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A Dataset of Synchronized Raw and Preprocessed Finger-Contact ECG and Dual-Wavelength PPG Signals from Healthy Subjects at Rest and During Seated Post-Exercise Recovery

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  • Shiyong Li

    (School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China)

  • Chenlu Gu

    (School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China)

  • Jiating Pan

    (School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China)

  • Yanke Guo

    (School of Artificial Intelligent Medicine, Guilin Medical University, Guilin 541199, China)

  • Zhang Di

    (School of Engineering, Xizang Minzul University, Xianyang 712082, China)

  • Qunfeng Tang

    (School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China)

  • Zhencheng Chen

    (School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China)

Abstract

Electrocardiogram (ECG) and photoplethysmogram (PPG) signals are widely used noninvasive methods for assessing cardiovascular activity and provide complementary information about the cardiac cycle. ECG records cardiac electrical activity, whereas PPG records optically detected blood-volume changes in peripheral tissue. This paper describes a synchronized ECG-PPG dataset collected from 148 apparently healthy subjects under a controlled seated protocol at rest and during post-exercise recovery after two treadmill-running conditions. Signals were acquired using a custom card-type handheld finger-contact prototype that records single-lead ECG and dual-wavelength PPG at 660 nm and 940 nm concurrently. The dataset contains 444 condition-specific records, with each subject contributing one seated resting record, one seated recovery record after light treadmill running, and one seated recovery record after moderate treadmill running. Both raw ADC-count signals and preprocessed signals are provided, and the accompanying software and example code are publicly available. The dataset is intended for research on synchronized ECG-PPG signal analysis, waveform-quality assessment, controlled post-exercise recovery physiology, and exploratory PPG-to-ECG reconstruction under controlled conditions. It should not be interpreted as a free-living wearable dataset or as clinical diagnostic ECG ground truth without external validation.

Suggested Citation

  • Shiyong Li & Chenlu Gu & Jiating Pan & Yanke Guo & Zhang Di & Qunfeng Tang & Zhencheng Chen, 2026. "A Dataset of Synchronized Raw and Preprocessed Finger-Contact ECG and Dual-Wavelength PPG Signals from Healthy Subjects at Rest and During Seated Post-Exercise Recovery," Data, MDPI, vol. 11(7), pages 1-16, June.
  • Handle: RePEc:gam:jdataj:v:11:y:2026:i:7:p:155-:d:1974023
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