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Detection of Sleep Apnea Using Wearable AI: Systematic Review and Meta-Analysis
Wearable AI can be used for (1) detecting apnea events in respiration, (2) identifying the type of apnea events in respiration (hypopnea, OSA, CSA, and mixed), (3) detecting patients with sleep apnea, and (4) estimating the severity of sleep apnea.
In the last decade, numerous investigations have been carried out to evaluate the effectiveness of wearable AI in detecting sleep apnea.
J Med Internet Res 2024;26:e58187
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Obstructive sleep apnea/hypopnea syndrome (OSAHS) is a common condition that affects a large portion of the world population [1]. It is estimated that mild to severe OSAHS affects 24% of men and 9% of women in North America [2], with an increase in prevalence over the last 2 decades [3]. OSAHS originates from repetitive closure of the upper airway (UA). The negative impacts of OSAHS include a deterioration of quality of life [4] and an increase in cardiovascular and metabolic morbidity [5-10].
JMIR Biomed Eng 2024;9:e51901
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