ArticleSensors (Basel, Switzerland)2018
A Combined Approach to Predicting Rest in Dogs Using Accelerometers.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 26 citations in OpenAlex.
- Who is disrupting whom? Examining the nighttime activity patterns of humans and their dogs.PloS one · 2026Article
- Effects of a joint outdoor exercise program for dog owners and dogs on physical activity, sedentary time and sleep-related behaviors.PloS one · 2026Article
- Actical Accelerometers as a Clinical Tool for the Monitoring of Sleeping and Resting Periods in Individual Dogs.Animals : an open access journal from MDPI · 2025Article
- Physical Activity Monitors in Companion Animal Chronic Pain Research-A Review Focused on Osteoarthritis Pain.Animals : an open access journal from MDPI · 2025Review
- Dose-dependent responses: a preliminary investigation into the olfactory effects of essential oil concentrations on canine behavior.Veterinary research communications · 2024Article
- The Use of Triaxial Accelerometers and Machine Learning Algorithms for Behavioural Identification in Domestic Dogs (Sensors (Basel, Switzerland) · 2024Article
- Automated Observations of Dogs' Resting Behaviour Patterns Using Artificial Intelligence and Their Similarity to Behavioural Observations.Animals : an open access journal from MDPI · 2024Article
- Evaluating Behavior Recognition Pipeline of Laying Hens Using Wearable Inertial Sensors.Sensors (Basel, Switzerland) · 2023Article
- Testing the Accuracy of Wearable Technology to Assess Sleep Behaviour in Domestic Dogs: A Prospective Tool for Animal Welfare Assessment in Kennels.Animals : an open access journal from MDPI · 2023Article
- Enhanced Classification of Dog Activities with Quaternion-Based Fusion Approach on High-Dimensional Raw Data from Wearable Sensors.Sensors (Basel, Switzerland) · 2022Article
- Ecological and social pressures interfere with homeostatic sleep regulation in the wild.eLife · 2022Article
- Detection of Generalized Tonic-Clonic Seizures in Dogs With a Seizure Detection System Established Using Acceleration Data and the Mahalanobis Distance: A Preliminary Study.Frontiers in veterinary science · 2022Article
- Characteristics and Welfare of Long-Term Shelter Dogs.Animals : an open access journal from MDPI · 2021Article
- Co-Sleeping between Adolescents and Their Pets May Not Impact Sleep Quality.Clocks & sleep · 2021Article
- Feeding Cannabidiol (CBD)-Containing Treats Did Not Affect Canine Daily Voluntary Activity.Frontiers in veterinary science · 2021Article
- A functional linear modeling approach to sleep-wake cycles in dogs.Scientific reports · 2020Article
- Human-Animal Co-Sleeping: An Actigraphy-Based Assessment of Dogs' Impacts on Women's Nighttime Movements.Animals : an open access journal from MDPI · 2020Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ability to objectively measure episodes of rest has clear application for assessing health and well-being. Accelerometers afford a sensitive platform for doing so and have demonstrated their use in many human-based trials and interventions. Current state of the art methods for predicting sleep from accelerometer signals are either based on posture or low movement. While both have proven to be sensitive in humans, the methods do not directly transfer well to dogs, possibly because dogs are commonly alert but physically inactive when recumbent. In this paper, we combine a previously validated low-movement algorithm developed for humans and a posture-based algorithm developed for dogs. The hybrid approach was tested on 12 healthy dogs of varying breeds and sizes in their homes. The approach predicted state of rest with a mean accuracy of 0.86 (SD = 0.08). Furthermore, when a dog was in a resting state, the method was able to distinguish between head up and head down posture with a mean accuracy of 0.90 (SD = 0.08). This approach can be applied in a variety of contexts to assess how factors, such as changes in housing conditions or medication, may influence a dog's resting patterns.
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Registered trials
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.