Application of a computer vision algorithm to quantify the frequency and duration of children's microactivities in different play scenarios

应用计算机视觉算法量化儿童在不同游戏场景中的微活动频率和持续时间

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Abstract

BACKGROUND: Microactivity rates, including hand- and object-to-mouth contacts, are inputs for modeling children's exposure to chemicals in soil and dust and from toys. EPA's confidence in its current recommended microactivity frequency estimates for use in exposure assessments is low. OBJECTIVE: We aimed to quantify children's hand- and object-to-mouth microactivities using a novel computer vision method and explored differences by lifestage and fine and gross motor development. METHODS: We recorded 20-minute videos of 61 children aged 6 to ≤18 months playing in their homes under two play contexts. We employed a novel computer vision approach that uses multiview video to estimate 3D body keypoints and measure hand-to-mouth distances, enabling quantification of each child's hand-and object-to-mouth contact without the need for human coders. We explored differences in the frequency and duration of microactivity contacts by age and motor development. RESULTS: We observed at least one instance of a microactivity event (i.e., hand- or object-to-mouth contact) among 41 of the 61 participants observed. The median rate of object-to-mouth contacts (23 contacts/hour) was greater than hand-to-mouth contacts (6 contacts/hour). We did not observe significant differences in the frequency of either hand-to-mouth and object-to-mouth contacts by age or motor development, but we did observe greater variation in object-to-mouth contacts than previously reported. The median durations of hand- and object-to-mouth contact were 0.24 min/hour and 1.57 min/hour, respectively. SIGNIFICANCE: Our observed rates of microactivities are comparable and in some cases, less than the current EPA central tendency estimates recommended for use in risk assessments. Our high-end (95th percentile) estimate for object-to-mouth contacts, however, underscores the need for better characterization of population variability in order to protect the most highly exposed children. IMPACT: We apply a novel computer vision algorithm to quantify the microactivity frequencies and durations of 61 children 6 to ≤18 months old. We examine differences in these frequencies and durations by child lifestage and motor development. Demonstration of this method paves the way for future, larger studies that observe children for longer durations to develop confident estimates of population variability in microactivity behaviors. These and future data could inform analyses in support of the revision of EPA recommendations for children's soil and dust ingestion rates.

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