Multiple Bio-signal Data Compression Design for Portable Healthcare Monitoring Systems
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 algo...
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ndltd-TW-105YZU054420362017-09-19T04:29:39Z http://ndltd.ncl.edu.tw/handle/85465598659011871475 Multiple Bio-signal Data Compression Design for Portable Healthcare Monitoring Systems 可攜式健康照護監測系統之多生理訊號資料壓縮設計 Hao-Te Lin 林浩德 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. Shu-Yen Lin 林書彥 2017 學位論文 ; thesis 66 en_US |
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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.
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Shu-Yen Lin |
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Shu-Yen Lin Hao-Te Lin 林浩德 |
author |
Hao-Te Lin 林浩德 |
spellingShingle |
Hao-Te Lin 林浩德 Multiple Bio-signal Data Compression Design for Portable Healthcare Monitoring Systems |
author_sort |
Hao-Te Lin |
title |
Multiple Bio-signal Data Compression Design for Portable Healthcare Monitoring Systems |
title_short |
Multiple Bio-signal Data Compression Design for Portable Healthcare Monitoring Systems |
title_full |
Multiple Bio-signal Data Compression Design for Portable Healthcare Monitoring Systems |
title_fullStr |
Multiple Bio-signal Data Compression Design for Portable Healthcare Monitoring Systems |
title_full_unstemmed |
Multiple Bio-signal Data Compression Design for Portable Healthcare Monitoring Systems |
title_sort |
multiple bio-signal data compression design for portable healthcare monitoring systems |
publishDate |
2017 |
url |
http://ndltd.ncl.edu.tw/handle/85465598659011871475 |
work_keys_str_mv |
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