Compression Techniques of Biomedical Signals in Remote Healthcare Monitoring Systems: A Comparative Study
AUTHORS
Islam S. Fathi*,Department of Mathematics, Faculty of Science, Suez Canal University, Ismailia, Egypt
Mohamed Ali Ahmed,Department of Mathematics, Faculty of Science, Suez Canal University, Ismailia, Egypt
M. A. Makhlouf,Department of Information System, Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt
E. A. Osman,Department of Electrical Engineering, Faculty of Engineering, Alazhar University, Cairo, Egypt
ABSTRACT
A Remote Healthcare Monitoring system is a technology to track patients in a remote or home place outside a traditional health care environment. The portable and wearable devices are used to collect personal health information and send the collected data to the gateway continuously. These devices are usually powered by batteries and limited capabilities regarding memory, processors, and battery life. Data size reduction on these devices decreases the power required to process these data and minimizes the storage and energy needed to transmit them. Applying data compression techniques is an essential issue on these devices to decrease the power consumed by batteries. The biomedical signals are stranded clinical used in diagnosing many diseases, which are the most common clinical body organs used in Remote Health Monitoring System. In this paper, the methods of biomedical signal compression such as Electrocardiography (ECG) signal, Electroencephalography (EEG) signal, and Electromyography (EMG) signal are reviewed and summarized. We provide a survey and comparative study in terms of the contribution of the used compression technique, compression type, methodology, dataset, and performance metrics
KEYWORDS
Bio-signal compression, ECG, EEG, EMG, Remote healthcare monitoring