L'évaluation des tensions musculaires chez l'Homme dans les sciences du mouvement et les études posturales présente un grand intérêt pour le sport, la santé ou encore l'ergonomie. La biomécanique s'intéresse tout particulièrement à ces problèmes utilise la cinématique inverse pour recalculer, à partir de mesures physiques externes, les tensions musculaires internes. Le verrou scientifique principal de cette technique est la redondance musculaire, propre au vivant. En effet les actionneurs (muscles) sont plus nombreux que les degrés de liberté à contrôler. Les problèmes de cinématique inverse sont sous-déterminés, ils présentent plus d'inconnues que d'équations, et nécessitent l'usage de procédures d'optimisation. Dans ce contexte l'usage de l'électromyographie (EMG), signal électro-physiologique mesurable à la surface de la peau et témoin de l'activité musculaire, peut donner une idée de l'activité des muscles sous-jacents. La connaissance de l'activité des muscles permettrait d'introduire de l'information supplémentaire dans cette méthodologie inverse afin d'améliorer l'estimation des tensions musculaires réelles au cours de mouvements ou dans une posture donnée. De plus certaines applications ne permettent pas ou peu l'enregistrement de forces ou positions articulaires externes qui nécessitent un appareillage conséquent et rendent difficile l'étude de situations de la vie courante. L'électromyographie est dans un tel contexte une mesure non-invasive et peu encombrante, facilement réalisable. Elle a cependant elle aussi ses propres verrous scientifiques. L'EMG de surface sur de petits muscles très rapprochés comme les nombreux muscles des avant-bras peut être sujette à ce qui est communément appelé « cross-talk » ; la contamination croisée des voies. Ce cross-talk est le résultat de la propagation des signaux musculaires sur plusieurs voies simultanément, si bien qu'il est compliqué d'associer l'activité d'un muscle à une unique voie EMG. Le traitement numérique du signal dispose d'outils permettant, dans certaines conditions, de retrouver des sources inconnues mélangées sur plusieurs capteurs. Ainsi la séparation de sources peut être utilisée sur des signaux EMG afin de retrouver de meilleures estimations des signaux sources reflétant plus fidèlement l'activité de muscles sans l'effet du cross-talk. Ce travail de thèse montre dans un premier temps l'intérêt de l'EMG dans l'étude de l'utilisation d'un prototype d'interface homme-machine novateur. L'EMG permet en particulier de mettre en évidence la présence forte de cocontraction musculaire permettant de stabiliser les articulations pour permettre un contrôle précis du dispositif. En outre des perspectives d'analyse plus fines seraient envisageables en utilisant des techniques de séparation de sources performantes en électromyographie. Dans un second temps l'accent est mis sur l'étude des conditions expérimentales précises permettant l'utilisation des techniques de séparation de sources en contexte linéaire instantané en électromyographie de surface. L'hypothèse d'instantanéité du mélange des sources en particulier est étudiée et sa validité est vérifiée sur des signaux réels. Enfin une solution d'amélioration de la robustesse de la séparation de sources à l'hypothèse de l'instantanéité est proposée. Celle-ci repose sur la factorisation en matrices non-négatives (NMF) des enveloppes des signaux EMG. / Evaluation of muscle tensions in movement and gait sciences is of great interest in the fields of sports, health or ergonomics. Biomechanics in particular has been looking forward to solving these problems and developed the use of inverse kinematics to compute internal muscle tensions from external physical measures. Muscular redundancy remains however a complex issue, there are more muscles than degrees of freedom and thus more unknown variables which makes inverse kinematics an under-determined problem needing optimization techniques to be solved. In this context using electromyography (EMG), an electro-physiological signal that can be measured on the skin surface, gives an idea of underlying muscle activities. Knowing muscle activities could be additional information to feed the optimization procedures with and could help improving accuracy of estimated muscle tensions during real gestures or gait situation. There are even situations in which measuring external physical variables like forces, positions or accelerations is not feasible because it might require equipment incompatible with the object of the study. It is often the case in ergonomics when equipping the object of the study with sensors is either too expensive or physically too cumbersome. In such cases EMG can become very handy as a non-invasive measure that does not require the environment to be equipped with other sensors. EMG however has its own limits, surface EMG on small and closely located muscles like muscles of the forearm can be subject to “cross-talk”. Cross-talk is the cross contamination of several sensors it is the result of signal propagation of more than one muscle on one sensor. In presence of cross-talk it is not possible to associate an EMG sensor with a given muscle. There are signal processing techniques dealing with this kind of problem. Source separation techniques allow estimation of unknown sources from several sensors recording mixtures of these sources. Applying source separation techniques on EMG can provide EMG source estimations reflecting individual muscle activities without the effect of cross-talk. First the benefits of using surface EMG during an ergonomics study of an innovative human-computer interface are shown. EMG pointed out a relatively high level of muscle co-contraction that can be explained by the need to stabilize the joints for a more accurate control of the device. It seems legitimate to think that using source separation techniques would provide signals that better represent single muscle activities and these would improve the quality of this study. Then the precise experimental conditions for linear instantaneous source separation techniques to work are studied. Validity of the instantaneity hypothesis in particular is tested on real surface EMG signals and its strong dependency on relative sensor locations is shown. Finally a method to improve robustness of linear instantaneous source separation versus instantaneity hypothesis is proposed. This method relies on non-negative matrix factorization of EMG signal envelopes.

Venous thromboembolism (VTE) is one of the most common cardiovascular diseases. KTH and its academic and industrial partners intend to develop a system to combat VTE by forcing movements of inactive muscles. An important part of this system is a unit that can sense muscular activity over time. Electromyography (EMG) is used to measure the activation potential of muscles. The goal of this thesis is to develop an EMG device that can measure bioelectric signals and convey this data to other devices. This thesis is mainly an exploration to identify the potential solution and more work is needed to develop the required system. The EMG device must be small, modular, battery powered and be able to communicate wirelessly with other devices. A functioning EMG system requires an appropriate amplification for the result to be legible and requires extensive filtering as well as detailed circuit board design to eliminate noise or interference that can affect the result.This project utilized a top down approach. An architecture of the EMG system was made and broken down into functional blocks. Each block was implemented separately and the whole solution was tested experimentally to ensure that all the specifications were fulfilled. To validate the EMG device, a series of reference images were used together with directly observing the correlation between muscle activation and its signal with an oscilloscope.The result was a fully functional EMG device that consisted of two PCB: a PCB with EMG circuitry (analog circuit) and a PCB with digital processing for communication (digital circuit). The EMG results were consistent between test subjects and could easily be correlated to muscle movement and force. The reference images indicated that it was functioning as intended. There was still 50 Hz common mode noise present in the EMG device which could have been due to its wide bandwidth and poor low frequency properties.The goals and requirements were fulfilled: a fully functional wireless, modular, small and battery driven EMG device was developed. The noise level of the EMG could have been lower and would need some further improvements. An integrated battery could be implemented to eliminate the need for users to provide a battery. An app could be developed in tandem with the EMG device, with friendly user interface, for healthcare personnel.The thesis workers strived to minimize the number of used components and power consumption. All components were RoHS certified and discarded components were collected for proper waste management. Energy consumption could have been further minimized in the digital PCB by implementing sleep mode and a watchdog timer. This thesis strived to implement as much of the 17 global sustainability goals set by the United Nations (UN). In conclusion, the main sustainability goal of this thesis was “3 – Good Health and well-being”. Other sustainability goals were “12 – Responsible consumption and production”, “13 – Climate action”, “15 – Life on land” were deemed to have been considered in this thesis. / Venös tromboemboli (VTE) är en av de vanligaste kardiovaskulära sjukdomarna. KTH och dess akademiska och industriella partner avser att utveckla ett system med uppdrag att bekämpa VTE genom att stimulera inaktiva muskler. Elektromyografi (EMG) används för att mäta musklernas aktiveringspotential. Syftet med denna avhandling är att utveckla en EMG-enhet som kan mäta bioelektriska signaler och överföra denna data till andra enheter. Ett fungerande EMG system kräver en lämplig förstärkning för att resultatet ska vara läsbart och kräver filtrering samt utförlig kretskortdesign för att eliminera brus/störningar som kan påverka resultatet negativt.Projektet använde en Top-Down strategi. En arkitektur av EMG-systemet genomfördes och sedan delades upp i funktionella block. Varje block implementerades separat och hela lösningen testades experimentellt för att säkerställa att alla specifikationer uppfylldes. För att validera EMG- enheten användes referensbilder tillsammans med att direkt observera sambandet mellan muskelaktivering och dess signal via ett oscilloskop.Resultatet var en helt funktionell EMG-enhet som bestod av två PCB: en PCB med EMG funktionalitet (analog krets) och en PCB med digital processering för kommunikation (digital krets). EMG mätningarna var konsistenta mellan testpersoner och kunde lätt korreleras med muskelrörelse och spänningskraft. Referensbilderna indikerade att den fungerade som avsedd. Det fanns fortfarande 50 Hz common mode brus i EMG-enheten, vilket kan ha orsakas av dess breda bandbredd och dåliga lågfrekvensegenskaper.Målen och kraven uppfylldes: en fullt funktionell trådlös, modulär, liten och batteridriven EMG- enhet. Brusnivån för EMG kunde ha varit lägre och skulle behöva ytterligare förbättringar. Ett integrerat batteri kunde implementeras för att eliminera användarnas behov av att tillhandahålla ett batteri. En applikation kunde ha utvecklats för EMG-enheten, med ett användarvänligt användargränssnitt, för vårdpersonal.Examensarbetarna strävade efter att minimera användning av komponenter och strömförbrukning under arbetsprocessen. Alla komponenter var RoHS-certifierade och kasserade komponenter insamlades för korrekt avfallshantering. Energiförbrukning kunde ha minimerats ytterligare i det digitala kretskortet genom att implementera sleep mode och en watchdog timer. I detta examensarbete var det önskvärt att implemnetera de 17 globala hållbarhetsmålen uppsatta av FN (Förenta Nationerna). Sammanfattningsvis uppfylldes huvudsakligen “3 – Good Health and well-being”. Hållbarhetsmålen ”12 - Ansvarig konsumtion och produktion”, ”13 – Klimatåtgärder”, ”15 - Liv på land” anses även att ha beaktas i denna avhandling.

No description available.

No description available.

В данной магистерской работе мы исследуем возможности построения словаря волн биомедицинских сигналов электрокардиограммы, который в дальнейшем позволит применять методы NLP для обработки временных рядов биомедицинских сигналов. В частности, мы сосредоточимся на анализе структуры пиков и интервалов электрокардиограммы здоровых и больных аритмией и другими заболеваниями людей, средствами языка python и автоматизации этого процесса для извлечения значимой информации из биомедицинских временных рядов ЭКГ. Наша конечная цель – улучшение точности и эффективности обработки и анализа биомедицинских сигналов, что имеет важное значение как для клинической диагностики, так и для научных исследований. Решение этой задачи имеет большое практическое значение для различных областей, таких как медицина, биология и фармакология, где обработка и анализ временных рядов играют важную роль. / In this master's thesis, we are exploring the possibility of constructing a dictionary of waves of biomedical electrocardiogram signals, which in the future will allow the use of NLP methods for processing time series of biomedical signals. In particular, we will focus on analyzing the structure of peaks and intervals of the electrocardiogram of healthy people and patients with arrhythmia and other diseases, using the Python language and automating this process to extract meaningful information from biomedical ECG time series. Our ultimate goal is to improve the accuracy and efficiency of biomedical signal processing and analysis, which is important for both clinical diagnostics and scientific research. The solution to this problem is of great practical importance for various fields, such as medicine, biology and pharmacology, where processing and analysis of time series play an important role.

With recent advances in electronics and communication technologies, our daily lives are immersed in an environment of Internet-connected smart things. Despite the great convenience brought by the development of these technologies, privacy concerns and security issues are two topics that deserve more attention. On one hand, as smart things continue to grow in their abilities to sense the physical world and capabilities to send information out through the Internet, they have the potential to be used for surveillance of any individuals secretly. Nevertheless, people tend to adopt wearable devices without fully understanding what private information can be inferred and leaked through sensor data. On the other hand, security issues become even more serious and lethal with the world embracing the Internet of Things (IoT). Failures in computing systems are common, however, a failure now in IoT may harm people's lives. As demonstrated in both academic research and industrial practice, a software vulnerability hidden in a smart vehicle may lead to a remote attack that subverts a driver's control of the vehicle. Our approach to the aforementioned challenges starts by understanding privacy leakage in the IoT era and follows with adding defense layers to the IoT system with attackers gaining increasing capabilities. The first question we ask ourselves is "what new privacy concerns do IoT bring". We focus on discovering information leakage beyond people's common sense from even seemingly benign signals. We explore how much private information we can extract by designing information extraction systems. Through our research, we argue for stricter access control on newly coming sensors. After noticing the importance of data collected by IoT, we trace where sensitive data goes. In the IoT era, edge nodes are used to process sensitive data. However, a capable attacker may compromise edge nodes. Our second research focuses on applying trusted hardware to build trust in large-scale networks under this circumstance. The application of trusted hardware protects sensitive data from compromised edge nodes. Nonetheless, if an attacker becomes more powerful and embeds malicious logic into code for trusted hardware during the development phase, he still can secretly steal private data. In our third research, we design a static analyzer for detecting malicious logic hidden inside code for trusted hardware. Other than the privacy concern of data collected, another important aspect of IoT is that it affects the physical world. Our last piece of research work enables a user to verify the continuous execution state of an unmanned vehicle. This way, people can trust the integrity of the past and present state of the unmanned vehicle. / Doctor of Philosophy / The past few years have witnessed a rising in computing and networking technologies. Such advances enable the new paradigm, IoT, which brings great convenience to people's life. Large technology companies like Google, Apple, Amazon are creating smart devices such as smartwatch, smart home, drones, etc. Compared to the traditional internet, IoT can provide services beyond digital information by interacting with the physical world by its sensors and actuators. While the deployment of IoT brings value in various aspects of our society, the lucrative reward from cyber-crimes also increases in the upcoming IoT era. Two unique privacy and security concerns are emerging for IoT. On one hand, IoT brings a large volume of new sensors that are deployed ubiquitously and collect data 24/7. User's privacy is a big concern in this circumstance because collected sensor data may be used to infer a user's private activities. On the other hand, cyber-attacks now harm not only cyberspace but also the physical world. A failure in IoT devices could result in loss of human life. For example, a remotely hacked vehicle could shut down its engine on the highway regardless of the driver's operation. Our approach to emerging privacy and security concerns consists of two directions. The first direction targets at privacy protection. We first look at the privacy impact of upcoming ubiquitous sensing and argue for stricter access control on smart devices. Then, we follow the data flow of private data and propose solutions to protect private data from the networking and cloud computing infrastructure. The other direction aims at protecting the physical world. We propose an innovative method to verify the cyber state of IoT devices.

Nous avons étudié les effets de la baisse de la vigilance sur les mécanismes de contrôle de l'erreur lors d'une tâche de temps de réaction de choix (TR). Lors de la première expérience, la baisse de vigilance a été obtenue par un éveil prolongé de 26 heures. Dans les expériences deux et trois, on a diminué le niveau de vigilance par voie pharmacologique en choisissant de n'affecter qu'une des voies neurochimiques impliquées dans l'éveil (voie histaminergique puis voie dopaminergique) pour déterminer si les indices du contrôle de l'erreur seraient ou non affectés de la même façon qu'après un éveil prolongé. Si oui, cela supposerait un effet redondant des systèmes neurochimiques impliqués dans l'éveil sur le contrôle de l'erreur, dans le cas contraire, cela supposerait une influence spécifique de ces différents systèmes sur le contrôle de l'erreur. Le contrôle de l'erreur peut être décomposé en contrôle proactif et contrôle réactif. Ce contrôle de l'erreur est dit en ligne s'il opère au cours d'un essai, hors-ligne s'il s'opère d'un essai sur l'autre.La privation de sommeil affecte le contrôle de l'erreur proactif en ligne et le contrôle de l'erreur réactif. La baisse de l'activité histaminergique n'affecte que le contrôle de l'erreur réactif et on n'a pas mis en évidence d'effets de la déplétion dopaminergique sur le contrôle de l'erreur. Les effets observés sur le contrôle de l'erreur par la baisse de vigilance induite par la privation de sommeil n'étaient pas reproduits par la baisse de vigilance induite par les déplétions des activités dopaminergiques et histaminergiques, suggérant des influences spécifiques de ces deux voies sur le contrôle de l'erreur. / To study the impact of a vigilance decrease on error monitoring mechanisms in healthy participants, electromyogram and electroencephalogram were recorded during a choice reaction time task. The aim of experiment one was to decipher which indices of error monitoring at the behavioral and electrophysiological levels, were altered by sleep deprivation. In experiments two and three, decreases in vigilance were obtained through pharmacological treatments. We attempted to selectively inhibit one arousal system (either by acting on the histaminergic or on the dopaminergic pathway), so as to determine whether indices of error monitoring would be affected in the same way than after extended wakefulness. Proactive (implemented before an error execution) and reactive modes (implemented after an error execution) of error monitoring were distinguished. Within each mode, we further distinguished on-line (implemented within-trial) and off-line (between-trials) processes.Proactive off-line monitoring was unaffected by the decrease in vigilance, whether this caused by extended wakefulness, histaminergic depeltion or dopaminergic depletion). Sleep deprivation affected proactive on-line and off-line monitoring and reactive control. Histaminergic depletion affected only reactive control and reactive control seemed insensitive to dopaminergic depletion.As sleep deprivation, both histaminergic and dopaminergic depletion induced decrease in vigilance. However, effects of sleep deprivation on error monitoring were entirely reproduced neither by histaminergic nor by dopaminergic depletion, suggesting specific influences of the corresponding systems on error monitoring.

Objective: Cervical vestibular evoked myogenic potentials (cVEMPs) are short-latency electromyogram (EMG) evoked by high-level acoustic stimuli recorded from the activated sternocleidomastoid muscle and used to evaluate otolith organ function. The purpose of this study was to investigate the effects of aging on the cVEMP and on the sternocleidomastoid muscle EMG level. Design: A cross-sectional observational study was used to investigate differences in cVEMP and sternocleidomastoid muscle EMG level in a group of 24 younger and 24 older individuals. cVEMPs were recorded during activation of the sternocleidomastoid muscle at target EMG levels ranging from 0 to 90 μV and during maximum voluntary contraction of the sternocleidomastoid muscle. Results: The sternocleidomastoid muscle EMG amplitude increased as a function of target EMG level for both age groups; however, the mean EMG amplitude was greater for the younger group than the older group, and the variability of EMG amplitude was greater for the older group. The EMG amplitude at maximum voluntary contraction ranged from 88 to 279 μV for the younger subjects and from 32 to 230 μV for the older subjects, and the mean EMG amplitude at maximum voluntary contraction was significantly greater for the younger group than the older group. The cVEMP amplitude increased as a function of EMG target level for each age group. Although cVEMP amplitude increased as a function of target EMG level for both groups, the older group exhibited smaller cVEMP amplitudes, overall, compared with the younger group. To separate the influence of EMG level from aging on cVEMP amplitude, only the responses obtained at the 30 μV target EMG level were considered for the statistical analysis because there was no significant difference in EMG level between groups at the 30 μV target level. The mean cVEMP amplitudes at the 30 μV target level were 101 and 51 μV for the younger and older groups, respectively, and a statistical analysis indicated that cVEMP amplitude for the younger group was significantly greater than the older group. Conclusions: The findings suggest that the decrement in cVEMP amplitude is related to both age-related changes in the vestibular system and age-related changes in the sternocleidomastoid muscle.

A recent model of Parkinson’s disease (PD) suggests that the neuropathological, behavioural and cognitive symptoms progress in stages. There is substantial evidence for a prodromal stage of PD, during which time pre-motor symptoms develop. Rapid eye movement (REM) sleep behaviour disorder (RBD) is a risk factor for developing PD and may be part of the pre-motor stage. In both disorders, neuropathological α-synuclein aggregates are thought to be a direct cause of the resulting symptoms. One model has shown that in rats, proteasome inhibition produced by systemic exposure to environmental toxins results in α-synuclein pathology and motor behaviour dysfunction that mimics the progression of PD in humans. The present study examined the hypothesis that the systemic proteasome inhibition model would produce pre-Parkinsonian RBD-like pathology in rats. It was expected that sleep disturbances would be seen prior to behavioural disturbances in rats treated systemically with PSI (a proteasome inhibitor). Following baseline sleep recording and training on the inclined beam-traverse task, rats were injected with PSI (a proteasome inhibitor) or ethanol (control), 6 times over 2 wk. Sleep recording over 8 wk and behavioural testing over 16 wk provided no evidence of sleep disturbances or motor dysfunction. Post-mortem immunohistochemical analyses of brain tissue provided no evidence of PSI-associated α-synuclein aggregates in the locus coeruleus, subcoeruleus (dorsal part), or substantia nigra (areas involved in RBD and/or PD). These results did not provide support for RBD as a prodromal phase of PD within the systemic proteasome inhibitor-based model and add to a growing body of research reporting inconsistent findings using this model. We suggest that systemic PSI exposure in rats does not produce a viable model of RBD or PD. Whether RBD is an early symptom in the progression of PD remains to be established. / Thesis (Master, Neuroscience Studies) -- Queen's University, 2010-04-28 12:04:50.613

A constantly growing corpus of interdisciplinary studies support the idea that music is a complex multimodal medium that is experienced not only by means of sounds but also through body movement. From this perspective, musical instruments can be seen as technological objects coupled with a repertoire of performance gestures. This repertoire is part of an ecological knowledge shared by musicians and listeners alike. It is part of the engine that guides musical experience and has a considerable expressive potential. This thesis explores technical and conceptual issues related to the analysis and creative use of music-related body movements in instrumental music performance. The complexity of this subject required an interdisciplinary approach, which includes the review of multiple theoretical accounts, quantitative and qualitative analysis of data collected in motion capture laboratories, the development and implementation of technologies for the interpretation and interactive use of motion data, and the creation of short musical pieces that actively employ the movement of the performers as an expressive musical feature. The theoretical framework is informed by embodied and enactive accounts of music cognition as well as by systematic studies of music-related movement and expressive music performance. The assumption that the movements of a musician are part of a shared knowledge is empirically explored through an experiment aimed at analysing the motion capture data of a violinist performing a selection of short musical excerpts. A group of subjects with no prior experience playing the violin is then asked to mime a performance following the audio excerpts recorded by the violinist. Motion data is recorded, analysed, and compared with the expert’s data. This is done both quantitatively through data analysis xii as well as qualitatively by relating the motion data to other high-level features and structures of the musical excerpts. Solutions to issues regarding capturing and storing movement data and its use in real-time scenarios are proposed. For the interactive use of motion-sensing technologies in music performance, various wearable sensors have been employed, along with different approaches for mapping control data to sound synthesis and signal processing parameters. In particular, novel approaches for the extraction of meaningful features from raw sensor data and the use of machine learning techniques for mapping movement to live electronics are described. To complete the framework, an essential element of this research project is the com- position and performance of études that explore the creative use of body movement in instrumental music from a Practice-as-Research perspective. This works as a test bed for the proposed concepts and techniques. Mapping concepts and technologies are challenged in a scenario constrained by the use of musical instruments, and different mapping ap- proaches are implemented and compared. In addition, techniques for notating movement in the score, and the impact of interactive motion sensor systems in instrumental music practice from the performer’s perspective are discussed. Finally, the chapter concluding the part of the thesis dedicated to practical implementations describes a novel method for mapping movement data to sound synthesis. This technique is based on the analysis of multimodal motion data collected from multiple subjects and its design draws from the theoretical, analytical, and practical works described throughout the dissertation. Overall, the parts and the diverse approaches that constitute this thesis work in synergy, contributing to the ongoing discourses on the study of musical gestures and the design of interactive music systems from multiple angles.