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1

Barry, Daniel T. "Acoustic myography." Journal of the Acoustical Society of America 84, no. 6 (December 1988): 2308. http://dx.doi.org/10.1121/1.396771.

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Barry, Daniel T. "Acoustic myography." Muscle & Nerve 20, no. 12 (December 1997): 1601. http://dx.doi.org/10.1002/(sici)1097-4598(199712)20:12<1601::aid-mus19>3.0.co;2-2.

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3

Kelava, Leonardo, Ivan Ivić, Eszter Pakai, Kata Fekete, Peter Maroti, Roland Told, Zoltan Ujfalusi, and Andras Garami. "Stereolithography 3D Printing of a Heat Exchanger for Advanced Temperature Control in Wire Myography." Polymers 14, no. 3 (January 25, 2022): 471. http://dx.doi.org/10.3390/polym14030471.

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We report the additive manufacturing of a heat-exchange device that can be used as a cooling accessory in a wire myograph. Wire myography is used for measuring vasomotor responses in small resistance arteries; however, the commercially available devices are not capable of active cooling. Here, we critically evaluated a transparent resin material, in terms of mechanical, structural, and thermal behavior. Tensile strength tests (67.66 ± 1.31 MPa), Charpy impact strength test (20.70 ± 2.30 kJ/m2), and Shore D hardness measurements (83.0 ± 0.47) underlined the mechanical stability of the material,
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4

Herzog, Walter. "Acoustic myography (a reply)." Muscle & Nerve 20, no. 12 (December 1997): 1601–2. http://dx.doi.org/10.1002/(sici)1097-4598(199712)20:12<1601::aid-mus20>3.0.co;2-1.

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5

Zelinskaya, I. A., and Ya G. Toropova. "Wire myography in modern scientific researches: methodical aspects." Regional blood circulation and microcirculation 17, no. 1 (March 30, 2018): 83–89. http://dx.doi.org/10.24884/1682-6655-2018-17-1-83-89.

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In the present work modern approaches to investigation of isolated vessel's vasoactive properties with myography method were described. Authors give detailed illustrated description to the vessels preparation technique and order of actions during myography based on own experience and published data. Authors described approaches to investigate mechanical properties of vessel wall and vasoactive properties with wire myography method.
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6

Curcio, Brittney C., Nicholas V. Cirillo, and Michael Wininger. "Force Myography across Socket Material." Journal of Prosthetics and Orthotics 32, no. 1 (January 2020): 52–58. http://dx.doi.org/10.1097/jpo.0000000000000295.

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7

LUNDERVOLD, ARNE. "A TECHNICAL ERROR IN ELECTRO-MYOGRAPHY." Acta Psychiatrica Scandinavica 24, no. 2 (August 23, 2007): 199–206. http://dx.doi.org/10.1111/j.1600-0447.1949.tb03493.x.

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8

Kapravchuk, Vladislava, Andrey Briko, Alexander Kobelev, Ahmad Hammoud, and Sergey Shchukin. "An Approach to Using Electrical Impedance Myography Signal Sensors to Assess Morphofunctional Changes in Tissue during Muscle Contraction." Biosensors 14, no. 2 (January 31, 2024): 76. http://dx.doi.org/10.3390/bios14020076.

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This present work is aimed at conducting fundamental and exploratory studies of the mechanisms of electrical impedance signal formation. This paper also considers morphofunctional changes in forearm tissues during the performance of basic hand actions. For this purpose, the existing research benches were modernized to conduct experiments of mapping forearm muscle activity by electrode systems on the basis of complexing the electrical impedance signals and electromyography signals and recording electrode systems’ pressing force using force transducers. Studies were carried out with the involvem
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9

Dwivedi, Anany, Helen Groll, and Philipp Beckerle. "A Systematic Review of Sensor Fusion Methods Using Peripheral Bio-Signals for Human Intention Decoding." Sensors 22, no. 17 (August 23, 2022): 6319. http://dx.doi.org/10.3390/s22176319.

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Humans learn about the environment by interacting with it. With an increasing use of computer and virtual applications as well as robotic and prosthetic devices, there is a need for intuitive interfaces that allow the user to have an embodied interaction with the devices they are controlling. Muscle–machine interfaces can provide an intuitive solution by decoding human intentions utilizing myoelectric activations. There are several different methods that can be utilized to develop MuMIs, such as electromyography, ultrasonography, mechanomyography, and near-infrared spectroscopy. In this paper,
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10

Scalise, Lorenzo, Sara Casaccia, Paolo Marchionni, Ilaria Ercoli, and Enrico Primo Tomasini. "Muscle activity characterization by laser Doppler Myography." Journal of Physics: Conference Series 459 (September 6, 2013): 012017. http://dx.doi.org/10.1088/1742-6596/459/1/012017.

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11

Godiyal, Anoop Kant, Upinderpal Singh, Sneh Anand, and Deepak Joshi. "Analysis of force myography based locomotion patterns." Measurement 140 (July 2019): 497–503. http://dx.doi.org/10.1016/j.measurement.2019.04.009.

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12

Statland, Jeffrey M., Chad Heatwole, Katy Eichinger, Nuran Dilek, William B. Martens, and Rabi Tawil. "Electrical impedance myography in facioscapulohumeral muscular dystrophy." Muscle & Nerve 54, no. 4 (May 25, 2016): 696–701. http://dx.doi.org/10.1002/mus.25065.

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13

Chu, Kelvin HT, Xianta Jiang, and Carlo Menon. "Wearable step counting using a force myography-based ankle strap." Journal of Rehabilitation and Assistive Technologies Engineering 4 (January 2017): 205566831774630. http://dx.doi.org/10.1177/2055668317746307.

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Introduction Step counting can be used to estimate the activity level of people in daily life; however, commercially available accelerometer-based step counters have shown inaccuracies in detection of low-speed walking steps (&lt;2.2 km/h), and thus are not suitable for older adults who usually walk at low speeds. This proof-of-concept study explores the feasibility of using force myography recorded at the ankle to detect low-speed steps. Methods Eight young healthy participants walked on a treadmill at three speeds (1, 1.5, and 2.0 km/h) while their force myography signals were recorded at th
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14

Kobelev, A. V., and S. I. Shchukin. "Antropomorphic Prothesis Control Based on Electric Impedance Myography." Физические основы приборостроения 8, no. 4 (December 15, 2019): 62–68. http://dx.doi.org/10.25210/jfop-1904-062068.

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15

Smith, D., J. Stout, T. Housh, G. Johnson, T. Evetovich, and K. Ebersole. "ELECTROMYOGRAPHY, ACOUSTIC MYOGRAPHY, AND ECCENTRIC ISOKINETIC PEAK TORQUE1000." Medicine &amp Science in Sports &amp Exercise 28, Supplement (May 1996): 168. http://dx.doi.org/10.1097/00005768-199605001-00997.

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16

Evetovich, T., J. Stout, T. Housh, G. Johnson, D. Smith, and K. Ebersole. "ELECTROMYOGRAPHY, ACOUSTIC MYOGRAPHY, AND CONCENTRIC ISOKINETIC PEAK TORQUE1001." Medicine &amp Science in Sports &amp Exercise 28, Supplement (May 1996): 168. http://dx.doi.org/10.1097/00005768-199605001-00998.

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17

Kwon, H., S. B. Rutkove, and B. Sanchez. "Recording characteristics of electrical impedance myography needle electrodes." Physiological Measurement 38, no. 9 (August 21, 2017): 1748–65. http://dx.doi.org/10.1088/1361-6579/aa80ac.

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18

Rutkove, Seward. "Electrical impedance myography as a biomarker for ALS." Lancet Neurology 8, no. 3 (March 2009): 226. http://dx.doi.org/10.1016/s1474-4422(09)70030-4.

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19

Stokes, M. J., and P. A. Dalton. "Acoustic myography for investigating human skeletal muscle fatigue." Journal of Applied Physiology 71, no. 4 (October 1, 1991): 1422–26. http://dx.doi.org/10.1152/jappl.1991.71.4.1422.

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Sounds produced during voluntary isometric contractions of the quadriceps muscle were studied by acoustic myography (AMG) in five healthy adults. With the subject seated, isometric force, surface electromyography (EMG), and AMG were recorded over rectus femoris, and the EMG and AMG signals were integrated (IEMG and IAMG). Contractions lasting 5 s each were performed at 10, 25, 50, 60, 75, and 100% of maximum voluntary contraction (MVC) force. Fatigue was then induced by repeated voluntary contractions (10 s on, 10 s off) at 75% MVC until only 40% MVC could be sustained. After 15 min of rest, t
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20

Rutkove, Seward B., Ramon A. Partida, Gregory J. Esper, Ronald Aaron, and Carl A. Shiffman. "Electrode position and size in electrical impedance myography." Clinical Neurophysiology 116, no. 2 (February 2005): 290–99. http://dx.doi.org/10.1016/j.clinph.2004.09.002.

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21

Jiang, Xianta, Lukas-Karim Merhi, and Carlo Menon. "Force Exertion Affects Grasp Classification Using Force Myography." IEEE Transactions on Human-Machine Systems 48, no. 2 (April 2018): 219–26. http://dx.doi.org/10.1109/thms.2017.2693245.

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22

Godiyal, Anoop Kant, Milton Mondal, Shiv Dutt Joshi, and Deepak Joshi. "Force Myography Based Novel Strategy for Locomotion Classification." IEEE Transactions on Human-Machine Systems 48, no. 6 (December 2018): 648–57. http://dx.doi.org/10.1109/thms.2018.2860598.

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23

Xiao, Zhen Gang, and Carlo Menon. "A Review of Force Myography Research and Development." Sensors 19, no. 20 (October 20, 2019): 4557. http://dx.doi.org/10.3390/s19204557.

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Information about limb movements can be used for monitoring physical activities or for human-machine-interface applications. In recent years, a technique called Force Myography (FMG) has gained ever-increasing traction among researchers to extract such information. FMG uses force sensors to register the variation of muscle stiffness patterns around a limb during different movements. Using machine learning algorithms, researchers are able to predict many different limb activities. This review paper presents state-of-art research and development on FMG technology in the past 20 years. It summari
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24

Rutkove, S. "S77: Electrical impedence myography and amyotrophic lateral sclerosis." Clinical Neurophysiology 125 (June 2014): S18. http://dx.doi.org/10.1016/s1388-2457(14)50076-4.

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25

Spieker, Andrew J., Pushpa Narayanaswami, Laura Fleming, John C. Keel, Stefan C. Muzin, and Seward B. Rutkove. "Electrical impedance myography in the diagnosis of radiculopathy." Muscle & Nerve 48, no. 5 (September 11, 2013): 800–805. http://dx.doi.org/10.1002/mus.23833.

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26

Rutkove, Seward B., Gregory J. Esper, Kyungmouk S. Lee, Ronald Aaron, and Carl A. Shiffman. "Electrical impedance myography in the detection of radiculopathy." Muscle & Nerve 32, no. 3 (2005): 335–41. http://dx.doi.org/10.1002/mus.20377.

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27

Esper, Gregory J., Carl A. Shiffman, Ronald Aaron, Kyungmouk S. Lee, and Seward B. Rutkove. "Assessing neuromuscular disease with multifrequency electrical impedance myography." Muscle & Nerve 34, no. 5 (2006): 595–602. http://dx.doi.org/10.1002/mus.20626.

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28

Rutkove, Seward B., Patricia M. Fogerson, Lindsay P. Garmirian, and Andrew W. Tarulli. "Reference values for 50-kHZ electrical impedance myography." Muscle & Nerve 38, no. 3 (September 2008): 1128–32. http://dx.doi.org/10.1002/mus.21075.

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29

Rutkove, Seward B., Jeremy M. Shefner, Matt Gregas, Hailly Butler, Jayson Caracciolo, Connie Lin, Patricia M. Fogerson, Phillip Mongiovi, and Basil T. Darras. "Characterizing spinal muscular atrophy with electrical impedance myography." Muscle & Nerve 42, no. 6 (November 22, 2010): 915–21. http://dx.doi.org/10.1002/mus.21784.

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30

Zakia, Umme, and Carlo Menon. "Dataset on Force Myography for Human–Robot Interactions." Data 7, no. 11 (November 8, 2022): 154. http://dx.doi.org/10.3390/data7110154.

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Force myography (FMG) is a contemporary, non-invasive, wearable technology that can read the underlying muscle volumetric changes during muscle contractions and expansions. The FMG technique can be used in recognizing human applied hand forces during physical human robot interactions (pHRI) via data-driven models. Several FMG-based pHRI studies were conducted in 1D, 2D and 3D during dynamic interactions between a human participant and a robot to realize human applied forces in intended directions during certain tasks. Raw FMG signals were collected via 16-channel (forearm) and 32-channel (fore
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31

Kadkhodayan, Anita, Xianta Jiang, and Carlo Menon. "Continuous Prediction of Finger Movements Using Force Myography." Journal of Medical and Biological Engineering 36, no. 4 (July 29, 2016): 594–604. http://dx.doi.org/10.1007/s40846-016-0151-y.

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32

Sanford, Joe, Rita Patterson, and Dan O. Popa. "Concurrent surface electromyography and force myography classification during times of prosthetic socket shift and user fatigue." Journal of Rehabilitation and Assistive Technologies Engineering 4 (January 2017): 205566831770873. http://dx.doi.org/10.1177/2055668317708731.

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Objective Surface electromyography has been a long-standing source of signals for control of powered prosthetic devices. By contrast, force myography is a more recent alternative to surface electromyography that has the potential to enhance reliability and avoid operational challenges of surface electromyography during use. In this paper, we report on experiments conducted to assess improvements in classification of surface electromyography signals through the addition of collocated force myography consisting of piezo-resistive sensors. Methods Force sensors detect intrasocket pressure changes
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33

Briko, Andrey, Vladislava Kapravchuk, Alexander Kobelev, Alexey Tikhomirov, Ahmad Hammoud, Mugeb Al-Harosh, Steffen Leonhardt, Chuong Ngo, Yury Gulyaev, and Sergey Shchukin. "Determination of the Geometric Parameters of Electrode Systems for Electrical Impedance Myography: A Preliminary Study." Sensors 22, no. 1 (December 24, 2021): 97. http://dx.doi.org/10.3390/s22010097.

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The electrical impedance myography method is widely used in solving bionic control problems and consists of assessing the change in the electrical impedance magnitude during muscle contraction in real time. However, the choice of electrode systems sizes is not always properly considered when using the electrical impedance myography method in the existing approaches, which is important in terms of electrical impedance signal expressiveness and reproducibility. The article is devoted to the determination of acceptable sizes for the electrode systems for electrical impedance myography using the P
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34

Te Winkel, Jan, Quincy E. John, Brian D. Hosfield, Natalie A. Drucker, Amitava Das, Ken R. Olson, and Troy A. Markel. "Mesenchymal stem cells promote mesenteric vasodilation through hydrogen sulfide and endothelial nitric oxide." American Journal of Physiology-Gastrointestinal and Liver Physiology 317, no. 4 (October 1, 2019): G441—G446. http://dx.doi.org/10.1152/ajpgi.00132.2019.

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Mesenteric ischemia is a devastating process that can result in intestinal necrosis. Mesenchymal stem cells (MSCs) are becoming a promising treatment modality. We hypothesized that 1) MSCs would promote vasodilation of mesenteric arterioles, 2) hydrogen sulfide (H2S) would be a critical paracrine factor of stem cell-mediated vasodilation, 3) mesenteric vasodilation would be impaired in the absence of endothelial nitric oxide synthase (eNOS) within the host tissue, and 4) MSCs would improve the resistin-to-adiponectin ratio in mesenteric vessels. H2S was measured with a specific fluorophore (7-
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35

Bellemare, François, Jacques Couture, François Donati, and Benoît Plaud. "Temporal Relation between Acoustic and Force Responses at the Adductor Pollicis during Nondepolarizing Neuromuscular Block." Anesthesiology 93, no. 3 (September 1, 2000): 646–52. http://dx.doi.org/10.1097/00000542-200009000-00012.

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Background Contracting muscle emits sounds. The purpose of this study was to compare the time course of muscular paralysis at the adductor pollicis muscle (AP) with use of acoustic myography and mechanomyography. Methods Thirteen elective surgery patients, American Society of Anesthesiologists physical status I, received rocuronium (0.6 mg/kg intravenously) as a bolus dose during general anesthesia. Force of AP was measured with use of a strain gauge, and sounds were recorded simultaneously with use of a small condenser microphone fixed on the palmar surface of the hand over the AP. Supramaxim
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36

Prakash, Alok, Neeraj Sharma, and Shiru Sharma. "An affordable transradial prosthesis based on force myography sensor." Sensors and Actuators A: Physical 325 (July 2021): 112699. http://dx.doi.org/10.1016/j.sna.2021.112699.

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37

Stokes, M. J. "Acoustic Myography: Applications and Considerations in Measuring Muscle Performance." Isokinetics and Exercise Science 3, no. 1 (January 1, 1993): 4–15. http://dx.doi.org/10.3233/ies-1993-3101.

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38

Shiffman, C. A., H. Kashuri, and R. Aaron. "Electrical impedance myography at frequencies up to 2 MHz." Physiological Measurement 29, no. 6 (June 1, 2008): S345—S363. http://dx.doi.org/10.1088/0967-3334/29/6/s29.

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39

Belyea, Alexander T., Kevin B. Englehart, and Erik J. Scheme. "A proportional control scheme for high density force myography." Journal of Neural Engineering 15, no. 4 (June 19, 2018): 046029. http://dx.doi.org/10.1088/1741-2552/aac89b.

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40

Sanchez, Benjamin, and Seward B. Rutkove. "Electrical Impedance Myography and Its Applications in Neuromuscular Disorders." Neurotherapeutics 14, no. 1 (November 3, 2016): 107–18. http://dx.doi.org/10.1007/s13311-016-0491-x.

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41

Rutkove, Seward B., Kyungmouk S. Lee, Carl A. Shiffman, and Ronald Aaron. "Test–retest reproducibility of 50kHz linear-electrical impedance myography." Clinical Neurophysiology 117, no. 6 (June 2006): 1244–48. http://dx.doi.org/10.1016/j.clinph.2005.12.029.

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42

Nie, Rui, N. Abimbola Sunmonu, Anne B. Chin, Kyungmouk S. Lee, and Seward B. Rutkove. "Electrical impedance myography: Transitioning from human to animal studies." Clinical Neurophysiology 117, no. 8 (August 2006): 1844–49. http://dx.doi.org/10.1016/j.clinph.2006.03.024.

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43

Rutkove, S., A. Chin, C. Shiffman, and R. Aaron. "P22.9 Measurement of muscle anisotropy using electrical impedance myography." Clinical Neurophysiology 117 (September 2006): 102. http://dx.doi.org/10.1016/j.clinph.2006.06.426.

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44

L'ESTRANGE, P. R., J. ROWELL, and M. J. STOKES. "Acoustic myography in the assessment of human masseter muscle." Journal of Oral Rehabilitation 20, no. 4 (July 1993): 353–62. http://dx.doi.org/10.1111/j.1365-2842.1993.tb01618.x.

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45

Schwartz, Daniel P., Jahannaz Dastgir, Anam Salman, Barbara Lear, Carsten G. Bönnemann, and Tanya J. Lehky. "Electrical impedance myography discriminates congenital muscular dystrophy from controls." Muscle & Nerve 53, no. 3 (August 13, 2015): 402–6. http://dx.doi.org/10.1002/mus.24770.

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46

Rutkove, Seward B., Kush Kapur, Craig M. Zaidman, Jim S. Wu, Amy Pasternak, Lavanya Madabusi, Sung Yim, et al. "Electrical impedance myography for assessment of Duchenne muscular dystrophy." Annals of Neurology 81, no. 5 (May 2017): 622–32. http://dx.doi.org/10.1002/ana.24874.

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47

Rutkove, Seward B. "Electrical impedance myography: Background, current state, and future directions." Muscle & Nerve 40, no. 6 (December 2009): 936–46. http://dx.doi.org/10.1002/mus.21362.

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48

Tarulli, Andrew W., Naven Duggal, Gregory J. Esper, Lindsay P. Garmirian, Patricia M. Fogerson, Connie H. Lin, and Seward B. Rutkove. "Electrical Impedance Myography in the Assessment of Disuse Atrophy." Archives of Physical Medicine and Rehabilitation 90, no. 10 (October 2009): 1806–10. http://dx.doi.org/10.1016/j.apmr.2009.04.007.

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49

Seliverstova, Ekaterina G., Mikhail V. Sinkin, Anton Y. Kordonsky, and Andrey A. Grin. "Value of paraspinal muscle myography in diagnosing L5 radiculopathy." Annals of Clinical and Experimental Neurology 17, no. 3 (September 29, 2023): 66–73. http://dx.doi.org/10.54101/acen.2023.3.8.

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Introduction. Electromyography (EMG) is an important diagnostic tool for the evaluation of radiculopathy. Since 1990s a paraspinal mapping technique is used, which detects spontaneous activity in paraspinal muscles (PM) at the level of several vertebral segments. This modality seems to be highly conclusive for diagnosing radicular lesions. The main limitation of this method is spontaneous activity dependence on the disease duration.&#x0D; The aim of the study is to assess if PM EMG with motor unit potential (MUP) analysis is conclusive for diagnosing lumbar radiculopathy.&#x0D; Materials and m
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50

Zakia, Umme, and Carlo Menon. "Detecting Safety Anomalies in pHRI Activities via Force Myography." Bioengineering 10, no. 3 (March 5, 2023): 326. http://dx.doi.org/10.3390/bioengineering10030326.

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The potential application of using a wearable force myography (FMG) band for monitoring the occupational safety of a human participant working in collaboration with an industrial robot was studied. Regular physical human–robot interactions were considered as activities of daily life in pHRI (pHRI-ADL) to recognize human-intended motions during such interactions. The force myography technique was used to read volumetric changes in muscle movements while a human participant interacted with a robot. Data-driven models were used to observe human activities for useful insights. Using three unsuperv
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