Evidence map›Paper›PMID 41007885›Full record

ArticleAnimals : an open access journal from MDPI2025

Continuous Activity Monitoring Using a Wearable Sensor in Dogs with Osteoarthritis: An Exploratory Case Series.

Carina Sacoor, Sara Leitão, Carolina Domingues, Joana Babo, Cátia M Sá, Ricardo Cabeças, Felisbina L Queiroga

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2025. 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. Article
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

7 authors.

Carina SacoorVasco da Gama Research Center (CIVG), Vasco da Gama University School (EUVG), 3020-210 Coimbra, Portugal.ORCID 0000-0002-0849-643X
Sara LeitãoMaven Pet Inc., Wilmington, DE 19801, USA.ORCID 0009-0001-7502-8214
Carolina DominguesMaven Pet Inc., Wilmington, DE 19801, USA.ORCID 0009-0005-4544-4275
Joana BaboMaven Pet Inc., Wilmington, DE 19801, USA.ORCID 0009-0009-6635-3785
Cátia M SáCentro Veterinário VetCura, 4050-145 Porto, Portugal.ORCID 0009-0002-1024-0369
Ricardo CabeçasVasco da Gama Research Center (CIVG), Vasco da Gama University School (EUVG), 3020-210 Coimbra, Portugal.ORCID 0000-0001-7229-9775
Felisbina L QueirogaDepartment of Veterinary Sciences, School of Agrarian and Veterinary Sciences, University of Trás-os-Montes e Alto Douro (UTAD), 5000-801 Vila Real, Portugal.ORCID 0000-0001-6130-8381

Funding

Fundação para a Ciência e Tecnologia UIDB/00772Maven Pet N/A
6 · The paper itself

Abstract

Canine osteoarthritis (OA) is a chronic, progressive disease that impacts mobility and welfare, often with subtle clinical signs that fluctuate over time. This exploratory case series evaluated the potential of a wearable sensor system (Maven Pet AI System) to detect real-time deviations in activity and rest patterns in dogs with OA under home-based conditions. Five client-owned dogs were monitored over periods ranging from 56 to 126 days, generating longitudinal data on activity and rest patterns. Nine clinically relevant events were identified: seven OA-related flare-ups and two non-orthopedic health issues. In eight of these events, deviations in activity profiles were temporally aligned with symptom onset, therapeutic response, or recovery. Statistically significant changes were observed in six out of nine events, particularly in the Active and Excited categories, while visual trend analysis revealed clinically relevant deviations even in the absence of statistical significance. In one case, decreased activity preceded owner recognition, suggesting potential for early detection. Sensor data also contextualized episodes of overexertion and non-orthopedic conditions, such as pruritus and gastroenteritis. Owner and clinician feedback indicated high usability and perceived clinical value. Despite the small sample, these findings suggest that continuous sensor-based monitoring may complement conventional evaluations and support earlier, more individualized OA management in real-world settings. Further studies are needed to validate and expand these preliminary observations.

Indexed as

accelerometryosteoarthritisreal-time monitoringsmart collarswearable sensors

Identifiers

PMID41007885
PMCPMC12466750

What OpenQuestion holds

Textmetadata
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.