Clinical Usefulness of New R-R Interval Analysis Using the Wearable Heart Rate Sensor WHS-1 to Identify Obstructive Sleep Apnea: OSA and RRI Analysis Using a Wearable Heartbeat Sensor

Autor: Masashi Sakuma, Hiroyuki Kaneda, Hirohisa Amano, Shichiro Abe, Takeshi Tsutsumi, Akio Nakata, Akiko Haruyama, Toshiaki Nakajima, Teruo Inoue, Masayuki Miyamoto, Hiroko Yazawa, Ryo Shinozaki, Takuo Arikawa, Syotaro Obi, Shigeru Toyoda, Taishi Matsui
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Clinical Medicine
Volume 9
Issue 10
Journal of Clinical Medicine, Vol 9, Iss 3359, p 3359 (2020)
ISSN: 2077-0383
DOI: 10.3390/jcm9103359
Popis: Obstructive sleep apnea (OSA) is highly associated with cardiovascular diseases, but most patients remain undiagnosed. Cyclic variation of heart rate (CVHR) occurs during the night, and R-R interval (RRI) analysis using a Holter electrocardiogram has been reported to be useful in screening for OSA. We investigated the usefulness of RRI analysis to identify OSA using the wearable heart rate sensor WHS-1 and newly developed algorithm. WHS-1 and polysomnography simultaneously applied to 30 cases of OSA. By using the RRI averages calculated for each time series, tachycardia with CVHR was identified. The ratio of integrated RRIs determined by integrated RRIs during CVHR and over all sleep time were calculated by our newly developed method. The patient was diagnosed as OSA according to the predetermined criteria. It correlated with the apnea hypopnea index and 3% oxygen desaturation index. In the multivariate analysis, it was extracted as a factor defining the apnea hypopnea index (r = 0.663, p = 0.003) and 3% oxygen saturation index (r = 0.637, p = 0.008). Twenty-five patients could be identified as OSA. We developed the RRI analysis using the wearable heart rate sensor WHS-1 and a new algorithm, which may become an expeditious and cost-effective screening tool for identifying OSA.
Databáze: OpenAIRE
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