Evidence map›Paper›PMID 39687850›Full record

ArticleFrontiers in veterinary science2024

A novel approach for contactless heart rate monitoring from pet facial videos.

Renjie Hu, Yu Gao, Guoying Peng, Hongyu Yang, Jiajin Zhang

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Renjie Hu *College of Big Data, Yunnan Agricultural University, Kunming, China.
Yu Gao *College of Big Data, Yunnan Agricultural University, Kunming, China.
Guoying PengCollege of Big Data, Yunnan Agricultural University, Kunming, China.
Hongyu YangCollege of Mechanical and Electrical Engineering, Yunnan Agricultural University, Kunming, China.
Jiajin ZhangCollege of Big Data, Yunnan Agricultural University, Kunming, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Monitoring the heart rate (HR) of pets is challenging when contact with a conscious pet is inconvenient, difficult, injurious, distressing, or dangerous for veterinarians or pet owners. However, few established, simple, and non-invasive techniques for HR measurement in pets exist. Methods: To address this gap, we propose a novel, contactless approach for HR monitoring in pet dogs and cats, utilizing facial videos and imaging photoplethysmography (iPPG). This method involves recording a video of the pet's face and extracting the iPPG signal from the video data, offering a simple, non-invasive, and stress-free alternative to conventional HR monitoring techniques. We validated the accuracy of the proposed method by comparing it to electrocardiogram (ECG) recordings in a controlled laboratory setting. Results: Experimental results indicated that the average absolute errors between the reference ECG monitor and iPPG estimates were 2.94 beats per minute (BPM) for dogs and 3.33 BPM for cats under natural light, and 2.94 BPM for dogs and 2.33 BPM for cats under artificial light. These findings confirm the reliability and accuracy of our iPPG-based method for HR measurement in pets. Discussion: This approach can be applied to resting animals for real-time monitoring of their health and welfare status, which is of significant interest to both veterinarians and families seeking to improve care for their pets.

Indexed as

animal healthcontactless monitoringheart rateiPPGpetwelfare monitoring

Identifiers

PMID39687850
PMCPMC11647959

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.