Article ; Online: Artificial intelligence-driven wearable technologies for neonatal cardiorespiratory monitoring: Part 1 wearable technology.
2023 Volume 93, Issue 2, Page(s) 413–425
Abstract: With the development of Artificial Intelligence techniques, smart health monitoring is becoming more popular. In this study, we investigate the trend of wearable sensors being adopted and developed in neonatal cardiorespiratory monitoring. We performed a ...
| Abstract | With the development of Artificial Intelligence techniques, smart health monitoring is becoming more popular. In this study, we investigate the trend of wearable sensors being adopted and developed in neonatal cardiorespiratory monitoring. We performed a search of papers published from the year 2000 onwards. We then reviewed the advances in sensor technologies and wearable modalities for this application. Common wearable modalities included clothing (39%); chest/abdominal belts (25%); and adhesive patches (15%). Popular singular physiological information from sensors included electrocardiogram (15%), breathing (24%), oxygen saturation and photoplethysmography (13%). Many studies (46%) incorporated a combination of these signals. There has been extensive research in neonatal cardiorespiratory monitoring using both single and multi-parameter systems. Poor data quality is a common issue and further research into combining multi-sensor information to alleviate this should be investigated. IMPACT STATEMENT: State-of-the-art review of sensor technology for wearable neonatal cardiorespiratory monitoring. Review of the designs for wearable neonatal cardiorespiratory monitoring. The use of multi-sensor information to improve physiological data quality has been limited in past research. Several sensor technologies have been implemented and tested on adults that have yet to be explored in the newborn population. |
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| MeSH term(s) | Adult ; Infant, Newborn ; Humans ; Artificial Intelligence ; Monitoring, Physiologic/methods ; Wearable Electronic Devices ; Respiration | ||||||||||
| Language | English | ||||||||||
| Publishing date | 2023-01-02 | ||||||||||
| Publishing country | United States | ||||||||||
| Document type | Journal Article ; Review ; Research Support, Non-U.S. Gov't | ||||||||||
| ZDB-ID | 4411-8 | ||||||||||
| ISSN | 1530-0447 ; 0031-3998 | ||||||||||
| ISSN (online) | 1530-0447 | ||||||||||
| ISSN | 0031-3998 | ||||||||||
| DOI | 10.1038/s41390-022-02416-x | ||||||||||
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| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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