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Purpose: There is a need to create objective and reproducible tool for assessing the quality of infant movements. It's substantially important to detect movement disorders in infants as early as possible. The study aimed to evaluate the reproducibility of kinesiological measurements of spontaneous movements performed by 51 infants (aged 6 to 15 weeks) recorded three times for two consecutive days using OSESEC computer analysis algorithms by determining numerical values of parameters, i.e., speed, acceleration, direction, and movement trajectory. Methods: The study group consisted of 51 infants. The diagnostic method of Prechtl was used for qualitative assessment. The quantitative assessment was based on the use of a OSESEC system. Numerical values for all movement parameters were determined, and the data obtained in the study were used for statistical analysis. Results: Analysis including movement parameter values on three consecutive recordings for the same infant revealed no statistically significant differences in location (p = 0.073), range (p = 0.557), shape (p = 0.289), mean acceleration (p = 0.124) and mean speed (p = 0.767). This confirms the reproducibility of measurements of the proposed parameters of the objectification of spontaneous infant movements. Conclusions: The interpretability and accuracy of the presented parameters were proved. All parameters estimation is fully automated. Further research and testing requires a larger study group to create an objective diagnostic device for infants. [ABSTRACT FROM AUTHOR]

Purpose: In clinical practice, motor development in infants is assessed subjectively. Many researchers propose objective methods, which have numerous limitations, by attaching markers or sensors to the child's limbs. The purpose of this study is to attempt to develop objectified numerical indices to describe the limb movements of infants without interfering with spontaneous activity. Methods: 20-minute video recordings of three infants' movements who were purposively selected from 51 subjects were included in the study. The procedure of automatic calculation of head position time in 3 positions was applied. Movement features were determined to allow for the delineation of coefficients describing the movement in numerical values. Results: Presented parameters describe three infant's movement aspects: quality (strength), distribution of postural tonus and asymmetry in relation to head position, described as four independent values. Estimated parameters variability over time was weighted up according to expert observations. The presented method is a direct reflection of infants' observation, currently performed by highly educated and experienced therapists. Conclusions: The interpretability and usefulness of the presented parameters were proved. All parameters estimation is fully automated. The conducted research is a prelude to future work related to creating an objective and repeatable tool, initially monitoring and ultimately supporting early diagnosis for differentiating normal and abnormal motor development. [ABSTRACT FROM AUTHOR]

Observation of neuromotor development at an early stage of an infant's life allows for early diagnosis of deficits and the beginning of the therapeutic process. General movement assessment is a method of spontaneous movement observation, which is the foundation for contemporary attempts at objectification and computer-aided diagnosis based on video recordings' analysis. The present study attempts to automatically detect writhing movements, one of the normal general movement categories presented by newborns in the first weeks of life. A set of 31 recordings of newborns on the second and third day of life was divided by five experts into videos containing writhing movements (with occurrence time) and poor repertoire, characterized by a lower quality of movement in relation to the norm. Novel, objective pose-based features describing the scope, nature, and location of each limb's movement are proposed. Three machine learning algorithms are evaluated in writhing movements' detection in leave-one-out cross-validation for different feature extraction time windows and overlapping time. The experimental results make it possible to indicate the optimal parameters for which 80% accuracy was achieved. Based on automatically detected writhing movement percent in the video, infant movements are classified as writhing movements or poor repertoire with an area under the ROC (receiver operating characteristics) curve of 0.83. [ABSTRACT FROM AUTHOR]