HealthGear: Automatic Sleep Apnea Detection and Monitoring with a Mobile Phone

We present HealthGear, a real-time wearable system for monitoring, visualizing and analyzing physiological signals. HealthGear consists of a set of non-invasive physiological sensors wirelessly connected via Bluetooth to a cell phone which stores, transmits and analyzes the physiological data, and presents it to the user in an intelligible way. In this paper, we focus on an implementation of HealthGear using a blood oximeter to monitor the user’s blood oxygen level and pulse while sleeping. We also describe two different algorithms for automatically detecting sleep apnea events, and illustrate the performance of the overall system in a sleep study with 20 volunteers.

[1]  D F Kripke,et al.  Sleep apnea and periodic movements in an aging sample. , 1985, Journal of gerontology.

[2]  F. Sériès,et al.  Utility of Nocturnal Home Oximetry for Case Finding in Patients with Suspected Sleep Apnea Hypopnea Syndrome , 1993, Annals of Internal Medicine.

[3]  K. Wac,et al.  Mobile patient monitoring: the MobiHealth system. , 2004, Studies in health technology and informatics.

[4]  Partha Pratim Kanjilal,et al.  Analysis and characterization of photo-plethysmographic signal , 2001, IEEE Transactions on Biomedical Engineering.

[5]  Jose R. Rodriguez,et al.  Utility of oxygen saturation and heart rate spectral analysis obtained from pulse oximetric recordings in the diagnosis of sleep apnea syndrome. , 2003, Chest.

[6]  Paul Lukowicz,et al.  AMON: a wearable multiparameter medical monitoring and alert system , 2004, IEEE Transactions on Information Technology in Biomedicine.

[7]  R. Paradiso,et al.  Wearable health care system for vital signs monitoring , 2003, 4th International IEEE EMBS Special Topic Conference on Information Technology Applications in Biomedicine, 2003..

[8]  M. Bister,et al.  Automated detection of obstructive apnea and hypopnea events from oxygen saturation signal , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[9]  T. Young,et al.  The occurrence of sleep-disordered breathing among middle-aged adults. , 1993, The New England journal of medicine.

[10]  N. Lomb.  Least-squares frequency analysis of unequally spaced data , 1976 .

[11]  Pai-Tsun Cheng,et al.  The design of PDA-based biomedical data processing and analysis for intelligent wearable health monitoring systems , 2004, The Fourth International Conference onComputer and Information Technology, 2004. CIT '04..

[12]  Dirk Husemann,et al.  Personal mobile hub , 2004, Eighth International Symposium on Wearable Computers.

[13]  Matt Welsh,et al.  CodeBlue: An Ad Hoc Sensor Network Infrastructure for Emergency Medical Care , 2004 .

[14]  A. Williams,et al.  Screening for sleep apnea using pulse oximetry and a clinical score. , 1991, Chest.

[15]  Aleksandar Milenkovic,et al.  Journal of Neuroengineering and Rehabilitation Open Access a Wireless Body Area Network of Intelligent Motion Sensors for Computer Assisted Physical Rehabilitation , 2005 .

[16]  W A Whitelaw,et al.  Automated analysis of digital oximetry in the diagnosis of obstructive sleep apnoea , 2000, Thorax.

[17]  C. Brambilla,et al.  Accuracy of oximetry for detection of respiratory disturbances in sleep apnea syndrome. , 1996, Chest.

[18]  Emil Jovanov,et al.  Issues in wearable computing for medical monitoring applications: a case study of a wearable ECG monitoring device , 2000, Digest of Papers. Fourth International Symposium on Wearable Computers.

[19]  Sungmee Park,et al.  Enhancing the quality of life through wearable technology , 2003, IEEE Engineering in Medicine and Biology Magazine.

[20]  B M Psaty,et al.  The medical cost of undiagnosed sleep apnea. , 1999, Sleep.