Contactless Gait Assessment in Home-like Environments

Area of Science:

• Biomedical Engineering
• Sensor Technology
• Neurology

Background:

• Gait analysis is crucial for assessing neurodegenerative diseases.
• Current methods rely on manual scoring or restrictive technologies.
• There is a need for unobtrusive, accurate gait assessment tools.

Purpose of the Study:

• To introduce and evaluate an unobtrusive sensor system for gait analysis.
• To assess the system's accuracy and reliability in home-like environments.
• To compare the system against state-of-the-art gait measurement technologies.

Main Methods:

• Developed a contactless sensor system using light detection and ranging (LiDAR) technology.
• Collected data from 25 participants performing 8 different walks each (200 measurements).
• Compared the LiDAR system against a pressure mat and inertial measurement unit (IMU) sensors.

Main Results:

• The LiDAR system demonstrated high correlation (r>0.95) with gold standards for most gait parameters.
• Stride length and velocity showed excellent correlation (r≥0.98, R2≥0.95).
• Multi-hour recordings confirmed no systematic drift, indicating long-term reliability.

Conclusions:

• The proposed unobtrusive gait measurement system provides accurate, contactless, long- and short-term gait assessments.
• This technology is suitable for home-like environments, offering a significant improvement over current methods.
• The system has potential applications in monitoring various health conditions, particularly neurodegenerative diseases.