BIOFEEDBACK SYSTEM FOR ENHANCED MOTOR CONTROL UNDER MICROGRAVITY (original) (raw)

2021, Aerospace and Environmental Medicine

Introduction. Microgravity conditions are physiologically compromising and motor and fine-dexterity tasks involving the extremities including grasp and release are undermined, becoming delayed and placing greater force demands. Our group has recently developed an advanced model incorporating a sensorimotor platform that integrates sensing accelerometers. However, we described design specifications for 1-G conditions and these specifications must still be optimized for microgravity conditions. The mechanism of this model relies on the use of a tri-axial system, whereby sensors and controllers are utilized to detect and correct for key motor control elements consisting of 1) segment orientation, 2) motion compensation, and 3) inertial platform. Methods. The novel accelerometer design utilizing our model was tested using MATLAB simulations and compared to existing gold standards for its sensitivity. Simulation modelling was based on crank-slider mechanism optimization, which uses predictive and output data to calculate position, crank velocity, and acceleration over time. We utilized available tracked prosthetic movement data with six DOFs and generated acceleration over time plots to compare the signal-to-noise ratio and drift between conventional accelerometers and our novel design. We additionally obtained dynamics data capturing translational movement along an X-axis, translation along a Y-axis, translation along a Z-axis, rotation around a roll axis, rotation around a pitch axis, and rotation around a yaw axis. This data included movement requiring segment orientation, motion compensation and an inertial platform. Results. The results of the simulations for a calibrated conventional accelerometer model and our novel prototype design model demonstrated a significant difference in signal quality during segment orientation, motion compensation, and inertial platform. As a result, these algorithms can then used to generate command outputs in a prosthetic system. Of the two, our prototype was determined to reduce signal-noise effects observed in conventional accelerometers. Our modelling and prototype therefore demonstrates it is not only possible to mechanically dampen a system, but also that we can reduce noise and increase signal sensitivity by upgrading accelerometer design specifications. Limitations and Future Avenues. While promising, this model has certain limitations: (i) it is a proof-of-concept and only been tested via simulation and must be further evaluated in varying microgravity conditions, (ii) our simulation focuses on two main accelerometer subtypes in modelling signal, (iii) considerations must still be made for mass and design of an incorporated and functional spacesuit system, and (iv) model needs to be enhanced for six or more degrees of freedom for maximal motor control.