Evaluation of the repeatability of kinesiological measurements of spontaneous infant movements using OSESEC computer analysis algorithms

• Autorzy: Kieszczyńska Katarzyna , Doroniewicz Iwona , Bugdol Monika , Ledwoń Daniel , Affanasowicz Alicja , Latos Dominika , Matyja Małgorzata , Myśliwiec Andrzej

Identyfikatory

DOI

10.37190/ABB-02358-2023-02

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

infant; infant development; spontaneous movements; mobility assessment; objective methods of diagnosing; computer analysis

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Acta of Bioengineering and Biomechanics
• Rocznik: 2024
• Tom: Vol. 26, no. 1
• Strony: 67--75
• Opis fizyczny: Bibliogr. 34 poz., rys., tab.

Twórcy

autor

Kieszczyńska Katarzyna

• Institute of Physiotherapy and Health Science, Academy of Physical Education in Katowice, Katowice, Poland.

autor

Doroniewicz Iwona

• Institute of Physiotherapy and Health Science, Academy of Physical Education in Katowice, Katowice, Poland.

autor

Bugdol Monika

• Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland.

autor

Ledwoń Daniel

• Faculty of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland.

autor

Affanasowicz Alicja

• Institute of Physiotherapy and Health Science, Academy of Physical Education in Katowice, Katowice, Poland.

autor

Latos Dominika

• Institute of Physiotherapy and Health Science, Academy of Physical Education in Katowice, Katowice, Poland.

autor

Matyja Małgorzata

• Institute of Physiotherapy and Health Science, Academy of Physical Education in Katowice, Katowice, Poland.

autor

Myśliwiec Andrzej

• Institute of Physiotherapy and Health Science, Academy of Physical Education in Katowice, Katowice, Poland.

Bibliografia

• [1] BARTLETT D.J., FANNING J.E.K., Use of the Alberta Infant Motor Scale to characterize the motor development of infants born preterm at eight months corrected age, Phys. Occup. Ther. Pediatr., 2003, 23 (4), 31–45.
• [2] BLAUW-HOSPERS C.H., HADDERS-ALGRA M., A systematic review of the effects of early intervention on motor development, Developmental Medicine and Child Neurology, 2005, 47 (6), 421–432.
• [3] CAO Z., HIDALGO G., SIMON T., WEI S., SHEIKH Y., OpenPose: realtime multi-person 2D pose estimation using Part Affinity Fields, IEEE TPAMI, 2019, 43, 172–186.
• [4] CHAMBERS C., SEETHAPATHI N., SALUJA R., LOEB H., PIERCE S.R., BOGEN D.K., PROSSER L., JOHNSON M.J., KORDING K.P., Computer vision to automatically assess infant neuromotor risk, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020, 28 (11), 2431–2442.
• [5] CIURAJ M., KIESZCZYŃSKA K., DORONIEWICZ I., LIPOWICZ A., Subjective and objective assessment of developmental dysfunction in children aged 0–3 years comparative study, Springer, 2019, 382–391.
• [6] DORONIEWICZ I., LEDWOŃ D., AFFANASOWICZ A., KIESZCZYŃSKA K., LATOS D., MATYJA M., MITAS A.W., MYŚLIWIEC A., Writhing Movement Detection in Newborns on the Second and Third Day of Life Using Pose-Based Feature Machine Learning Classification, Sensors, 2020, 20, 5986.
• [7] DORONIEWICZ I., LEDWOŃ D., DANACH-WIERZCHOWSKA M., BUGDOL M., KIESZCZYŃSKA K., AFFANASOWICZ A., MATYJA M., MICHNIK R., MITAS A.W., MYŚLIWIEC A., Temporal and spatial variability of the fidgety movement descriptors and their relations to head position in automized general movement assessment, Acta Bioeng. Biomech., 2021, 23 (3), 69–78.
• [8] DUSING S.C., Postural variability and sensorimotor development in infancy, Developmental Medicine and Child Neurology, 2016, 58, 17–21.
• [9] EINSPIELER C., MARSCHIK P.B., BOS A.F., FERRARI F., CIONI G., PRECHTL H.F., Early markers for cerebral palsy: insights from the assessment of general movements, Future Neurology, 2012, 7(6), 709–717.
• [10] EINSPIELER C., PEHARZ R., MARSCHIK P.B., Fidgety movements – tiny in appearance, but huge in impact, J. Pediatr., (Rio J), 2016, 92, 64–70.
• [11] EINSPIELER C., PRECHTL H.F., FERRARI F., CIONI G., BOS A.F., The qualitative assessment of general movements in preterm, term and young infants – review of the methodology, Early Hum. Dev., 1997, 50 (1), 47–60.
• [12] EINSPIELER C., PRECHTL H.F., Prechtl’s assessment of general movements: a diagnostic tool for the functional assessment of the young nervous system, Ment. Retard Dev. Disabil. Res. Rev., 2005, 11 (1), 61–67.
• [13] EINSPIELER C., YANG H., BARTL-POKORNY K.D., CHI X., ZANG F.F., MARSCHIK P.B., GUZZETTA A., FERRARI F., BOS A.F., CIONI G., Are sporadic fidgety movements as clinically relevant as is their absence?, Early Hum. Dev., 2015, 91 (4), 247–252.
• [14] GIBSON E.J., Perceptual learning in development: Some basic concepts, Ecological Psychology, 2000, 12 (4), 295–302.
• [15] HADDERS-ALGRA M., Early human motor development: From variation to the ability to vary and adapt, Neurosci. Biobehav. Rev., 2018, 90, 411–427.
• [16] HADDERS-ALGRA M., Evaluation of motor function in young infants by means of the assessment of general movements: a review, PPT, 2001, 13 (1), 27–36.
• [17] HESSE N., PUJADES S., BLACK M.J., ARENS M., HOFMANN U.G., SCHROEDER A.S., Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequence, IEEE Trans Pattern Anal. Mach. Intell., 2020, 42, 2540–2551.
• [18] IHLEN E.A.F., STØEN R., BOSWELL L., DE REGNIER R.A.,FJØRTOFT T., GAEBLER-SPIRA D., LABORI C., LOENNECKEN M.C., MSALL M.E., MÖINICHEN U.I., PEYTON C., SCHREIBER M.D., SILBERG I.E., SONGSTAD N.T., VÅGEN R.T., ØBERG G.K., ADDE L., Machine Learning of Infant Spontaneous Movements for the Early Prediction of Cerebral Palsy: A Multi-Site Cohort Study, J. Clin. Med., 2020, 9, 5.
• [19] IRSHAD M.T., NISAR M.A., GOUVERNEUR P., RAPP M., GRZEGORZEK M., AI approaches towards Prechtl’s assessment of general movements: A systematic literature review, Sensors, 2020, 20 (18), 5321.
• [20] KARCH D., KIM K.S., WOCHNER K., PIETZ J., DICKHAUS H., PHILIPPI H., Quantification of the segmental kinematics of spontaneous infant movements, J. Biomech., 2008, 41 (13), 2860–2867.
• [21] KEPENEK-VAROL B., ÇALISKAN M., İNCE Z., TATLI B., ERASLAN E., ÇOBAN A., The comparison of general movements assessment and neurological examination during early infancy, Turk J. Pediatr., 2016, 58 (1), 54.
• [22] NOVAK I., MORGAN C., ADDE L., BLACKMAN J., BOYD R.N., BRUNSTROM-HERNANDEZ J., CIONI G., DAMIANO D., DARRAH J., ELIASSON A.C. et al., Early, accurate diagnosis and early intervention in cerebral palsy: Advances in Diagnosis and Treatment, JAMA Pediatrics, 2017, 171, 897–907.
• [23] OHGI S., MORITA S., LOO K.K., MIZUIKE C., Time series analysis of spontaneous upper-extremity movements of premature infants with brain injuries, Physical Therapy, 2008, 88 (9), 1022–1033.
• [24] PEYTON C., EINSPIELER C., General movements: a behavioral biomarker of later motor and cognitive dysfunction in NICU graduates, Pediatr. Ann., 2018, 47 (4), e159–e164.
• [25] PLOEGSTRA W.M., BOS A.F., DE VRIES N.K., General movements in healthy full term infants during the first week after birth, Early Hum. Dev., 2014, 90 (1), 55–60.
• [26] PORTNEY L.G., WATKINS M.P., Foundations of clinical research: applications to practice, Upper Saddle River, NJ, Pearson/Prentice Hall, 2009, 892, 11–15.
• [27] REICH S., ZHANG D., KULVICIUS T., BÖLTE S., NIELSEN-SAINES K., POKORNY F.B., PEHARZ R., POUSTKA L., WÖRGÖTTER F., EINSPIELER C., MARSCHIK P.B., Novel AI driven approach to classify infant motor functions, Sci. Rep., 2021, 11 (1), 1–13.
• [28] SAKKOS D., MCCAY K.D., MARCROFT C., EMBLETON N.D., CHATTOPADHYAY S., HO E.S., Identification of Abnormal Movements in Infants: A Deep Neural Network for Body Part-Based Prediction of Cerebral Palsy, IEEE Access, 2021, 9, 94281–94292.
• [29] SAVITZKY A., GOLAY M.J.E., Smoothing and differentiation of data by simplified least squares procedures, Anal. Chem., 1964, 36, 1627–1639.
• [30] SILVA N., ZHANG D., KULVICIUS T., GAIL A., BARREIROS C., LINDSTAEDT S, MARSCHIK P.B., The future of General Movement Assessment: The role of computer vision and machine learning – A scoping review, RIDD, 2021, 110, 103854.
• [31] STØEN R., SONGSTAD N.T., SILBERG I.E., FJØRTOFT T., JENSENIUS A.R., ADDE L., Computer-based video analysis identifies infants with absence of fidgety movements on behalf of the CIMA Norway Study Group, Pediatr. Res., 2017, 82 (4), 665–670.
• [32] TOUWEN B.C., Variability and stereotypy of spontaneous motility as a predictor of neurological development of preterm infants, Developmental Medicine & Child Neurology, 1990, 32 (6), 501–508.
• [33] TSUJI T., NAKASHIMA S., HAYASHI H., SOH Z., FURUI A., SHIBANOKI T., SHIMA K., SHIMATANI K., Markerless Measurement and evaluation of General Movements in infants, Sci. Rep., 2020, 10, 1–13.
• [34] VAN DER HEIDE J.C., PAOLICELLI P.B., BOLDRINI A., CIONI G., Kinematic and qualitative analysis of lower-extremity movements in preterm infants with brain lesions, Phys. Ther., 1999, 79 (6), 546–557.