Legal Implications of Functional Disability Evaluation Using Biomedical Technologies

Functional disability evaluation is central to medico-legal decision-making, yet conventional assessments rely heavily on subjective clinical judgment. This study presents a technology-driven framework for objective disability assessment using integrated biomedical systems. A wearable sensing platform comprising inertial measurement units (IMUs; 3-axis accelerometer ±16 g, gyroscope ±2000°/s, sampling rate 100 Hz) and instrumented plantar pressure insoles (8–16 capacitive sensors, pressure range 0–600 kPa) was deployed to capture lower-limb biomechanics during gait tasks. Data acquisition was synchronized via Bluetooth Low Energy with a latency of <50 ms. Extracted features included joint angle trajectories, spatiotemporal gait parameters, center of pressure progression, and load symmetry indices. Signal preprocessing involved a fourth-order Butterworth filter (cutoff 6 Hz) and normalization. A supervised machine learning model (support vector machine with radial basis function kernel) was trained to classify functional impairment levels, achieving an accuracy of 92.3%, sensitivity of 90.1%, and specificity of 93.5%. The system demonstrated high repeatability (intra-class correlation coefficient >0.88), reducing observer bias and enhancing evidentiary reliability. From a legal perspective, the framework supports standardized, quantifiable reporting of disability, improving transparency in injury claims and compensation cases. However, issues related to data privacy, calibration standards, and admissibility of digital evidence remain critical for regulatory integration.