tremor relief in most patients. FUS thalamotomy for tremor may delay initiation of levodopa treatment.
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Louis, Elan D., Seth L. Pullman, David Eidelberg, and Vijay Dhawan. "Re-Emergent Tremor without Accompanying Rest Tremor in Parkinson’s Disease." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 35, no. 4 (September 2008): 513–15. http://dx.doi.org/10.1017/s0317167100009239.
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Rana, Abdul Qayyum, Ishraq Siddiqui, Abdullah A. Mosabbir, Abdul-Rehman M. Qureshi, Abdul Fattah, and Naeem Awan. "Is action tremor in Parkinson’s disease related to resting tremor?" Neurological Research 36, no. 2 (December 6, 2013): 107–11. http://dx.doi.org/10.1179/1743132813y.0000000274.
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Morgan, Sarah, and Elan D. Louis. "Re-Emergent Tremor of Parkinson’s Disease Masquerading as Essential Tremor." Tremor and Other Hyperkinetic Movements 6 (March 11, 2016): 370. http://dx.doi.org/10.5334/tohm.327.
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Skaramagkas, Vasileios, George Andrikopoulos, Zinovia Kefalopoulou, and Panagiotis Polychronopoulos. "A Study on the Essential and Parkinson’s Arm Tremor Classification." Signals 2, no. 2 (April 19, 2021): 201–24. http://dx.doi.org/10.3390/signals2020016.
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In this article, the challenge of discriminating between essential and Parkinson’s tremor is addressed. Although a variety of methods have been proposed for diagnosing the severity of these highly occurring tremor types, their rapid and effective identification, especially in their early stages, proves particularly difficult and complicated due to their wide range of causes and similarity of symptoms. To this goal, a clinical analysis was performed, where a number of volunteers including essential and Parkinson’s tremor-diagnosed patients underwent a series of pre-defined motion patterns, during which a wearable sensing setup was used to measure their lower arm tremor characteristics from multiple selected points. Extracted features from the acquired accelerometer signals were used to train classification algorithms, including decision trees, discriminant analysis, support vector machine (SVM), K-nearest neighbor (KNN) and ensemble learning algorithms, for providing a comparative study and evaluating the potential of utilizing machine learning to accurately discriminate among different tremor types. Overall, SVM related classifiers proved to be the most successful in terms of classifying between Parkinson’s, essential and no tremor diagnosed with percentages reaching up to 100% for a single accelerometer measurement at the metacarpal area. In general and in motion while holding an object position, Coarse Gaussian SVM classifier reached 82.62% accuracy.
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Dirkx, Michiel F., Heidemarie Zach, Annelies van Nuland, Bastiaan R. Bloem, Ivan Toni, and Rick C. Helmich. "Cerebral differences between dopamine-resistant and dopamine-responsive Parkinson’s tremor." Brain 142, no. 10 (September 11, 2019): 3144–57. http://dx.doi.org/10.1093/brain/awz261.
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Resting tremor in Parkinson’s disease does not always respond to dopaminergic medication. Dirkx et al. report that dopamine-resistant tremor may be the result of increased cerebellar and reduced somatosensory influences on the cerebellar thalamus, making this key node of the tremor circuit less susceptible to the inhibitory effects of dopamine.
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Molparia, Bhuvan, Brian N. Schrader, Eli Cohen, Jennifer L. Wagner, Sandeep R. Gupta, Sherrie Gould, Nelson Hwynn, Emily G. Spencer, and Ali Torkamani. "Combined accelerometer and genetic analysis to differentiate essential tremor from Parkinson’s disease." PeerJ 6 (July 20, 2018): e5308. http://dx.doi.org/10.7717/peerj.5308.
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Essential tremor (ET) and Parkinson’s disease (PD) are among the most common adult-onset tremor disorders. Clinical and pathological studies suggest that misdiagnosis of PD for ET, and vice versa, occur in anywhere from 15% to 35% of cases. Complex diagnostic procedures, such as dopamine transporter imaging, can be powerful diagnostic aids but are lengthy and expensive procedures that are not widely available. Preliminary studies suggest that monitoring of tremor characteristics with consumer grade accelerometer devices could be a more accessible approach to the discrimination of PD from ET, but these studies have been performed in well-controlled clinical settings requiring multiple maneuvers and oversight from clinical or research staff, and thus may not be representative of at-home monitoring in the community setting. Therefore, we set out to determine whether discrimination of PD vs. ET diagnosis could be achieved by monitoring research subject movements at home using consumer grade devices, and whether discrimination could be improved with the addition of genetic profiling of the type that is readily available through direct-to-consumer genetic testing services. Forty subjects with PD and 27 patients with ET were genetically profiled and had their movements characterized three-times a day for two weeks through a simple procedure meant to induce rest tremors. We found that tremor characteristics could be used to predict diagnosis status (sensitivity = 76%, specificity = 65%, area under the curve (AUC) = 0.75), but that the addition of genetic risk information, via a PD polygenic risk score, did not improve discriminatory power (sensitivity = 80%, specificity = 65%, AUC = 0.73).
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San-Segundo, Rubén, Ada Zhang, Alexander Cebulla, Stanislav Panev, Griffin Tabor, Katelyn Stebbins, Robyn E. Massa, Andrew Whitford, Fernando de la Torre, and Jessica Hodgins. "Parkinson’s Disease Tremor Detection in the Wild Using Wearable Accelerometers." Sensors 20, no. 20 (October 14, 2020): 5817. http://dx.doi.org/10.3390/s20205817.
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Continuous in-home monitoring of Parkinson’s Disease (PD) symptoms might allow improvements in assessment of disease progression and treatment effects. As a first step towards this goal, we evaluate the feasibility of a wrist-worn wearable accelerometer system to detect PD tremor in the wild (uncontrolled scenarios). We evaluate the performance of several feature sets and classification algorithms for robust PD tremor detection in laboratory and wild settings. We report results for both laboratory data with accurate labels and wild data with weak labels. The best performance was obtained using a combination of a pre-processing module to extract information from the tremor spectrum (based on non-negative factorization) and a deep neural network for learning relevant features and detecting tremor segments. We show how the proposed method is able to predict patient self-report measures, and we propose a new metric for monitoring PD tremor (i.e., percentage of tremor over long periods of time), which may be easier to estimate the start and end time points of each tremor event while still providing clinically useful information.
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Povalej Bržan, P., J. A. Gallego, J. P. Romero, V. Glaser, E. Rocon, J. Benito-León, F. Bermejo-Pareja, I. J. Posada, and A. Holobar. "New Perspectives for Computer-Aided Discrimination of Parkinson’s Disease and Essential Tremor." Complexity 2017 (2017): 1–17. http://dx.doi.org/10.1155/2017/4327175.
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Pathological tremor is a common but highly complex movement disorder, affecting ~5% of population older than 65 years. Different methodologies have been proposed for its quantification. Nevertheless, the discrimination between Parkinson’s disease tremor and essential tremor remains a daunting clinical challenge, greatly impacting patient treatment and basic research. Here, we propose and compare several movement-based and electromyography-based tremor quantification metrics. For the latter, we identified individual motor unit discharge patterns from high-density surface electromyograms and characterized the neural drive to a single muscle and how it relates to other affected muscles in 27 Parkinson’s disease and 27 essential tremor patients. We also computed several metrics from the literature. The most discriminative metrics were the symmetry of the neural drive to muscles, motor unit synchronization, and the mean log power of the tremor harmonics in movement recordings. Noteworthily, the first two most discriminative metrics were proposed in this study. We then used decision tree modelling to find the most discriminative combinations of individual metrics, which increased the accuracy of tremor type discrimination to 94%. In summary, the proposed neural drive-based metrics were the most accurate at discriminating and characterizing the two most common pathological tremor types.
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Zach, Heidemarie, Michiel Dirkx, Bastiaan R. Bloem, and Rick C. Helmich. "The Clinical Evaluation of Parkinson’s Tremor." Journal of Parkinson's Disease 5, no. 3 (September 14, 2015): 471–74. http://dx.doi.org/10.3233/jpd-150650.
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Gunawardena, Indunil. "Parkinson’s tremor mimicking torsades de pointes." British Journal of Hospital Medicine 72, no. 10 (October 2011): 593. http://dx.doi.org/10.12968/hmed.2011.72.10.593.
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Kumar, Shivam, Lav Goyal, and Shamsher Singh. "Tremor and Rigidity in Patients with Parkinson’s Disease: Emphasis on Epidemiology, Pathophysiology and Contributing Factors." CNS & Neurological Disorders - Drug Targets 21, no. 7 (August 2022): 596–609. http://dx.doi.org/10.2174/1871527320666211006142100.
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: Parkinson's disease (PD) is the second most prominent neurodegenerative movement disorder after Alzheimer’s disease, involving 2-3% of the population aged above 65 years. This is mainly triggered by the depletion of dopaminergic neurons located in substantia nigra pars compacta (SNpc) in the region of basal ganglia. At present, diagnosis for symptoms of PD is clinical, contextual, unspecified and therapeutically incomprehensive. Analysis of various causes of PD is essential for an accurate examination of the disease. Among the different causes, such as tremors and rigidity, unresponsiveness to the current treatment approach contributes to mortality. In the present review article, we describe various key factors of pathogenesis and physiology associated with tremors and rigidity necessary for the treatment of PI (postural instability) in patients with PD. Additionally, several reports showing early tremor and rigidity causes, particularly age, cortex lesions, basal ganglia lesions, genetic abnormalities, weakened reflexes, nutrition, fear of fall, and altered biomechanics, have been explored. By summarizing the factors that contribute to the disease, histopathological studies can assess rigidity and tremor in PD. With a clear understanding of the contributing factors, various prospective studies can be done to assess the incidence of rigidity and tremors.
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Park, Sangmin, Jung Geol Lim, Hee Jin Chang, and Eungseok Oh. "What Shall We Do for the Patients with Shaky Leg Syndrome? A Review of 23 Patients." Neurodegenerative Diseases 20, no. 1 (2020): 46–54. http://dx.doi.org/10.1159/000509411.
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Orthostatic tremor (OT) is not an uncommon symptom in various neurodegenerative diseases. However, the nature and pathophysiology of OT involve a complex network of tremors and dopaminergic pathways. We assessed patients who complained of prominent leg tremors described as “shaky leg.” We analyzed their characteristics and evaluated them with neuroimaging and electrophysiological tools. A total of 23 patients who experienced an uncomfortable symptom of leg tremor were retrospectively enrolled from April 2014 to October 2019. Previous medical history, brain MRI, and surface electromyography (EMG) data were analyzed. The [18F]-FP-CIT brain positron emission tomography (PET) and the Unified Parkinson’s Disease Rating Scale (UPDRS) were assessed for patients who showed parkinsonism. The causes of OT varied: parkinsonism (n = 5), idiopathic causes (n = 4), secondary causes (n = 3, trauma, brain lesion, arteriovenous malformation), drug reactions (n = 3, valproate, perphenazine, haloperidol), other neurological disorders (n = 5, essential tremor, dystonia, restless leg syndrome, REM sleep behavior disorder, dementia), alcohol withdrawal (n = 1), functional movement disorder (n = 1), and an unknown cause (n = 1). The frequency range varied (2.6–15 Hz) and according to the new consensus statement on the classification of OT, 4 patients had primary OT, 2 had “primary OT plus,” 12 had slow OT, and 5 had orthostatic myoclonus. The prognosis associated with the use of medication was generally poor; however, clonazepam and levodopa were the most effective drugs. In conclusion, we found that different types of OT and orthostatic myoclonus were diagnosed by electrophysiological evaluation and neuroimaging tools even if they showed the same symptoms as “shaky leg.” In addition, it is possible to roughly estimate the response to medication according to the type of OT and the cause. To clarify the pathophysiology of OT, a large number of longitudinal cohort studies and detailed neuroimaging and electrophysiological evaluations are needed.
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Munhoz, Renato P., Marina Picillo, Susan H. Fox, Veronica Bruno, Michel Panisset, Christopher R. Honey, and Alfonso Fasano. "Eligibility Criteria for Deep Brain Stimulation in Parkinson’s Disease, Tremor, and Dystonia." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 43, no. 4 (May 3, 2016): 462–71. http://dx.doi.org/10.1017/cjn.2016.35.
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AbstractIn this review, the available evidence to guide clinicians regarding eligibility for deep brain stimulation (DBS) in the main conditions in which these forms of therapy are generally indicated—Parkinson’s disease (PD), tremor, and dystonia—is presented. In general, the literature shows that DBS is effective for PD, essential tremor, and idiopathic dystonia. In these cases, key points in patient selection must include the level of disability and inability to manage symptoms using the best available medical therapy. Results are, however, still not optimal when dealing with other aetiologies, such as secondary tremors and symptomatic dystonia. Also, in PD, issues such as age and neuropsychiatric profile are still debatable parameters. Overall, currently available literature is able to guide physicians on basic aspects of patient selection and indications for DBS; however, a few points are still debatable and controversial. These issues should be refined and clarified in future studies.
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AlMahadin, Ghayth, Ahmad Lotfi, Marie Mc Carthy, and Philip Breedon. "Task-Oriented Intelligent Solution to Measure Parkinson’s Disease Tremor Severity." Journal of Healthcare Engineering 2021 (September 10, 2021): 1–15. http://dx.doi.org/10.1155/2021/9624386.
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Tremor is a common symptom of Parkinson’s disease (PD). Currently, tremor is evaluated clinically based on MDS-UPDRS Rating Scale, which is inaccurate, subjective, and unreliable. Precise assessment of tremor severity is the key to effective treatment to alleviate the symptom. Therefore, several objective methods have been proposed for measuring and quantifying PD tremor from data collected while patients performing scripted and unscripted tasks. However, up to now, the literature appears to focus on suggesting tremor severity classification methods without discrimination tasks effect on classification and tremor severity measurement. In this study, a novel approach to identify a recommended system is used to measure tremor severity, including the influence of tasks performed during data collection on classification performance. The recommended system comprises recommended tasks, classifier, classifier hyperparameters, and resampling technique. The proposed approach is based on the above-average rule of five advanced metrics results of four subdatasets, six resampling techniques, six classifiers besides signal processing, and features extraction techniques. The results of this study indicate that tasks that do not involve direct wrist movements are better than tasks that involve direct wrist movements for tremor severity measurements. Furthermore, resampling techniques improve classification performance significantly. The findings of this study suggest that a recommended system consists of support vector machine (SVM) classifier combined with BorderlineSMOTE oversampling technique and data collection while performing set of recommended tasks, which are sitting, stairs up and down, walking straight, walking while counting, and standing.
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Doder, M., E. A. Rabiner, N. Turjanski, A. J. Lees, and D. J. Brooks. "Tremor in Parkinson’s disease and serotonergic dysfunction." Neurology 60, no. 4 (February 25, 2003): 601–5. http://dx.doi.org/10.1212/01.wnl.0000031424.51127.2b.
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Background: The pathophysiologic mechanisms underlying parkinsonian tremor remain unclear. The response to dopaminergic treatment is variable and nondopaminergic mechanisms may play a role in tremor generation. Midbrain raphe 5-HT1A binding provides a functional measure of serotonergic system integrity. With PET, the aim of this study was to examine regional cerebral 11C-WAY 100635 binding to 5-HT1A receptors in patients with PD and to correlate it with severity of tremor.Methods:11C-WAY 100635 PET was performed on 23 patients with PD and eight age-matched healthy volunteers. Brain 5-HT1A receptor binding was computed using compartmental modeling with a cerebellar reference tissue input function.Results: The authors found mean 27% reduction in the midbrain raphe 5-HT1A binding potential in patients with PD compared to healthy volunteers (p < 0.001). They also showed that Unified Parkinson’s Disease Rating Scale composite tremor scores, but not rigidity or bradykinesia, correlate with 5-HT1A binding in the raphe (p < 0.01).Conclusions: These findings support previous indirect evidence that serotonergic neurotransmission is decreased in PD in vivo. The authors hypothesize that the reduction in raphe 5-HT1A binding represents receptor dysfunction or loss of cell bodies due to Lewy body degeneration in PD, or both. An association between 5-HT1A receptor availability in the raphe and severity of parkinsonian tremor was also found.
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Locatelli, Patrick, Dario Alimonti, Gianluca Traversi, and Valerio Re. "Classification of Essential Tremor and Parkinson’s Tremor Based on a Low-Power Wearable Device." Electronics 9, no. 10 (October 15, 2020): 1695. http://dx.doi.org/10.3390/electronics9101695.
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Among movement disorders, essential tremor is by far the most common, as much as eight times more prevalent than Parkinson’s disease. Although these two conditions differ in their presentation and course, clinicians do not always recognize them, leading to common misdiagnoses. Proper and early diagnosis is important for receiving the right treatment and support. In this paper, the development of a portable and reliable tremor classification system based on a wearable device, enabling clinicians to differentiate between essential tremor and Parkinson’s disease-associated one, is reported. Inertial data were collected from subjects with a well-established diagnosis of tremor, and analyzed to extract different sets of relevant spectral features. Supervised learning methods were then applied to build several classification models, among which the best ones achieved an average accuracy above 90%. Results encourage the use of wearable technology as effective and affordable tools to support clinicians.
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Szumilas, Mateusz, Krzysztof Lewenstein, Elżbieta Ślubowska, Stanisław Szlufik, and Dariusz Koziorowski. "A Multimodal Approach to the Quantification of Kinetic Tremor in Parkinson’s Disease." Sensors 20, no. 1 (December 28, 2019): 184. http://dx.doi.org/10.3390/s20010184.
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Parkinson’s disease results in motor impairment that deteriorates patients’ quality of life. One of the symptoms negatively interfering with daily activities is kinetic tremor which should be measured to monitor the outcome of therapy. A new instrumented method of quantification of the kinetic tremor is proposed, based on the analysis of circles drawn on a digitizing tablet by a patient. The aim of this approach is to obtain a tremor scoring equivalent to that performed by trained clinicians. Models are trained with the least absolute shrinkage and selection operator (LASSO) method to predict the tremor scores on the basis of the parameters computed from the patients’ drawings. Signal parametrization is derived from both expert knowledge and the response of an artificial neural network to the raw data, thus the approach was named multimodal. The fitted models are eventually combined into model ensembles that provide aggregated scores of the kinetic tremor captured in the drawings. The method was verified with a set of clinical data acquired from 64 Parkinson’s disease patients. Automated and objective quantification of the kinetic tremor with the presented approach yielded promising results, as the Pearson’s correlations between the visual ratings of tremor and the model predictions ranged from 0.839 to 0.890 in the best-performing models.
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Wagle Shukla, Aparna, Michael Okun, David Vaillancourt, and Lisa Warren. "The ice test to differentiate essential tremor from Parkinson’s disease tremor." Clinical Neurophysiology 128, no. 11 (November 2017): 2181–83. http://dx.doi.org/10.1016/j.clinph.2017.08.015.
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Visser, F., L. J. Bour, Y. X. Lee, T. R. ten Brinke, and A. F. van Rootselaar. "Eye movement abnormalities in essential tremor versus tremor dominant Parkinson’s disease." Clinical Neurophysiology 130, no. 5 (May 2019): 683–91. http://dx.doi.org/10.1016/j.clinph.2019.01.026.
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Milosevic, Luka, Robert F. Dallapiazza, Renato P. Munhoz, Suneil K. Kalia, Milos R. Popovic, and William D. Hutchison. "Case Studies in Neuroscience: Lack of inhibitory synaptic plasticity in the substantia nigra pars reticulata of a patient with lithium-induced tremor." Journal of Neurophysiology 122, no. 4 (October 1, 2019): 1367–72. http://dx.doi.org/10.1152/jn.00203.2019.
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Tremor is a well-known side effect from many psychiatric medications, including lithium and dopamine antagonists. In patients whose psychiatric symptoms are stabilized and only respond to certain medications, deep brain stimulation may offer relief of the consequent motor complications. We report the case of an elderly male with disabling tremor related to lithium therapy for bipolar affective disorder, who was subsequently treated with deep brain stimulation. In this patient, we obtained recordings from the substantia nigra pars reticulata and performed a high-frequency stimulation protocol that robustly elicits long-term potentiation (LTP)-like changes in patients with Parkinson’s disease. We hypothesized that in this patient, who did not have Parkinson’s disease, the levels of inhibitory plasticity would be much greater. However, we found an unanticipated lack of plasticity in the patient with lithium-induced tremor, compared with two de novo control patients with Parkinson’s disease. This patient was successfully treated with deep brain stimulation in the vicinity of the ventral oral posterior nucleus, an area of the thalamus that receives inputs from the basal ganglia. We postulate that the lithium-induced blockade of LTP may bring about motor complications such as tremor while simultaneously contributing to the therapeutic mechanism for treating the symptoms of psychiatric disorders such as bipolar affective disorder. NEW & NOTEWORTHY Use of a dual-microelectrode technique enabled us to compare long-term potentiation (LTP)-like changes in a patient with lithium-induced tremor to that of patients with Parkinson’s disease. This study corroborated the findings in rodent brain slices that chronic lithium treatment may block LTP. Whereas a deficit in LTP may underlie the therapeutic mechanism for treating psychiatric disorders such as bipolar affective disorder, it may simultaneously contribute to consequent appearance of tremor.
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Valeikiene, Vaineta, Jelena Ceremnych, Diana Mieliauskaite, and Vidmantas Alekna. "The prevalence of Parkinson’s disease among Vilnius inhabitants." Open Medicine 3, no. 2 (June 1, 2008): 195–98. http://dx.doi.org/10.2478/s11536-008-0014-1.
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AbstractIn a hospital-based study we investigated the prevalence of Parkinson’s disease among inhabitants of the Vilnius city, the capital of Lithuania. The study group was selected from patients who were diagnosed with Parkinson’s disease during the time frame of 1978-2005. Patients’ time of diagnosis were based on the data of dispensary cards, registration journals and/or other documentation. A questionnaire and Mini Mental State Examination provided data for analysis on the conditions of the patients. The prevalence of Parkinson’s disease in Vilnius is 1.32/1000 inhabitants and is higher in men than in women (p < 0.05). The age of Parkinson’s disease onset in men and women is the same (63.77 ± 0.70 years). The rigidity-tremor form of Parkinson’s disease is the most frequent (76.8% of all cases). The PD prevalence rate in Vilnius inhabitants are close to the mean levels observed in studies made in Finland, Austria, Germany. The prevailing form of Parkinson’s disease is rigidity-tremor.
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Burleigh, Anne, Fay Horak, John Nutt, and James Frank. "Levodopa Reduces Muscle Tone and Lower Extremity Tremor in Parkinson’s Disease." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 22, no. 4 (November 1995): 280–85. http://dx.doi.org/10.1017/s0317167100039470.
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AbstractObjectiveWe have quantified the effects of levodopa treatment in Parkinsonian subjects during maintained stance.MethodsElectromyographic muscle activity during quiet stance was assessed in subjects with Parkinson’s disease, who exhibited a fluctuating response to levodopa, and in age-matched control subjects. Stance stability was also assessed from mean displacement and velocity of the center of pressure excursions during stance.ResultsLower extremity and trunk muscles showed high amplitude activity in all Parkinson’s subjects when “off”, and a 4–5 Hz tremor in three of these subjects. When “on”, the amplitude of muscle activity was reduced in the distal muscles more than the proximal, while tremor was suppressed in all muscles. Corresponding to the excessive muscle activity, the Parkinson’s subjects had increased velocity and variability of velocity in the anterior-posterior center of foot pressure excursions, but the mean displacement of the center of pressure excursion was not different from the controls. The velocity of center of pressure excursions in the Parkinson’s subjects “on”, approached those of the control subjects suggesting that the excessive distal muscle amplitude and tremor contributed to the high velocity of the center of pressure.ConclusionsThese findings suggest that dopaminergic systems are involved in the regulation of muscle tone during stance. Depletion of dopaminergic transmission results in increased muscle tone and tremor in the lower extremities which may contribute to changes in posture and stability.
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Hopkins, Hannah K., Elizabeth M. Traverse, and Kelli L. Barr. "Viral Parkinsonism: An underdiagnosed neurological complication of Dengue virus infection." PLOS Neglected Tropical Diseases 16, no. 2 (February 9, 2022): e0010118. http://dx.doi.org/10.1371/journal.pntd.0010118.
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Dengue virus (DENV) is a flavivirus that is a significant cause of human disease costing billions of dollars per year in medical and mosquito control costs. It is estimated that up to 20% of DENV infections affect the brain. Incidence of DENV infections is increasing, which suggests more people are at risk of developing neurological complications. The most common neurological manifestations of DENV are encephalitis and encephalopathy, and movement disorders such as parkinsonism have been observed. Parkinsonism describes syndromes similar to Parkinson’s Disease where tremors, stiffness, and slow movements are observed. Parkinsonism caused by viral infection is characterized by patients exhibiting at least two of the following symptoms: tremor, bradykinesia, rigidity, and postural instability. To investigate DENV-associated parkinsonism, case studies and reports of DENV-associated parkinsonism were obtained from peer-reviewed manuscripts and gray literature. Seven reports of clinically diagnosed DENV-associated parkinsonism and 15 cases of DENV encephalitis, where the patient met the case criteria for a diagnosis of viral parkinsonism were found. Clinically diagnosed DENV-associated parkinsonism patients were more likely to be male and exhibit expressionless face, speech problems, and lymphocytosis. Suspected patients were more likely to exhibit tremor, have thrombocytopenia and low hemoglobin. Viral parkinsonism can cause a permanent reduction in neurons with consequential cognitive and behavior changes, or it can leave a latent imprint in the brain that can cause neurological dysfunction decades after recovery. DENV-associated parkinsonism is underdiagnosed and better adherence to the case definition of viral parkinsonism is needed for proper management of potential sequalae especially if the patient has an ongoing or potential to develop a neurodegenerative disease.
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Bonifati, Vincenzo, Edito Fabrizio, Nicola Vanacore, Michele De Mari, and Giuseppe Meco. "Familial Parkinson’s Disease: A Clinical Genetic Analysis." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 22, no. 4 (November 1995): 272–79. http://dx.doi.org/10.1017/s0317167100039469.
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AbstractObjectiveTo study the frequency, clinical features and clinical genetics of familial Parkinson’s disease (PD).MethodsFamily history for PD and tremors was studied in 100 consecutive PD cases. Spouses served as controls. Clinical features were compared between personally verified familial and sporadic PD cases, from the same consecutive clinical series. Clinical genetic analysis was performed in a larger group of non-consecutive multicase PD families.ResultsFamily history for PD was positive in 24% of consecutive PD cases and in 6% of spouse controls (p < 0.001). When family history for isolated tremor is also considered, the number of positive cases rises to 43% compared with 9% in controls (p < 0.001). Nine of the consecutive cases had at least one living affected relative, for a total of 20 familial PD cases. These familial cases showed an earlier onset age when compared with sporadic ones from the same consecutive series. Within 22 non-consecutive PD families with at least two living and personally examined PD cases (total 52 PD cases), the crude segregation ratios were similar for parents and siblings and the lifetime cumulative risks approached 0.4 in siblings and tended to be comparable, but at later ages, in parents. Ancestral relatives were all unilaterally distributed. In some families, anticipation of onset age in new generations was observed.ConclusionsThe frequency of positive family history for PD and for PD and tremor is higher among PD cases than controls. Familial and sporadic PD only differ in onset age. The clinical genetic analyses support autosomal dominant inheritance with strongly age-related penetrance as most likely in familial PD.