Abstract
Background
With the development of Artificial Intelligence (AI) techniques, smart health monitoring, particularly neonatal cardiorespiratory monitoring with wearable devices, is becoming more popular. To this end, it is crucial to investigate the trend of AI and wearable sensors being developed in this domain.
Methods
We performed a review of papers published in IEEE Xplore, Scopus, and PubMed from the year 2000 onwards, to understand the use of AI for neonatal cardiorespiratory monitoring with wearable technologies. We reviewed the advances in AI development for this application and potential future directions. For this review, we assimilated machine learning (ML) algorithms developed for neonatal cardiorespiratory monitoring, designed a taxonomy, and categorised the methods based on their learning capabilities and performance.
Results
For AI related to wearable technologies for neonatal cardio-respiratory monitoring, 63% of studies utilised traditional ML techniques and 35% utilised deep learning techniques, including 6% that applied transfer learning on pre-trained models.
Conclusions
A detailed review of AI methods for neonatal cardiorespiratory wearable sensors is presented along with their advantages and disadvantages. Hierarchical models and suggestions for future developments are highlighted to translate these AI technologies into patient benefit.
Impact
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State-of-the-art review in artificial intelligence used for wearable neonatal cardiorespiratory monitoring.
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Taxonomy design for artificial intelligence methods.
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Comparative study of AI methods based on their advantages and disadvantages.
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Data availability
Data sharing is not applicable to this article as no data sets were generated or analysed during the current study.
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Funding
E.G. acknowledges the support of the MIME-Monash Partners-CSIRO sponsored PhD research support programme and Research Training Program (RTP). T.C.K. and D.S. are supported by the National Institute of Health Research (NIHR) Children and Young People MedTech Co-operative (CYP MedTech). D.S. has received funding for technology development from the Medical Research Council, NIHR and Action Medical Research, and is a non-executive director of SurePulse Medical who are developing monitoring solutions for neonatal care. A.M.’s research is supported by the NHMRC (Aus) and Cerebral Palsy Alliance. The study is supported by the Monash Institute of Medical Engineering (MIME). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or of the Department of Health.
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Sitaula, C., Grooby, E., Kwok, T.C. et al. Artificial intelligence-driven wearable technologies for neonatal cardiorespiratory monitoring. Part 2: artificial intelligence. Pediatr Res 93, 426–436 (2023). https://doi.org/10.1038/s41390-022-02417-w
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DOI: https://doi.org/10.1038/s41390-022-02417-w
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