An intelligent sensing system for sleep motion and stage analysis

Monitoring the movements of the human during sleep can potentially give us a good estimation of aspects of the bodily as well as mental state of a human. When such data are combined, either with the knowledge of a sleep pathologist or with a special automated diagnosis system, they could prove quite useful towards the diagnosis of various types of sleep disorders such as parasomnias, insomnia, and dyspnea. Furthermore, such data could also be useful towards diagnosis of various medical conditions, and towards quantitative evaluation of the effects of drug therapy that is administered to a patient who is suffering from poor sleep quality, an important indication of which is the duration and patterns of various sleep stages. The intelligent sensing system that we present consists of a thermal infrared camera, a budget three-electrode budget EEG device, and algorithms for analysis and motion processing which we designed for this system. The main measurables that we derived from our system are of three kinds: a) descriptions of sleep stages (personalized probabilistic model), b) movement graphs, and c) relations between stages and motion. An empirical study with two subjects was carried out, where sensory recordings for multiple nights were captured and analyzed, illustrating the capacity of our sensory system towards providing the above measurables, and quite importantly, towards acting as a strong foundation for future wider deployment of in-home sleep self-monitoring and diagnosis tools.