Real-Time Step-Count Detection and Activity Monitoring Using A Triaxial Accelerometer

We have developed a wearable device that can convert sensor data into real-time step counts and activity levels. Sensor data on gait were acquired using a triaxial accelerometer. A test was performed according to a test protocol for different walking speeds, e.g., slow walking, walking, fast walking, slow running, running, and fast running. Each test was carried out for 36 min on a treadmill with the participant wearing a portable gas analyzer(K4B2), an Actical device, and the device developed in this study. The signal vector magnitude(SVIvi) was used to process the X, Y, and Z values output by the triaxial accelerometer into one representative value. In addition, for accurate step-count detection, we used three algorithms: a heuristic algorithm(HA), the adaptive threshold algorithm(ATA), and the adaptive locking period algorithm(ALPA). A regression equation to estimate the energy expenditure(EE) was derived by using acceleration data and information of the participants. The recognition rate of o...