A Wearable Ultrasonic-Based Ankle Angle and Toe Clearance Sensing System for Gait Analysis

Traditional methods of gait analysis are being done in an expensive motion-capture laboratory under a controlled environment. Although this provides accurate results, continuous monitoring and feedback are not feasible. The alternative is wearable systems that employ inertial measurement unit (IMU). However, IMUs suffer from drift due to the double integration to arrive at the position information. Although there are methods to overcome this drift using zero velocity updates and Kalman filtering techniques, these indirect methods of determining key gait parameters such as the ankle's angular position require complex computation and predictive approaches. This paper presents a simple direct measurement of the ankle angle (AA) by triangulation methods using ultrasonic sensors without any complex sensor fusion algorithms. In addition, the proposed scheme senses the minimum toe clearance (MTC) which is another critical gait measure. The gait events are determined using the AA and toe clearance data obtained in a gait cycle. The gait events and temporal parameter measurements of the gait cycle were tested and compared with an in-house made video-based reference system. The root mean square error values were found to be varying between 0.91 to 1.54 degrees for ankle angle and 0.36 to 1.26 cm for toe clearance across gait phases. Repeatability of proposed system using the standard deviation found to vary between 1.53 to 2.56 degrees for ankle angle and 0.27 to 1.42 cm for toe clearance across gait phases. It is found to have a good correlation with
r
value of 0.98 and 0.99 for
p
<; 0.001 for ankle angle and toe clearance, respectively, and matching with normative gait patterns, as expected.