Sampling Development

Adolph, Karen E.; Robinson, Scott R.

doi:10.1080/15248372.2011.608190

Cited by 30 publications

(25 citation statements)

References 36 publications

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“…Visual inspection of Figure 3 does not show individual infant trajectories converging closer to a composite score of 100 over time. These findings fit with our knowledge that development is a complex, non-linear process 25 26 , and support the theory that optimal variability (not too much and not too little) is a defining characteristic of a healthy neuromotor system 20 24 .…”

Section: Discussionsupporting

confidence: 89%

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

et al. 2018

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Background: Advances in wearable sensor technology now allow us to quantify the number, type and kinematic characteristics of bouts of infant arm movement made across a full day in the natural environment. Our aim here was to determine whether the amount and kinematic characteristics of arm movements made across the day in the natural environment were related to developmental status in infants with typical development as they learned to reach for objects using their arms. Methods: We used wearable sensors to measure arm movement across days and months as infants developed arm reaching skills. In total, 22 infants with typical development participated, aged between 38 and 203 days. Of the participants, 2 infants were measured once and the other 20 infants were measured once per month for 3 to 6 visits. The Bayley Scales of Infant Development was used to measure developmental level. Results: Our main findings were: 1) infant arm movement characteristics as measured by full-day wearable sensor data were related to Bayley motor, cognitive and language scores, indicating a relationship between daily movement characteristics and developmental status; 2) infants who moved more had larger increases in language and cognitive scores across visits; and 3) larger changes in movement characteristics across visits were related to higher motor scores. Conclusions: This was a preliminary, exploratory, small study of the potential importance of infant arm movement characteristics as measured by full-day wearable sensor data. Our results support full-day arm movement activity as an area of interest for future study as a biomarker of neurodevelopmental status and as a target for early intervention.

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Section: Discussionsupporting

confidence: 89%

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

et al. 2018

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“…Studies of infant leg movements tend to quantify infants’ behavior from seconds [ 1 ] to minutes [ 2 , 3 ], up to an hour or two [ 4 – 6 ]. Despite the great knowledge gathered from these studies, it has recently been argued that to further advance the field, we must use new technologies to sample development for a minimum of 24 h per sample in order to overcome the effects of circadian rhythms, behavioral context, environmental stimuli, mood and motivation, among others [ 7 ]. Newer technologies, namely accelerometers, allow for longer-term data collection and analysis of infants behavior over 24 or even 48 continuous hours [ 8 – 10 ].…”

Section: Introductionmentioning

confidence: 99%

Sample Entropy Identifies Differences in Spontaneous Leg Movement Behavior between Infants with Typical Development and Infants at Risk of Developmental Delay

et al. 2017

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We are interested in using wearable sensor data to analyze detailed characteristics of movement, such as repeatability and variability of movement patterns, over days and months to accurately capture real-world infant behavior. The purpose of this study was to explore Sample Entropy (SampEn) from wearable sensor data as a measure of variability of spontaneous infant leg movement and as a potential marker of the development of neuromotor control. We hypothesized that infants at risk (AR) of developmental delay would present significantly lower SampEn values than infants with typical development (TD). Participants were 11 infants with TD and 20 infants AR. We calculated SampEn from 1–4 periods of data of 7200 samples in length when the infants were actively playing across the day. The infants AR demonstrated smaller SampEn values (median 0.21) than the infants with TD (median 1.20). Lower values of SampEn indicate more similarity in patterns across time, and may indicate more repetitive, less exploratory behavior in infants AR compared to infants with TD. In future studies, we would like to expand to analyze longer periods of wearable sensor data and/or determine how to optimally sample representative periods across days and months.

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“…Another explanation is that the 5–8 min of movement observed in these studies [ 13 , 17 ] is not sufficient to accurately capture the relationships of interest. Infant behavior is highly variable and affected by context, thus a snapshot of behavior may not reflect the true relationship [ 18 ]. Currently, there is no benchmark for the daily quantity of leg movements generated by typically-developing infants.…”

Section: Introductionmentioning

confidence: 99%

Daily Quantity of Infant Leg Movement: Wearable Sensor Algorithm and Relationship to Walking Onset

Smith

Trujillo-Priego

Lane

et al. 2015

Sensors

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Background: Normative values are lacking for daily quantity of infant leg movements. This is critical for understanding the relationship between the quantity of leg movements and onset of independent walking, and will begin to inform early therapy intervention for infants at risk for developmental delay. Methods: We used wearable inertial movement sensors to record full-day leg movement activity from 12 infants with typical development, ages 1–12 months. Each infant was tested three times across 5 months, and followed until the onset of independent walking. We developed and validated an algorithm to identify infant-produced leg movements. Results: Infants moved their legs tens of thousands of times per day. There was a significant effect of leg movement quantity on walking onset. Infants who moved their legs more walked later than infants who moved their legs less, even when adjusting for age, developmental level or percentile length. We will need a much larger sample to adequately capture and describe the effect of movement experience on developmental rate. Our algorithm defines a leg movement in a specific way (each pause or change in direction is counted as a new movement), and further assessment of movement characteristics are necessary before we can fully understand and interpret our finding that infants who moved their legs more walked later than infants who moved their legs less. Conclusions: We have shown that typically-developing infants produce thousands of leg movements in a typical day, and that this can be accurately captured in the home environment using wearable sensors. In our small sample we can identify there is an effect of leg movement quantity on walking onset, however we cannot fully explain it.

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Sampling Development

Cited by 30 publications

References 36 publications

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

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

Sample Entropy Identifies Differences in Spontaneous Leg Movement Behavior between Infants with Typical Development and Infants at Risk of Developmental Delay

Daily Quantity of Infant Leg Movement: Wearable Sensor Algorithm and Relationship to Walking Onset

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