Pushing their experiments further, the authors integrated soft strain sensors to their perspiration-powered e-skin to monitor muscle contraction. The strain signals were then sent to a human-prosthesis, in effect, turning the PPES as a human-machine interface. Even under mechanical deformation, with a bending curvature of 1.5cm in radius, the PPES maintained consistent sensor readings, the researchers reported.
Applying CNTs/PDMS elastomer-based strain sensors on the hand and the elbow, connected to the PPES, the e-skin was able to accurately monitor the bending of the finger and elbow (from resistance changes of the strain sensors). A robotic arm wirelessly fed with these signals could mimick the gestures of the wearer's arm, approaching and grabbing a target object. Another practical use case envisaged by the authors is robotic assistance in the rehabilitation settings.
By extrapolation, they anticipate that the incorporation of more physical sensors for electroencephalogram and electromyography recording along with the continuous metabolic monitoring could make multimodal PPES useful for the design and optimization of novel prostheses that bring the human into the loop of prosthesis control, for real-time user-specific responses to human intent and behavior.
California Institute of Technology - www.caltech.edu