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Recognition of Patient Groups with Sleep Related Disorders using Bio-signal Processing and Deep Learning.

, , , , , , and . Sensors, 20 (9): 2594 (2020)

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Recognition of Patient Groups with Sleep Related Disorders using Bio-signal Processing and Deep Learning., , , , , , and . CoRR, (2021)Feature extraction using MS Kinect and data fusion in analysis of sleep disorders., , , , , , and . IWCIM, page 1-5. IEEE, (2015)Statistical recognition of breathing by MS Kinect depth sensor., , , , , , and . IWCIM, page 1-4. IEEE, (2015)Adaptive segmentation of multimodal polysomnography data for sleep stages detection., , , , and . DSP, page 1-4. IEEE, (2017)Sleep scoring using polysomnography data features., , , , , , and . Signal Image Video Process., 12 (6): 1043-1051 (2018)Permutation Entropy and Signal Energy Increase the Accuracy of Neuropathic Change Detection in Needle EMG., , , , , , and . Comput. Intell. Neurosci., (2018)Extraction of breathing features using MS Kinect for sleep stage detection., , , , , and . Signal Image Video Process., 10 (7): 1279-1286 (2016)Recognition of Patient Groups with Sleep Related Disorders using Bio-signal Processing and Deep Learning., , , , , , and . Sensors, 20 (9): 2594 (2020)Sleep Apnea Detection with Polysomnography and Depth Sensors., , , and . Sensors, 20 (5): 1360 (2020)