Multi-modal Non-intrusive Sleep Pattern Recognition in Elder Assistive Environment

Quality of sleep is an important attribute of an elder's health state and its assessment is still a challenge. Sleep pattern is a significant aspect to evaluate the quality of sleep, and how to recognizethe elder's sleep pattern is an importantissuefor elder-care community. This paper presents a novel multimodal sensing system to monitor the elder's sleep behavior with the pressure sensor matrix and ultra wide band (UWB) tags.Based on the proposed sleep monitoring system, the paper addresses the unobtrusive sleep postures detection and pattern recognition approaches, and the processing methods of experimental data and theclassification algorithms for sleep pattern recognitionare also discussed.

[1]  Pat Langley,et al.  Estimating Continuous Distributions in Bayesian Classifiers , 1995, UAI.

[2]  Yeh-Liang Hsu,et al.  Development of a portable device for telemonitoring of snoring and obstructive sleep apnea syndrome symptoms. , 2008, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[3]  S. Ancoli-Israel,et al.  Sleep disturbances and chronic disease in older adults: results of the 2003 National Sleep Foundation Sleep in America Survey. , 2004, Journal of psychosomatic research.

[4]  H. Schulz,et al.  Rate and Distribution of Body Movements during Sleep in Humans , 1983, Perceptual and motor skills.

[5]  J A Hobson,et al.  Brain state and body position. A time-lapse video study of sleep. , 1982, Archives of general psychiatry.

[6]  A. Gaddam,et al.  Necessity of a bed-sensor in a smart digital home to care for elder-people , 2008, 2008 IEEE Sensors.

[7]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[8]  Gaetano Marrocco,et al.  RFID technology for the neuroscience: Feasibility of sleep disease monitoring , 2009, 2009 3rd European Conference on Antennas and Propagation.

[9]  I. Smith,et al.  The validation of a new actigraphy system for the measurement of periodic leg movements in sleep. , 2005, Sleep medicine.

[10]  Hannu Lauerma,et al.  Quantitative rest activity in ambulatory monitoring as a physiological marker of restless legs syndrome: A controlled study , 2003, Movement disorders : official journal of the Movement Disorder Society.

[11]  Lucinda Simoceli,et al.  Restrições posturais não interferem nos resultados da manobra de reposição canalicular , 2005 .

[12]  H. Vincent Poor,et al.  Position Estimation via Ultra-Wide-Band Signals , 2008, Proceedings of the IEEE.

[13]  Warren W Tryon,et al.  Issues of validity in actigraphic sleep assessment. , 2004, Sleep.

[14]  J. Fahrenberg,et al.  Simultaneous assessment of posture and limb movements (e.g., periodic leg movements) with calibrated multiple accelerometry. , 2006, Physiological measurement.

[15]  Roseli Saraiva Moreira Bittar,et al.  Posture restrictions do not interfere in the results of canalith repositioning maneuver , 2015, Brazilian journal of otorhinolaryngology.

[16]  D J Foley,et al.  Sleep complaints among elderly persons: an epidemiologic study of three communities. , 1995, Sleep.