An efficient PPG Compression Technique for Wearable Health Devices

Abstract

Photoplethysmography is a simple, widely used, low-cost technique to acquire important diagnostic information for assessing significant physiological parameters of the human body based on the amount of light reflected from or absorbed by the body. Photoplethysmogram (PPG) signal is recognized as one of the most powerful signals in the diagnosis of variations in heart rate, blood pressure, oxygenation saturation levels etc. With the great advancements in communication, information technology and Internet of Things (IoT), wearable health devices have been extensively used to measure PPG signals in telemedicine, remote health monitoring, ambulatory systems and in several mobile health systems. As these small wearable medical devices are battery operated and resource constrained, dedicated and efficient compression techniques are required to optimally manage energy and memory requirements, without jeopardizing the relevant clinical morphologies. The thesis deals with the study of the existing PPG compression techniques, type of the compression used, the basic implementation and a comparative analysis of these techniques, which could be helpful for choosing a suitable technique for specific applications. The thesis aims to design efficient compression techniques for the compression of PPG Signals. The proposed techniques exhibit superior performances compared to the state-of-the-art methods.