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RECRUITING
NCT07652437
NA

Study of Wearable Interventions for Improving Mobility of Individuals With Knee Osteoarthritis

Sponsor: Massachusetts Institute of Technology

View on ClinicalTrials.gov

Summary

Knee osteoarthritis (OA) affects an estimated 654 million people over age 40 world-wide. In the United States, approximately 16% of adults over the age of 40 have knee OA. Pain, activity limitations and disability are common symptoms. Exercise is widely recommended as a non-invasive, first line strategy for people with knee OA. Yet, less than 1/3 of adults with knee OA meet recommended levels of physical activity, and rates are even lower among people who are overweight. Furthermore, adherence to evidence-based structured programs is poor once the therapeutic support is removed. End stage disease is treated by total joint replacement. Under-active people with knee OA would benefit from general walking activity, even if joint replacement surgery is expected; however, walking is difficult and motivation is low. Thus, people with knee OA encounter a difficult paradox: exercise could help decrease pain and improve function but doing so can be difficult and may not always be possible. There is a tremendous need to address this situation. This is a small device-feasibility study evaluating the Dephy ExoBoot, a wearable powered exoskeleton, in individuals with knee OA. The study assesses whether the device can reliably deliver positive assistance during walking and is tolerated across walking tasks. Additional measures, including changes in knee loading and walking speed with versus without the device, are also collected.

Key Details

Gender

All

Age Range

21 Years - 100 Years

Study Type

INTERVENTIONAL

Enrollment

9

Start Date

2025-12-15

Completion Date

2029-07-01

Last Updated

2026-06-17

Healthy Volunteers

Yes

Interventions

DEVICE

Dephy Exoboot

Individuals administered the wearable intervention will have the device accurately predict appropriate dynamics based on non-invasive sensor inputs, adapt assistance timing and magnitude to match individual gait patterns, demonstrate reliable performance across various walking conditions and provide assistance that integrates naturally with the user's biomechanics

Locations (1)

MIT Media Lab

Cambridge, Massachusetts, United States