ArticleIEEE journal of translational engineering in health and medicine2018
A Ballistographic Approach for Continuous and Non-Obtrusive Monitoring of Movement in Neonates.
Article in IEEE journal of translational engineering in health and medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Future perspectives of heart rate and oxygenation monitoring in the neonatal intensive care unit - a narrative review.Journal of clinical monitoring and computing · 2025Review
- A Two-Dimensional Position and Motion Monitoring System for Preterm Infants Using a Fiber-Optic Pressure-Sensitive Mattress.Sensors (Basel, Switzerland) · 2025Article
- Exploring the predictive value of carotid Doppler ultrasound and clinical features for spinal anesthesia-induced hypotension: a prospective observational study.Perioperative medicine (London, England) · 2025Article
- Non-obtrusive monitoring of obstructive sleep apnea syndrome based on ballistocardiography: a preliminary study.Frontiers in neuroscience · 2025Article
- Towards Non-Invasive and Continuous Blood Pressure Monitoring in Neonatal Intensive Care Using Artificial Intelligence: A Narrative Review.Healthcare (Basel, Switzerland) · 2023Review
- The impact of healthy pregnancy on features of heart rate variability and pulse wave morphology derived from wrist-worn photoplethysmography.Scientific reports · 2023Article
- Unobstructive Heartbeat Monitoring of Sleeping Infants and Young Children Using Sheet-Type PVDF Sensors.Sensors (Basel, Switzerland) · 2023Article
- Remote Patient Monitoring and Teleconsultation to Improve Health Outcomes and Reduce Health Care Utilization of Pediatric Asthma (ALPACA Study): Protocol for a Randomized Controlled Effectiveness Trial.JMIR research protocols · 2023Article
- Review
- Cardiorespiratory signature of neonatal sepsis: development and validation of prediction models in 3 NICUs.Pediatric research · 2023Article
- Vital signs as physiomarkers of neonatal sepsis.Pediatric research · 2022Review
- Prediction of Late-Onset Sepsis in Preterm Infants Using Monitoring Signals and Machine Learning.Critical care explorations · 2021Article
- Heart Rate Variability in the Perinatal Period: A Critical and Conceptual Review.Frontiers in neuroscience · 2020Review
- Predictive Monitoring of Critical Cardiorespiratory Alarms in Neonates Under Intensive Care.IEEE journal of translational engineering in health and medicine · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Continuously monitoring body movement in preterm infants can have important clinical applications since changes in movement-patterns can be a significant marker for clinical deteriorations including the onset of sepsis, seizures, and apneas. This paper proposes a system and method to monitor body movement of preterm infants in a clinical environment using ballistography. The ballistographic signal (BSG) is acquired using a thin and a film-like sensor that is placed underneath an infant. Manual annotations based on video-recordings served as a reference standard for identifying movement. We investigated the performance of multiple features, constructed from the BSG waveform, to discriminate movement from no movement based on data acquired from 10 preterm infants. Since routine cardiorespiratory monitoring is prone to movement artifacts, we also compared the application of these features on the simultaneously acquired cardiorespiratory waveforms, i.e., the electrocardiogram, the chest impedance, and the photoplethysmogram. The BSG-based-features consistently outperformed those based on the routinely acquired cardiorespiratory waveforms. The best performing BSG-based feature-the signal instability index-had a mean (standard deviation) effect size of 0.90 (0.06), as measured by the area under the receiver operating curve. The proposed system for monitoring body movement is robust to noise, non-obtrusive, and has high performance in clinical settings.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.