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The use of smartphone for gait analysis
Author(s)
Yodpijit, Nantakrit
Tavichaiyuth, Nicha
Jongprasithporn, Manutchanok
Songwongamarit, Chalida
Sittiwanchai, Teppakorn
Date Issued
June 7, 2017
Type
Conference Paper
Abstract
In today's information-rich environment, one of the most popular devices is a smartphone. Research has shown significant growth in the use of smartphones and apps all over the world. Accelerometer within smartphone is a motion sensor that can be used to detect human movements. Compared to other major vital signs, gait characteristics represent general health status, and can be determined using smartphones. The objective of the current study is to design and develop the alternative technology that can potentially predict health status and reduce healthcare cost. This study uses a smartphone as a wireless accelerometer for quantifying human motion characteristics from four steps of the system design and development (data acquisition operation, feature extraction algorithm, classifier design, and decision making strategy). Findings indicate that it is possible to extract features from a smartphone's accelerometer using a peak detection algorithm. Gait characteristics obtain from the peak detection algorithm include stride time, stance time, swing time and cadence. Applications and limitations of this study are also discussed.
Citation
2017 3rd International Conference on Control Automation and Robotics Iccar 2017, 543-546, 2017