Browsing by Author "Li, Shih-Hong"

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Design of wearable and wireless multi-parameter monitoring system for evaluating cardiopulmonary function
(2017-09-01)
Li, Shih-Hong
;
Lin, Bor-Shing
;
Wang, Chen-An
;
Yang, Cheng-Ta
;
Lin, Bor-Shyh
The 6-minute walking test (6MWT) is the test most commonly used to evaluate cardiopulmonary function in patients with respiratory or heart disease. However, there was previously no integrated monitoring system available to simultaneously record both the real-time cardiopulmonary physiological parameters and the walking information (i.e., walking distance, speed, and acceleration) during the 6MWT. In this study, then, a wearable and wireless multi-parameter monitoring system was proposed to simultaneously monitor oxygen saturation (SpO(2)), heart rhythm, and the walking information during the 6MWT. A multi parameter detection algorithm was also designed to estimate the heart rate effectively. The results of the study indicate that this system was able to reveal the dynamic changes and differences in walking speed and acceleration during the 6MWT. As such, the system has the potential to provide a more integrated approach to monitoring cardiopulmonary parameters and walking information simultaneously during the 6MWT. The proposed system warrants further investigation as an assistive assessment tool in evaluating cardiopulmonary function and may be widely applied in cardiopulmonary-related and sports medicine applications in the future. (C) 2017 IPEM. Published by Elsevier Ltd. All rights reserved.
Design of Wearable Breathing Sound Monitoring System for Real-Time Wheeze Detection
(2017-01-01)
Li, Shih-Hong
;
Lin, Bor-Shing
;
Tsai, Chen-Han
;
Yang, Cheng-Ta
;
Lin, Bor-Shyh
In the clinic, the wheezing sound is usually considered as an indicator symptom to reflect the degree of airway obstruction. The auscultation approach is the most common way to diagnose wheezing sounds, but it subjectively depends on the experience of the physician. Several previous studies attempted to extract the features of breathing sounds to detect wheezing sounds automatically. However, there is still a lack of suitable monitoring systems for real-time wheeze detection in daily life. In this study, a wearable and wireless breathing sound monitoring system for real-time wheeze detection was proposed. Moreover, a breathing sounds analysis algorithm was designed to continuously extract and analyze the features of breathing sounds to provide the objectively quantitative information of breathing sounds to professional physicians. Here, normalized spectral integration (NSI) was also designed and applied in wheeze detection. The proposed algorithm required only short-term data of breathing sounds and lower computational complexity to perform real-time wheeze detection, and is suitable to be implemented in a commercial portable device, which contains relatively low computing power and memory. From the experimental results, the proposed system could provide good performance on wheeze detection exactly and might be a useful assisting tool for analysis of breathing sounds in clinical diagnosis.