Applying ML Algorithms for Classification of Sleep Disorders

Jakkireddy Manisha; Poreddy Bashithareddy; Chikki Reddy Gari Arun Kumar Reddy; Hasini C; D.Pravallika

Applying ML Algorithms for Classification of Sleep Disorders

Author(s)	Jakkireddy Manisha, Poreddy Bashithareddy, Chikki Reddy Gari Arun Kumar Reddy, Hasini C, D.Pravallika
Country	India
Abstract	Since sleep disorders can have a major impact on general well-being, classifying them is crucial to enhancing human health. Experts have historically categorized the stages of sleep, but this is a challenging and error-prone process. By more efficiently assessing, tracking, and diagnosing sleep disturbances, accurate machine learning algorithms (MLAs) can be beneficial. This study uses the publicly accessible Sleep Health and Lifestyle Dataset to evaluate deep learning algorithms and traditional MLAs for the categorization of sleep disorders. Thirteen characteristics pertaining to sleep and everyday activities are included in the 400-row dataset. A genetic algorithm was employed to adjust the parameters of the machine learning models in order to maximize their performance. The Artificial Neural Network (ANN) method was evaluated in the study. Significant performance differences were found in the results, with the ANN obtaining the best classification accuracy of 92.92%. In addition, it outperformed the other algorithms tested with high precision (92.01%), recall (93.80%), and F1-score (91.93%).
Keywords	Sleep Disorder, Artificial Neural Networks (ANN), Polysomnography (PSG), obstructive sleep apnea (OSA).
Field	Engineering
Published In	Volume 16, Issue 1, January-June 2025
Published On	2025-04-03
Cite This	Applying ML Algorithms for Classification of Sleep Disorders - Jakkireddy Manisha, Poreddy Bashithareddy, Chikki Reddy Gari Arun Kumar Reddy, Hasini C, D.Pravallika - IJAIDR Volume 16, Issue 1, January-June 2025.

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Applying ML Algorithms for Classification of Sleep Disorders

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