Recognition of elementary arm movements using orientation of a tri-axial accelerometer located near the wrist

In this paper we present a method for recognising three fundamental movements of the human arm (reach and retrieve, lift cup to mouth, rotation of the arm) by determining the orientation of a tri-axial accelerometer located near the wrist. Our objective is to detect the occurrence of such movements performed with the impaired arm of a stroke patient during normal daily activities as a means to assess their rehabilitation. The method relies on accurately mapping transitions of predefined, standard orientations of the accelerometer to corresponding elementary arm movements. To evaluate the technique, kinematic data was collected from four healthy subjects and four stroke patients as they performed a number of activities involved in a representative activity of daily living, 'making-a-cup-of-tea'. Our experimental results show that the proposed method can independently recognise all three of the elementary upper limb movements investigated with accuracies in the range 91–99% for healthy subjects and 70–85% for stroke patients

Feasibility of using combined EMG and kinematic signals for prosthesis control : A simulation study using a virtual reality environment

Acknowledgment This study was partly supported by a UK Medical Research Council Centenary Award to Keele University.Peer reviewedPublisher PD

Computational Intelligence in Electromyography Analysis

Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG may be used clinically for the diagnosis of neuromuscular problems and for assessing biomechanical and motor control deficits and other functional disorders. Furthermore, it can be used as a control signal for interfacing with orthotic and/or prosthetic devices or other rehabilitation assists. This book presents an updated overview of signal processing applications and recent developments in EMG from a number of diverse aspects and various applications in clinical and experimental research. It will provide readers with a detailed introduction to EMG signal processing techniques and applications, while presenting several new results and explanation of existing algorithms. This book is organized into 18 chapters, covering the current theoretical and practical approaches of EMG research

Computational Analysis of Upper Extremity Movements for People Post-Stroke

Wearable sensors have been beneficial in assessing motor impairment after stroke. Individuals who have experienced stroke may benefit from the use of wearable sensors to quantify and assess quality of motions in unobserved environments. Seven individuals participated in a study wherein they performed various gestures from the Fugl-Meyer Assessment (FMA), a measure of post-stroke impairment. Participants performed these gestures while being monitored by wearable sensors placed on each wrist. A series of MATLAB functions were written to process recorded sensor data, extract meaningful features from the data, and prepare those features for further use with various machine learning techniques. A combination of linear and nonlinear regression was applied to frequency domain values from each gesture to determine which can more accurately predict the time spent performing the gesture, and the associated gesture FMA score. General performance suggests that linear regression techniques appear to better fit paretic gestures, while nonlinear regression techniques appear to better fit non-paretic gestures. A use of classifier techniques were used to determine if a classifier can distinguish between paretic and non-paretic gestures. The combinations include determining if a higher performance is obtained through the use of either accelerometer, rate gyroscope, or both modalities combined. Our findings indicate that, for upper-extremity motion, classifiers trained using a combination of accelerometer and rate gyroscope data performed the best (accuracy of 73.1%). Classifiers trained using accelerometer data alone and rate gyroscope data alone performed slightly worse than the combined data classifier (70.2% and 65.7%, respectively). These results suggest specific features and methods suitable for the quantification of impairment after stroke

Gaze, visual, myoelectric, and inertial data of grasps for intelligent prosthetics

A hand amputation is a highly disabling event, having severe physical and psychological repercussions on a person’s life. Despite extensive efforts devoted to restoring the missing functionality via dexterous myoelectric hand prostheses, natural and robust control usable in everyday life is still challenging. Novel techniques have been proposed to overcome the current limitations, among them the fusion of surface electromyography with other sources of contextual information. We present a dataset to investigate the inclusion of eye tracking and first person video to provide more stable intent recognition for prosthetic control. This multimodal dataset contains surface electromyography and accelerometry of the forearm, and gaze, first person video, and inertial measurements of the head recorded from 15 transradial amputees and 30 able-bodied subjects performing grasping tasks. Besides the intended application for upper-limb prosthetics, we also foresee uses for this dataset to study eye-hand coordination in the context of psychophysics, neuroscience, and assistive robotics

Gaze, visual, myoelectric, and inertial data of grasps for intelligent prosthetics

A hand amputation is a highly disabling event, having severe physical and psychological repercussions on a person’s life. Despite extensive efforts devoted to restoring the missing functionality via dexterous myoelectric hand prostheses, natural and robust control usable in everyday life is still challenging. Novel techniques have been proposed to overcome the current limitations, among them the fusion of surface electromyography with other sources of contextual information. We present a dataset to investigate the inclusion of eye tracking and first person video to provide more stable intent recognition for prosthetic control. This multimodal dataset contains surface electromyography and accelerometry of the forearm, and gaze, first person video, and inertial measurements of the head recorded from 15 transradial amputees and 30 able-bodied subjects performing grasping tasks. Besides the intended application for upper-limb prosthetics, we also foresee uses for this dataset to study eye-hand coordination in the context of psychophysics, neuroscience, and assistive robotics

Sensing with the Motor Cortex

The primary motor cortex is a critical node in the network of brain regions responsible for voluntary motor behavior. It has been less appreciated, however, that the motor cortex exhibits sensory responses in a variety of modalities including vision and somatosensation. We review current work that emphasizes the heterogeneity in sensorimotor responses in the motor cortex and focus on its implications for cortical control of movement as well as for brain-machine interface development

Biomechanical gait pattern changes associated with functional fitness levels and falls in the elderly

Doutoramento em Motricidade Humana na especialidade de BiomecânicaThis thesis aimed to provide a better understanding on the determinant factors for falling in Portuguese older adults, with a special emphasis on the biomechanical changes in gait patterns associated with the functional fitness decline in this population. Our methodological approach to this problem encompassed two different levels of analysis: in the first part two epidemiological studies were conducted in order to establish the determinant factors for falling within the Portuguese older adults; in the second part three laboratory-based studies were performed in order to determine the influence of functional fitness levels on elderly gait patterns. Falls were shown to result from the interaction of many risk factors. Within these, gender, functional fitness level and health parameters were found to be the strongest fall determinants. Interestingly, age was not a determinant factor for falling, even within very old individuals (≥75 years or ≥80 years). Therefore, in the subsequent studies, the gait patterns of a subgroup of older adults, who had participated in the epidemiological studies, were characterized according with their functional fitness levels. The results showed that older subjects with a lower functional fitness level score, consistently re-distribute lower limb joint moments while performing different locomotor tasks (walking, stair ascent and stair descent). Because the success of physical activity interventions aiming at falls and disability prevention is dependent on subgroup characterization, these biomechanical gait pattern changes may yield important information for the health and exercise professionals working with the elderly.RESUMO: A presente dissertação objetiva o aprofundamento do conhecimento sobre os determinantes das quedas na população idosa portuguesa, com especial enfoque nas alterações biomecânicas nos padrões de marcha associadas ao declínio funcional característico desta população. A abordagem metodológica preconizada para a análise do problema compreende duas fases complementares: uma primeira fase, que englobou dois estudos epidemiológicos com o objetivo de estabelecer os fatores determinantes de quedas na população idosa portuguesa; uma segunda fase, onde foram considerados três estudos experimentais (laboratoriais), com o propósito de determinar a influência de diferentes níveis de aptidão funcional nos padrões de marcha desta população. Os resultados demonstraram que as quedas resultam da interação de diversos fatores de risco, destacando-se os seguintes: género, parâmetros de aptidão funcional e de saúde. De relevar que o fenómeno de queda se revelou independente da idade, mesmo quando analisada a sua associação com os fatores determinantes em grupos etários mais avançados (≥75 e ≥80 anos). Neste sentido, nos estudos subsequentes, foram analisados os padrões de marcha de subgrupos de idosos recrutados do grupo de participantes dos estudos anteriores e estratificados em função do seu nível de aptidão funcional. Observou-se então que os idosos com baixos níveis de aptidão funcional adotavam estratégias consistentes de redistribuição dos momentos de força articulares dos membros inferiores, aquando da execução de diferentes tarefas locomotoras (marcha, subir e descer escadas). Considerando o sucesso demonstrado das intervenções sustentadas em programas de atividade física para a prevenção de quedas e incapacidade, as alterações biomecânicas dos padrões de marcha observadas poderão constituir um importante suporte informacional para os profissionais de saúde e exercício que trabalham com a população idosa.FCT - Fundação para a Ciência e a Tecnologi

Biomechatronics: Harmonizing Mechatronic Systems with Human Beings

This eBook provides a comprehensive treatise on modern biomechatronic systems centred around human applications. A particular emphasis is given to exoskeleton designs for assistance and training with advanced interfaces in human-machine interaction. Some of these designs are validated with experimental results which the reader will find very informative as building-blocks for designing such systems. This eBook will be ideally suited to those researching in biomechatronic area with bio-feedback applications or those who are involved in high-end research on manmachine interfaces. This may also serve as a textbook for biomechatronic design at post-graduate level