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

Area of Science:

• Biomedical Engineering
• Signal Processing
• Wearable Technology

Background:

• Accurate, long-term monitoring of human physiological states is crucial for health assessment.
• Existing methods often require specialized equipment and are intrusive, limiting real-world application.
• The ubiquity of cellular phones presents an opportunity for unobtrusive physiological data acquisition.

Purpose of the Study:

• To develop and validate an analytical technique for real-life implementation of human physiological state evaluation.
• To achieve stable physiological data acquisition during normal daily activities, despite constraints and interruptions.
• To enable continuous monitoring of physiological patterns with minimal intrusiveness using cellular phones.

Main Methods:

• Development of an analytical technique for physiological state evaluation.
• Application of wavelet analysis and data processing for physiological data.
• Implementation of data recovery and denoising methodologies for incomplete datasets.
• Utilizing cellular phones for continuous heart rate and body temperature measurement.

Main Results:

• Stable acquisition of physiological data during normal human activity, even with interruptions.
• Successful recovery and denoising of physiological data from incomplete datasets.
• Demonstrated ability to expose changes in daily physiological patterns through continuous monitoring.
• Identification of subtle changes in human body response with limited instrumentation.

Conclusions:

• The developed technique enables reliable, long-term physiological monitoring using everyday cellular phones.
• Wavelet analysis and data processing are effective for handling noisy and interrupted physiological data.
• This approach facilitates early detection of health anomalies by identifying subtle physiological shifts.