Transforming Sleep Monitoring: Review of Wearable and Remote Devices Advancing Home Polysomnography and Their Role in Predicting Neurological Disorders DOI Creative Commons
Diana Vitazkova, Helena Svobodová,

Daniela Turonova

и другие.

Biosensors, Год журнала: 2025, Номер 15(2), С. 117 - 117

Опубликована: Фев. 17, 2025

This paper explores the progressive era of sleep monitoring, focusing on wearable and remote devices contributing to advances in concept home polysomnography. We begin by exploring basic physiology sleep, establishing a theoretical basis for understanding stages associated changes physiological variables. The review then moves an analysis specific cutting-edge technologies, with emphasis their practical applications, user comfort, accuracy. Attention is also given ability these predict neurological disorders, particularly Alzheimer's Parkinson's disease. highlights integration hardware innovations, targeted parameters, partially advanced algorithms, illustrating how elements converge provide reliable health information. By bridging gap between clinical diagnosis real-world applicability, this aims elucidate role modern monitoring tools improving personalised healthcare proactive disease management.

Язык: Английский

Transforming Sleep Monitoring: Review of Wearable and Remote Devices Advancing Home Polysomnography and Their Role in Predicting Neurological Disorders DOI Creative Commons
Diana Vitazkova, Helena Svobodová,

Daniela Turonova

и другие.

Biosensors, Год журнала: 2025, Номер 15(2), С. 117 - 117

Опубликована: Фев. 17, 2025

This paper explores the progressive era of sleep monitoring, focusing on wearable and remote devices contributing to advances in concept home polysomnography. We begin by exploring basic physiology sleep, establishing a theoretical basis for understanding stages associated changes physiological variables. The review then moves an analysis specific cutting-edge technologies, with emphasis their practical applications, user comfort, accuracy. Attention is also given ability these predict neurological disorders, particularly Alzheimer's Parkinson's disease. highlights integration hardware innovations, targeted parameters, partially advanced algorithms, illustrating how elements converge provide reliable health information. By bridging gap between clinical diagnosis real-world applicability, this aims elucidate role modern monitoring tools improving personalised healthcare proactive disease management.

Язык: Английский

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