TY - JOUR
T1 - Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement
AU - Wang, Ting Wei
AU - Syu, Jhen Yang
AU - Chu, Hsiao Wei
AU - Sung, Yen Ling
AU - Chou, Lin
AU - Escott, Endian
AU - Escott, Olivia
AU - Lin, Ting Tse
AU - Lin, Shien Fong
N1 - Funding Information:
Funding: This research was funded by Ministry of Science and Technology, Taiwan under funding number MOST 110-2917-I-564-026, MOST 110-2628-B-002-055, and MOST 109-2628-B-002-033; University-Industry Collaboration (National Yang Ming Chiao Tung University and Leadtek Research Inc.) under Grant 109A159.
Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2022/3
Y1 - 2022/3
N2 - Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel physiological acquisition systems that impede wearable applications. Recently, wearable and smart health electronics have become significant for next-generation personalized healthcare progress. This study proposes an intelligent single-channel bio-impedance system for personalized BP monitoring. Compared to the PTT-based methods, the proposed sensing configuration greatly reduces the hardware complexity, which is beneficial for wearable applications. Most of all, the proposed system can extract the significant BP features hidden from the measured bio-impedance signals by an ultra-lightweight AI algorithm, implemented to further establish a tailored BP model for personalized healthcare. In the human trial, the proposed system demonstrates the BP accuracy in terms of the mean error (ME) and the mean absolute error (MAE) within 1.7 ± 3.4 mmHg and 2.7 ± 2.6 mmHg, respectively, which agrees with the criteria of the Association for the Advancement of Medical Instrumentation (AAMI). In conclusion, this work presents a proof-of-concept for an AI-based single-channel bio-impedance BP system. The new wearable smart system is expected to accelerate the artificial intelligence of things (AIoT) technology for personalized BP healthcare in the future.
AB - Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel physiological acquisition systems that impede wearable applications. Recently, wearable and smart health electronics have become significant for next-generation personalized healthcare progress. This study proposes an intelligent single-channel bio-impedance system for personalized BP monitoring. Compared to the PTT-based methods, the proposed sensing configuration greatly reduces the hardware complexity, which is beneficial for wearable applications. Most of all, the proposed system can extract the significant BP features hidden from the measured bio-impedance signals by an ultra-lightweight AI algorithm, implemented to further establish a tailored BP model for personalized healthcare. In the human trial, the proposed system demonstrates the BP accuracy in terms of the mean error (ME) and the mean absolute error (MAE) within 1.7 ± 3.4 mmHg and 2.7 ± 2.6 mmHg, respectively, which agrees with the criteria of the Association for the Advancement of Medical Instrumentation (AAMI). In conclusion, this work presents a proof-of-concept for an AI-based single-channel bio-impedance BP system. The new wearable smart system is expected to accelerate the artificial intelligence of things (AIoT) technology for personalized BP healthcare in the future.
KW - Artificial intelligence
KW - Bio-impedance measurement
KW - Continuous blood pressure measurement
KW - Impedance plethysmography
KW - Intelligent system
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U2 - 10.3390/bios12030150
DO - 10.3390/bios12030150
M3 - Article
C2 - 35323420
AN - SCOPUS:85125992419
SN - 0956-5663
VL - 12
JO - Biosensors
JF - Biosensors
IS - 3
M1 - 150
ER -