Abstract
This research implements a wireless accelerometer sensor module and an algorithm to determine an individual's posture, activity, and fall. An analog wireless, two-axis accelerometer sensor module was used. Using a wireless radiofrequency module, the accelerometer signal is displayed on a PC-based "Acceloger" (e-Digitalmed, Seoul, Korea) viewer program. The activities of daily living algorithm uses the AC components of the accelerometer signal to determine posture, activity, and fall, and posture while standing, sitting, lying, walking, running, and so on is determined by the DC component. The performance of 30 subjects was evaluated by assessing the algorithm and calculating the detection rate for postures, motions, and subjects. Using a wireless sensor network in an experimental space, subject's postures, motions, and fall monitoring system was implemented. In conclusion, this system can be applied to patients such as the elderly for activity monitoring and fall detection and also for sports athlete's exercise measurement and pattern analysis.
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.
