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Title: Electromyography-guided and robot-assisted ergonomics
Author: Shafti, Seyed Ali
ISNI:       0000 0004 7659 9814
Awarding Body: King's College London
Current Institution: King's College London (University of London)
Date of Award: 2017
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Comfort within the workplace is an issue that is many times overlooked. This, combined with the amount of time average people spend at work, leads to a high risk of work-related musculoskeletal disorders (WMSD). Ergonomics is the study of human musculoskeletal system with the aim to improve comfort at work and avoid risks of WMSDs. With the increased use of robots in close physical collaboration with humans, they are now becoming part of the human work environment. It is therefore important to consider the human's comfort during interaction with the robot. This is achieved through an understanding of human comfort and ergonomics. This dissertation therefore provides an engineering perspective of ergonomics and reports on PhD research performed to bring the two fields together. This has led to contributions within the areas of applied ergonomics, biomedical engineering and robotics. A novel ergonomics assessment method is created and introduced as the Muscle Effort Score (MES), which provides for the first time an objective technique to consider both the effect of posture geometry and real-time muscle activity due to external load based on electromyography (EMG), providing a full picture of the human musculoskeletal status. This is further extended with the creation of a novel textile-based EMG acquisition system, fully integrated into garment for continuous and comfortable monitoring of muscle activity. Finally, a novel algorithm is created for robot-assisted ergonomics in which the robot uses real-time sensor data to understand the human posture, identify causes of discomfort, and respond with the appropriate cooperative movements to bring the human back into the ergonomic optimum. In effect, this new approach optimises human-robot relative position and orientation based on the human's comfort and ergonomics. The above methods are also applied in surgical environments to show their usability in different scenarios. The dissertation concludes with a description of future areas of research.
Supervisor: Liu, Hongbin ; Althoefer, Kaspar Alexander Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available