A trunk-wrist IMU pair with XGBoost detects compensatory trunk movements at macro-F1 0.80 on simulated impairment data from ten able-bodied subjects and retains usable performance on four neurological patients.
Real-time detection of compensatory patterns in patients with stroke to reduce compensation during robotic rehabilitation therapy
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Machine Learning-Based Real-Time Detection of Compensatory Trunk Movements Using Trunk-Wrist Inertial Measurement Units
A trunk-wrist IMU pair with XGBoost detects compensatory trunk movements at macro-F1 0.80 on simulated impairment data from ten able-bodied subjects and retains usable performance on four neurological patients.