Enhanced monitoring of sleep position in sleep apnea patients: smartphone triaxial accelerometry compared with video-validated position from polysomnography
Poor sleep quality is a risk factor for multiple mental, cardiovascular, and cerebrovascular diseases. Certain sleep positions or excessive position changes can be related to some diseases and poor sleep quality. Nevertheless, sleep position is usually classified into four discrete values: supine, p...
| Autores: | , , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2021 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositório: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglês |
| OAI Identifier: | oai:upcommons.upc.edu:2117/351221 |
| Acesso em linha: | https://hdl.handle.net/2117/351221 https://dx.doi.org/10.3390/s21113689 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Medicine -- Data processing Sleep apnea syndromes Accelerometry Biomedical signal processing MHealth Monitoring Sleep apnea Sleep position Smartphone Medicina -- Informàtica Síndromes d'apnea del son Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
| Resumo: | Poor sleep quality is a risk factor for multiple mental, cardiovascular, and cerebrovascular diseases. Certain sleep positions or excessive position changes can be related to some diseases and poor sleep quality. Nevertheless, sleep position is usually classified into four discrete values: supine, prone, left and right. An increase in sleep position resolution is necessary to better assess sleep position dynamics and to interpret more accurately intermediate sleep positions. This research aims to study the feasibility of smartphones as sleep position monitors by (1) developing algorithms to retrieve the sleep position angle from smartphone accelerometry; (2) monitoring the sleep position angle in patients with obstructive sleep apnea (OSA); (3) comparing the discretized sleep angle versus the four classic sleep positions obtained by the video-validated polysomnography (PSG); and (4) analyzing the presence of positional OSA (pOSA) related to its sleep angle of occurrence. Results from 19 OSA patients reveal that a higher resolution sleep position would help to better diagnose and treat patients with position-dependent diseases such as pOSA. They also show that smartphones are promising mHealth tools for enhanced position monitoring at hospitals and home, as they can provide sleep position with higher resolution than the gold-standard video-validated PSG. |
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