在家中使用可穿戴系统绘制婴儿运动发育图表：验证和与身体生长图表的比较。

Charting infants' motor development at home using a wearable system: validation and comparison to physical growth charts.

机构信息

BABA Center, Pediatric Research Center, Department of Clinical Neurophysiology, New Children's Hospital and HUS Imaging, Helsinki University Hospital, Helsinki, Finland.

出版信息

EBioMedicine. 2023 Jun;92:104591. doi: 10.1016/j.ebiom.2023.104591. Epub 2023 May 1.

DOI:10.1016/j.ebiom.2023.104591

PMID:37137181

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10176156/

Abstract

BACKGROUND

Early neurodevelopmental care and research are in urgent need of practical methods for quantitative assessment of early motor development. Here, performance of a wearable system in early motor assessment was validated and compared to developmental tracking of physical growth charts.

METHODS

Altogether 1358 h of spontaneous movement during 226 recording sessions in 116 infants (age 4-19 months) were analysed using a multisensor wearable system. A deep learning-based automatic pipeline quantified categories of infants' postures and movements at a time scale of seconds. Results from an archived cohort (dataset 1, N = 55 infants) recorded under partial supervision were compared to a validation cohort (dataset 2, N = 61) recorded at infants' homes by the parents. Aggregated recording-level measures including developmental age prediction (DAP) were used for comparison between cohorts. The motor growth was also compared with respective DAP estimates based on physical growth data (length, weight, and head circumference) obtained from a large cohort (N = 17,838 infants; age 4-18 months).

FINDINGS

Age-specific distributions of posture and movement categories were highly similar between infant cohorts. The DAP scores correlated tightly with age, explaining 97-99% (94-99% CI 95) of the variance at the group average level, and 80-82% (72-88%) of the variance in the individual recordings. Both the average motor and the physical growth measures showed a very strong fit to their respective developmental models (R = 0.99). However, single measurements showed more modality-dependent variation that was lowest for motor (σ = 1.4 [1.3-1.5 CI 95] months), length (σ = 1.5 months), and combined physical (σ = 1.5 months) measurements, and it was clearly higher for the weight (σ = 1.9 months) and head circumference (σ = 1.9 months) measurements. Longitudinal tracking showed clear individual trajectories, and its accuracy was comparable between motor and physical measures with longer measurement intervals.

INTERPRETATION

A quantified, transparent and explainable assessment of infants' motor performance is possible with a fully automated analysis pipeline, and the results replicate across independent cohorts from out-of-hospital recordings. A holistic assessment of motor development provides an accuracy that is comparable with the conventional physical growth measures. A quantitative measure of infants' motor development may directly support individual diagnostics and care, as well as facilitate clinical research as an outcome measure in early intervention trials.

FUNDING

This work was supported by the Finnish Academy (314602, 335788, 335872, 332017, 343498), Finnish Pediatric Foundation (Lastentautiensäätiö), Aivosäätiö, Sigrid Jusélius Foundation, and HUS Children's Hospital/HUS diagnostic center research funds.

摘要

背景

早期神经发育护理和研究迫切需要定量评估早期运动发育的实用方法。在这里，验证了可穿戴系统在早期运动评估中的性能，并将其与身体生长图表的发育追踪进行了比较。

方法

使用多传感器可穿戴系统分析了 116 名婴儿（4-19 个月）226 次记录中的 1358 小时自发运动。基于深度学习的自动流水线可在秒级时间尺度上量化婴儿姿势和运动的类别。在存档队列（数据集 1，N=55 名婴儿）中记录的结果与在婴儿家中由父母记录的验证队列（数据集 2，N=61 名婴儿）进行了比较。使用聚合记录级别的措施，包括发育年龄预测（DAP），对队列之间进行比较。还将运动生长与从大型队列（N=17838 名婴儿；4-18 个月）获得的基于身体生长数据（长度、体重和头围）的相应 DAP 估计值进行了比较。

发现

婴儿队列之间的姿势和运动类别的特定年龄分布非常相似。DAP 分数与年龄密切相关，在群体平均水平上解释了 97-99%（94-99%CI95）的方差，在个体记录中解释了 80-82%（72-88%CI95）的方差。平均运动和身体生长测量都与各自的发育模型非常吻合（R=0.99）。然而，单次测量显示出更多的模式依赖性变化，最低的是运动（σ=1.4 [1.3-1.5 CI 95]个月）、长度（σ=1.5 个月）和综合身体（σ=1.5 个月）测量，体重（σ=1.9 个月）和头围（σ=1.9 个月）测量的变化明显更高。纵向跟踪显示出清晰的个体轨迹，其准确性在运动和身体测量之间相当，且测量间隔更长。