Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement

Abstract

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.

The Feasibility of Semi-Continuous and Multi-Frequency Thoracic Bioimpedance Measurements by a Wearable Device during Fluid Changes in Hemodialysis Patients

“…On the other hand, when interpreting changes in high-frequency resistance, additional changes in intracellular volume must be taken into account. Moreover, bioimpedance at high frequency (>50 kHz) [ 28 ] reflects blood pressure changes through changes in the cross-sectional area of the targeted arteria [ 15 , 29 , 30 , 31 ].…”

Flexible wearable devices for intelligent health monitoring

“…37 To further promote the application of wearable blood pressure sensor, Lin and co-authors developed a proofof-concept flexible bio-impedance system with the accuracy of mean error with 1.7 ± 3.4 mmHg and mean absolute error with 2.7 ± 2.6 mmHg for personalized blood pressure monitoring, which were higher than the criteria of the Association for the Advancement of Medical Instrumentation. 53 Specifically, a single-channel impedance plethysmography signal acquisition device was implemented for recording real-time bio-impedance signals originated from the pulsation of carotid artery. Moreover, an artificial intelligence-based algorithm was employed to extract blood pressure features and finally provide blood pressure information, which made the realization of next-generation personalized blood pressure monitoring possible.…”

AIoT in Healthcare: A Systematic Mapping Study

“…5-COVID-19 6-Various healthcare applications. Table III presents the reference of the studies that discussed the above categorizations: [1,3,12,13,18,20,21,24,25,26,27,28,29,32,34,35,36,37,39,45,46,48,51,52,53,55,57,59,61,62,63,64,65,68,69,70,72,73,75] IV.…”