Quantification and Visualization of Coordination during Non-Cyclic Upper Extremity Motion
Richard Fineman
PhD Candidate, MEMP Bioastronautics
Harvard-MIT Health Science & Technology (HST)
Abstract:
There are many design challenges in creating at-home tele-monitoring systems that enable quantification and visualization of the complex biomechanical behavior. One such challenge is robustly quantifying the features monitored by clinicians (e.g. balance, coordination, fluidity, compensatory mechanisms, etc.) in a way that supports clinical decision-making. Current measures for coordination consider cyclic or bimanual motion (e.g., walking, swimming, or crawling). This work presents a novel coordination metric and accompanying normalization schemes to be used during non-constrained, non-cyclic motion to quantify the coordination between body segments at any given time. This metric is then used to interpret upper extremity coordination patterns during a reach, grasp, and release task in a healthy population. Twenty healthy subjects performed a reach, grasp, transport, and release task with a cup (diameter: 6 cm, height: 9 cm). Kinematics were collected using a Bonita VICON system and joint angles were estimated using a 7 degree of freedom (DOF) model of the upper arm. The joint angles were then time-normalized and the coordination phase time-series were calculated between the shoulder-elbow, shoulder-wrist, and elbow-wrist. Coordination phase was normalized using four differing criteria that consider the selected joint DOF, angular velocity, and range of motion.