A Lightweight Exoskeleton-Based Portable Gait Data Collection System.

Area of Science:

• Biomechanics
• Robotics
• Wearable Technology

Background:

• Quantitative human locomotion data is essential for controlling lower-limb assistive devices.
• Traditional marker-based motion capture is confined to laboratory settings, limiting real-world data collection.
• There is a need for portable and accurate gait data acquisition systems.

Purpose of the Study:

• To develop and validate a novel exoskeleton-based system for independent lower limb gait data collection.
• To enable gait analysis in real-world, daily-living scenarios outside of laboratory environments.
• To ensure the system minimizes interference with natural human movement and enhances user comfort.

Main Methods:

• A lightweight exoskeleton with articulated knee and ankle joints was designed.
• A two-degrees-of-freedom joint mechanism was incorporated for natural movement and accurate measurement.
• The system integrated goniometers, inertia measurement units (IMUs), and foot-plate force sensors, with data logged by a microcontroller.
• Validation involved comparing exoskeleton-measured joint angles against a marker-based optical motion capture system during various locomotion tasks.

Main Results:

• The exoskeleton system demonstrated high accuracy in measuring knee and ankle joint angles.
• Correlation coefficients of 0.97 for knee and 0.96 for ankle joint angles were achieved compared to optical motion capture.
• The system successfully collected gait data during overground walking, treadmill walking, and sit-to-stand/stand-to-sit transitions.

Conclusions:

• The proposed exoskeleton-based gait measurement system is accurate and reliable for quantifying lower limb movement.
• This system overcomes the limitations of laboratory-bound motion capture, facilitating real-world gait data collection.
• The technology holds significant potential for advancing the control and intent recognition of wearable lower-limb assistive devices.