About this trial
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.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Aged between 18 to 65 years
Weigh less than 300 lbs (due to challenges in bracing heavier participants)
BMI < 40 (due to challenges in bracing heavier participants)
Aged between 30 to 85 years
Disqualifiers
Pregnant (self-report)
Any significant neuromuscular or musculoskeletal disorder that would interfere with the study
Unable to walk for 20 minutes
History of any cardiovascular, vestibular, or visual diseases and/or impairments that may interfere with the study
Trial design
Single group
Treatments tested in this trial
Modular powered orthosis
DeviceThis study will investigate modular, lower-limb, powered orthoses that fit to user-specific weakened joints and control force/torque in a manner that enhances voluntary motion in broad patient populations. The central hypothesis is that high-torque, low-inertia motor systems controlled with energetic objectives will enable modular powered orthoses to partially assist the joints. High-torque electric motors combined with minimal transmissions can be freely rotated (i.e., backdriven) by human joints, allowing the use of an emerging torque control method called energy shaping to reduce the perceived weight/inertia of the body during any motion. By mounting these modular actuators to commercial orthoses, this technology will be easily prescribed/configured by clinicians.
Treatment groups
Trial outcomes
Primary outcomes
Muscle effort
Muscle activity will be measured by surface EMG electrodes, and EMG sites will be averaged by flexors and extensors. For each condition (no orthosis vs. powered orthosis), signals will be normalized by their peaks during the no-orthosis condition, and then averaged over cycle, repetitions, and tasks to obtain overall muscle effort (focusing on knee extension for the powered knee orthosis, hip extension and flexion for the powered hip orthosis, and ankle plantarflexion for the powered ankle orthosis).
Joint moment load
Biological torques will be estimated by subtracting the assistive torques from the total joint torques computed via inverse dynamics (using OpenSim). Biological torques will be divided into flexion and extension. For each condition (no orthosis vs. powered orthosis), signals will be normalized by their peaks during the no-orthosis condition, and then averaged over cycle, repetitions, and tasks to obtain overall joint moment load (focusing on knee extension for the powered knee orthosis, hip extension and flexion for the powered hip orthosis, and ankle plantarflexion for the powered ankle orthosis).
Pain score
The Knee Injury and Osteoarthritis Outcome Score (KOOS) will be used to assess perceived pain for a multi-activity circuit test and isolated activity tests. The KOOS evaluates both short-term and long-term consequences of knee injury. It holds 42 items in 5 separately scored subscales; Pain, other Symptoms, Function in daily living (ADL), Function in Sport and Recreation (Sport/Rec), and knee-related Quality of Life (QOL). It is an extension of the WOMAC Osteoarthritis Index. A Likert scale is used and all items have five possible answer options scored from 0 (No Problems) to 4 (Extreme Problems) and each of the five scores is calculated as the sum of the items included. Scores are transformed to a 0-100 scale, with zero representing extreme knee problems and 100 representing no knee problems as common in orthopaedic assessment scales and generic measures.
Secondary outcomes
10-meter walk test
A 10-meter walk test on an overground walkway will assess self-selected walking speed across three conditions: no orthosis, conventional orthosis, and powered orthosis at their preferred assistance level.
Joint range of motion
Joint range of motion for each task will be recorded using optical motion capture and averaged over cycle and repetitions. Motion capture data will be recorded during study visits and used to calculate joint angle, which will then be averaged over gait cycles and activity repetitions to get a range of motion value.
Joint compressive forces
In Aim 3, joint compressive forces for each task will be modeled using OpenSim / inverse dynamics and
Difficulty score
The Knee Injury and Osteoarthritis Outcome Score (KOOS) will be used to assess perceived difficulty for a multi-activity circuit test and isolated activity tests. The KOOS evaluates both short-term and long-term consequences of knee injury. It holds 42 items in 5 separately scored subscales; Pain, other Symptoms, Function in daily living (ADL), Function in Sport and Recreation (Sport/Rec), and knee-related Quality of Life (QOL). It is an extension of the WOMAC Osteoarthritis Index. A Likert scale is used and all items have five possible answer options scored from 0 (No Problems) to 4 (Extreme Problems) and each of the five scores is calculated as the sum of the items included. Scores are transformed to a 0-100 scale, with zero representing extreme knee problems and 100 representing no knee problems as common in orthopaedic assessment scales and generic measures.
Sponsors and contacts
Click on the lead sponsor to view all of their trials.
University of Michigan
Lead sponsor
National Institute for Biomedical Imaging and Bioengineering (NIBIB)
Collaborator