Heart Rate Estimation From Photoplethysmography Signals Using Fast Fourier Transform

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

Abstract

Heart rate (HR) estimation is crucial for monitoring cardiovascular health and overall well-being. Advances in sensor technology have led to portable heart rate monitors that allow accurate HR estimation at home. Photoplethysmography (PPG) signals, known for their non-invasive nature, are commonly used in wearable devices for HR estimation. This study introduces a heart rate estimation system using PPG signals from a custom-designed sensory system. The signals are digitized by a high-resolution Analog-to-Digital Converter (ADC), and an innovative Fast Fourier Transform (FFT) module with a novel single path delay commutator processing element (SPD-PE), which is used for efficient HR extraction. This system achieves an accuracy of ± 1.52BPM, enhancing computational efficiency and reliability for real-time monitoring in portable and wearable devices, thereby advancing health monitoring technology.

Original languageEnglish
Title of host publication2024 7th International Conference on Signal Processing and Information Security, ICSPIS 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350368673
DOIs
Publication statusPublished - 2024
Event7th International Conference on Signal Processing and Information Security, ICSPIS 2024 - Dubai, United Arab Emirates
Duration: Nov 12 2024Nov 14 2024

Publication series

Name2024 7th International Conference on Signal Processing and Information Security, ICSPIS 2024

Conference

Conference7th International Conference on Signal Processing and Information Security, ICSPIS 2024
Country/TerritoryUnited Arab Emirates
CityDubai
Period11/12/2411/14/24

Keywords

  • Analog-to-DigitalConvertor
  • Fast Fourier Transform
  • Heart Rate
  • Photoplethysmography

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Signal Processing
  • Safety, Risk, Reliability and Quality

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