ArticleAnimals : an open access journal from MDPI2020
Reliability of Family Dogs' Sleep Structure Scoring Based on Manual and Automated Sleep Stage Identification.
Article in Animals : an open access journal from MDPI, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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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.
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.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Non-invasive canine electroencephalography (EEG): a systematic review.BMC veterinary research · 2025Pooled it
- Stress, needs, and behaviour: understanding chronic stress in pet domestic dogs (Canis lupus familiaris) from the prism of needs.Biological reviews of the Cambridge Philosophical Society · 2026Review
- qEEG and Functional Connectivity as a Translational Bridge Between Humans and Dogs in Epilepsy and Associated Disorders: From Spontaneous Model to Automatic Classification-An Integrative Review.Veterinary sciences · 2026Review
- Association of brachycephaly, sleep-disordered breathing, and inflammatory response in dogs.Journal of veterinary internal medicine · 2026Review
- Family Dogs' Sleep Macrostructure Reflects Worsened Sleep Quality When Sleeping in the Absence of Their Owners: A Non-Invasive Polysomnography Study.Animals : an open access journal from MDPI · 2025Article
- Repeated Task Exposure and Sufficient Sleep May Mitigate ADHD-Related Cognitive Flexibility Impairments in Family Dogs.Animals : an open access journal from MDPI · 2025Article
- 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
- Potential interactive effect of positive expectancy violation and sleep on memory consolidation in dogs.Scientific reports · 2024Article
- Sleep-physiological correlates of brachycephaly in dogs.Brain structure & function · 2023Article
- Event-related potentials indicate differential neural reactivity to species and valence information in vocal stimuli in sleeping dogs.Scientific reports · 2023Article
- Emotional Arousal Impacts Physical Health in Dogs: A Review of Factors Influencing Arousal, with Exemplary Case and Framework.Animals : an open access journal from MDPI · 2023Review
- Owner-rated hyperactivity/impulsivity is associated with sleep efficiency in family dogs: a non-invasive EEG study.Scientific reports · 2023Article
- Sleep Characteristics in Dogs; Effect on Caregiver-Reported Problem Behaviours.Animals : an open access journal from MDPI · 2022Article
- Attachment towards the Owner Is Associated with Spontaneous Sleep EEG Parameters in Family Dogs.Animals : an open access journal from MDPI · 2022Article
- Developmental features of sleep electrophysiology in family dogs.Scientific reports · 2021Article
- Interhemispheric asymmetry during NREM sleep in the dog.Scientific reports · 2021Article
- Averaging sleep spindle occurrence in dogs predicts learning performance better than single measures.Scientific reports · 2020Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Non-invasive polysomnography recording on dogs has been claimed to produce data comparable to those for humans regarding sleep macrostructure, EEG spectra and sleep spindles. While functional parallels have been described relating to both affective (e.g., emotion processing) and cognitive (e.g., memory consolidation) domains, methodologically relevant questions about the reliability of sleep stage scoring still need to be addressed. In Study 1, we analyzed the effects of different coders and different numbers of visible EEG channels on the visual scoring of the same polysomnography recordings. The lowest agreement was found between independent coders with different scoring experience using full (3 h-long) recordings of the whole dataset, and the highest agreement within-coder, using only a fraction of the original dataset (randomly selected 100 epochs (i.e., 100 × 20 s long segments)). The identification of drowsiness was found to be the least reliable, while that of non-REM (rapid eye movement, NREM) was the most reliable. Disagreements resulted in no or only moderate differences in macrostructural and spectral variables. Study 2 targeted the task of automated sleep EEG time series classification. Supervised machine learning (ML) models were used to help the manual annotation process by reliably predicting if the dog was sleeping or awake. Logistic regression models (LogREG), gradient boosted trees (GBT) and convolutional neural networks (CNN) were set up and trained for sleep state prediction from already collected and manually annotated EEG data. The evaluation of the individual models suggests that their combination results in the best performance: ~0.9 AUC test scores.
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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.