Sensor Anomaly Detection in Wireless Sensor Networks for Healthcare

作     者：Haque, Shah Ahsanul Rahman, Mustafizur Aziz, Syed Mahfuzul 

作者机构：Univ S Australia Sch Engn Mawson Lakes SA 5095 Australia Def Sci & Technol Org Dept Def Adelaide SA 5111 Australia 

出 版 物：《SENSORS》 (传感器)

年 卷 期：2015年第15卷第4期

页      面：8764-8786页

核心收录：

学科分类：0710[理学-生物学] 071010[理学-生物化学与分子生物学] 0808[工学-电气工程] 07[理学] 0804[工学-仪器科学与技术] 0703[理学-化学] 

主　　题：wireless sensor networks healthcare medical sensors sensor fault sensor anomaly detection prediction 

摘      要：Wireless Sensor Networks (WSN) are vulnerable to various sensor faults and faulty measurements. This vulnerability hinders efficient and timely response in various WSN applications, such as healthcare. For example, faulty measurements can create false alarms which may require unnecessary intervention from healthcare personnel. Therefore, an approach to differentiate between real medical conditions and false alarms will improve remote patient monitoring systems and quality of healthcare service afforded by WSN. In this paper, a novel approach is proposed to detect sensor anomaly by analyzing collected physiological data from medical sensors. The objective of this method is to effectively distinguish false alarms from true alarms. It predicts a sensor value from historic values and compares it with the actual sensed value for a particular instance. The difference is compared against a threshold value, which is dynamically adjusted, to ascertain whether the sensor value is anomalous. The proposed approach has been applied to real healthcare datasets and compared with existing approaches. Experimental results demonstrate the effectiveness of the proposed system, providing high Detection Rate (DR) and low False Positive Rate (FPR).