Bibliografías temáticas / Movement detection system

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Literatura académica sobre el tema "Movement detection system"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 17 de febrero de 2022

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Artículos de revistas sobre el tema "Movement detection system"

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Kozhekin, Nikita, Ichiro Hagiwara, Mikhail Senin y Vladimir Savchenko. "Simple CSRBF animation system with movement interpolation and collision detection". Proceedings of Design & Systems Conference 2004.14 (2004): 99–100. http://dx.doi.org/10.1299/jsmedsd.2004.14.99.

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Kozhekin, N., I. Hagiwara, M. Senin y V. Savchenko. "Simple CSRBF animation system with movement interpolation and collosion detection". Proceedings of The Computational Mechanics Conference 2004.17 (2004): 213–14. http://dx.doi.org/10.1299/jsmecmd.2004.17.213.

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Nakano, T. "System for driver's eye movement detection". JSAE Review 16, n.º 1 (enero de 1995): 74–76. http://dx.doi.org/10.1016/0389-4304(94)00054-w.

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Mohd Tamil, Emran, Ti Siang Tey, Mohd Rais Mustafa, Mohd Yamani Idna Idris y Mohd Hairul Nizam Md Nasir. "Automated Clinical Research Mice Movement Detection System". International Journal of Technology, Knowledge, and Society 4, n.º 6 (2008): 63–76. http://dx.doi.org/10.18848/1832-3669/cgp/v04i06/55953.

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Felisberto, Filipe, Rosalía Laza, Florentino Fdez-Riverola y António Pereira. "A Distributed Multiagent System Architecture for Body Area Networks Applied to Healthcare Monitoring". BioMed Research International 2015 (2015): 1–17. http://dx.doi.org/10.1155/2015/192454.

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In the last years the area of health monitoring has grown significantly, attracting the attention of both academia and commercial sectors. At the same time, the availability of new biomedical sensors and suitable network protocols has led to the appearance of a new generation of wireless sensor networks, the so-called wireless body area networks. Nowadays, these networks are routinely used for continuous monitoring of vital parameters, movement, and the surrounding environment of people, but the large volume of data generated in different locations represents a major obstacle for the appropriate design, development, and deployment of more elaborated intelligent systems. In this context, we present an open and distributed architecture based on a multiagent system for recognizing human movements, identifying human postures, and detecting harmful activities. The proposed system evolved from a single node for fall detection to a multisensor hardware solution capable of identifying unhampered falls and analyzing the users’ movement. The experiments carried out contemplate two different scenarios and demonstrate the accuracy of our proposal as a real distributed movement monitoring and accident detection system. Moreover, we also characterize its performance, enabling future analyses and comparisons with similar approaches.
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Srikanth, K. "Alert System for Fall Detection". International Journal for Research in Applied Science and Engineering Technology 9, n.º 8 (31 de agosto de 2021): 1739–47. http://dx.doi.org/10.22214/ijraset.2021.37658.

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Abstract: Healthcare is one of the most important industries, yet new ideas must travel a long way before being fully adopted due to its complexity, scope of duty, and stringent laws. The Internet of Things (IoT) may be the key to resolving healthcare challenges. The Internet of Things (IoT) has a lot of potential in healthcare, but it's still in its early stages. With the advancement of medical IoT, new possibilities for telemedicine, remote monitoring of a patient's status, and much more will emerge. Falling is a significant health danger for the elderly. If the problem is not detected in a timely manner, it can result in the death or impairment of the elderly, lowering their quality of life. Falls are a major public health concern for the elderly around the world. When it comes to old age, we must keep an eye on our loved ones to ensure their health and safety. It is therefore critical to determine if an elderly person has fallen so that help can be provided promptly. Proposing a person fall detection system based on a wearable device for detecting the falls of people in every situation, which takes advantage of lowpower wireless sensor networks, smart devices, and analyses human body motions. The system detects movement using an accelerometer and a gyro sensor. The sensor is wired to a microprocessor, which transmits the acceleration data continuously. Fall detection and sudden movement changes in the person would be monitored by the system. The sensors are getting values from a quick movement shift with shock in the system. When a person falls and becomes unconscious, the system determines whether the person has indeed fallen. If the person has truly fallen, the system will send an alert to the caregivers and sound an alarm to alert anyone nearby. When the system detects that a person has fallen, it immediately sends an alert to the individual's care takers. It is an IoT-based fall detection system that assists people by telling their caregivers about their fall so that quick attention may be drawn to the situation and essential actions can be taken to save the person who has fallen. Keywords: Threshold Based Fall Detection, Arduino, Bi-Axial, Accelerometer, Gyroscope,
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Che, Zhong-Yong y Sangchul Kim. "A Surveillance System Using Images and Movement Detection Sensors". Journal of the Institute of Webcasting, Internet and Telecommunication 13, n.º 1 (28 de febrero de 2013): 181–89. http://dx.doi.org/10.7236/jiibc.2013.13.1.181.

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Baec, Sung-Ho, Min-Sik Jeon y Bong-Jin Ko. "Implementation of Movement Detection System for Patient on Bed". Journal of Korea Navigation Institute 19, n.º 5 (30 de octubre de 2015): 458–63. http://dx.doi.org/10.12673/jant.2015.19.5.458.

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Lin, Chih-Lung, Wen-Ching Chiu, Ting-Ching Chu, Yuan-Hao Ho, Fu-Hsing Chen, Chih-Cheng Hsu, Ping-Hsiao Hsieh et al. "Innovative Head-Mounted System Based on Inertial Sensors and Magnetometer for Detecting Falling Movements". Sensors 20, n.º 20 (12 de octubre de 2020): 5774. http://dx.doi.org/10.3390/s20205774.

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This work presents a fall detection system that is worn on the head, where the acceleration and posture are stable such that everyday movement can be identified without disturbing the wearer. Falling movements are recognized by comparing the acceleration and orientation of a wearer’s head using prespecified thresholds. The proposed system consists of a triaxial accelerometer, gyroscope, and magnetometer; as such, a Madgwick’s filter is adopted to improve the accuracy of the estimation of orientation. Moreover, with its integrated Wi-Fi module, the proposed system can notify an emergency contact in a timely manner to provide help for the falling person. Based on experimental results concerning falling movements and activities of daily living, the proposed system achieved a sensitivity of 96.67% in fall detection, with a specificity of 98.27%, and, therefore, is suitable for detecting falling movements in daily life.
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Lin, Chin-Teng, Wei-Ling Jiang, Sheng-Fu Chen, Kuan-Chih Huang y Lun-De Liao. "Design of a Wearable Eye-Movement Detection System Based on Electrooculography Signals and Its Experimental Validation". Biosensors 11, n.º 9 (17 de septiembre de 2021): 343. http://dx.doi.org/10.3390/bios11090343.

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In the assistive research area, human–computer interface (HCI) technology is used to help people with disabilities by conveying their intentions and thoughts to the outside world. Many HCI systems based on eye movement have been proposed to assist people with disabilities. However, due to the complexity of the necessary algorithms and the difficulty of hardware implementation, there are few general-purpose designs that consider practicality and stability in real life. Therefore, to solve these limitations and problems, an HCI system based on electrooculography (EOG) is proposed in this study. The proposed classification algorithm provides eye-state detection, including the fixation, saccade, and blinking states. Moreover, this algorithm can distinguish among ten kinds of saccade movements (i.e., up, down, left, right, farther left, farther right, up-left, down-left, up-right, and down-right). In addition, we developed an HCI system based on an eye-movement classification algorithm. This system provides an eye-dialing interface that can be used to improve the lives of people with disabilities. The results illustrate the good performance of the proposed classification algorithm. Moreover, the EOG-based system, which can detect ten different eye-movement features, can be utilized in real-life applications.
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Tesis sobre el tema "Movement detection system"

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Liu, Yi. "Movement detection in outdoor scenes for traffic monitoring". Thesis, University of Ottawa (Canada), 2004. http://hdl.handle.net/10393/26698.

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One important application of image processing and computer vision is traffic monitoring and control. In this thesis, a system for detection of moving vehicles approaching an intersection from a sequence of color images acquired by a stationary camera in the context of traffic light control systems is presented. As the system is dedicated to outdoor applications, efficient and robust vehicle detection under various weather and illumination conditions is examined. To deal with these ever changing conditions, vehicle detection relies on motion segmentation and on an original algorithm using color mapping to achieve feature space segmentation. Experimental results on real outdoor sequences of images demonstrate the system's robustness under various environmental conditions.
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Zhu, Shiping. "Robust detection of object movement by a mobile camera system". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq28696.pdf.

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Blanchard, Jonathan Mark. "Collision avoidance : a biologically inspired neural network for the detection of approaching objects". Thesis, University of Newcastle upon Tyne, 1998. http://hdl.handle.net/10443/3590.

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The frequently studied lobula giant movement detector (LGMD) system of the locust responds most strongly to approaching objects. This thesis describes simulations which were designed with the ultimate aim of constructing a comprehensive model of the neural circuitry showing the effects of individual neurons on the overall responses of the system. The Rind and Bramwell neural network model of the LGMD was studied using new stimuli which revealed that the responses of the model are dependent on the shape of the stimulus. A modification of the model removes this dependence and allows the model to respond to more complex stimuli. Two models of a locust photoreceptor were developed with the aim of producing a detailed model of a light-adapting photoreceptor which could be used to study the responses of the LGMD to natural scenes. The first model, an electrical model of the cell membrane which describes the principal ionic conductances, was found to be overly complex for use in large scale simulations. However, the model was used to calculate from the photoreceptor's impulse response the average conductance change produced by individual photons. The second photoreceptor model, which is suitable for large scale simulations, uses two leaky integrators to mimic the effects of light adaptation on the photoreceptor's response. An electrical model of the lamina region of the optic lobe allowed the proposal that inhibition in the lamina is produced by electrical presynaptic inhibition to be studied, along with the possible effects of this inhibition on the visual input to the LGMD. The responses of the model correspond well with those measured from the LMCs of locusts and other insects, and their implications for the LGMD system are discussed.
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Feng, Dehua. "Determining Intersection Turning Movements with Detection Errors". University of Akron / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=akron1512746695445707.

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Jalloul, Nahed. "Development of a system of acquisition and movement analysis : application on Parkinson's disease". Thesis, Rennes 1, 2016. http://www.theses.fr/2016REN1S096/document.

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Le travail présenté dans ce mémoire porte sur le développement d'un système de surveillance ambulatoire pour la détection de la dyskinésie induite par la Levodopa (LID) chez les patients de la maladie de Parkinson (PD). Le système est composé d’unités de mesure inertielle (IMUs) qui recueillent des signaux de mouvement chez des sujets sains et des patients parkinsoniens. Des méthodes différentes sont évaluées pour la détection de LID avec et sans classification des activités. Les données recueillies auprès des sujets sains sont utilisées pour concevoir un classificateur d'activité fiable. Par la suite, un algorithme qui effectue la classification des activités et la détection de la dyskinésie sur les données recueillies auprès de des patients parkinsoniens est proposé. Une nouvelle approche basée sur l'analyse de réseau complexe est également explorée et présente des résultats intéressants. Les méthodes de traitement développées ont été intégrées dans une plateforme complète d’analyse nommée PARADYSE
The work presented in this thesis is concerned with the development of an ambulatory monitoring system for the detection of Levodopa Induced Dyskinesia (LID) in Parkinson’s disease (PD) patients. The system is composed of Inertial Measurement Units (IMUs) that collect movement signals from healthy individuals and PD patients. Different methods are evaluated which consist of LID detection with and without activity classification. Data collected from healthy individuals is used to design a reliable activity classifier. Following that, an algorithm that performs activity classification and dyskinesia detection on data collected from PD patients is tested. A new approach based on complex network analysis is also explored and presents interesting results. The evaluated analysis methods are incorporated into a platform PARADYSE in order to further advance the system’s capabilities
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Uppströmer, Viktor y Henning Råberg. "Detecting Lateral Movement in Microsoft Active Directory Log Files : A supervised machine learning approach". Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18337.

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Cyberattacker utgör ett stort hot för dagens företag och organisationer, med engenomsnittlig kostnad för ett intrång på ca 3,86 miljoner USD. För att minimera kostnaden av ett intrång är det viktigt att detektera intrånget i ett så tidigt stadium som möjligt. Avancerande långvariga hot (APT) är en sofistikerad cyberattack som har en lång närvaro i offrets nätverk. Efter attackerarens första intrång kommer fokuset av attacken skifta till att få kontroll över så många enheter som möjligt på nätverket. Detta steg kallas för lateral rörelse och är ett av de mest kritiska stegen i en APT. Syftet med denna uppsats är att undersöka hur och hur väl lateral rörelse kan upptäckas med hjälp av en maskininlärningsmetod. I undersökningen jämförs och utvärderas fem maskininlärningsalgoritmer med upprepad korsvalidering följt av statistisk testning för att bestämma vilken av algoritmerna som är bäst. Undersökningen konkluderar även vilka attributer i det undersökta datasetet som är väsentliga för att detektera laterala rörelser. Datasetet kommer från en Active Directory domänkontrollant där datasetets attributer är skapade av korrelerade loggar med hjälp av datornamn, IP-adress och användarnamn. Datasetet består av en syntetisk, samt, en verklig del vilket skapar ett semi-syntetiskt dataset som innehåller ett multiklass klassifierings problem. Experimentet konkluderar att all fem algoritmer klassificerar rätt med en pricksäkerhet (accuracy) på 0.998. Algoritmen RF presterar med den högsta f-measure (0.88) samt recall (0.858), SVM är bäst gällande precision (0.972) och DT har denlägsta inlärningstiden (1237ms). Baserat på resultaten indikerar undersökningenatt algoritmerna RF, SVM och DT presterar bäst i olika scenarier. Till exempel kan SVM användas om en låg mängd falsk positiva larm är viktigt. Om en balanserad prestation av de olika prestanda mätningarna är viktigast ska RF användas. Undersökningen konkluderar även att en stor mängd utav de undersökta attributerna av datasetet kan bortses i framtida experiment, då det inte påverkade prestandan på någon av algoritmerna.
Cyber attacks raise a high threat for companies and organisations worldwide. With the cost of a data breach reaching $3.86million on average, the demand is high fora rapid solution to detect cyber attacks as early as possible. Advanced persistent threats (APT) are sophisticated cyber attacks which have long persistence inside the network. During an APT, the attacker will spread its foothold over the network. This stage, which is one of the most critical steps in an APT, is called lateral movement. The purpose of the thesis is to investigate lateral movement detection with a machine learning approach. Five machine learning algorithms are compared using repeated cross-validation followed statistical testing to determine the best performing algorithm and feature importance. Features used for learning the classifiers are extracted from Active Directory log entries that relate to each other, with a similar workstation, IP, or account name. These features are the basis of a semi-synthetic dataset, which consists of a multiclass classification problem. The experiment concludes that all five algorithms perform with an accuracy of 0.998. RF displays the highest f1-score (0.88) and recall (0.858), SVM performs the best with the performance metric precision (0.972), and DT has the lowest computational cost (1237ms). Based on these results, the thesis concludes that the algorithms RF, SVM, and DT perform best in different scenarios. For instance, SVM should be used if a low amount of false positives is favoured. If the general and balanced performance of multiple metrics is preferred, then RF will perform best. The results also conclude that a significant amount of the examined features can be disregarded in future experiments, as they do not impact the performance of either classifier.
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Yekhshatyan, Lora. "Detecting distraction and degraded driver performance with visual behavior metrics". Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/910.

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Driver distraction contributes to approximately 43% of motor-vehicle crashes and 27% of near-crashes. Rapidly developing in-vehicle technology and electronic devices place additional demands on drivers, which might lead to distraction and diminished capacity to perform driving tasks. This situation threatens safe driving. Technology that can detect and mitigate distraction by alerting drivers could play a central role in maintaining safety. Correctly identifying driver distraction in real time is a critical challenge in developing distraction mitigation systems, and this function has not been well developed. Moreover, the greatest benefit may be from real-time distraction detection in advance of dangerous breakdowns in driver performance. Based on driver performance, two types of distraction - visual and cognitive - are identified. These types of distraction have very different effects on visual behavior and driving performance; therefore, they require different algorithms for detection. Distraction detection algorithms typically rely on either eye measures or driver performance measures because the effect of distraction on the coordination of measures has not been established. Combining both eye glance and vehicle data could enhance the ability of algorithms to detect and differentiate visual and cognitive distraction. The goal of this research is to examine whether poor coordination between visual behavior and vehicle control can identify diminished attention to driving in advance of breakdowns in lane keeping. The primary hypothesis of this dissertation is that detection of changes in eye-steering relationship caused by distraction could provide a prospective indication of vehicle state changes. Three specific aims are pursued to test this hypothesis. The first aim examines the effect of distracting activity on eye and steering movements to assess the degree to which the correlation parameters are indicative of distraction. The second aim applies a control-theoretic system identification approach to the eye movement and steering data to distinguish between distracted and non-distracted conditions. The third aim examines whether changes of eye-steering coordination associated with distraction provide a prospective indication of breakdowns in driver performance, i.e., lane departures. Together, the three aims show how that a combination of visual and steering behavior, i.e., eye-steering model, can differentiate between non-distracted and distracted state. This model revealed sensitivity to distraction associated with off-road glances. The models derived for different drivers have similar structure and fit to data from other drivers reasonably well. In addition, the differences in model order and model coefficients indicate the variability in driving behavior: some people generate more complex behavior than others. As was expected, eye-steering correlation on straight roads is not as strong as observed on curvy roads. However, eye-steering correlation measured through correlation coefficient and time delay between two movements is sensitive to different types of distraction. Time delay mediates changes in lane position and the eye-steering system predicts breakdowns in lane keeping. This dissertation contributes to developing a distraction detection system that integrates visual and steering behavior. More broadly, these results suggest that integrating eye and steering data can be helpful in detecting and mitigating impairments beyond distraction, such as those associated with alcohol, fatigue, and aging.
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8

Al, Mahdawi Basil Mohamed Nouri. "Senior monitoring by using sensors network and optical metrology". Thesis, Bourgogne Franche-Comté, 2017. http://www.theses.fr/2017UBFCD085.

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L’objectif du travail de cette thèse est la contribution au développement de nouvelles techniques dans le domaine dessystèmes de détection sans marqueur pour une utilisation dans trois domaines vitaux de la santé en utilisant des capteursinnovants et peu coûteux. Pour la réalisation de nos objectifs nous avons eu recours principalement à de l’électroniqueembarquées et du traitement du signal en utilisant le capteur Kinect. Des résultats encourageants ont été obtenus et sontprésentés tout au long de cette thèse. Dans la première partie de ce travail, nous présentons un nouveau système desurveillance visuelle sans marqueur en temps réel pour détecter et suivre les personnes âgées et surveiller leurs activitésdans leur environnement intérieur en utilisant un réseau de capteurs Kinect. Le système identifie également l’événementde chute des personnes âgées sous surveillance. Dans la deuxième partie nous utilisons également le capteur Kinectmais cette fois ci pour la détection sans marqueur des mouvements de la tête d’un patient lors d’un examen utilisant LaTomographie par Emission de Positons (CT/PET) du cerveau. Ce travail est basé sur la compensation de la dégradationde l’image TEP due aux mouvements de la tête du patient. Pour nos essais un cobaye dit « fantôme » a été réalisé,les résultats sur le fantôme sont prometteur ce qui a donné lieu à un test sur un vrai patient volontaire. Les résultatsfinaux montrent l’efficacité de ce nouveau système. La troisième partie du travail présente la mise en oeuvre d’un nouveausystème intelligent pour contrôler un fauteuil roulant électrique par des mouvements spéciaux de la tête toujours sansmarqueur. Un algorithme adapté est conçu pour détecter en continu les degrés des mouvements du visage en utilisant lecapteur Kinect. Fautes de fauteuil roulant électrique, le système a été testé sur un véhicule radio commandé
The objective of the work of this thesis is the contribution in developing novel technical methods in the field of marker-lesssensing systems for use in three vital health areas by using new inexpensive sensors. Several scientific areas are involvedin achieving our objective such as; electronics and signal processing by using the Kinect sensor. Encouraging results wereachieved as presented throughout this thesis. In the first part of this work we present a new real-time marker-less visualsurveillance system for detecting and tracking seniors and monitoring their activities in the indoor environment by usingnetwork of Kinect sensors. The system also identifies the fall event with the elderly. In the second part, we present anew approach for a marker-less movement detection system for influential head movements in the brain Positron EmissionTomography imaging (CT/PET) by employing the Kinect sensor. This work addresses the compensation of the PET imagedegradation due to subject’s head movements. A developed particular phantom and volunteer studies were carried out.The experimental results show the effectiveness of this new system. The third part of the work presents the design andimplementation of a new smart system for controlling an electric wheelchair by special mark-less head movements. Anadaptable algorithm is designed to continuously detect the rotation degrees of the face pose using the Kinect sensor inreal-time that are interpreted as controlling signals through a hardware interface for the electric wheelchair actuators
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Giesel, M., A. Yakovleva, Marina Bloj, A. R. Wade, A. M. Norcia y J. M. Harris. "Relative contributions to vergence eye movements of two binocular cues for motion-in-depth". Springer Nature Group, 2019. http://hdl.handle.net/10454/17514.

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Yes
When we track an object moving in depth, our eyes rotate in opposite directions. This type of “disjunctive” eye movement is called horizontal vergence. The sensory control signals for vergence arise from multiple visual cues, two of which, changing binocular disparity (CD) and inter-ocular velocity differences (IOVD), are specifically binocular. While it is well known that the CD cue triggers horizontal vergence eye movements, the role of the IOVD cue has only recently been explored. To better understand the relative contribution of CD and IOVD cues in driving horizontal vergence, we recorded vergence eye movements from ten observers in response to four types of stimuli that isolated or combined the two cues to motion-in-depth, using stimulus conditions and CD/IOVD stimuli typical of behavioural motion-in-depth experiments. An analysis of the slopes of the vergence traces and the consistency of the directions of vergence and stimulus movements showed that under our conditions IOVD cues provided very little input to vergence mechanisms. The eye movements that did occur coinciding with the presentation of IOVD stimuli were likely not a response to stimulus motion, but a phoria initiated by the absence of a disparity signal.
Supported by NIH EY018875 (AMN), BBSRC grants BB/M001660/1 (JH), BB/M002543/1 (AW), and BB/MM001210/1 (MB).
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Mills, Clayton Harry. "Movement and Force Measurement Systems as a Foundation for Biomimetic Research on Insects". Thesis, University of Canterbury. Electrical and Computer Engineering, 2008. http://hdl.handle.net/10092/2895.

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During the undertaken research and development, two major systems were designed. These were; a prototype force sensor, and a movement measurement system. Both the developed systems were designed for the intended field of insect research, but were developed using very different underlying principles. The force measurement system uses the piezo-electric effect induced in piezo-electric bimorph elements to produce a measure of force exerted on the sensor. The movement measurement system on the other hand uses computer vision (CV) techniques to find and track the three dimensional (3D) position of markers on the insect, and thereby record the pose of the insect. To further increase the usefulness of the two measurement systems, a prototype graphical user interface (GUI) was produced to encapsulate the functionality of the systems and provide an end user with a more complete and functional research tool. The GUI allows a user to easily define the parameters required for the CV operations and presents the results of these operations to the user in an easily understood visual format. The GUI is also intended to display force measurements in a graphical means to make them easily interpreted. The GUI has been named Weta Evaluation Tracking and Analysis (WETA). Testing on the developed prototype force sensor shows that the piezo-electric bimorph elements provide an adequate measure of force exerted on them, when the voltage signal produced by an element is integrated. Furthermore, the testing showed that the developed force sensor layout produces an adequate measure of forces in the two horizontal linear degrees of freedom (DOF), but the prototype did not produce a good measure of forces in the vertical linear DOF. Development and testing of the movement measurement system showed that stereo vision techniques have the ability to produce accurate measurements of 3D position using two cameras. Although, when testing these techniques with one of the cameras replaced by a mirror, the system produced less than satisfactory results. Further testing on the feature detection and tracking portions of the movement system showed that even though these systems were implemented in a relatively simple way, they were still adequate in their associated operations. However, it was found that with some simple changes in colour spaces used during feature detection, the performance of the feature detection system in varying illumination was greatly improved. The tracking system on the other hand, operated adequately using just its associated basic principles. During the development of both prototype measurement systems, a number of conclusions were formulated that indicated areas of future development. These areas include; advanced force sensor configurations, force sensor miniaturisation, design of a force plate, improvement of feature detection and tracking, and refining of the stereo vision equipment.
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Libros sobre el tema "Movement detection system"

1

Sharpe, Sybil. Search and surveillance: The movement from evidence to information. Aldershot: Ashgate/Dartmouth, 2000.

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2

Sharpe, Sybil. Search and Surveillance: The Movement from Evidence to Information. Taylor & Francis Group, 2017.

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3

Terrigenous Mass Movements Detection Modelling Early Warning And Mitigation Using Geoinformation Technology. Springer, 2012.

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4

Mohamed Fathy Hassan.* El-Maghraby. Use of geodetic methods in detecting terrain movements with special reference to the global positioning system. 1991.

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5

Michelle, Sneed, Coachella Valley Water District (Calif.) y Geological Survey (U.S.), eds. Detection and measurement of land subsidence using Global Positioning System and interferometric synthetic aperture radar, Coachella Valley, California, 1996-98. Sacramento, Calif: U.S. Dept. of the Interior, U.S. Geological Survey, 2001.

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Mason, Peggy. The Vestibular Sense. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190237493.003.0018.

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The vestibular system contains semicircular canals that respond to angular acceleration and otoconial organs that respond to linear acceleration of the head. Information is sent to the motor system and, under normal circumstances, does not lead to conscious perception. Yet damage to the vestibular system can result in disequilibrium or vertigo, disturbing perceptions that dominate conscious experience. The shared residence of the cochlear and vestibular end organs in the inner ear can give rise to inner ear disorders such as Ménière’s disease. The effect of gravity on the otoconial masses in the sacculus and utriculus enable detection of static head tilt. Age-related disequilibrium, benign paroxysmal positional vertigo, motion sickness, and alcohol intoxication–induced vertigo are explained. How natural head movements elicit combined canal and otoconial organ responses is described. Finally, the dependence of posture and gaze on vestibular inputs is introduced as a segue to the next chapter.
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Phillips, Ian. No More than Meets the Eye. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198722304.003.0009.

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This chapter develops a view of shadows as pure visibilia: objects constitutively and exhaustively connected in nature, existence and qualities to our experience of them. It takes as its stalking horse Sorensen’s very different view, arguing that, contrary to his intended purpose, the hypothesis that shadows are pure visibilia provides a more satisfying account of his striking cases of shadow movement. The claim that shadows are pure visibilia is further motivated by drawing on considerations from aesthetics and vision science. The chapter ends with a puzzle: if shadows do not strictly represent independent elements of our environments, why do we perceive them at all? A speculative answer is tendered. Shadows are visual artefacts: creatures of the light world, carved by our visual systems in the service of the better detection and discrimination of ordinary material objects.
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Mazer, Jeffrey y Mitchell M. Levy. Policies, bundles, and protocols in critical care. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0017.

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Recently, the medicine community has been driven to think about patient safety in new ways, and with this new found interest in patient safety, large health care systems and individual institutions have been forced to develop mechanisms to track and measure performance. There is ample evidence that physicians and systems can do better. The tools of this new craft include checklists, protocols, guidelines, and bundles. These tools help to decrease variability in care and enhance the translation of evidence-based medicine to bedside care. Ongoing measurement of both performance and clinical outcomes is central to this movement. This allows for rapid detection of both successes and possible unintended consequences associated with the rapid translation of evidence into practice. As hospitals and intensive care units (ICU) worldwide have embraced the field of quality improvement (QI), many lessons have been learned about the process. QI includes four essential phases—development, implementation, evaluation, and maintenance. Essential to the QI process and each of these QI phases is that the project must be tailored to each individual ICU and/or Institution. A one-size-fits-all project is less efficient, less effective, and at times unnecessary compare with a locally-driven process.
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Mauguière, François y Luis Garcia-Larrea. Somatosensory and Pain Evoked Potentials. Editado por Donald L. Schomer y Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0043.

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This chapter discusses the use of somatosensory evoked potentials (SEPs) and pain evoked potentials for diagnostic purposes. The generators of SEPs following upper limb stimulation have been identified through intracranial recordings, permitting the analysis of somatosensory disorders caused by neurological diseases. Laser activation of fibers involved in thermal and pain sensation has extended the applications of evoked potentials to neuropathic pain disorders. Knowledge of the effects of motor programming, paired stimulations, and simultaneous stimulation of adjacent somatic territories has broadened SEP use in movement disorders. The recording of high-frequency cortical oscillations evoked by peripheral nerve stimulation gives access to the functioning of SI area neuronal circuitry. SEPs complement electro-neuro-myography in patients with neuropathies and radiculopathies, spinal cord and hemispheric lesions, and coma. Neuroimaging has overtaken SEPs in detecting and localizing central nervous system lesions, but SEPs still permit assessment of somatosensory and pain disorders that remain unexplained by anatomical investigations.
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Jacquemyn, Yves y Anneke Kwee. Antenatal and intrapartum fetal evaluation. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198713333.003.0006.

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Antenatal and intrapartum fetal monitoring aim to identify the beginning of the process of fetal hypoxia before irreversible fetal damage has taken place. Fetal movement counting by the mother has not been reported to be of any benefit. The biophysical profile score, incorporating ultrasound and fetal heart rate monitoring, has not been proven to reduce perinatal mortality in randomized trials. Doppler ultrasound allows the exploration of the perfusion of different fetal organ systems and provides data on possible hypoxia and fetal anaemia. Maternal uterine artery Doppler can be used to select women with a high risk for intrauterine growth restriction and pre-eclampsia but does not directly provide information on fetal status. Umbilical artery Doppler has been shown to reduce perinatal mortality significantly in high-risk pregnancies (but not in low-risk women). Adding middle cerebral artery Doppler to umbilical artery Doppler does not increase accuracy for detecting adverse perinatal outcome. Ductus venosus Doppler demonstrates moderate value in diagnosing fetal compromise; it is not known whether its use adds any value to umbilical artery Doppler alone. Cardiotocography (CTG) reflects the interaction between the fetal brain and peripheral cardiovascular system. Prelabour routine use of CTG in low-risk pregnancies has not been proven to improve outcome; computerized CTG significantly reduces perinatal mortality in high-risk pregnancies. Monitoring the fetus during labour with intermittent auscultation has not been compared to no monitoring at all; when compared with CTG no difference in perinatal mortality or cerebral palsy has been noted. CTG does lower neonatal seizures and is accompanied by a statistically non-significant rise in caesarean delivery. Fetal blood sampling to detect fetal pH and base deficit lowers caesarean delivery rate and neonatal convulsions when used in adjunct to CTG. Determination of fetal scalp lactate has not been shown to have an effect on neonatal outcome or on the rate of instrumental deliveries but is less often hampered by technical failure than fetal scalp pH. Analysis of the ST segment of the fetal ECG (STAN®) in combination with CTG during labour results in fewer vaginal operative deliveries, less need for neonatal intensive care, and less use of fetal blood sampling during labour, without a change in fetal metabolic acidosis when compared to CTG alone.
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Capítulos de libros sobre el tema "Movement detection system"

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Mendes, Paulo A. S. y A. Paulo Coimbra. "Movement Detection and Moving Object Distinction Based on Optical Flow for a Surveillance System". En Transactions on Engineering Technologies, 143–58. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8273-8_12.

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Iwamoto, Shinnosuke, Takashi Sakamoto, Toru Nakata y Toshikazu Kato. "Detection System for Distinguishing Between Initial Reading and Rereading of a Digital Document by Observing Focal Point Movement". En Advances in Intelligent Systems and Computing, 78–83. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60018-5_8.

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Hwang, Chi Yeon, Geun do Park, Hyang Jun Jeong, In Gyu Park, Yun Joong Kim, Hyeo-Il Ma y Unjoo Lee. "A Portable and User Friendly REM Sleep Detection System Based on Differential Movement of Eyeball Using Optical Sensors". En Communications in Computer and Information Science, 224–28. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58750-9_32.

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Shin, Jaewan, Dongkyoo Shin, Dongil Shin, Sungmin Her, Soohan Kim y Myungsoo Lee. "Human Movement Detection Algorithm Using 3-Axis Accelerometer Sensor Based on Low-Power Management Scheme for Mobile Health Care System". En Advances in Grid and Pervasive Computing, 81–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13067-0_12.

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Bessonova, Yulia V. y Alexander A. Oboznov. "Eye Movements and Lie Detection". En Intelligent Human Systems Integration, 149–55. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-73888-8_25.

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Hatori, Ayaka. "Automatic Movement Detection Using Mobile Phones". En Advances in Intelligent Systems and Computing, 325–29. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61578-3_50.

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Reda, Radwa, Manal Tantawi, Howida shedeed y Mohamed F. Tolba. "Analyzing Electrooculography (EOG) for Eye Movement Detection". En Advances in Intelligent Systems and Computing, 179–89. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14118-9_18.

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Shameem Sharmina, C. H. y Rajesh Reghunadhan. "Electromyography-Based Detection of Human Hand Movement Gestures". En Algorithms for Intelligent Systems, 729–35. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5243-4_69.

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Guevara, Cesar, Matilde Santos y Janio Jadán. "Movement Detection Algorithm for Patients with Hip Surgery". En Advances in Intelligent Systems and Computing, 439–48. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94120-2_42.

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Li, Ci-Rong, Chie-Yang Kuan, Bing-Zhe He, Wu-En Wu, Chi-Yao Weng y Hung-Min Sun. "A Security System Based on Door Movement Detecting". En Intelligent Data analysis and its Applications, Volume I, 155–63. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07776-5_17.

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Actas de conferencias sobre el tema "Movement detection system"

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Paputungan, Irving Vitra, Mahbub Ramadhan Al Fitri y Unan Yusmaniar Oktiawati. "Motion and Movement Detection for DIY Home Security System". En 2019 IEEE Conference on Sustainable Utilization and Development in Engineering and Technologies (CSUDET). IEEE, 2019. http://dx.doi.org/10.1109/csudet47057.2019.9214684.

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Fourlas, George K. y Ilias Maglogiannis. "Human movement detection using attitude and heading reference system". En the 7th International Conference. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2674396.2674454.

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Tangsuksant, Watcharin, Chittaphon Aekmunkhongpaisal, Patthiya Cambua, Theekapun Charoenpong y Theerasak Chanwimalueang. "Directional eye movement detection system for virtual keyboard controller". En 2012 5th Biomedical Engineering International Conference (BMEiCON). IEEE, 2012. http://dx.doi.org/10.1109/bmeicon.2012.6465432.

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Li, Xiao, Yu Yang, Yiming Xu, Chao Wang y Linyang Li. "Crowd Abnormal Behavior Detection Combining Movement and Emotion Descriptors". En ICNSER2020: The 2nd International Conference On Industrial Control Network And System Engineering Research. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3411016.3411166.

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Darmakusuma, Reza, Ary S. Prihatmanto, Adi Indrayanto y Tati L. Mengko. "Pattern recognition of finger movement detection using Support Vector Machine". En 2012 International Conference on System Engineering and Technology (ICSET). IEEE, 2012. http://dx.doi.org/10.1109/icsengt.2012.6339335.

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Izzuddin, T. A., M. A. Ariffin, Z. H. Bohari, R. Ghazali y M. H. Jali. "Movement intention detection using neural network for quadriplegic assistive machine". En 2015 IEEE International Conference on Control System, Computing and Engineering (ICCSCE). IEEE, 2015. http://dx.doi.org/10.1109/iccsce.2015.7482197.

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Azargoshasb, S., A. H. Korayem y Sh Tabibian. "A Voice Command Detection system for controlling Movement of SCOUT Robot". En 2018 6th RSI International Conference on Robotics and Mechatronics (IcRoM). IEEE, 2018. http://dx.doi.org/10.1109/icrom.2018.8657523.

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Parzych, M., A. Chmielewska, T. Marciniak, A. Dabrowski, A. Chrostowska y M. Klincewicz. "Automatic people density maps generation with use of movement detection analysis". En 2013 6th International Conference on Human System Interactions (HSI). IEEE, 2013. http://dx.doi.org/10.1109/hsi.2013.6577798.

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Chaudhary, Mitika, Vinay Prakash y Neeraj Kumari. "Identification Vehicle Movement Detection in Forest Area using MFCC and KNN". En 2018 International Conference on System Modeling & Advancement in Research Trends (SMART). IEEE, 2018. http://dx.doi.org/10.1109/sysmart.2018.8746936.

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Miron, Casian, Alexandru Pasarica, Dragos Arotaritei, Hariton Costin, Radu Gabriel Bozomitu y Cristian Rotariu. "Hand gesture detection using a stereo camera system and simulation of movement". En 2017 10th International Symposium on Advanced Topics in Electrical Engineering (ATEE). IEEE, 2017. http://dx.doi.org/10.1109/atee.2017.7905134.

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Informes sobre el tema "Movement detection system"

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Ianakiev, Kiril D. SNM Movement Detection / Radiation Sensors and Advanced Materials Portfolio Review RadSensing2011 6Li-Metal Based Neutron Detector Systems for Replacing 3He Gas Proportional Counters. Office of Scientific and Technical Information (OSTI), marzo de 2013. http://dx.doi.org/10.2172/1072253.

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