Estimation of Systolic and Diastolic Blood Pressure in a Non-Contact Method Using Microwaves

Miyu Matsuda, Jiang Liu, Taka Aki Nakada, Shigeru Shimamoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

According to the World Health Organization, an estimated 1.28 billion adults aged 30-79 years worldwide have hypertension. 46% of adults with hypertension are unaware that they have the condition. The only way to know is to get your blood pressure checked. Typically, we use a blood pressure monitor (cuff) at home. However, this method can be uncomfortable and stressful. This paper proposes a non-contact method for estimating blood pressure using 2.4GHz microwave signals. We conduct experiments aimed at capturing the pulse waveform through the reflection of microwave signals. In our previous paper, we only estimated the SBP and focused on increasing the number of features value. In this paper, we estimate both SBP and DBP, and clarify which feature values are important to estimate blood pressure. Also, we attempt the real-time detection of blood pressure. Our studies show that both SBP and DBP can be estimated at a chest. This paper is to achieve predicted blood pressure values that meet the accuracy standards defined by the Japanese Industrial Standards (JIS).

Original languageEnglish
Title of host publication2024 IEEE 21st Consumer Communications and Networking Conference, CCNC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages638-639
Number of pages2
ISBN (Electronic)9798350304572
DOIs
Publication statusPublished - 2024
Event21st IEEE Consumer Communications and Networking Conference, CCNC 2024 - Las Vegas, United States
Duration: 2024 Jan 62024 Jan 9

Publication series

NameProceedings - IEEE Consumer Communications and Networking Conference, CCNC
ISSN (Print)2331-9860

Conference

Conference21st IEEE Consumer Communications and Networking Conference, CCNC 2024
Country/TerritoryUnited States
CityLas Vegas
Period24/1/624/1/9

Keywords

  • Diastolic blood pressure
  • Systolic blood pressure
  • machine learning
  • microwave
  • non-contact
  • pulse wave
  • real-time detection

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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