IntelliSleepScorer, a Software Package with a Graphic User Interface for Mice Automated Sleep Stage Scoring

Sleep stage scoring in rodents is the process of identifying the three stages: nonrapid eye movement sleep (NREM), rapid eye movement sleep (REM), and wake. Sleep stage scoring is crucial for studying sleep stage-specific measures and effects. Sleep patterns in rodents differ from those in humans, characterized by shorter episodes of NREM and REM interspaced by waking, and traditional manual sleep stage scoring by human experts is time-consuming. To address this issue, previous studies have used machine learning-based approaches to develop algorithms to automatically categorize sleep stages, but high-performing models with great generalizability are often not publicly available/cost-free nor user-friendly for non-trained sleep researchers. Therefore, we developed a machine learning-based LightGBM algorithm trained with a large dataset. To make the model available to sleep researchers without coding experience, a software tool named IntelliSleepScorer (v1.2- newest version) was developed based on the model, which features an easy-to-use graphic user interface. In this manuscript, we present step-by-step instructions for using the software to demonstrate a convenient and effective automatic sleep stage scoring tool in mice for sleep researchers.

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Publication Details

Journal
Journal of Visualized Experiments
Published
2024-11-08
DOI
https://doi.org/10.3791/66950
Primary Topic
Sleep and Wakefulness Research
Type
article
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article

IntelliSleepScorer, a Software Package with a Graphic User Interface for Mice Automated Sleep Stage Scoring

Jen Q. Pan, Ryan Kern, Lei Wang, Ziyue Zhu
Journal of Visualized Experiments
Sleep and Wakefulness Research
article

IntelliSleepScorer, a Software Package with a Graphic User Interface for Mice Automated Sleep Stage Scoring

Jen Q. Pan, Ryan Kern, Lei Wang, Ziyue Zhu
article en

Abstract

Sleep stage scoring in rodents is the process of identifying the three stages: nonrapid eye movement sleep (NREM), rapid eye movement sleep (REM), and wake. Sleep stage scoring is crucial for studying sleep stage-specific measures and effects. Sleep patterns in rodents differ from those in humans, characterized by shorter episodes of NREM and REM interspaced by waking, and traditional manual sleep stage scoring by human experts is time-consuming. To address this issue, previous studies have used machine learning-based approaches to develop algorithms to automatically categorize sleep stages, but high-performing models with great generalizability are often not publicly available/cost-free nor user-friendly for non-trained sleep researchers. Therefore, we developed a machine learning-based LightGBM algorithm trained with a large dataset. To make the model available to sleep researchers without coding experience, a software tool named IntelliSleepScorer (v1.2- newest version) was developed based on the model, which features an easy-to-use graphic user interface. In this manuscript, we present step-by-step instructions for using the software to demonstrate a convenient and effective automatic sleep stage scoring tool in mice for sleep researchers.

Journal of Visualized Experiments(213)
Broad Institute (US), Stanford University (US)
Openalex Percentile: Top 80%
Sleep and Wakefulness Research
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IntelliSleepScorer, a Software Package with a Graphic User Interface for Mice Automated Sleep Stage Scoring — Jen Q. Pan, Ryan Kern, et al. · Journal of Visualized Experiments (2024) | TGRS Research Map | TGRS