Gait cycle spectrogram analysis using a torso-attached inertial sensor.
Measurement of gait parameters can provide important information about a person's health and safety. Automatic analysis of gait using kinematic sensors is a newly emerging area of research. We describe a new way to detect walking, and measure gait cadence, by using time-frequency signal processing together with spectrogram analysis of signals from a chest-worn inertial measurement unit (IMU). A pilot study of 11 participants suggests that this method is able to distinguish between walk and non-walk activities with up to 88.70% sensitivity and 97.70% specificity. Limitations of the method include instability associated with manual fine-tuning of local and global threshold levels.
Faculty of Engineering and Information Technology, University of Technology, Sydney, Ultimo, 2007 NSW, Australia. mitchellyuwono@gmail.com
Mitchell
M
Yuwono
Steven W
SW
Su
Bruce D
BD
Moulton
Hung T
HT
Nguyen
D000054:Acceleration; D000368:Aged; D000465:Algorithms; D001696:Biomechanical Phenomena; D001330:Electronic Data Processing; D005684:Gait; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008875:Middle Aged; D015233:Models, Statistical; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods*; D016011:Normal Distribution; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D012984:Software; D016138:Walking