TY - GEN
T1 - A Heart-related Physiological Signal Monitoring SoC for Wearable ECG Analysis Systems
AU - Huang, Peng Wei
AU - Lee, Shuenn Yuh
AU - Tsou, Chieh
AU - Hung, Yi Wen
AU - Su, Po Han
AU - Chen, Ju Yi
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The prevalence of cardiovascular diseases highlights the importance of heart-related studies. Several research works on the acquirement of physiological signal focused on the enhancement of sensing types and tolerance ability [1-2]. In addition to the increase in channel numbers, the completion of digital platform is emphasized [3]. The specific wireless transmission on the human body is also mentioned in [4]. This proposed configurable electrocardiogram (ECG) analysis system-on-chip (CEASoC) allows ECG monitoring and complex QRS detection and classification, thereby reducing the manpower requirements of the analysis. ECG analyses conducted by a person are effort- and time-consuming. Thus, an automatic ECG analysis device with a CEASoC and BLE module is necessary. This device can improve the healthcare environment through the convenience of instant detection. The burden of long-term care can then be relieved. Moreover, considering individual differences, the important analysis parameters in CEASoC can be updated using external devices and software to enhance the flexibility of the proposed system.
AB - The prevalence of cardiovascular diseases highlights the importance of heart-related studies. Several research works on the acquirement of physiological signal focused on the enhancement of sensing types and tolerance ability [1-2]. In addition to the increase in channel numbers, the completion of digital platform is emphasized [3]. The specific wireless transmission on the human body is also mentioned in [4]. This proposed configurable electrocardiogram (ECG) analysis system-on-chip (CEASoC) allows ECG monitoring and complex QRS detection and classification, thereby reducing the manpower requirements of the analysis. ECG analyses conducted by a person are effort- and time-consuming. Thus, an automatic ECG analysis device with a CEASoC and BLE module is necessary. This device can improve the healthcare environment through the convenience of instant detection. The burden of long-term care can then be relieved. Moreover, considering individual differences, the important analysis parameters in CEASoC can be updated using external devices and software to enhance the flexibility of the proposed system.
UR - http://www.scopus.com/inward/record.url?scp=85146603387&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146603387&partnerID=8YFLogxK
U2 - 10.1109/A-SSCC56115.2022.9980825
DO - 10.1109/A-SSCC56115.2022.9980825
M3 - Conference contribution
AN - SCOPUS:85146603387
T3 - 2022 IEEE Asian Solid-State Circuits Conference, A-SSCC 2022 - Proceedings
BT - 2022 IEEE Asian Solid-State Circuits Conference, A-SSCC 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Asian Solid-State Circuits Conference, A-SSCC 2022
Y2 - 6 November 2022 through 9 November 2022
ER -
