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Curone, D., Bertolotti, G.M., Cristiani, A., Secco, E.L. and Magenes, G. (2010) A Real-Time and Self-Calibrating Algorithm Based on Triaxial Accelerometer Signals for the Detection of Human Posture and Activity. IEEE Transactions on Information Technology in Biomedicine, 14, 1098-1105.
https://doi.org/10.1109/TITB.2010.2050696

has been cited by the following article:

• TITLE: Patient Centered Real-Time Mobile Health Monitoring System

  AUTHORS: Won-Jae Yi, Jafar Saniie

  KEYWORDS: Patient Remote Health Monitoring, Real-Time Sensor Data Processing, Wireless Body Sensor Network, Fall Detection, Heart Monitoring

  JOURNAL NAME: E-Health Telecommunication Systems and Networks, Vol.5 No.4, December 30, 2016

  ABSTRACT: In this paper, we introduce a system architecture for a patient centered mobile health monitoring (PCMHM) system that deploys different sensors to determine patients’ activities, medical conditions, and the cause of an emergency event. This system combines and analyzes sensor data to produce the patients’ detailed health information in real-time. A central computational node with data analyzing capability is used for sensor data integration and analysis. In addition to medical sensors, surrounding environmental sensors are also utilized to enhance the interpretation of the data and to improve medical diagnosis. The PCMHM system has the ability to provide on-demand health information of patients via the Internet, track real-time daily activities and patients’ health condition. This system also includes the capability for assessing patients’ posture and fall detection.