Musculoskeletal Load Analysis for the Design and Control of a Wearable Robot Bracing the Human Body While Crawling on a Floor

• Published in: IEEE access Vol. 10; pp. 6814 - 6829
• Main Authors: Daniel, Phillip H., Fu, Chenglong, Asada, H. Harry
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuation; Biomechanics; crawling; Exoskeletons; Feedforward control; Human body; Human motion; Inverse dynamics; Kinematics; Limbs; Lumbar region; Motion capture; Muscles; Musculoskeletal load; musculoskeletal modeling; Musculoskeletal system; Optimization; Robot control; Robotics; Robots; supernumerary robotic limbs; Task analysis; Wearable robots; Wearable technology; Wrist
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3134056

Wearable robots, such as exoskeletons, can potentially reduce the load at targeted muscles of the human body during fatiguing tasks. It is common, however, that use of a wearable robot causes increased load at untargeted muscles, leading to minimal net improvement. Here, musculoskeletal impacts of a wearable robotic device are examined to establish a foundation for the design and control of a robot based on a musculoskeletal model and experimental data. The model predicts the effect of the device, called Supernumerary Robotic Limbs (SuperLimbs), on the wearer's whole body muscular effort. SuperLimbs brace the upper body of a human while they work near floor-level. Its effectiveness varies depending on how it is attached to the human (harness design), how it is coupled to the floor (wrist and hand design), and how it is controlled (actuation policy). These behaviors and their interplay are analyzed and used to inform the design and control of the robot. First, body movements are measured with a motion capture system while a human subject crawls on the floor. Their muscular activity and the floor reaction forces are then estimated based on a musculoskeletal model's inverse dynamics optimization. The effect of the SuperLimbs is assessed by replacing both human arms in the model with robotic limbs. The analysis reveals that the human muscle load is minimized with a particular combination of SuperLimbs joint torques that can be used as feedforward commands to the SuperLimbs controller. Desirable harness and wrist properties are obtained by varying the parameters of the Human+Robot model, and tracking the effect of these changes on the distribution of muscles forces in the human's back. It is found that a harness chest plate of the SuperLimbs attached at its anterior edge minimizes muscle activity in the back's vulnerable lower lumbar region. The model is verified with ground reaction force experiments, and its validity is examined for every simulation experiment.