CoChat
Sign Up
Cited by 148Non-Invasive Vital Sign MonitoringHeart Rate Variability and Autonomic ControlCardiovascular and exercise physiology

Evaluation of wearable consumer heart rate monitors based on photopletysmography

Parak, Jakub, Korhonen, Ilkka·2014·2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
DOI 10.1109/embc.2014.6944419
Open this paper in CoChat — free account

Abstract

Wearable monitoring of heart rate (HR) during physical activity and exercising allows real time control of exercise intensity and training effect. Recently, technologies based on pulse plethysmography (PPG) have become available for personal health management for consumers. However, the accuracy of these monitors is poorly known which limits their application. In this study, we evaluated accuracy of two PPG based (wrist i.e. Mio Alpha vs forearm i.e. Schosche Rhythm) commercially available HR monitors during exercise. 21 healthy volunteers (15 male and 6 female) completed an exercise protocol which included sitting, lying, walking, running, cycling, and some daily activities involving hand movements. HR estimation was compared against values from the reference electrocardiogram (ECG) signal. The heart rate estimation reliability scores for <;5% accuracy against reference were following: mio Alpha 77,83% and Scosche Rhytm 76,29%. The estimated results indicate that performance of devices depends on various parameters, including specified activity, sensor type and device placement.

Integrity signals

Registry

Crossref · 10.1109/embc.2014.6944419

Cites

14 of 14 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Smartwatches often emit insufficient light for accurate readings on darker-skinned users, leading to inconsistent results and potential misdiagnosis.

    “Studies show that smartwatches often emit insufficient light for accurate readings on darker-skinned users, leading to inconsistent results and potential misdiagnosis.”

    From Photoplethysmography in Diverse Skin Tones: Evaluating Bias in Smartwatch Health Monitoring (2025) · cites this paper as [21]

  • PPG sensors generate heart rate measurements by applying LEDs to measure skin-based light reflection through photodetectors that evaluate changes in intensity.

    “PPG sensors generate heart rate measurements by applying LEDs to measure skin-based light reflection through photodetectors that evaluate changes in intensity [21].”

    From Photoplethysmography in Diverse Skin Tones: Evaluating Bias in Smartwatch Health Monitoring (2025) · cites this paper as [21]

  • Socioeconomic disparities in access to smartwatches may interact with skin-tone-related bias, raising additional equity concerns.

    “However, regional variations may exist, and socioeconomic disparities in access to these devices may further interact with skin-tone-related bias, raising additional equity concerns [17-23].”

    From Photoplethysmography in Diverse Skin Tones: Evaluating Bias in Smartwatch Health Monitoring (2025) · cites this paper as [21]

  • These discrepancies undermine trust in wearable health devices, especially when inaccurate readings affect fitness tracking or miss critical signs like arrhythmias.

    “These discrepancies undermine trust in wearable health devices, especially when inaccurate readings affect fitness tracking or miss critical signs like arrhythmias [21,22].”

    From Photoplethysmography in Diverse Skin Tones: Evaluating Bias in Smartwatch Health Monitoring (2025) · cites this paper as [21]

  • Although most consumer-grade wearable devices are designed to measure heart or pulse rate rather than rhythm, their sensitivity and specificity for heart rate and arrhythmia detection are poorly defined, and there is limited information on their agreement with medical-grade lead-based ECG monitors.

    “Although most of these devices are designed to measure heart or pulse rate rather than rhythm, the sensitivity and specificity for heart rate, let alone, arrhythmia detection, are poorly defined, and there is limited information on the agreement of these devices with medical-grade lead-based ECG monitors (Parak & Korhonen, 2014).”

    From 2017 ISHNE-HRS expert consensus statement on ambulatory ECG and external cardiac monitoring/telemetry (2017) · cites this paper as Parak & Korhonen, 2014

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Parak, J., & Korhonen, I.
Affiliations
Tampere University of Technology (FI)
ORCID
Korhonen, Ilkka
Venue
2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Publisher
IEEE
Published
2014-08
Volume
2014
Pages
3670-3673
ISSN
2375-7477 (ISSN-L)
DOI
10.1109/embc.2014.6944419
OpenAlex
W2332318080
Cited by
148
References
14
Citations by year
2026: 5 · 2025: 5 · 2024: 4 · 2023: 18 · 2022: 10 · 2021: 12 · 2020: 13 · 2019: 24 · 2018: 25 · 2017: 16 · 2016: 12 · 2015: 4
FWCI
20.72
Type
conference paper
Language
en
Open access
closed
Locations
  • Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
  • Health Sciences › Medicine › Complementary and alternative medicine › Cardiovascular and exercise physiology
Keywords
wearable heart rate monitor, photoplethysmography, heart rate accuracy, exercise monitoring, wrist-worn sensors, sensor placement, physical activity
MeSH terms
Adult, Electrocardiography, Exercise Test, Female, Heart Rate, Humans, Male, Monitoring, Physiologic, Running, Wrist, Walking, Photoplethysmography, Healthy Volunteers

About these checks

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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review