Evidence map›Paper›PMID 41471550›Full record

ReviewSensors (Basel, Switzerland)2025

Signal Quality Assessment and Reconstruction of PPG-Derived Signals for Heart Rate and Variability Estimation in In-Vehicle Applications: A Comparative Review and Empirical Validation.

Ruimin Gao, Carl S Miller, Brian T W Lin, Chris W Schwarz, Monica L H Jones

Abstract readReviewComparative Study
In one paragraph

Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ruimin GaoSchool of Psychology, Georgia Institute of Technology, Atlanta, GA 30332, USA.ORCID 0009-0007-0306-2433
Carl S MillerTransportation Research Institute, College of Engineering, University of Michigan, Ann Arbor, MI 48109, USA.
Brian T W LinTransportation Research Institute, College of Engineering, University of Michigan, Ann Arbor, MI 48109, USA.
Chris W SchwarzDriving Safety Research Institute, College of Engineering, University of Iowa, Iowa City, IA 52242, USA.ORCID 0000-0003-0291-7157
Monica L H JonesTransportation Research Institute, College of Engineering, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0001-8690-9829

Funding

Ford-University of Michigan Alliance N/A
6 · The paper itself

Abstract

Electrocardiography (ECG) is widely recognized as the gold standard for measuring heart rate (HR) and heart rate variability (HRV). However, photoplethysmography (PPG) presents notable advantages in terms of wearability, affordability, and ease of integration into consumer devices, despite its susceptibility to motion artifacts and the absence of standardized processing protocols. In this study, we review current ECG and PPG signal processing methods and propose a signal quality assessment and reconstruction pipeline tailored for dynamic, in-vehicle environments. This pipeline was evaluated using data gathered from participants riding in an automated vehicle. Our findings demonstrate that while blood volume pulse (BVP) derived from PPG can provide reliable heart rate estimates and support extraction of certain HRV features, its utility in accurately capturing high-frequency HRV components remains constrained due to motion-induced noise and signal distortion. These results underscore the need for caution in interpreting PPG-derived HRV, particularly in mobile or ecologically valid contexts, and highlight the importance of establishing best practices and robust preprocessing methods to enhance the reliability of PPG sensing for field-based physiological monitoring.

Indexed as

Heart RatePhotoplethysmographySignal Processing, Computer-AssistedElectrocardiographyHumanselectrocardiography (ECG)heart rate (HR)heart rate variability (HRV)in-vehicle monitoringmotion artifactsphotoplethysmography (PPG)signal quality assessmentsignal reconstructionwearable sensors

Identifiers

PMID41471550
PMCPMC12736534

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.