A Systematic Review of Sensing Technologies for Wearable Sleep Staging
Designing wearable systems for sleep detection and staging is extremely challenging due to the numerous constraints associated with sensing, usability, accuracy, and regulatory requirements. Several researchers have explored the use of signals from a subset of sensors that are used in polysomnograph...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/21/5/1562 |
| _version_ | 1797395460646764544 |
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| author | Syed Anas Imtiaz |
| author_facet | Syed Anas Imtiaz |
| author_sort | Syed Anas Imtiaz |
| collection | DOAJ |
| description | Designing wearable systems for sleep detection and staging is extremely challenging due to the numerous constraints associated with sensing, usability, accuracy, and regulatory requirements. Several researchers have explored the use of signals from a subset of sensors that are used in polysomnography (PSG), whereas others have demonstrated the feasibility of using alternative sensing modalities. In this paper, a systematic review of the different sensing modalities that have been used for wearable sleep staging is presented. Based on a review of 90 papers, 13 different sensing modalities are identified. Each sensing modality is explored to identify signals that can be obtained from it, the sleep stages that can be reliably identified, the classification accuracy of systems and methods using the sensing modality, as well as the usability constraints of the sensor in a wearable system. It concludes that the two most common sensing modalities in use are those based on electroencephalography (EEG) and photoplethysmography (PPG). EEG-based systems are the most accurate, with EEG being the only sensing modality capable of identifying all the stages of sleep. PPG-based systems are much simpler to use and better suited for wearable monitoring but are unable to identify all the sleep stages. |
| first_indexed | 2024-03-09T00:35:50Z |
| format | Article |
| id | doaj.art-c631d4b5736b42beab7db614f2fb883b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T00:35:50Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-c631d4b5736b42beab7db614f2fb883b2023-12-11T18:12:48ZengMDPI AGSensors1424-82202021-02-01215156210.3390/s21051562A Systematic Review of Sensing Technologies for Wearable Sleep StagingSyed Anas Imtiaz0Wearable Technologies Lab, Imperial College London, London SW7 2AZ, UKDesigning wearable systems for sleep detection and staging is extremely challenging due to the numerous constraints associated with sensing, usability, accuracy, and regulatory requirements. Several researchers have explored the use of signals from a subset of sensors that are used in polysomnography (PSG), whereas others have demonstrated the feasibility of using alternative sensing modalities. In this paper, a systematic review of the different sensing modalities that have been used for wearable sleep staging is presented. Based on a review of 90 papers, 13 different sensing modalities are identified. Each sensing modality is explored to identify signals that can be obtained from it, the sleep stages that can be reliably identified, the classification accuracy of systems and methods using the sensing modality, as well as the usability constraints of the sensor in a wearable system. It concludes that the two most common sensing modalities in use are those based on electroencephalography (EEG) and photoplethysmography (PPG). EEG-based systems are the most accurate, with EEG being the only sensing modality capable of identifying all the stages of sleep. PPG-based systems are much simpler to use and better suited for wearable monitoring but are unable to identify all the sleep stages.https://www.mdpi.com/1424-8220/21/5/1562sleepwearablessleep stagingsleep sensorssleep scoring |
| spellingShingle | Syed Anas Imtiaz A Systematic Review of Sensing Technologies for Wearable Sleep Staging Sensors sleep wearables sleep staging sleep sensors sleep scoring |
| title | A Systematic Review of Sensing Technologies for Wearable Sleep Staging |
| title_full | A Systematic Review of Sensing Technologies for Wearable Sleep Staging |
| title_fullStr | A Systematic Review of Sensing Technologies for Wearable Sleep Staging |
| title_full_unstemmed | A Systematic Review of Sensing Technologies for Wearable Sleep Staging |
| title_short | A Systematic Review of Sensing Technologies for Wearable Sleep Staging |
| title_sort | systematic review of sensing technologies for wearable sleep staging |
| topic | sleep wearables sleep staging sleep sensors sleep scoring |
| url | https://www.mdpi.com/1424-8220/21/5/1562 |
| work_keys_str_mv | AT syedanasimtiaz asystematicreviewofsensingtechnologiesforwearablesleepstaging AT syedanasimtiaz systematicreviewofsensingtechnologiesforwearablesleepstaging |