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The purpose of this study is to determine how well people can be trained to produce new and different movements through the use of haptic feedback. One particular application is retraining individuals to walk differently in order to reduce knee joint loads to prevent or treat knee osteoarthritis as an alternative to surgical treatments.
During the movement retraining session, you be given different combinations of haptic, visual, and auditory feedback in order to inform you on desired movement changes. This will take place at the Human Performance Laboratory at Stanford University. Motion analysis will be done while you perform movement activities (such as locomotion).
Prior to performing these movement tasks the investigators will attach reflective markers to your body using tape, pre-wrap and/or ace bandages. The investigators will record motion of your body's movements using infrared cameras which capture anatomical data from the reflective markers on your body.
The investigators will provide you with feedback to inform you of desired movement modifications. Haptic feedback devices such as vibration motors and skin stretch devices will be attached to your body via velcro straps and will be used to give "touch" feedback. There will be a computer monitor in front of you during testing to provide visual feedback. Sounds will be played using speakers near the testing area to provide auditory feedback.
The time needed for set up and performance of the above set of tests is approximately 90 minutes. You will be performing walking and other movements for only a small part of that time. The rest of the time will be spent preparing you for the experiment. After the investigators examine your movement data, if some of the data appear inaccurate or the investigators are unable to process the data, the investigators may ask you to repeat the movement analysis at a later time.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Walking modification | Experimental | Changing kinematics for walking |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Gait retraining | Behavioral | Changing the kinematics of walking |
|
| Measure | Description | Time Frame |
|---|---|---|
| Measure: Knee pain and function | Knee pain and function will be assessed through the standardized KOOS survey | four weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Learning retention, knee adduction moment | Learning retention of gait kinematics and knee joint loading including the knee adduction moment will be measured through motion capture and ground reaction force plates | four weeks |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Pete B Shull | Stanford University | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Stanford University School of Medicine | Stanford | California | 94305 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 21459384 | Background | Shull PB, Lurie KL, Cutkosky MR, Besier TF. Training multi-parameter gaits to reduce the knee adduction moment with data-driven models and haptic feedback. J Biomech. 2011 May 17;44(8):1605-9. doi: 10.1016/j.jbiomech.2011.03.016. Epub 2011 Apr 2. | |
| 21428681 | Background | Wheeler JW, Shull PB, Besier TF. Real-time knee adduction moment feedback for gait retraining through visual and tactile displays. J Biomech Eng. 2011 Apr;133(4):041007. doi: 10.1115/1.4003621. |
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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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| 23146322 | Result | Shull PB, Shultz R, Silder A, Dragoo JL, Besier TF, Cutkosky MR, Delp SL. Toe-in gait reduces the first peak knee adduction moment in patients with medial compartment knee osteoarthritis. J Biomech. 2013 Jan 4;46(1):122-8. doi: 10.1016/j.jbiomech.2012.10.019. Epub 2012 Nov 10. |
| D012216 |
| Rheumatic Diseases |