IoT Healthcare Analytics: The Importance of Anomaly Detection

被引：129

作者：

Ukil, Arijit ^{[1
]}

Bandyoapdhyay, Soma ^{[1
]}

Puri, Chetanya ^{[1
]}

Pal, Arpan ^{[1
]}

机构：

[1] Tata Consultancy Serv, Innovat Labs, Kolkata, India

来源：

IEEE 30TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION NETWORKING AND APPLICATIONS IEEE AINA 2016 | 2016年

关键词：

anomaly detection; m-health; IoT; heart monitoring; analytics;

D O I：

10.1109/AINA.2016.158

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Healthcare data is quite rich and often contains human survival related information. Analyzing healthcare data is of prime importance particularly considering the immense potential of saving human life and improving quality of life. Furthermore, IoT revolution has redefined modern health care systems and management. IoT offers its greatest promise to deliver excellent progress in healthcare domain. In this talk, proactive healthcare analytics specifically for cardiac disease prevention will be discussed. Anomaly detection plays a prominent role in healthcare analytics. In fact, the anomalous events are to be accurately detected with low false negative alarms often under high noise (low SNR) condition. An exemplary case of smartphone based cardiac anomaly detection will be presented which depicts the potential benefit of the ubiquity of smartphone in realizing affordable and pervasive m-health.

引用

页码：994 / 997

页数：4

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