At-home wireless monitoring of acute hemodynamic disturbances to detect sleep apnea and sleep stages via a soft sternal patch
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Description
Biosensors, Free Full-Text
Obstructive sleep apnoea and perioperative medicine: a growing concern
Nathan Zavanelli - Postdoctoral Research Associate - Carnegie Mellon University
Georgia Tech Researchers Develop Wireless Monitoring Patch System to Detect Sleep Apnea at Home
Apnoea–hypopnoea indices determined via continuous positive airway pressure (AHI-CPAPflow) versus those determined by polysomnography (AHI-PSGgold): a protocol for a systematic review and meta-analysis
Soft wireless sternal patch to detect systemic vasoconstriction using photoplethysmography - ScienceDirect
Soft wireless sternal patch to detect systemic vasoconstriction using photoplethysmography. - Abstract - Europe PMC
Biosensors, Free Full-Text
Machine learning implementations for sleep staging and apnea detection.
Mechanical assessment of a soft sternal patch. (A) Image of a soft
Characterization of pharyngeal resistance during sleep in a spectrum of sleep-disordered breathing
Obstructive sleep apnea syndrome detection based on ballistocardiogram via machine learning approach
Multifunctional wearable humidity and pressure sensors based on biocompatible graphene/bacterial cellulose bioaerogel for wireless monitoring and early warning of sleep apnea syndrome - ScienceDirect
Scatter plots to show correlations between AHI and sleep parameters
Figure 2 from Evaluate different machine learning techniques for classifying sleep stages on single-channel EEG
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