Machine Learning-based Wearable Bio-processor for Real-Time Blood Pressure Estimation

Jee Ye Yoon, Hayeon Kim, Eun Gyeong Ham, Hannah Yang, Ji Hoon Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Recently, as continuous monitoring of blood pressure (BP) becomes important for the treatment and management of hypertension, which is a representative chronic disease, many studies on non-invasive cuff-less BP have been conducted. Due to accuracy degradation of the simple linear algorithms, complex nonlinear algorithms are preferred, but its latency and energy efficiency are suffered from the limited CPU computational capability on wearable devices. In this paper, we present a wearable bio-processor that is capable of real-time BP estimation based on Electrocardiogram (ECG) and Photoplethysmography (PPG), which can provide high BP estimation accuracy with a nonlinear regression machine learning model. The proposed bio-processor including Arm Cortex-M0 and dedicated hardware accelerators runs at 50MHz and is prototyped with a Xilinx Artix-7 FPGA. It shows the root mean square error (RMSE) of 6.04 mmHg and 5.88 mmHg for Systolic BP and Diastolic BP, respectively.

Original languageEnglish
Title of host publication2022 International Conference on Electronics, Information, and Communication, ICEIC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665409346
DOIs
StatePublished - 2022
Event2022 International Conference on Electronics, Information, and Communication, ICEIC 2022 - Jeju, Korea, Republic of
Duration: 6 Feb 20229 Feb 2022

Publication series

Name2022 International Conference on Electronics, Information, and Communication, ICEIC 2022

Conference

Conference2022 International Conference on Electronics, Information, and Communication, ICEIC 2022
Country/TerritoryKorea, Republic of
CityJeju
Period6/02/229/02/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • BP Estimation
  • Bio-processor
  • Blood Pressure
  • Machine Learning
  • SoC (System-on-Chip)

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