Continuous sensing and quantification of body motion in infants: A systematic review

Peng, Zheng; Kommers, Deedee; Liang, Rong-Hao; Long, Xi; Cottaar, Ward; Niemarkt, Hendrik J.; Andriessen, Peter; Pul, Carola van

doi:10.1016/j.heliyon.2023.e18234

Cited by 5 publications

(5 citation statements)

References 66 publications

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“…In this study, we have introduced a novel approach for quantifying movement in preterm infants using a 2-D fiber mat, aiming to provide safe and robust movement monitoring for the optimal care of infants in the NICU and NMCU. As reported in our recent systematic review [2], continuous and unobtrusive movement monitoring can offer valuable insights into infants' movement patterns, which are essential for assessing their physiological status and developmental progress. This movement-based vital sign can complement traditional physiological parameters and enable a more holistic understanding of the condition of infants, allowing for timely intervention and early detection of clinical pathologies, such as sepsis and seizure [6], [7].…”

Section: Discussionmentioning

confidence: 96%

“…M ONITORING movements in infants, particularly preterm infants, can provide insights into their physiological conditions throughout various aspects of neonatal care [1], [2]. It plays a vital role in, for example, sleep assessment [3], developmental maturation tracking [4], and early disease detection, such as cerebral palsy, sepsis, and epilepsy [5], [6], [7].…”

Section: Introductionmentioning

confidence: 99%

“…To address this need, different noncontact or unobtrusive approaches to quantify movement in infants have been explored. As summarized in our recent systematic review [2], video-based motion quantification approaches were most often investigated as a noncontact and less obtrusive monitoring technology in infants, showing promising results on movement and cerebral palsy detection [5], [9]. Specifically, as reported in [9], an average area under the receiver operating curve (AUC) of 0.86 was obtained for general movement detection in preterm infants by using the background substruction method in video recordings.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Continuous Movement Quantification in Preterm Infants Using Fiber Mat: Advancing Long-Term Monitoring in Hospital Settings

Peng,

Zhao,

Kommers

et al. 2024

IEEE Trans. Instrum. Meas.

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Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Continuous Movement Quantification in Preterm Infants Using Fiber Mat: Advancing Long-Term Monitoring in Hospital Settings

Peng,

Zhao,

Kommers

et al. 2024

IEEE Trans. Instrum. Meas.

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“…, wearables, mattresses, radar, or waveform artifacts). 35 Similar workflow integrations are used to monitor for arrhythmias and apnea-bradycardia events.…”

Section: Discussionmentioning

confidence: 99%

“…Such interpretability is not the case with other infant motion sensing technology (e.g., wearables, mattresses, radar, or waveform artifacts). 35 Similar workflow integrations are used to monitor for arrhythmias and apnea-bradycardia events.…”

Section: Discussionmentioning

confidence: 99%

Accurate prediction of neurologic changes in critically ill infants using pose AI

Gleason,

Richter,

Beller

et al. 2024

Preprint

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Importance: Infant alertness and neurologic changes are assessed by exam, which can be intermittent and subjective. Reliable, continuous methods are needed. Objective: We hypothesized that our computer vision method to track movement, pose AI, could predict neurologic changes. Design: Retrospective observational study from 2021-2022. Setting: A level four urban neonatal intensive care unit (NICU). Participants: Infants with corrected age ≤1 year, comprising 115 patients with 4,705 hours of video data linked to electroencephalograms (EEG), including 46% female and 25.2% white non-Hispanic. Exposures: Pose AI prediction of anatomic landmark position and an XGBoost classifier trained on one-minute variance in pose. Main outcomes and measures: Outcomes were cerebral dysfunction, diagnosed from EEG readings by an epileptologist, and sedation, defined by the administration of sedative medications. Measures of algorithm performance were receiver operating characteristic-area under the curves (ROC-AUCs) on cross-validation and on two test datasets comprised of held-out infants and held-out video frames from infants used in training. Results: Infant pose was accurately predicted in cross-validation, held-out frames, and held-out infants (respective ROC-AUCs 0.94, 0.83, 0.89). Median movement increased with age and, after accounting for age, was lower with sedative medications and in infants with cerebral dysfunction (all P<5x10-3, 10,000 permutations). Sedation prediction had high performance on cross-validation, held-out frames, and held-out infants (ROC-AUCs 0.90, 0.91, 0.87), as did prediction of cerebral dysfunction (ROC-AUCs 0.91, 0.90, 0.76). Conclusions and Relevance: We used pose AI to predict sedation and cerebral dysfunction in 4,705 hours of video from a large, diverse cohort of infants. Pose AI may offer a scalable, minimally invasive method for neuro-telemetry in the NICU.

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Movement Quantification in Preterm Infants: Comparing Motion Extraction from ECG Signals and from Pressure Sensitive Fiber Optics Mat

Palladino,

Peng,

Kommers

et al. 2024

2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA)

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Continuous sensing and quantification of body motion in infants: A systematic review

Cited by 5 publications

References 66 publications

Continuous Movement Quantification in Preterm Infants Using Fiber Mat: Advancing Long-Term Monitoring in Hospital Settings

Continuous Movement Quantification in Preterm Infants Using Fiber Mat: Advancing Long-Term Monitoring in Hospital Settings

Accurate prediction of neurologic changes in critically ill infants using pose AI

Movement Quantification in Preterm Infants: Comparing Motion Extraction from ECG Signals and from Pressure Sensitive Fiber Optics Mat

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