  Stroke patients with Upper Limb Disability (ULD) are re-acclimated to their
lost motor capability through therapeutic interventions, following assessment
by Physiotherapists (PTs) using various qualitative assessment protocols.
However, the assessments are often biased and prone to errors. Real-time
visualization and quantitative analysis of various Performance Metrics (PMs) of
patient's motion data, such as - Range of Motion (RoM), Repetition Rate (RR),
Velocity (V), etc., may be vital for proper assessment. In this study, we
present Renovo, a wearable inertial sensor-based therapeutic system, which
assists PTs with real-time visualization and quantitative patient assessment,
while providing patients with progress feedback. We showcase the results of a
three-week pilot study on the rehabilitation of ULD patients (N=16), in 3
successive sessions at one-week interval, following evaluation both by Renovo
and PTs (N=5). Results suggest that sensor-based quantitative assessment
reduces the possibility of human error and bias, enhancing efficiency of
rehabilitation.
