Human activity recognition based on wireless body area networks plays an essential role in various applications such as health monitoring, rehabilitation, and physical training. Currently, most of the human activity recognition is based on smartphone, and it provides more possibilities for this task with the rapid proliferation of wearable devices. To obtain satisfactory accuracy and adapt to various scenarios, we built a smart-belt which embedded the VG350 as posture data collector. This article proposes a hierarchical activity recognition structure, which divides the recognition process into two levels. Then a multi-classification Support Vector Machine algorithm optimized by Particle Swarm Optimization is applied to identify five kinds of conventional human postures. And we compare the effectiveness of triaxial accelerometer and gyroscope when used together and separately. Finally, we conduct systematic performance analysis. Experimental results show that our overall classification accuracy is 92.3% and the F-Measure can reach 92.63%, which indicates the human activity recognition system is accurate and effective.
Considering the characteristics of lower power resources in multi-point wireless body area networks (WBANs), the wireless energy and information transmission in full duplex (FD) mode is considered. We propose a transmission protocol based on time division multiple access, which includes two phases. In the inactive phase, the signal access point (AP) broadcasts Radio Frequency (RF) energy to the sensors. When the energy collected by all sensors reaches their respective energy thresholds, the active phase will start. In the active phase, the sensors send back the collected physiological information parameters to the AP, while sensors still collecting the energy transmitted from the AP to achieve the purpose of energy accumulating. Our goal is to obtain the optimal time allocation ratio through the joint objective linear programming method to obtain the maximum average sum-throughput. The simulation results compared with the AP with FD and the sensors with half duplex (HD) show that our proposed optimization method can improve system throughput obviously. INDEX TERMS Wireless body area network (WBAN), energy harvest, energy and information transfer, full duplex (FD), half duplex (HD), linear programming method.
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