Rehabilitation Engineering Explained: Assistive Technology & Human Recovery Systems
Abstract
This open educational resource (OER) curriculum module delivers a comprehensive, mathematically grounded foundation in Rehabilitation Engineering, detailing technologies that restore, augment, and support physical mobility and cognitive independence for individuals with neuromuscular and musculoskeletal impairments. The module provides rigorous treatment of modern assistive systems, including powered lower-limb exoskeletons, myoelectric upper-limb prosthetics, carbon-fiber energy-storage-and-return (ESR) orthoses, smart wheelchair mechanics, and augmentative and alternative communication (AAC) gaze/neural decoders. Contemporary 2026 computational paradigms are integrated, highlighting:- Physics-Informed Neural Networks (PINNs) embedding Euler-Lagrange equations and Hill-type muscle contraction dynamics for non-invasive joint torque and muscle force estimation.- Invariant Extended Kalman Filtering (IEKF) formulated on the Lie group SE(3) to preserve kinematic invariants during multi-sensor inertial fusion.- Deep reinforcement learning and real-time admittance modulation for zero-impedance exoskeleton transparency.- A multi-variable systems engineering trade-off matrix analyzing actuator reflected inertia, prosthetic socket interface pressure limits (capillary ischemia threshold at 32 mmHg), and BCI sensor invasiveness.- An interactive kinematic gait simulator modeling real-time knee flexion angle compensation under variable muscle deficit, motor assist torque, and stride cadence.- Three tiers of self-assessment modules covering foundational principles, clinical scenario evaluations, and quantitative biomechanical calculations with step-by-step solutions. Permanent web resource: https://prep4uni.online/stem/physical-technologies/biomedical-engineering/rehabilitation-engineering/
