Orange: from experimental machine learning to interactive data mining
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Multimodality Sensors for Sleep Quality Monitoring and Logging
ICDEW '06 Proceedings of the 22nd International Conference on Data Engineering Workshops
An RFID based system for monitoring free weight exercises
Proceedings of the 6th ACM conference on Embedded network sensor systems
Recognizing daily activities with RFID-based sensors
Proceedings of the 11th international conference on Ubiquitous computing
Context-aware wireless sensor networks for assisted living and residential monitoring
IEEE Network: The Magazine of Global Internetworking
Empath: a continuous remote emotional health monitoring system for depressive illness
Proceedings of the 2nd Conference on Wireless Health
Demonstration of sleep monitoring and caregiver displays for depression monitoring
Proceedings of the 2nd Conference on Wireless Health
Combining wearable and environmental sensing into an unobtrusive tool for long-term sleep studies
Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
DRAP: a Robust Authentication protocol to ensure survivability of computational RFID networks
Proceedings of the 27th Annual ACM Symposium on Applied Computing
USC-HAD: a daily activity dataset for ubiquitous activity recognition using wearable sensors
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Proceedings of the 2012 ACM Research in Applied Computation Symposium
Will you have a good sleep tonight?: sleep quality prediction with mobile phone
Proceedings of the 7th International Conference on Body Area Networks
Tracking influence of reflective exercise for persons with epilepsy
Proceedings of the conference on Wireless Health
iSleep: unobtrusive sleep quality monitoring using smartphones
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
Sleep posture analysis using a dense pressure sensitive bedsheet
Pervasive and Mobile Computing
Journal of Ambient Intelligence and Smart Environments
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Sleep monitoring is very important for elderly people as inadequate and irregular sleep are often related to serious diseases such as depression and diabetes. In many cases, it is necessary to monitor the body positions and movements made while sleeping because of their relationships to particular diseases (i.e., sleep apnea and restless legs syndrome). Analyzing movements during sleep also helps in determining sleep quality and irregular sleeping patterns. This paper presents a sleep monitoring system based on the WISP platform - active RFID-based sensors equipped with accelerometers. We show how our system accurately infers fine-grained body positions from accelerometer data collected from the WISPs attached to the bed mattress. Movements and their duration are also detected by the system. We present the results of our empirical study from 10 subjects on three different mattresses in controlled experiments to show the accuracy of our inference algorithms. Finally, we evaluate the accuracy of the movement detection and body position inference for six nights on one subject, and compare these results with two baseline systems: one that uses bed pressure sensors and the other is an iPhone application.