Authors : Atiya Masood Rana and Hussain Saleem
Abstract: The Obstructive Sleep Apnea (OSA) is a disease which blocks airway during sleep, leading to serious consequences. There is a need for Polysomnography (PSG), i.e., simultaneous and continuous monitoring of normal and abnormal physiological activity during sleep. The current standard of diagnosis for OSA and PSG requires hospitalization of patient spending one full day at hospital which is an expensive, un-affordable and inconvenient procedure for each and every patient. So, the home monitoring sleep apnea system is needed that would provide an inexpensive and comfortable instant alert system for virtual healthcare solution. This research proposes an embedded system that processes different bio signals, persuasive technology for sleep pattern analysis that then using data mining and soft computing method for inference and diagnosis of OSA. The proposed solution is a low cost, low power, reliable, non-intrusive and non-invasive vital signs monitor that processes and analyses the sleep data pattern and transmit it to the health informatics system using wireless communication medium, e.g., RFID to get retrieval on smart phone and other workstations. The diagnosis of OSA is done by using soft computing approach.
Atiya Masood Rana and Hussain Saleem, 2014. Novel Integrated Sensor Based Sleep Apnea Monitoring and Tracking System Using Soft Computing and Persuasive Technology for Healthcare Suppor. International Journal of Signal System Control and Engineering Application, 7: 43-48.