Evaluating a Novel Infant Heart Rate Detector for Neonatal Resuscitation Efforts: Protocol for a Proof-of-Concept Study (Preprint) Article Swipe
YOU?
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· 2023
· Open Access
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· DOI: https://doi.org/10.2196/preprints.45512
BACKGROUND Over 10 million newborns worldwide undergo resuscitation at birth each year. Pediatricians may use electrocardiogram (ECG), pulse oximetry (PO), and stethoscope in determining heart rate (HR), as HR guides the need for and steps of resuscitation. HR must be obtained quickly and accurately. Unfortunately, the current diagnostic modalities are either too slow, obtaining HR in more than a minute, or inaccurate. With time constraints, a reliable robust heart rate detector (HRD) modality is required. This paper discusses a protocol for conducting a methods-based comparison study to determine the HR accuracy of a novel real-time HRD based on 3D-printed dry-electrode single-lead ECG signals for cost-effective and quick HR determination. The HRD’s HR results are compared to either clinical-grade ECG or PO monitors to ensure robustness and accuracy. OBJECTIVE The purpose of this study is to design and examine the feasibility of a proof-of-concept HRD that quickly obtains HR using biocompatible 3D-printed dry electrodes for single-lead neonatal ECG acquisition. This study uses a novel HRD and compares it to the gold-standard 3-lead clinical ECG or PO in a hospital setting. METHODS A cross-sectional study is planned to be conducted in the neonatal intensive care unit or postpartum unit of a large community teaching hospital in Toronto, Canada, from June 2023 to June 2024. In total, 50 newborns will be recruited for this study. The HRD and an ECG or PO monitor will be video recorded using a digital camera concurrently for 3 minutes for each newborn. Hardware-based signal processing and patent-pending embedded algorithm-based HR estimation techniques are applied directly to the raw collected single-lead ECG and displayed on the HRD in real time during video recordings. These data will be annotated and compared to the ECG or PO readings at the same points in time. Accuracy, F1-score, and other statistical metrics will be produced to determine the HRD’s feasibility in providing reliable HR. RESULTS The study is ongoing. The projected end date for data collection is around July 2024. CONCLUSIONS The study will compare the novel patent-pending 3D-printed dry electrode–based HRD’s real-time HR estimation techniques with the state-of-the-art clinical-grade ECG or PO monitors for HR accuracy and examines how fast the HRD provides reliable HR. The study will further provide recommendations and important improvements that can be made to implement the HRD for clinical applications, especially in neonatal resuscitation efforts. This work can be seen as a stepping stone in the development of robust dry-electrode single-lead ECG devices for HR estimations in the pediatric population. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/45512
Related Topics
- Type
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4384154170Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.2196/preprints.45512Digital Object Identifier
- Title
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Evaluating a Novel Infant Heart Rate Detector for Neonatal Resuscitation Efforts: Protocol for a Proof-of-Concept Study (Preprint)Work title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
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2023-07-10Full publication date if available
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Abdelrahman Abdou, Sridhar Krishnan, Niraj MistryList of authors in order
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https://doi.org/10.2196/preprints.45512Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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Medicine, Heart rate, Internal medicine, Blood pressureTop concepts (fields/topics) attached by OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.<title>CONCLUSIONS</title> | 337 |
| abstract_inverted_index.<i>F</i><sub>1</sub>-score, | 300 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.19183059 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |