Performance Evaluation of Wearable Sensor Systems: A Case Study in Moderate-Scale Deployment in Hospital Environment.

Wen Sun,Wai-Choong Wong,Yu Ge,Zhiqiang Zhang

doi:10.3390/s151024977

Abstract

A wearable sensor system enables continuous and remote health monitoring and is widely considered as the next generation of healthcare technology. The performance, the packet error rate (PER) in particular, of a wearable sensor system may deteriorate due to a number of factors, particularly the interference from the other wearable sensor systems in the vicinity. We systematically evaluate the performance of the wearable sensor system in terms of PER in the presence of such interference in this paper. The factors that affect the performance of the wearable sensor system, such as density, traffic load, and transmission power in a realistic moderate-scale deployment case in hospital are all considered. Simulation results show that with 20% duty cycle, only 68.5% of data transmission can achieve the targeted reliability requirement (PER is less than 0.05) even in the off-peak period in hospital. We then suggest some interference mitigation schemes based on the performance evaluation results in the case study.

Highlights

Wearable sensor systems have been attracting intense research interest over the recent years due to their potential in practical applications such as healthcare monitoring, sports training, and interactive gaming [1,2]
We address the significance of the inter-user interference in a realistic body sensor network (BSN) deployment scenario and provide suggestions on the interference mitigation schemes
We model the effects of human effects by observing the locations of BSN users and interaction between them in the waiting area of a hospital

Summary

Introduction

Wearable sensor systems have been attracting intense research interest over the recent years due to their potential in practical applications such as healthcare monitoring, sports training, and interactive gaming [1,2]. A wearable sensor system can be referred to as body sensor network (BSN), which comprises multiple sensor nodes and a coordinator worn on a human body. The physiological information of the human body collected by the sensor nodes is first delivered to the coordinator, which forwards the information to a remote server through a network interface for further processing [3,4]. Due to the presence of the human body, BSNs have some stringent requirements for communication systems:. In BSNs, where health and motion information are monitored in real-time, QoS requirements are strict

Results

Discussion

Conclusion