Cited by 24Non-Invasive Vital Sign MonitoringECG Monitoring and AnalysisBiometric Identification and Security

Photoplethysmogram Signal Quality Evaluation by Unsupervised Learning Approach

Roy, Monalisa Singha, Gupta, Rajarshi, Sharma, Kaushik Das·2020·2020 IEEE Applied Signal Processing Conference (ASPCON)

Abstract

The following topics are dealt with: feature extraction; medical signal processing; image classification; convolutional neural nets; learning (artificial intelligence); image segmentation; medical image processing; particle swarm optimisation; control system synthesis; support vector machines.

Integrity signals

Registry

Crossref · 10.1109/aspcon49795.2020.9276733

Cites

27 of 27 references verified0 citation errors · 0 not checkable

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  • A clean BVP signal from the Empatica E4 without noise from motion artifacts has a smooth quasi-periodic signature, which can be separated from random noise or motion artifacts by analyzing the entropy of the signal spectrum.

    “A clean BVP signal from the Empatica E4 without noise from motion artifacts has a smooth quasi-periodic signature, which can be separated from random noise or, more importantly, from motion artifacts by analyzing the entropy of the signal spectrum.”

    From Data quality evaluation in wearable monitoring (2022) · cites this paper as [33]

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Authors
Roy, M. S., Gupta, R., & Sharma, K. D.
Affiliations
University of Calcutta (IN)
Venue
2020 IEEE Applied Signal Processing Conference (ASPCON)
Publisher
IEEE
Published
2020-10-07
Pages
6-10
OpenAlex
W3111412575
Cited by
24
References
27
Citations by year
2026: 1 · 2025: 1 · 2024: 4 · 2023: 6 · 2022: 9 · 2021: 3
FWCI
8.17
Type
conference paper
Language
en
Open access
closed
Locations
IEEE Applied Signal Processing Conference (ASPCON) (publishedVersion)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
  • Physical Sciences › Computer Science › Signal Processing › Biometric Identification and Security
Keywords
photoplethysmogram, signal quality evaluation, unsupervised learning, feature extraction, biomedical signal processing, image classification, convolutional neural networks, image segmentation, particle swarm optimization, support vector machine, controller synthesis

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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