Development and Validation of 2D-LiDAR-Based Gait Analysis Instrument and Algorithm.

Acquiring gait parameters from usual walking is important to predict clinical outcomes including life expectancy, risk of fall, and neurocognitive performance in older people. We developed a novel gait analysis tool that is small, less-intrusive and is based on two-dimensional light detection and ranging (2D-LiDAR) technology. Using an object-tracking algorithm, we conducted a validation study of the spatiotemporal tracking of ankle locations of young, healthy participants (n = 4) by comparing our tool and a stereo camera with the motion capture system as a gold standard modality. We also assessed parameters including step length, step width, cadence, and gait speed. The 2D-LiDAR system showed a much better accuracy than that of a stereo camera system, where mean absolute errors were 46.2 ± 17.8 mm and 116.3 ± 69.6 mm, respectively. Gait parameters from the 2D-LiDAR system were in good agreement with those from the motion capture system (r = 0.955 for step length, r = 0.911 for cadence). Simultaneous tracking of multiple targets by the 2D-LiDAR system was also demonstrated. The novel system might be useful in space and resource constrained clinical practice for older adults.