Browsing by Author "Hsu, Shao-You"

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A +/- 6ms-Accuracy, 0.68mm(2) and 2.21 mu W QRS Detection ASIC
(2010)
Wang, Hui-Min
;
Lai, You-Liang
;
Hou, Mark C.
;
Lin, Shih-Hsiang
;
Yen, Brad S.
Healthcare issues arose from population aging. Meanwhile, electrocardiogram (ECG) is a powerful measurement tool. The first step of ECG is to detect QRS complexes. A state-of-the-art QRS detection algorithm was modified and implemented. By the dedicated architecture design, the novel ASIC is proposed with 2.21 mu W power consumption and 0.68mm(2) core area. It is the smallest QRS detection ASIC so far in the world. In addition, the positive prediction of the ASIC is 99.36% based on the MIT/BIH arrhythmia database certification.
The Relationship between Music Processing and Electrocardiogram (ECG) in Vegetative State (VS)
(2010)
Yen, Brad S.
;
Wang, Hui-Min
;
Hou, Mark C.
;
Huang, Sheng-Chieh
;
Chou, Lei-Chun
Previous literature has suggested that consciousness of patients in vegetative state (VS) may be enhanced via music listening; however, studies empirically documenting the link among music, vegetative state, and electrocardiogram (ECG) are scant. Therefore, the current article attempts to explore how music improves the VS patient's condition with the assessment of ECG recordings. The present work involved a follow-up of case report, consisting of forty-two 150-min sessions, whose duration is longer than other VS studies. The quantitative analysis of the data was conducted through C programming language, HRV Analysis, EXCEL and MATLAB package software in order to find a specific pattern of HRV. Results of the study showed a medium level of consistence between the two variables of music and ECG. To conclude, this publication may be of importance in presenting some specific pattern of the ECG diagram while letting VS patients listen to the music.