A data process and wavelet analysis method used for monitoring daily physiological attributes

An analytical technique to evaluate human physiological states is developed for real-life implementation, achieving stable acquisition of data during normal human activity, even with the presence of several constraints and interruptions. Accurately measuring physiological characteristics for extended durations with minimal physical intrusiveness is desirable, something that can be accomplished by using the ubiquitous cellular phone already being used in daily life. Wavelet analysis and its data processing techniques for physiological data are proposed and examined. The data recovery and denoising methodologies are presented to make sense of human body attributes from incomplete data sets extracted when measuring normal daily life. Using the proposed techniques, the continuous measuring of both heart rate and body temperature can clearly expose changes in daily physiological patterns. The aim of developing this method is to identify subtle changes in human body response with limited instrumentation and calculation, by monitoring for long durations even when subjected to severe noise and data set interruptions.