URN | etd-0713122-140130 | Statistics | This thesis had been viewed 101 times. Download 3 times. |
Author | CHUNG-WEI LIAO | ||
Author's Email Address | davisliao0411@gmail.com | ||
Department | Technology for electrical engineering | ||
Year | 2021 | Semester | 2 |
Degree | Master | Type of Document | Master's Thesis |
Language | zh-TW.Big5 Chinese | Page Count | 68 |
Title | Integrated Cardiovascular Status Monitoring Device for Smart Home | ||
Keyword | |||
Abstract | ¡@¡@As civilization has progressed, individuals have become more concerned with their quality of life. In conjunction with the advancement of science and technology, numerous sensing technologies, ICT (Information & Commu-nication Technology) equipment, and systems have been gradually imple-mented. In recent years, people's living habits have changed due to the COVID-19 outbreak. The original audio-visual entertainment, working methods, diet, and even medical treatments can be gradually performed at home, thereby making the smart home a new industrial technology. In this context, this research has proposed an "integrated cardiovascular status monitoring device for the smart home" that focuses on the understanding of the daily physical status of individuals, particularly those with cardiovascular disease, making daily monitoring measurements at home more convenient. ¡@¡@Included among the physiological signals to be handled by this device have been electrocardiogram signals and pulse data. Consequently, the sen-sor design incorporates a self-developed hand-held electrocardiogram (ECG) sensor made of brass as the sensing material and a three-terminal photople-thysmography (PPG) sensor that uses a reflective light sensor to create a pulse-taking method similar to that of traditional Chinese medicine. In the design for signal processing, the ECG and PPG signals have been recorded by the Arduino Mega-2560-ESP8266 and then wirelessly transferred via the WIFI module. Node.js has been used to construct the cloud host and server. The ELVIS virtual instrument measures the analog sensing signal, which has been shown on the computer and mobile applications in web mode after data acquisition (DAQ) with the Arduino drawing sequencer. This research has incorporated technologies such as smart sensing, wireless transmission, network server setup, and human-machine interface, and its viability has been confirmed by practical tests. In the future, it could be included in a va-riety of elderly assistive devices to make them more useful. |
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Advisor Committee | |||
Files | indicate access worldwide | ||
Date of Defense | 2022-07-05 | Date of Submission | 2022-07-20 |