Abstract
A novel algorithm is proposed for robust step detection irrespective of step mode and device pose in smartphone usage environments. The dynamics of smartphones are decoupled into a peak-valley relationship with adaptive magnitude and temporal thresholds. For extracted peaks and valleys in the magnitude of acceleration, a step is defined as consisting of a peak and its adjacent valley. Adaptive magnitude thresholds consisting of step average and step deviation are applied to suppress pseudo peaks or valleys that mostly occur during the transition among step modes or device poses. Adaptive temporal thresholds are applied to time intervals between peaks or valleys to consider the time-varying pace of human walking or running for the correct selection of peaks or valleys. From the experimental results, it can be seen that the proposed step detection algorithm shows more than 98.6% average accuracy for any combination of step mode and device pose and outperforms state-of-the-art algorithms.
Highlights
Billions of smartphones are in use around the world, mainly for voice, visual and data communications
The second part is a comparison of the performance of the proposed algorithm to those of state-of-the-art algorithms for each step mode with fixed device pose and for time-varying device pose with fixed step mode
A novel step detection algorithm was proposed for robust step detection in real smartphone usage environments in which step mode and device pose are continuously changing
Summary
Billions of smartphones are in use around the world, mainly for voice, visual and data communications. The rapid development of micro-electro-mechanical systems (MEMS) has presented new possible application areas of inertial sensors, such as human activity monitoring [1,2,3,4,5], fall detection [5,6], medical treatment [7], remote rehabilitation and physical therapy [8,9,10,11,12], sports [13,14], education [15], security [16], life logging [17,18], etc. Pedestrian dead reckoning (PDR) or indoor/outdoor localization are important application areas for these sensors. Recent research has shown that the accuracy of PDR for low-cost inertial sensors used by smartphones can make these devices an affordable way to realize localization of pedestrian users [18,19,20,21,22]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
