UM scholar develops smart detection technology for identifying potential congestive heart failure
澳大教授研究心跳監測技術 準確偵察心律失常

Prof Tam Lap Mou from the University of Macau’s (UM) Department of Electromechanical Engineering received a Best Conference Paper Award at the 2019 Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability of the Institute of Electrical and Electronics Engineers (IEEE), for his paper titled ‘A Smart Detection Technology for Personal Heartbeat Monitoring’.

Interdisciplinary research has become a new trend, especially in research areas related to biomedical engineering and smart systems. Prof Tam and his co-workers have developed a smart detection technology which can produce key features for three different kinds of arrhythmias via the application of chaotic mapping strategy. Through appropriate adjustment of system parameters and an autonomous design, different key features can be obtained. The study has shown that this new technology can effectively identify a normal heartbeat, potential congestive heart failure, and sleep apnea. The technology can also be used to monitor personal electrocardiogram (ECG) in smart city development.

Held in Okinawa, Japan, the 2019 IEEE Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability aimed to promote interdisciplinary collaboration between scientists and engineering technologists. This year’s event received about 100 paper submissions.

澳門大學科技學院機電工程學系教授譚立武最近研究出“用於個人心跳監測的智能檢測技術＂，能準確偵察出三種不同類型的心律失常的關鍵特徵，從而可有效識別正常心跳、潛在充血性心力衰竭、睡眠呼吸暫停等個人心跳狀況。此研究於“2019 IEEE歐亞生物醫學工程、醫療保健及永續發展會議＂上發表，獲大會高度評價，奪“最佳會議論文獎”。

跨學科研究逐漸成為學術研究的新趨勢，特別是與生物醫學工程和智慧系統相關的範疇。譚立武與其工作夥伴開發了一種智能檢測技術：透過“渾沌映射策略＂有效產生三種不同類型心律失常的關鍵特徵，並透過適當的系統參數調整與自主式設計，擷取出不同的關鍵特徵用以辨識。是次研究成果顯示，所提出的策略可有效識別正常心跳、潛在充血性心力衰竭和睡眠呼吸暫停等三種個人心跳狀況；同時，也能應用於智慧城市中用來監測個人心電規律。

今屆IEEE歐亞生物醫學工程、醫療保健及永續發展會議在日本沖繩舉行，吸引多個國家的專家學者參與，分享相關研究領域的最新技術。是次會議約有100篇論文參賽，經過嚴格的評鑑，譚立武團隊的研究最終脫穎而出獲獎。