Title :
A comparative study of smart insole on real-world step count
Author :
Feng Lin; Aosen Wang; Chen Song; Wenyao Xu; Zhinan Li; Qin Li
Author_Institution :
Department of Computer Science and Engineering, University at Buffalo, SUNY, New York 14260-1660, USA
Abstract :
Daily step count is an important parameter in energy expenditure estimation, medical treatment, and rehabilitation. However, traditional step count methods are not user-friendly or require adhesive equipment. In this paper, we present our Smart Insole system design and evaluate its step count performance. Smart Insole is lightweight, thin, and convenient to use, providing an unobtrusive way to perform step counting. The Smart Insole step count method is based on the differential value threshold of the average plantar pressure obtained from the ambulatory gait assessment. We perform a set of real-world experiments considering different arm positions, walking styles, and daily life activities to evaluate the step count performance. The results show Smart Insole can achieve nearly 100% accuracy in step count under various circumstances, which outperforms other existing solutions.
Keywords :
"Legged locomotion","Intelligent sensors","Sensor arrays","Pressure sensors","Connectors","Textiles"
Conference_Titel :
Signal Processing in Medicine and Biology Symposium (SPMB), 2015 IEEE
DOI :
10.1109/SPMB.2015.7405425