TY - JOUR
T1 - An automated method to extract three-dimensional position data using an infrared time-of-flight camera
AU - Dunn, Marcus
AU - Pavan, Davide
AU - Ramirez, Paul
AU - Rava, Silvia
AU - Sharin, Atiqah
PY - 2018/2/11
Y1 - 2018/2/11
N2 - Traditional motion capture systems can be prohibitive in healthcare settings from time, cost, space and user-expertise perspectives. Ideally, movement analysis technologies for healthcare should be low-cost, quick, simple and usable in small spaces. This study demonstrates a simple, low-cost and close-range time-of-flight depth-camera system, for automatic gait analysis. A method to automatically track three-dimensional position and orientation of retro-reflective marker-triads in real-time was developed. A marker-triad was applied to a participant (self-selected walking pace): thigh angle (wrt. global-vertical) was calculated. Trials were concurrently recorded using a motion capture system. Root-mean-square error was 2.5°, 1.3° and 2.2° for depth-camera distances of 0.8 m, 1.1 m and 1.4 m respectively. Results indicate that walking distances of 1.1 m are optimal for the current system. Further development and investigation into potential healthcare applications (e.g., low-cost, close-range gait analysis) is warranted.
AB - Traditional motion capture systems can be prohibitive in healthcare settings from time, cost, space and user-expertise perspectives. Ideally, movement analysis technologies for healthcare should be low-cost, quick, simple and usable in small spaces. This study demonstrates a simple, low-cost and close-range time-of-flight depth-camera system, for automatic gait analysis. A method to automatically track three-dimensional position and orientation of retro-reflective marker-triads in real-time was developed. A marker-triad was applied to a participant (self-selected walking pace): thigh angle (wrt. global-vertical) was calculated. Trials were concurrently recorded using a motion capture system. Root-mean-square error was 2.5°, 1.3° and 2.2° for depth-camera distances of 0.8 m, 1.1 m and 1.4 m respectively. Results indicate that walking distances of 1.1 m are optimal for the current system. Further development and investigation into potential healthcare applications (e.g., low-cost, close-range gait analysis) is warranted.
KW - depth-camera
KW - gait
KW - analysis
KW - home-based
U2 - 10.3390/proceedings2060502
DO - 10.3390/proceedings2060502
M3 - Conference article
SN - 2504-3900
VL - 2
JO - Proceedings
JF - Proceedings
IS - 6
M1 - 502
ER -