Relationships between full-day arm movement characteristics and developmental status in infants with typical development as they learn to reach: An observational study

Outcomes and Hand Use of Reaching Attempts: Comparison of Infants at Risk for Developmental Disability and Infants With Typical Development

Background

Infants at risk for developmental disabilities often show signs of motor delay. Reaching is a skill that can help us identify atypical motor trajectories in early infancy. Researchers have studied performance after onset of reaching, but none have followed infants at risk from pre-reaching to skilled reaching.

Aims

We assessed differences in reaching outcomes and hand use as reaching skill emerged in infants at risk for developmental disabilities and with typical development.

Methods and Procedures

We followed infants at risk for developmental disabilities (n = 11) and infants with typical development (n = 21) longitudinally as they developed reaching skill. Infants reached for a toy at midline while sitting in the caregiver's lap. Video data were coded for reach outcome (miss, touch, partial grasp, and whole-hand grasp) and hand use (right, left, and bilateral).

Outcomes and Results

Infants at risk had a larger proportion of missed reaches across visits compared to infants with typical development. Infants at risk also showed less variability in hand use when grasping over the study period.

Conclusion and Implications

Our results provide information to support early differences in reaching performance to inform identification of typical and atypical developmental trajectories. Future studies should assess how the missed reaches are different and consider other quantitative measures of movement variability in infants at risk.

Design and validation of a smart garment to measure positioning practices of parents with young infants

The aim of this cross-sectional study was to evaluate the feasibility, construct validity, and reliability of a smart garment to characterize parent-child positioning practices in infants less than six months old. The smart garment (Get Around Garment, GG) was developed through feedback from seven infants and their parents. The final system was then tested with sixteen infants (M = 3.1 ± 1.1 months) assessed in their homes during one visit that consisted of a: 1) Structured Play Assessment (2.5 min): infant was placed in each of five positions (prone, supine, reclined/inclined, and upright) for 30 s, 2) Free Play Assessment (40-60 min): parents were asked to engage in typical daily activities, and 3) second Structured Play Assessment. Infants' body position was both coded from video and identified from sensor data using a custom program. Feasibility was measured by data from a Daily Wearing Log and Garment Perception Questionnaire. Validity was evaluated by comparing the coding and sensor data. Reliability was measured by comparing the sensor data between the two Structured Play Assessments. The GG was considered feasible for use. The smart wearable system showed high levels of accuracy for classifying body position secondby- second and when comparing cumulative duration across time. Reliability of the smart garment was excellent. Young infants spent more time in supine and supported upright positions relative to prone, reclined, or inclined positions. The results suggest that accelerometers can be integrated into garments in a manner that is feasible to provide accurate and consistent data about positioning practices of parents with young infants. Monitoring early positioning practices is important because these practices impact future motor and cognitive developmental trajectories.

Infant Leg Activity Intensity Before and After Naps

Wearable sensors are being used to measure intensity of infant physical activity across full days. The variability of infant activity intensity within and across days is important to study given the potential impact of physical activity on developmental trajectories. Using retrospective data, we analyzed the intensity of leg movements in 10 typically-developing infants before and after naptimes. Leg movement data were captured from 20 minutes before and after multiple events of naps across seven days for each infant. We hypothesized that leg movement intensity would be lower before a nap than after a nap potentially due to lower arousal and increased fatigue prior to attaining sleep. However, our results showed that leg movement intensity was not significantly different when comparing the 20-minute period pre- and post-naps (F(1,7)=3.91, p=0.089, η_p ²=0.358). Our results are a first step in describing patterns of infant activity across days and highlights the need for further research regarding infant energy expenditure and physical activity.

Quantifying Caregiver Movement when Measuring Infant Movement across a Full Day: A Case Report

There is interest in using wearable sensors to measure infant movement patterns and physical activity, however, this approach is confounded by caregiver motion. The purpose of this study is to estimate the extent that caregiver motion confounds wearable sensor data in full-day studies of infant leg movements. We used wearable sensors to measure leg movements of a four-month-old infant across 8.5 hours, during which the infant was handled by the caregiver in a typical manner. A researcher mimicked the actions of the caregiver with a doll. We calculated 7744 left and 7107 right leg movements for the infant and 1013 left and 1115 right "leg movements" for the doll. In this case, approximately 15% of infant leg movements can be attributed to background motion of the caregiver. This case report is the first step toward removing caregiver-produced background motion from the infant wearable sensor signal. We have estimated the size of the effect and described the activities that were related to noise in the signal. Future research can characterize the noise in detail and systematically explore different methods to remove it.

Sensor Measures of Symmetry Quantify Upper Limb Movement in the Natural Environment Across the Lifespan

Knowledge of upper limb activity in the natural environment is critical for evaluating the effectiveness of rehabilitation services. Wearable sensors allow efficient collection of these data and have the potential to be less burdensome than self-report measures of activity. Sensors can capture many different variables of activity and daily performance, many of which could be useful in identifying deviation from typical movement behavior or measuring outcomes from rehabilitation interventions. Although it has potential, sensor measurement is just emerging, and there is a lack of consensus regarding which variables of daily performance are valid, sensitive, specific, and useful. We propose that symmetry of full-day upper limb movement is a key variable. We describe here that symmetry is valid, robustly observed within a narrow range across the lifespan in typical development, and shows evidence of being different in populations with neuromotor impairment. Key next steps include the determination of sensitivity, specificity, minimal detectable change, and minimal clinically important change/difference. This information is needed to determine whether an individual belongs to the typical or atypical group, whether change has occurred, and whether that change is beneficial.

Relationships between variance in electroencephalography relative power and developmental status in infants with typical development and at risk for developmental disability: An observational study

Background: Electroencephalography (EEG) is a non-invasive tool that has the potential to identify and quantify atypical brain development. We introduce a new measure here, variance of relative power of resting-state EEG. We sought to assess whether variance of relative power of resting-state EEG could predict i) classification of infants as typical development (TD) or at risk (AR) for developmental disability, and ii) Bayley developmental scores at the same visit or future visits.

Methods: A total of 22 infants with TD participated, aged between 38 and 203 days. In addition, 11 infants broadly at risk participated (6 high-risk pre-term, 4 low-risk pre-term, 1 high-risk full-term), aged between 40 and 225 days of age (adjusted for prematurity). We used EEG to measure resting-state brain function across months. We calculated variance of relative power as the standard deviation of the relative power across each of the 32 EEG electrodes. The Bayley Scales of Infant Development (3 ^rd edition) was used to measure developmental level. Infants were measured 1-6 times each, with 1 month between measurements.

Results: Our main findings were: i) variance of relative power of resting state EEG can predict classification of infants as TD or AR, and ii) variance of relative power of resting state EEG can predict Bayley developmental scores at the same visit (Bayley raw fine motor, Bayley raw cognitive, Bayley total raw score, Bayley motor composite score) and at a future visit (Bayley raw fine motor).

Conclusions: This was a preliminary, exploratory, small study. Our results support variance of relative power of resting state EEG as an area of interest for future study as a biomarker of neurodevelopmental status and as a potential outcome measure for early intervention.