The transactional model of sleep identifies interactions between multiple factors, including infant temperament, parenting, and context contribute to variability in infant sleep. Research has focused on between-person designs and subjective or short observation periods, limiting the ability to examine variability in infant sleep. The present study utilized between-person methodologies to examine how supportive parenting and three temperamental characteristics were related to variability (i.e., fluctuations in sleep over time) and inertia (i.e., day-to-day influence of sleep) to capture stability in within-person sleep outcomes. Participants included parents (N = 208) of 4- to 12-month-old infants who were recruited by emails to Nanit baby monitor users. Sleep metrics from the Nanit baby monitor were provided nightly for up to two weeks, including total sleep time (TST) and parent visits to crib (PVC) through autovideosomnography and computer vision techniques from the Nanit. Participants completed questionnaires assessing infant temperament and parenting quality. Using dynamic structural equation modeling, we found that infant negative emotionality was associated with more TST inertia and lower PVC inertia. Infant effortful control was associated with more PVC inertia and lower TST inertia. Supportive parenting was associated with lower TST inertia and higher PVC inertia. When caregivers were higher in supportive parenting, there was a positive association between infant negative emotionality and TST inertia. In support of the transaction model of infant sleep, the current findings integrate social factors into infant sleep and build on infant sleep literature by identifying within-person variability in sleep behaviors in relation to infant temperament traits and supportive parenting.

Although parental emotional challenges and emotion-based media motivations are linked to screen media use patterns in families of toddlers, little work has examined parental emotion regulation strategies in relation to parents' and toddlers' screen media use. Because these strategies are modifiable components of how parents manage emotional demands, investigating them is an important next step for understanding factors associated with family media use and informing media guidance. The present study examined associations between maternal emotion regulation strategies (expressive suppression and cognitive reappraisal) and both maternal and toddlers' screen media use, distinguishing between non-interactive and interactive forms given their differing implications for toddler development. Mothers of toddlers (18-36 months, N = 296) reported their emotion regulation strategies and both their own and their toddlers' screen media use through an online survey. Data were analyzed using multivariable regression models, with additional analyses testing indirect associations. Results indicated that higher levels of maternal expressive suppression were associated with greater maternal non-interactive screen media use and with both types of toddlers' screen media use. Higher levels of maternal non-interactive screen media use were linked to greater non-interactive and interactive screen media use among toddlers, whereas maternal interactive screen media use was not related to either form of toddlers' screen media use. No significant associations were found between maternal cognitive reappraisal and maternal or toddlers' screen media use. These findings highlight the differential roles of parental emotion regulation strategies in maternal and toddlers' screen media use, particularly the distinct role of expressive suppression relative to cognitive reappraisal, and offer implications for supporting healthy family media practices.

We examined whether specific maternal-perceived prenatal life stress predicted infant cortisol output at 2 or 6 months. Expectant mothers reported the occurrence and perceived impact of 47 potential prenatal life stressors. Infant cortisol was assessed across four salivary samples collected during a laboratory/home visit including stressful activities. Associations were examined between infant cortisol output and each potential life stressor, accumulation of stress within 7 distinct categories, and total stress accumulation. Although total stress was associated with higher infant cortisol output, only four specific perceived life stressors (i.e., serious accident/illness, mental health challenges, and trauma experience (self and partners')) within two categories (health/mental health and vicarious stress) predicted heightened infant cortisol output after adjusting for covariates and the false discovery rate. Findings suggest that more severe stressors related to health/mental health may be more salient for early development of the hypothalamic-pituitary-adrenal system than less severe stressors (e.g., moving). Aggregating stressors regardless of severity may obscure meaningful effects.

Executive functioning (EF) in early childhood plays a critical role in shaping later cognitive, socioemotional, and academic outcomes. Although the influence of caregiving on EF is well documented in preschool and older children, relatively little is known about how early relational factors contribute to the emergence of rudimentary EF abilities during the first year of life. The present study examined the contributions of maternal sensitivity and mind-mindedness to the emergence of EF in infancy. Fifty-one typically developing infants aged 9-13 months were invited to participate. Infants completed the A-not-B task to assess their EF abilities. Maternal sensitivity and appropriate mind-minded comments were assessed during a structured interaction task, which included both non-distress (free-play) and distress-eliciting episodes. Results showed that both maternal sensitivity and appropriate mind-minded comments were related to infant EF, yet only mind-mindedness in non-distress contexts emerged as a significant predictor of early EF abilities. These findings emphasize the importance of caregivers' attunement to their infants' mental states in fostering the emergence of EF.

The recent rapid development of mobile and wearable sensing technologies and computational modeling has allowed for high-density and continuous measurement of infants' real-world behavior in natural settings. However, developmental science still struggles practically and methodologically to capture, label, integrate, and understand these data streams, especially in a way that is generalizable and inclusive. This review explores the state of the art in sensing and machine learning (ML) methods to study infants 0-36 months in natural environments. It delineates (i) sensing technologies, (ii) data collection and annotation approaches, (iii) ML approaches for behaviour recognition, prediction and modelling, and (iv) translational paths towards screening and early intervention, with a focus on feasibility, inclusivity, and ethics. A systematic review of literature published between 2015 and 2025 was performed in the following databases (Scopus, Web of Science, PubMed, IEEE Xplore, ACM), in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Inclusion criteria involved studies of infants between 0 and 36 months, naturalistic or free-flowing contexts, and mobile/wearable sensing, computer vision, signal processing or ML. The review examined the sensor modalities (egocentric and exocentric camera and microphone, inertial measurement unit/actigraphy, physiological sensors), data properties (temporal resolution, density, duration), and settings (home, clinic, community). The synthesis places a primary emphasis on naturalistic motor behavior, which is the area most well-represented in the studies included. Selectively considered sensing and ML evidence for vocal and communicative behavior (including language exposure and caregiver-infant interaction), social-affective behavior, and sleep-wake regulation are presented where relevant. It also explored ML paradigms (supervised, semi- and weakly supervised, self-supervised, multimodal, sequential, and transformer-based), validation approaches, and reporting quality.

This study examined the effects of Buzzy® and ShotBlocker® on pain and comfort levels in newborns during heel stick procedures. The study was conducted as a single-center randomized controlled trial in the Neonatal Intensive Care Unit and Obstetrics Department of Samandağ State Hospital between April and November 2025. A total of 174 term newborns were randomly assigned to three groups: Buzzy®, ShotBlocker®, and control. Data were collected using the Infant Information and Follow-up Form, the Neonatal Infant Pain Scale (NIPS), the Newborn Comfort Behavior Scale (NCBS), physiological measurements, and audio recordings used to assess crying duration. Newborns in both the Buzzy® and ShotBlocker® groups demonstrated significantly lower post-procedural pain scores compared to the control group. No significant difference in pain scores was observed between the two intervention groups. Post-procedural NCBS scores were significantly higher in the control group than in the intervention groups. Heart rate responses differed significantly between groups, whereas no significant between-group differences were found in oxygen saturation or post-procedural crying duration. These findings suggest that Buzzy® and ShotBlocker® may be considered as supportive non-pharmacological interventions for procedural pain management in neonatal care. Further multicenter studies are recommended to strengthen the evidence regarding their clinical effectiveness.

Infants learn through everyday interactions with the physical and social environment. For infants with cerebral palsy (CP), motor impairments may disrupt everyday learning opportunities. How can we measure real-world motor behavior and learning opportunities in infants with CP? Machine learning models have been developed to quantify body position throughout a day in infants with typical development (TD) using wearable sensor data. However, these models have not been validated in infants with motor impairments. This study assessed the validity of body position classification using machine learning and sensors in infants with CP. Ten infants with CP (7-18 months; one session each) and 19 infants with TD (4-12 months; 45 sessions) wore four inertial sensors on their legs throughout a day. Ninety minutes were video recorded and manually scored for body position in five categories: supine, prone, sitting, standing, and held. Random forest classifiers were trained to predict body position from sensor-derived motion features. Models trained on datasets that varied in size (9, 45, 54 sessions) and group composition (CP, TD, CP and TD) were compared to determine the most accurate model for infants with CP. Larger training sets and training sets that included data from infants with CP were the most accurate; the final models achieved similar performance in CP and TD (86% and 89% accuracy), captured meaningful individual differences (ICCs = 0.682-0.999), and generated predictions that were correlated with motor skill assessments. Findings demonstrate that wearable sensors and machine learning can accurately classify real-world body position in infants with CP.

The development of infant posture is shaped by a complex convergence of intrinsic abilities and environmental contexts. This longitudinal study examined how infants' postural engagement evolved across the first year of life, focusing on the roles of motor skill acquisition and movement context alongside age. Using naturalistic home video data, we tracked the frequency, duration, and diversity of postures across over 180 observations. Our findings reveal that postural transitions and engagement patterns shift dynamically with skill status and movement contexts (restrained vs. unrestrained), rather than following a linear age-based trajectory. Movement context effects were posture-specific: supine posture declined with age only in the unrestrained context; belly-on-the-floor posture declined with age overall; sitting flipped with skill - pre-sitters sat more in the restrained context, whereas sitters sat more in the unrestrained context; crawling showed no main effect of age but differed by crawling status, with an age × crawling status interaction; and upright increased modestly with age and showed the largest unrestrained context advantage, especially among cruisers. These results highlight the importance of considering how multiple interacting factors, not just chronological age, contribute to early postural development, extending skill-based accounts of motor development by demonstrating that movement context interacts with skill status in posture-specific ways.

Emotion regulation (ER) is a key developmental process shaped through parent-infant interactions, during which parents and infants dynamically co-regulate the infant's emotions. Successful co-regulation depends on parents' sensitivity to the infant's emotional cues; unadjusted parental responses, such as intrusiveness or withdrawal, can dysregulate the infant, reflected in physiological indicators such as heart rate (HR). Although research has advanced understanding of infant ER, most studies have focused on mothers and dyadic contexts and primarily compared infant HR during stressful versus non-stressful interactions, without examining the moment-to-moment dynamics of naturalistic interactions. We examined associations between infant HR and parental behaviors in three interaction contexts-mother-infant, father-infant, and triadic (mother-father-infant). Eighty families with three-month-old infants completed three successive two-minute free-play sessions corresponding to these contexts. Each session was divided into 5-s intervals, with parental intrusive and withdrawn behaviors (IWPBs) coded for intensity (0-4) and infant HR averaged per interval. Multilevel vector autoregression models were applied to assess lag-1 and contemporaneous effects at within- and between-family levels. IWPBs were associated with elevated infant HR, with cross-lagged effects showing that increases in IWPBs predicted subsequent increases in infant HR. For intrusive behaviors, associations with infant HR were bidirectional, suggesting dynamic co-regulation processes. Context differences also emerged: fathers showed delayed responses to infant arousal, whereas triadic interactions elicited stronger associations and higher HR levels when considering the whole sample. Overall, findings highlighted that parent-infant co-regulation is moment-to-moment, context-sensitive, and shaped by both parental behavior and infant physiological reactivity.

Autism Spectrum Disorder (ASD) is characterized by early challenges in social communication and behavioral flexibility, making timely behavioral analysis critical for early detection. We present a comprehensive framework for analyzing ASD-related child behaviors using a novel Play Behavior Protocol tailored to the Indian sociocultural context. Video recordings of semi-structured play interactions between the child, caregiver, and a clinically trained examiner were collected from children aged 0-36 months, including 34 children with ASD, 10 with developmental delay (DD), and 23 typically developing (TD) children. A comprehensive set of twenty-six behaviors, including facial, social, and play-based behaviors, were analyzed for frequency, duration, and variability across age and sex. Statistical analyses indicated that children with ASD exhibited reduced eye contact, social smiling, and joint attention, along with increased no affect, repetitive play, and solitary play compared to TD children. Additionally, children with ASD demonstrated lower levels of eye contact compared to children with DD. Furthermore, participant-level ratios, such as the eye-contact-to-gaze ratio and the social-smile-to-positive-affect ratio, emerged as potentially important markers for distinguishing ASD from DD and TD, with both ratios being lower in the ASD group compared to the DD and TD groups. Automated multimodal analysis of facial affect and gaze cues revealed that children with ASD exhibited reduced human-directed gaze, lower levels of happy and surprise expressions, and increased sad expressions compared to children with DD and TD. By integrating culturally contextualized data collection, systematic statistical analysis, and automated multimodal inference, this work presents the first comprehensive behavioral analysis framework of its kind for early ASD assessment in Indian children.

Spontaneous limb movements provide the foundation for motor development, yet knowledge of their normative characteristics has been limited by small homogenous samples and short observation windows. Leveraging the HEALthy Brain and Child Development (HBCD) study, we present descriptive characteristics of the first large-scale dataset of leg movements from 421 infants aged 0-2 months, captured with wearable sensors worn continuously for 72 h in naturalistic settings across multiple research sites in the United States. Our analysis focused on three domains: movement characteristics, variability of movement acceleration time-series, and physical activity intensity. Movement characteristics included leg movements per hour awake, peak acceleration per movement, average acceleration per movement, and movement duration. These characteristics aligned with earlier smaller-scale studies and showed highly consistent patterns between right and left legs. Sample entropy analysis revealed left-skewed distributions with median values near 1.3. Physical activity intensity estimations showed that infants spent the majority of time in sedentary activity, followed by light activity, with only brief periods of moderate-to-vigorous activity. Together, these findings provide initial characterization of multiple dimensions of infant leg movements, hence significantly contributing to derive reference distributions in early life. By establishing scalable, ecologically valid, and computationally tractable measures of infant motor behavior, this study lays the groundwork for integrating wearable sensing with longitudinal developmental science and for identifying early indicators of atypical trajectories. Ultimately, these findings contribute to the broader goals of the HBCD study: to understand how the brain develops and is shaped by environmental, social, and biological factors during pregnancy and after birth.

Segmental trunk control is central to upright motor development in preterm infants, yet evidence linking specific home environment attributes to condition-specific control in late infancy remains limited. This study aims to examine the associations between characteristics of commercial baby containers-defined as restricting equipment or furniture such as playpens and cots-and segmental trunk control during the standing-walking window. Additionally, age-related usage patterns of these containers from 8 to 13 months corrected age were described. In a prospective longitudinal study of 76 moderate-to-late preterm infants, caregivers provided monthly reports on container usage, specifically categorizing attributes of size, rail height, and floor surface compliance. Segmental trunk control was assessed monthly using the Segmental Assessment of Trunk Control (SATCo) under static, active, and reactive conditions. Results indicated that trunk control improved with age across all conditions, although reactive control initially developed more slowly than static and active control before converging at full proficiency by 13 months. Larger container size was consistently linked to better trunk control across static, active, and reactive conditions. Floor surface compliance also played a significant role; soft floors were associated with better static and active control but did not influence reactive control. Conversely, the height of the container rails showed no independent relationship with trunk control performance. Usage patterns shifted over time toward larger spaces and firmer surfaces. These findings suggest that in late infancy, expanded physical space consistently supports segmental trunk control, while surface compliance specifically benefits steady-state and anticipatory control. The results support low-cost, home-based guidance that encourages expanding safe play areas and selecting appropriately compliant surfaces to foster motor development in preterm infants.

Infants are provided unique, developmentally impactful experiences when in different positions. This research examined infant positioning over time, between assessment contexts, and in relation to child development. Infants one to six months old were assessed for six months. Infant position was measured during ten-minute play sessions using computer vision and across two full days when awake using a smart garment. Percent time supine, reclined, upright (sitting or standing), inclined, and prone were quantified. Linear mixed-effects models and Spearman correlation analyses were used to evaluate the data. Forty-nine dyads enrolled. Over time, infants spent less time supine and more time upright. Less time in supine was correlated with more advanced motor development. Infant positioning varied when assessed in different contexts. These findings highlight how infant positioning behavior changes across time, can be measured using novel technologies, and may be influenced by the context of measurement.

Capturing the complexity of infant behavior in naturalistic contexts remains a primary challenge in developmental science. High-density sensing can address this, but its adoption has been limited by the need for specialized, expensive, and physically intrusive hardware. We developed Expressions, an iOS application and data processing pipeline that repurposes Apple's TrueDepth camera system as a contactless, multimodal data collection tool. The application passively collects 60 Hz data on over 50 low-level features of facial expressions, 3D head movements for up to three interacting individuals, and eye gaze direction, while concurrently recording synchronized audio and video of the environment. We deployed Expressions in two developmental studies to test the feasibility and flexibility of this approach. In the first study, toddlers watched emotional videos on a computer that wirelessly streamed event markers to the recording device. This timestamping allowed us to time-lock and analyze the toddlers' micro-expressive and emotional responses to positive versus negative stimuli. In the second study, two wirelessly networked iPads captured simultaneous data from caregiver-infant dyads during free-flowing play. This markerless, dual-device setup allowed assessment of complex interaction dynamics without disrupting the interaction itself. These studies show that consumer mobile devices are a feasible and flexible platform for studying infant behavior. Because the facial tracking in Expressions runs entirely on-device, the app does not require internet access during data collection. This privacy feature allows deployment not only in labs and urban homes but also in remote and rural communities that have been underrepresented in developmental research.

Newborn sleep plays a vital role in early neurological and physiological development and may have lasting consequences for infants' developmental trajectories. However, few methods capture high-density sleep data in naturalistic settings during the newborn period. We address this by assessing the utility of the Owlet Dream Sock for capturing sleep patterns, timing, and duration in the home. Thirty-nine newborns (51.30% female, M age = 9.38 days old, SD = 6.40) wore the Owlet Dream Sock for fourteen days during all sleep periods. Newborns exhibited two common types of sleep bouts, light-only bouts (awake → light sleep → awake sequences) and full sleep cycles (awake → light sleep → deep sleep → light sleep → awake sequences). On average, sleep bouts began around 11:48 AM, and newborns spent approximately 172 monitoring minutes awake, 536 in light sleep, and 54 in deep sleep per day. The duration of time spent awake and in light sleep did not change over the assessment period; however, both the duration of deep sleep and the number of full sleep cycles increased each week. While nighttime sleep minutes did not change, daytime sleep minutes decreased. The Owlet Dream Sock shows acceptable feasibility for capturing high-density newborn sleep data to capture developmental changes in sleep patterns over the first weeks of life.