Sleep Apnea Projects for M.E, M.Tech, Masters, MS abroad, and PhD students. These Sleep Apnea ieee projects are implemented with future work and extension for final year project submission with research paper publishing. These research projects guide final year students to learn, practice, and complete their academic submissions successfully. Each project includes complete source code, project report, PPT, a tutorial, documentation, and a research paper.
Latest Sleep Apnea Projects
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From Scalp to Ear-EEG: A Generalizable Transfer Learning Model for Automatic Sleep Scoring in Older People
This project studies how to monitor sleep using a small, comfortable ear sensor instead of traditional scalp electrodes. Researchers used existing large EEG datasets to train a computer model and then improved it by fine-tuning with ear-EEG data. The approach works well for older adults and matches expert sleep stage classifications closely. This method could help track sleep remotely and non-invasively, especially in elderly patients. -
From Scalp to Ear-EEG A Generalizable Transfer Learning Model for Automatic Sleep Scoring in Older People
This project studies how to improve sleep monitoring using a small ear sensor instead of bulky head sensors. It uses existing brainwave data and trained models from scalp recordings to teach the ear-based system. By fine-tuning these models, the research achieved more accurate sleep stage detection in older adults. This could help develop simple, comfortable tools for tracking sleep at home. -
Detection of Obstructive Sleep Apnoea Using Features Extracted From Segmented Time-Series ECG Signals With a One Dimensional Convolutional Neural Network
This project uses heart signal data to automatically detect sleep apnea. It trains a computer model to learn patterns from ECG signals and identify signs of the disorder. The proposed method works faster and more accurately than other machine learning models. It can help doctors diagnose sleep apnea more quickly and reliably.
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