An Open-Source and Wearable System for Measuring 3D Human Motion in Real-Time

Area of Science:

• Biomechanics
• Wearable Technology
• Rehabilitation Engineering

Background:

• Accurate human motion analysis is crucial for diagnosing movement disorders and guiding rehabilitation.
• Optical motion capture is the gold standard but is expensive and lab-bound.
• Existing wearable systems often lack accuracy, require proximity to computers, and use proprietary software, hindering reproducibility.

Purpose of the Study:

• To introduce OpenSenseRT, an open-source, wearable system for real-time estimation of upper and lower extremity kinematics.
• To provide a low-cost, reproducible alternative to traditional motion analysis methods.

Main Methods:

• Utilizes inertial measurement units (IMUs) and a portable microcontroller.
• Employs a musculoskeletal model and inverse kinematics solver for real-time kinematic estimation.
• Open-source hardware and software are scalable for tracking 1 to 14 body segments.

Main Results:

• Validated against optical motion capture with an average RMSE of 4.4 degrees for lower limb and 5.6 degrees for upper extremity joints.
• Achieves real-time computation frequencies sufficient for many tasks (e.g., 7 segments at 30 Hz).
• System cost is approximately $100 USD plus $20 per tracked segment.

Conclusions:

• OpenSenseRT offers a validated, low-cost, and easily replicable solution for human movement analysis.
• Enables accessible kinematic assessment in diverse settings including clinics, homes, and free-living environments.
• Facilitates reproducible research and clinical application of motion analysis.