Enhancing Voluntary Motion in Broad Patient Populations With Modular Powered Orthoses Renewal

Summary

The overall goal of this project is to establish a novel design and control paradigm for modular, partial-assist powered orthoses (exoskeletons) to enhance voluntary lower-limb motion and manage pain in broad patient populations. Building upon a previous study period that addressed weakness from advanced age or muscle fatigue, this current period extends the technology to novel powered unloader orthoses designed to manage knee osteoarthritis (OA) pain. The investigators hypothesize that by providing 15-30% of biological joint torque, these motorized devices can reduce muscular contributions to painful loads on the joint's surfaces during activities of daily living (ADLs). The project aims to develop a task-agnostic, neural network-based controller and establish the feasibility of reducing knee pain and muscle effort in individuals with multi-compartment knee osteoarthritis.

Detailed Description

The overall goal of this project is to develop modular, lower-limb, powered orthoses that fit to user-specific joints and control torque in a manner that enhances voluntary motion and mitigates musculoskeletal pain. Commercial exoskeletons typically use actuation and control methods that force the human user to follow specific, rigid gait patterns. This has prevented emerging wearable robotics from effectively addressing the weakness and pain associated with mild to moderate impairments, such as knee osteoarthritis (OA). These populations require partial, task-agnostic assistance that works harmoniously with their voluntary motion rather than constraining it. To bridge this gap, this project utilizes a quasi-direct drive actuation paradigm, a high-torque motor combined with a low-ratio transmission, integrated into conventional knee stabilizer and unloader braces. This hardware is uniquely capable of producing large output torques without causing perceptible resistance when backdriven by the human joint. To control the device across various activities of daily living (ADLs) without requiring pre-programmed trajectories, the investigators are developing a neural network-based formulation of "energy shaping" (effectively combining virtual springs, dampers, and gravity/inertia compensation) trained on multi-activity human data. The specific objectives of this study period are to: 1. Integrate the modular quasi-direct drive actuator and miniaturized electronics into both a modified knee stabilizer brace and a modified unloader knee brace. 2. Implement and validate the neural network-based energy shaping controller to provide task-agnostic, biomimetic torque assistance with able-bodied subjects. 3. Establish the clinical feasibility of this technology in individuals with multi-compartment knee OA. The investigators hypothesize that the biomimetic torque assistance provided by these motorized braces will significantly reduce quadriceps effort, knee joint moment loads, and subjective pain across ADLs.

Eligibility Criteria

Interventions