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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Wearable Intervention for Individuals with Knee Osteoarthritis | Experimental | Participants wear the Dephy ExoBoot, a powered wearable exoskeleton, while completing walking tasks. Non-invasive sensors and motion capture monitor gait and device performance, and device assistance settings may be adjusted during sessions. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Dephy Exoboot | Device | 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 |
| Measure | Description | Time Frame |
|---|---|---|
| Number of Participants that Complete Walking Protocol with Real-time Device Assistance | Number of participants that complete the walking protocol with device providing assistance without device-related restrictions. | Up to 4 sessions across 4 weeks, each lasting up to 2 days. |
| Measure | Description | Time Frame |
|---|---|---|
| Peak external knee adduction moment | Quantitative analysis of knee adduction moment (N*m / kg) between device and no device condition. | Up to 4 sessions across 4 weeks, each lasting up to 2 days. |
| Change in self-selected walking speed |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Christopher Shallal, B.S. | Contact | 704-904-6112 | cshallal@mit.edu |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| MIT Media Lab | Recruiting | Cambridge | Massachusetts | 02139 | United States |
IPD will not be available as it may contain identifying information.
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| ID | Term |
|---|---|
| D020370 | Osteoarthritis, Knee |
| ID | Term |
|---|---|
| D010003 | Osteoarthritis |
| D001168 | Arthritis |
| D007592 | Joint Diseases |
| D009140 | Musculoskeletal Diseases |
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|
Analysis of walking speed (m/s) changes between device and no device conditions
| Up to 4 sessions across 4 weeks, each lasting up to 2 days. |
| D012216 |
| Rheumatic Diseases |