Abstract
Various attempts have been made to elucidate the development patterns in the spontaneous movements of infants through longitudinal evaluations. Movement complexity has been found to demonstrate u-shaped changes in the measurements focusing on limb movements. However, researchers have not yet clarified how other characteristics, besides movement complexity, change over time. This paper presents a longitudinal evaluation of spontaneous movements in infants using evaluation indices calculated through markerless video analysis. Nine infants with corrected ages from -1 to 15 weeks participated in the experiments. We confirmed the change in indices over time using statistical methods. Index changes can be classified as positively correlated, u-shaped, inverted u-shaped, and uncorrelated. We also confirmed that the u-shaped and inverted u-shaped indices are negatively correlated. Furthermore, the principal component analysis revealed that the first principal component had the inverted u-shaped changes with the corrected age. These results suggest that it is important to synchronize the inverted u-shaped variations in the movement and velocity with the u-shaped changes in the movement complexity for infant development.
Highlights
Movement abnormality in infants has been linked to neurological d isorders[1,2]
Tsuji et al proposed a markerless video analysis system that can calculate 25 evaluation indices, characterizing limb and whole-body movements, and demonstrated that the types of General movements (GMs) can be identified with high accuracy using machine learning[14]; this system has only been used for cross-sectional evaluation instead of longitudinal evaluation
The evaluation of longitudinal changes in the spontaneous movements accompanying infant development may help in further clarifying the developmental patterns in infants and possibly elucidate the role and meaning of u-shaped changes in spontaneous movement complexity for movement development
Summary
Movement abnormality in infants has been linked to neurological d isorders[1,2]. Spontaneous limb movement observations have been reported to be especially useful for neurological evaluations[3,4,5]. Tsuji et al proposed a markerless video analysis system that can calculate 25 evaluation indices, characterizing limb and whole-body movements, and demonstrated that the types of GMs can be identified with high accuracy using machine learning[14]; this system has only been used for cross-sectional evaluation instead of longitudinal evaluation. The evaluation of longitudinal changes in the spontaneous movements accompanying infant development may help in further clarifying the developmental patterns in infants and possibly elucidate the role and meaning of u-shaped changes in spontaneous movement complexity for movement development. We analyzed video images taken over a long period and calculated the evaluation indices using the markerless movement measurement and evaluation system proposed by Tsuji et al This system enables the longitudinal evaluation of spontaneous movements without the need to attach markers to the bodies of infants. This study aimed to evaluate infant developmental patterns both objectively and quantitatively
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