| Autor: |
Kuo-Kun Tseng, Linlin Liu, Chao Wang, K. L. Yung, W. H. Ip, Chih-Yu Hsu |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
IEEE Access, Vol 7, Pp 111662-111677 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2019.2933851 |
| Popis: |
Today, the Internet of Things (IOT) concept is gaining much attention and popularity; The related technologies as spacesuits and embedded ECG acquisition device is already existed. However, there are important issues to be resolved when an application is in a space environment. The ECG signal may be measured by different mobile conditions when embedded in spacesuits, requiring a more robust algorithm to remove exercise and noise issues. Thus, we propose a more complete architecture with a new storing polymorphic average template (SPAT) and a multistage identification algorithm (MIA) to improve the robustness of ECG identification in motion. In addition, we select better combinations of de-noising and feature extractions to create a better and more complete architecture. According to our experimental results, our proposed architecture offers better performance than previous adaptive boosting (AdaBoost) methods; thus, it is also suitable for application in astronaut spacesuits. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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