Sleep related breathing irregularities and sleep disturbances affect a surprisingly large number of people in the society. Due to the high risks of chronic and acute health situations associated with sleep disturbances, a robust sleep monitoring system is needed. While the current golden standard for sleep monitoring is the Polysomnograph (PSG), other approaches also require attachments to patients' body. Furthermore, these monitoring techniques are performed in sleep clinics. Therefore, they interfere with natural sleep patterns. Finally these techniques are usually expensive. The Intelligent Bed Sensor is proposed as a non-restraining home-based sleep monitoring system. It uses 144 pressure sensors embedded in a bed sheet for measuring the pressure that the patient's body exerts on the bed. The main theoretical contribution of this work is a new methodology for analyzing periodicity in pressure data via Computer Vision techniques. We prove that the Intelligent Bed Sensor is capable of detecting individual respiration cycles, apnea events and movements accurately.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:BVIV.1828/1297 |
| Date | 18 December 2008 |
| Creators | Malakuti, Kaveh |
| Contributors | Branzan Albu, Alexandra, Darcie, Thomas E. |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
Page generated in 0.0016 seconds