Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Geunbo Yang"'
Autor:
Geunbo Yang, Youngshin Kang, Peter H. Charlton, Panayiotis A. Kyriacou, Ko Keun Kim, Ling Li, Cheolsoo Park
Publikováno v:
Sensors, Vol 24, Iss 12, p 3980 (2024)
Respiratory rate (RR) is a vital indicator for assessing the bodily functions and health status of patients. RR is a prominent parameter in the field of biomedical signal processing and is strongly associated with other vital signs such as blood pres
Externí odkaz:
https://doaj.org/article/bd822939497b4b9089118820a71677bf
Autor:
Geunbo Yang, Wongyu Lee, Youjung Seo, Choongseop Lee, Woojoon Seok, Jongkil Park, Donggyu Sim, Cheolsoo Park
Publikováno v:
Sensors, Vol 23, Iss 16, p 7232 (2023)
A spiking neural network (SNN) is a type of artificial neural network that operates based on discrete spikes to process timing information, similar to the manner in which the human brain processes real-world problems. In this paper, we propose a new
Externí odkaz:
https://doaj.org/article/23569c085d8d4fcfb1c5b171d967e115
Publikováno v:
Sensors, Vol 23, Iss 3, p 1230 (2023)
In this study, the optimal features of electrocardiogram (ECG) signals were investigated for the implementation of a personal authentication system using a reinforcement learning (RL) algorithm. ECG signals were recorded from 11 subjects for 6 days.
Externí odkaz:
https://doaj.org/article/8dd64a829388406b8bb7cf421baf3fc1
Publikováno v:
Sensors, Vol 21, Iss 5, p 1568 (2021)
Recently, the interest in biometric authentication based on electrocardiograms (ECGs) has increased. Nevertheless, the ECG signal of a person may vary according to factors such as the emotional or physical state, thus hindering authentication. We pro
Externí odkaz:
https://doaj.org/article/e18e2a51e36a4a80b2652d3b8cc3f2a0
Autor:
Youngshin Kang, Geunbo Yang, Heesang Eom, Seungwoo Han, Suwhan Baek, Seungil Noh, Youngjoo Shin, Cheolsoo Park
Publikováno v:
Biomedical Engineering Letters. 13:197-207
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12d4c3240496cba0b56868b16402251d
https://doi.org/10.1007/s13534-023-00266-y
https://doi.org/10.1007/s13534-023-00266-y
Autor:
Yuntae Park, Unang Sunarya, Geunbo Yang, Choongseop Lee, Jaewoo Baek, Suwhan Baek, Cheolsoo Park
Publikováno v:
IEIE Transactions on Smart Processing & Computing. 12:64-71
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91ffc73b64269d3b8bf1251f0de34e58
https://doi.org/10.5573/ieiespc.2023.12.1.64
https://doi.org/10.5573/ieiespc.2023.12.1.64
Publikováno v:
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 5
Sensors, Vol 21, Iss 1568, p 1568 (2021)
Sensors
Volume 21
Issue 5
Sensors, Vol 21, Iss 1568, p 1568 (2021)
Recently, the interest in biometric authentication based on electrocardiograms (ECGs) has increased. Nevertheless, the ECG signal of a person may vary according to factors such as the emotional or physical state, thus hindering authentication. We pro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fff645a7735f774e692f3341163ec83b
https://pubmed.ncbi.nlm.nih.gov/33668148
https://pubmed.ncbi.nlm.nih.gov/33668148