Accessible Remote Rehabilitation System for Real-Time Biomechanical Monitoring

Conditions

• Hand Injury Rehabilitation
• Postoperative Rehabilitation

Eligibility Criteria

Sex

ALL

Age

18 Years - N/A

Healthy Volunteers

Accepted

Interventions

• AI-Based Camera Tele-Rehabilitation Monitoring System — DEVICE
  A single-camera, computer vision and inverse-dynamics modeling system that estimates biomechanical parameters (joint torque, muscle force, and range of motion) from video-based hand landmark tracking during rehabilitation exercises.
• Standard Telehealth Rehabilitation — BEHAVIORAL
  Participants perform standard rehabilitation exercises and receive routine telehealth follow-up with clinicians according to usual care practices. No camera-based biomechanical monitoring system is used during the rehabilitation process.

Study Details

This study evaluates a novel camera-based system designed to support remote rehabilitation by measuring hand and upper-limb biomechanics in real time. Many patients recovering from musculoskeletal or neurological conditions require frequent monitoring during rehabilitation, but regular clinic visits may be difficult due to distance, cost, or limited access to specialized care. Current telehealth approaches typically rely on qualitative assessments or self-reported feedback rather than objective biomechanical measurements. The purpose of this study is to determine whether a computer vision-based system can accurately estimate biomechanical parameters such as joint angles, range of motion, muscle force, and joint torque using only a standard camera. The system analyzes hand movement using artificial intelligence and biomechanical modeling to provide real-time measurements during rehabilitation exercises. Participants will perform guided hand-movement tasks while the system records video and extracts anatomical landmarks. These data will be used to compute biomechanical parameters and assess whether the system can reliably monitor rehabilitation progress remotely. The results will help determine whether this technology can provide clinicians with objective, continuous data to support personalized rehabilitation and improve patient outcomes.

Key Dates

Start date

Jun 1, 2026

Status verified

May 2026

Primary completion

Mar 14, 2027

Completion

Mar 14, 2027

Study Design

Enrollment

40 participants (estimated)

Allocation

RANDOMIZED

Intervention model

PARALLEL

Primary purpose

TREATMENT

Arms

• Experimental: Camera-Based Biomechanical Monitoring (Intervention)
  Participants perform standardized hand/upper-limb rehabilitation exercises while an AI-based camera system estimates joint torque, muscle force, and range of motion in real time. Clinicians may use the biomechanical feedback to guide rehabilitation adjustments over the 6-week study period.
• Active Comparator: Standard Telehealth Rehabilitation (Control)
  Participants receive standard telehealth rehabilitation with periodic/weekly check-ins and usual care guidance. No real-time camera-based biomechanical monitoring feedback is provided.

Primary Outcome Measure

Accuracy of Camera-Based Joint Torque Estimation [ Time Frame: Baseline assessment session ]

Central Contacts

• Soroush Korivand, PhD
  662-325-9154
  [email protected]

Locations (2)

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