Gait Adaptive Duty Cycle: Optimize the QoS of WBSN-HAR

To proliferate the traditional healthcare industry, the deep research is going on Wireless Body Sensor Network (WBSN). Many healthcare deployment models are designed for continuous and uninterrupted remote health monitoring system. But the Quality of Standard like energy, reliability and accuracy are to be pinned more. The Gait Adaptive Duty Cycle-Human Activity Recognition (GADC-HAR) is proposed with better performance in terms of energy, reliability and accuracy. To enhance the performance of model the two techniques were adopted: (i) design Energy Efficient and Reliable algorithm for the network coding (ii) optimization of sleep/wake timer to synchronise Controller Node with relay node. The performance validation is done with the real time implementation of GADC-HAR. The forty subjects (young and adult with same gender ratio) are examined with a 360 s activity pattern, a strategic process of self-optimization is adopted for gait cycle synchronization. At the end model is evaluated as 48.5% more energy efficient and packet loss ratio is reduced by 7.92%. Based on the gait cycle, population categories are sub-categorised in normal young/adult and fast young/adult subjects. GADC-HAR young normal 10.45%, young fast 11.28%, adult normal 25% and adult fast 25.13% were more accurate than WBSN-HAR generic model.

Automated summary

The research focuses on achieving better performance in Wireless Body Sensor Network to promote the traditional healthcare industry. The GADC-HAR model is proposed with improved energy efficiency, reliability, and accuracy, utilizing energy-efficient algorithms for network coding and optimizing sleep/wake timers. By examining subjects with a 360-second activity pattern and adopting a self-optimization strategy for gait cycle synchronization, the model achieves higher energy efficiency and reduced packet loss ratio.