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+++ vega_darwin [2019/04/09 14:07] (current) – [Annotated References] yuhanghe
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 Three things I learned from this paper were: (1) the basics of design, control and software features for tele-operation; (2) the interaction between the wearable exoskeleton and the physical platform; and (3) safety features implemented in the system to avoid any major damage.
+. [[https://ieeexplore.ieee.org/document/6198287|Intention-Based EMG Control for Powered Exoskeletons]]\\
+Publisher: IEEE Transactions on Biomedical Engineering 2012\\
+Keywords: Biomedical Engineering, Exoskeleton, EMG, human-assistive robotics
+T. Lenzi, S. M. M. De Rossi, N. Vitiello and M. C. Carrozza, "Intention-Based EMG Control for Powered Exoskeletons," in IEEE Transactions on Biomedical Engineering, vol. 59, no. 8, pp. 2180-2190, Aug. 2012.
+This paper describes using Electromyographical (EMG) signals to control an elbow powered exoskeleton.  The authors presents the description of the simple EMG-based proportional control system and its implementation on the NEUROExos platform, a powered exoskeleton for elbow assistance. The authors presents the results of ten healthy subjects' participation in experimentations where this technology was used to produce simple periodic elbow movement. From this presentation, the paper concludes that, even with a simple proportional EMG control, subjects adapt almost instantaneously to the assistance provided by the robot and can reduce their muscular effort while maintaining control of the movement.
+From the state-of-the-art, the paper identifies challenges in using EMG signals to estimate human muscular torques and apply this information effectively on human-assistive robotics. The technique is highly limited by the necessity of complex user-dependent and session-dependent calibration procedures. The paper addresses these challenges by proposing a simple proportional EMG control where users can calibrate the proportional gains independently in short amount of time.  The results of this approach are that subjects can quickly adapt to the proportional EMG control based elbow exoskeleton and use the skeleton to control their arm movement in sync with designed visual and audio feed-back.
+The paper presents the following theoretical principles: (1) The central nervous system's ability to adapt to external motor disturbances can allow subjects to compensate for the inaccuracy of EMG-signal-based torque estimation;(2) A simple proportional EMG control system applied on exoskeleton can allow subjects to benefit from assistive power from robot without needs for high precision muscular torque measurement; and (3) a simple calibration process where the subject adjust the gain value directly while testing the system.
+The principles are explained fairly.  For example the experimentation method show the correct application of the principles.
+From the principles and results, the paper concludes: (1) a proportional EMG control applied to exoskeleton is sufficient to provide movement assistance; (2) subjects were able to maintain control of movement and accuracy of movement in both amplitude and frequency; and (n) subjects were able to adapt to the assistance provided by exoskeleton in short periods of time (a few seconds).
+I liked this paper because the authors were able to arrange experimentation that provided positive experimental results that support their hypothesis. I disliked this paper because the author made assertive conclusion based on a narrow experimentation arrangement. The experiment only focused on one degree-of-freedom elbow movement. Furthermore, visual and audio feedback on the accuracy of movement could have contributed to the success. I would have liked to see the authors apply the same control system on multiple-degree-of-freedom exoskeleton and limit the effect of visual and audio feedback.
+Three things I learned from this paper were: (1) the limitation of EMG signal in estimate muscular torque; (2) the limitation of extensive session and individual-dependent calibration process for assistive technology;
+and (3) central nervous system's ability to adapt can overcome the inaccuracy in technology.