Archive · 30 Dec 2025
AI Revolutionizes Sleep Disorder Diagnosis
Researchers at IIITH in Hyderabad are using Artificial Intelligence (AI) to help doctors diagnose sleep disorders like insomnia and sleep apnea.
Traditionally, diagnosing sleep disorders involves a lot of manual work and can be time-consuming.
AI, especially deep learning models, can automatically classify different stages of sleep by analyzing brain wave patterns.
This makes the diagnosis process faster and more accurate.
IIITH has also developed a wearable mask that tracks eye movements to provide real-time sleep stage classification.
They have created a special dataset called iSLEEPS in collaboration with NIMHANS, which includes sleep data from stroke patients.
This dataset helps researchers understand sleep disorders better and develop AI models tailored to the Indian population.
In the future, these AI-driven solutions could lead to better wearable sleep technology and personalized healthcare.
Researchers at IIITH are using AI to automatically classify sleep stages for diagnosing sleep disorders.
AI models like CNNs and RNNs have shown high accuracy in classifying sleep stages.
IIITH has developed a wearable EOG-based mask for non-intrusive, real-time sleep monitoring.
The iSLEEPS dataset, created in collaboration with NIMHANS, includes PSG recordings of stroke patients with sleep disorders.
Future developments may integrate additional physiological signals for improved diagnostic accuracy.
- Who
- Researchers at the International Institute of Information Technology, Hyderabad (IIITH)
- What
- Developing AI-driven solutions for sleep disorder diagnosis
- When
- Ongoing research and recent breakthroughs
- Where
- Hyderabad, India
- Why
- To provide faster, more accurate, and non-intrusive solutions for diagnosing sleep disorders
- Institution
- International Institute of Information Technology, Hyderabad (IIITH)
- Key Technology
- Artificial Intelligence (AI) and deep learning (DL) models
- Innovation
- Automatic classification of sleep stages
- Dataset
- Indian SLEEP Stroke dataset (iSLEEPS)
- Collaboration
- NIMHANS Neurology Department
- Impact
- Faster, more accurate, and non-intrusive sleep disorder diagnosis
- Future Scope
- Integration of additional physiological signals for improved accuracy