Multiple Bio-signal Data Compression Design for Portable Healthcare Monitoring Systems

• Main Authors: Hao-Te Lin, 林浩德
• Other Authors: Shu-Yen Lin
• Format: Others
• Language: en_US
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/85465598659011871475

碩士 === 元智大學 === 電機工程學系 === 105 === In this work, the multiple bio-signals compression is proposed for the wearable devices. The electrocardiogram (ECG), blood pressure (BP), and respiration (RESP) signals are applied to the compression system for the cardiovascular diseases (CVDs). The proposed algorithm can detect the abnormal bio-signals and change the resolution of the output data dynamically with four different compression modes. In our experiments, It is demonstrated that many symptoms are detected and the transmitted data for the wearable devices is reduced. The compression ratios for ECG, BP, and RESP are up to 7.83, 13.06, and 7.48. The percentage root mean square differences (PRDs) for ECG, BP, and RESP are less than 12.54, 6.91, and 8.45. The proposed compression methods also could reduce the temperature of wearable devices by reducing energy consumption of Wi-Fi transmission. In our experiments, the temperature of the transmission of the compressed bio-signals is reduced by 6 (°C) compared with the transmission of the uncompressed bio-signals.