{"doi":"10.17760/d20385584","title":"Movement as a vital sign in neonates","abstract":"Early infant movement may serve as a marker for the functional integrity of the nervous system. The overt motor behavior in infants during their first few months after birth has been shown to predict neurodevelopmental outcomes at future ages. However, previous research has studied movement mostly after the infants have been discharged from the hospital, with research methods designed for a home or research lab environment. In the NICU environment, assessments of infant motor activity have been limited to qualitative observations by clinicians at the bedside or from video recordings. Such evaluations are episodic, subjective, time-consuming, require expertise and are susceptible to observer fatigue and attention, thus suffering from low intra- and inter-observer repeatability. This necessitates the need for automated technology. Automated movement recording has been explored using video motion capture systems, which are costly and difficult to set up in a clinical environment. Other recording methods include sensors attached to the infant, but they still lack validation, and there is general reluctance to approve of additional sensors and wires. Further, only a few monitoring methods in the NICU have demonstrated any clinical benefit, as they were of only short duration. This thesis proposes the use of the photoplethysmogram (PPG) signal for the quantification of movement. The PPG signal is acquired with a pulse oximeter sensor continuously placed on the infant's hand or foot for routine monitoring of arterial oxygen saturation and blood volume. Infant movements cause artifacts in the PPG signal which are estimated by a novel custom-developed algorithm. Applying this movement detection method, clinical applications of early movement in high-risk infants are examined. The central hypothesis of this thesis is that movement in newborn infants is a vital sign that can shed light on the infant's state of health. We tested this hypothesis in four different studies. One study monitored preterm infants for 2-3 months and investigated how features of movement change with maturation. Any deviation from normal maturation could serve as a marker for neurological dysfunction. A second study on preterm infants examined how movement is related to respiration. A series of analyses of movement and respiratory signals revealed that movement caused respiratory instabilities and apneas. Using this knowledge, another study demonstrated that a machine learning algorithm showed higher efficacy for prediction of apneic episodes if features of movement were included as predictors. Finally, a therapeutic intervention study on a cohort of infants undergoing neonatal drug withdrawal symptoms showed that movement was a useful marker of irritability. Results also revealed that stochastic vibrotactile stimulation was a non-pharmacological intervention that could reduce undue movement activity and other symptoms of withdrawal in opioid-exposed newborns. Overall, the results from this thesis demonstrate that movement estimated from routine photoplethysmography can be a vital marker of physiology. Along with cardiorespiratory signals, movement is a biomarker that can assist clinicians in assessing the stability of an infant as well as enabling automated interventions to address dysregulation.","journal":null,"year":2020,"id":128073,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9567,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":578360,"name":"Ian Zuzarte","orcid":"0000-0002-1428-6922","position":0,"is_corresponding":true}],"reference_count":281,"raw_metadata":null,"created_at":"2026-07-18T23:15:38.879956Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}