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Accessible Remote Rehabilitation System for Hand Injury and Postoperative Rehabilitation

This study is testing a new camera-based system called the AI-Based Camera Tele-Rehabilitation Monitoring System. This system uses artificial intelligence (AI) to measure how your hand and arm move during rehabilitation exercises, like joint torque (the twisting force around a joint) and range of motion. It aims to provide objective measurements that are usually only available in a clinic, but from your home. This could help people recovering from hand or upper-limb injuries or surgery who might find it hard to attend regular clinic visits. The study wants to see if this camera system can accurately measure these movements compared to standard methods. They are looking for 40 adults, aged 18 or older, who are currently undergoing or recovering from upper-limb or hand rehabilitation.

Study design
This interventional study plans to enroll 40 participants. It compares a new AI-based camera monitoring system with standard telehealth rehabilitation.
What's involved
Participants will perform standardized hand-movement exercises while video data are captured using a consumer-grade camera, such as a smartphone or laptop camera. The primary endpoints are measured at a Baseline assessment session.
Compensation
Not stated in the trial record.
Follow-up
Not specified.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT07492797

Accessible Remote Rehabilitation System for Real-Time Biomechanical Monitoring

Not Yet Recruiting
NAAges 18+InterventionalTreatment
Mississippi State University
~40 participants
Updated 2026-05-19 on ClinicalTrials.gov
What's tested:AI-Based Camera Tele-Rehabilitation Monitoring SystemStandard Telehealth Rehabilitation

At a glance

Recruiting sites
0 of 2 listed sites are recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Accuracy of Camera-Based Joint Torque Estimation
Measured over Baseline assessment session
+1 more outcome measured

Conditions

Hand Injury Rehabilitation
Postoperative Rehabilitation

Explore related trials

Hand InjuryPostoperative rehabilitation

NCT07492797

Where you'd take part

This study runs at 2 sites. They're the same protocol — you choose where, and that choice sets who your contact draft is addressed to.

  • Mississippi State University

    Starkville, Mississippistudy coordinator listed

  • University of Mississippi Medical Center

    Jackson, Mississippistudy coordinator listed

Sites open and close at different times, so the status above is per site — it can differ from the study's overall status.

Who to contact

Soroush Korivand, PhD
[email protected]
662-325-9154
Email the study team

Opens a ready-to-send draft in your own email app — review before sending.

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Eligibility criteria

Inclusion

Adults aged 18 years or older.
Individuals undergoing or recovering from upper-limb or hand rehabilitation following musculoskeletal or neurological injury or surgery.
Ability to perform basic hand or upper-limb movement tasks required for the rehabilitation exercises.
Ability to understand study instructions and provide informed consent.

Exclusion

Severe cognitive impairment preventing understanding of study procedures.
Medical conditions that prevent safe participation in hand or upper-limb rehabilitation exercises.
Severe visual impairment preventing interaction with the camera-based monitoring system.
Participation in another interventional study that could affect rehabilitation outcomes.

What this trial measures

  • Accuracy of Camera-Based Joint Torque EstimationBaseline assessment session

    Accuracy of the AI-based camera system in estimating joint torque during rehabilitation exercises compared with gold-standard dynamometer measurements. Accuracy will be evaluated using mean absolute percentage error (MAPE) between estimated torque values and reference dynamometer readings.

  • Correlation Between Camera-Based and Clinical Biomechanical MeasurementsBaseline assessment session

    Agreement between biomechanical parameters estimated by the camera-based system and reference clinical measurements. Pearson correlation coefficients and Bland-Altman analysis will be used to evaluate agreement between estimated joint torque and gold-standard measurements.