Movement Recognition Technology as a Method of Assessing Spontaneous General Movements in High Risk Infants
Open accessAbstract
Preterm birth is associated with increased risks of neurological and motor impairments such as cerebral palsy. The risks are highest in those born at the lowest gestations. Early identification of those most at risk is challenging meaning that a critical window of opportunity to improve outcomes through therapy-based interventions may be missed. Clinically, the assessment of spontaneous general movements is an important tool, which can be used for the prediction of movement impairments in high risk infants. Movement recognition aims to capture and analyze relevant limb movements through computerized approaches focusing on continuous, objective, and quantitative assessment. Different methods of recording and analyzing infant movements have recently been explored in high risk infants. These range from camera-based solutions to body-worn miniaturized movement sensors used to record continuous time-series data that represent the dynamics of limb movements. Various machine learning methods have been developed and applied to the analysis of the recorded movement data. This analysis has focused on the detection and classification of atypical spontaneous general movements. This article aims to identify recent translational studies using movement recognition technology as a method of assessing movement in high risk infants. The application of this technology within pediatric practice represents a growing area of inter-disciplinary collaboration, which may lead to a greater understanding of the development of the nervous system in infants at high risk of motor impairment.
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Direct sensing schemes such as inertial sensors and magnetic tracking devices are not optimally suited for infants due to bulk, size, rigid construction, and/or wired connections.
“As mentioned before, direct sensing schemes (e.g., inertial sensors, magnetic tracking devices) are not optimally suited for infants due to bulk, size, rigid construction, and/or wired connections (22).”
From Miniaturized wireless, skin-integrated sensor networks for quantifying full-body movement behaviors and vital signs in infants (2021) · cites this paper as [22]
The ‘Assessment through direct movement sensing’ section says attaching sensors to small infants can make clinical use more difficult, and Table 1 lists comfort and positioning issues. But the paper describes miniaturized accelerometers and small, lightweight magnetic sensors; it does not attribute the difficulty to bulk, rigid construction, or wired connections. (LLM, conf=0.87)
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Adams, J., Dinesh, K., Xiong, M., Tarolli, C. G., Sharma, S., Sheth, N., Aranyosi, A. J., Zhu, W. Y., Goldenthal, S. B., Biglan, K., et al. (2017) · Digital Biomarkers · doi:10.1159/000479018 · Cited by 3,190 · see citing works
A review of wearable sensors and systems with application in rehabilitation
Patel, S., Park, H., Bonato, P., Chan, L., & Rodgers, M. (2012) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-9-21 · Cited by 2,396 · see citing works
Born too soon : the Global action report on preterm birth
Howson, C. P., Kinney, M., & Lawn, J. E. (2012) · Cited by 1,928 · see citing works
A Survey of Computer Vision-Based Human Motion Capture
Moeslund, T. B., & Granum, E. (2001) · Computer Vision and Image Understanding · doi:10.1006/cviu.2000.0897 · Cited by 1,770 · see citing works
Gait Analysis Using Wearable Sensors
Tao, W., Liu, T., Zheng, R., & Feng, H. (2012) · Sensors · doi:10.3390/s120202255 · Cited by 1,170 · see citing works
Sensor-Based Activity Recognition
Chen, L., Hoey, J., Nugent, C. D., Cook, D. J., & Yu, Z. (2012) · IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/tsmcc.2012.2198883 · Cited by 1,074 · see citing works
Einspieler, C., & Prechtl, H. F. R. (2005) · Mental Retardation and Developmental Disabilities Research Reviews · doi:10.1002/mrdd.20051 · Cited by 793 · see citing works
Moore, T., Hennessy, E., Myles, J. P., Johnson, S. J., Draper, E. S., Costeloe, K., & Marlow, N. (2012) · BMJ · doi:10.1136/bmj.e7961 · Cited by 777 · see citing works
Prechtl, H. F. R. (1990) · Early Human Development · doi:10.1016/0378-3782(90)90011-7 · Cited by 620 · see citing works
Direct measurement of human movement by accelerometry
Godfrey, A., Conway, R., Meagher, D., & ÓLaighin, G. (2008) · Medical Engineering & Physics · doi:10.1016/j.medengphy.2008.09.005 · Cited by 591 · see citing works
A systematic review of tests to predict cerebral palsy in young children
Bosanquet, M., Copeland, L., Ware, R., & Boyd, R. (2013) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.12140 · Cited by 518 · see citing works
Cliff, D. P., Reilly, J. J., & Okely, A. D. (2009) · Journal of science and medicine in sport · doi:10.1016/j.jsams.2008.10.008 · Cited by 469 · see citing works
Quantitative wearable sensors for objective assessment of Parkinson's disease
Maetzler, W., Domingos, J., Srulijes, K., Ferreira, J. J., & Bloem, B. R. (2013) · Movement Disorders · doi:10.1002/mds.25628 · Cited by 374 · see citing works
Feature Learning for Activity Recognition in Ubiquitous Computing
Plötz, T., Hammerla, N., & Olivier, P. (2011) · Newcastle University · doi:10.25405/ncl.34175319 · Cited by 337 · see citing works
Self-citationA Review of Vision-Based Motion Analysis in Sport
Barris, S., & Button, C. (2008) · Sports Medicine · doi:10.2165/00007256-200838120-00006 · Cited by 302 · see citing works
Variation and Variability: Key Words in Human Motor Development
Hadders‐Algra, M. (2010) · Physical Therapy · doi:10.2522/ptj.20100006 · Cited by 256 · see citing works
Prechtl, H. F. R. (1997) · Early Human Development · doi:10.1016/s0378-3782(97)00088-1 · Cited by 246 · see citing works
The mobile fitness coach: Towards individualized skill assessment using personalized mobile devices
Kranz, M., Möller, A., Hammerla, N., Diewald, S., Plötz, T., Olivier, P. L., & Roalter, L. (2012) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2012.06.002 · Cited by 197 · see citing works
Self-citationGeneral Movements in Very Preterm Children and Neurodevelopment at 2 and 4 Years
Spittle, A. J., Spencer‐Smith, M. M., Cheong, J. L. Y., Eeles, A. L., Lee, K. J., Anderson, P. J., & Doyle, L. W. (2013) · PEDIATRICS · doi:10.1542/peds.2013-0177 · Cited by 190 · see citing works
A Kinect-based upper limb rehabilitation system to assist people with cerebral palsy
Chang, Y., Han, W.-Y., & Tsai, Y.-C. (2013) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2013.08.021 · Cited by 188 · see citing works
Oliva, L. L., Ortiz-Gutiérrez, R. M., Cano‐de‐la‐Cuerda, R., Martínez-Piédrola, R. M., Diego, I. M. A., Sánchez‐Camarero, C., & Culebras, M. D. C. M. (2013) · Neurorehabilitation · doi:10.3233/nre-131001 · Cited by 177 · see citing works
The predictive validity of general movements – A systematic review
Burger, M., & Louw, Q. A. (2008) · European Journal of Paediatric Neurology · doi:10.1016/j.ejpn.2008.09.004 · Cited by 169 · see citing works
Cerebral palsy and developmental coordination disorder in children born preterm
Spittle, A. J., & Orton, J. (2013) · Seminars in Fetal and Neonatal Medicine · doi:10.1016/j.siny.2013.11.005 · Cited by 153 · see citing works
Darsaklis, V., Snider, L., Majnemer, A., & Mazer, B. L. (2011) · Developmental Medicine & Child Neurology · doi:10.1111/j.1469-8749.2011.04017.x · Cited by 142 · see citing works
Adde, L., Helbostad, J. L., Jensenius, A. R., Taraldsen, G., Grunewaldt, K. H., & Støen, R. Ø. (2010) · Developmental Medicine & Child Neurology · doi:10.1111/j.1469-8749.2010.03629.x · Cited by 141 · see citing works
Hammerla, N. Y., Kirkham, R., Andras, P., & Ploetz, T. (2013) · Proceedings of the 2013 International Symposium on Wearable Computers · doi:10.1145/2493988.2494353 · Cited by 138 · see citing works
Self-citationClimbAX: skill assessment for climbing enthusiasts
Ladha, C., Hammerla, N. Y., Olivier, P., & Plötz, T. (2013) · Ubiquitous Computing · doi:10.1145/2493432.2493492 · Cited by 134 · see citing works
Self-citationSo, K., Adamson, T. M., & Horne, R. S. C. (2007) · Journal of Sleep Research · doi:10.1111/j.1365-2869.2007.00582.x · Cited by 133 · see citing works
Automatic assessment of problem behavior in individuals with developmental disabilities
Plötz, T., Hammerla, N., Rozga, A., Reavis, A. R., Call, N. A., & Abowd, G. D. (2012) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2370216.2370276 · Cited by 127 · see citing works
Self-citationUsing computer-based video analysis in the study of fidgety movements
Adde, L., Helbostad, J. L., Jensenius, A. R., Taraldsen, G., & Støen, R. Ø. (2009) · Early Human Development · doi:10.1016/j.earlhumdev.2009.05.003 · Cited by 125 · see citing works
Meinecke, L., Breitbach‐Faller, N., Bartz, C., Damen, R., Rau, G., & Dißelhorst-Klug, C. (2006) · Human Movement Science · doi:10.1016/j.humov.2005.09.012 · Cited by 122 · see citing works
Dog's life: wearable activity recognition for dogs
Ladha, C., Hammerla, N. Y., Hughes, E., Olivier, P., & Ploetz, T. (2013) · Ubiquitous Computing · doi:10.1145/2493432.2493519 · Cited by 116 · see citing works
Self-citationUsing unlabeled data in a sparse-coding framework for human activity recognition
Bhattacharya, S., Nurmi, P., Hammerla, N., & Plötz, T. (2014) · Pervasive and Mobile Computing · doi:10.1016/j.pmcj.2014.05.006 · Cited by 116 · see citing works
Self-citationFast feature selection with genetic algorithms: a filter approach
Lanzi, P. L. (2002) · IEEE International Conference on Evolutionary Computation (ICEC) · doi:10.1109/icec.1997.592369 · Cited by 113 · see citing works
Automated Detection of Stereotypical Motor Movements
Goodwin, M. S., Intille, S. S., Albinali, F., & Velicer, W. F. (2010) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-010-1102-z · Cited by 102 · see citing works
Fjørtoft, T., Einspieler, C., Adde, L., & Strand, L. I. (2009) · Early Human Development · doi:10.1016/j.earlhumdev.2008.12.001 · Cited by 96 · see citing works
Heinze, F., Hesels, K., Breitbach‐Faller, N., Schmitz‐Rode, T., & Dißelhorst-Klug, C. (2010) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-010-0624-z · Cited by 92 · see citing works
Early Markers For Cerebral Palsy: Insights From the Assessment of General Movements
Einspieler, C., Marschik, P. B., Bos, A. F., Ferrari, F., Cioni, G., & Prechtl, H. F. R. (2012) · Future Neurology · doi:10.2217/fnl.12.60 · Cited by 81 · see citing works
Fjørtoft, T., Grunewaldt, K. H., Løhaugen, G. C. C., Mørkved, S., Skranes, J. S., & Evensen, K. A. I. (2013) · Early Human Development · doi:10.1016/j.earlhumdev.2013.06.007 · Cited by 75 · see citing works
Occupancy monitoring using environmental & context sensors and a hierarchical analysis framework
Khan, A., Nicholson, J., Mellor, S., Jackson, D., Ladha, K., Ladha, C., Hand, J., Clarke, J., Olivier, P., & Plötz, T. (2014) · International Conference on Systems for Energy-Efficient Built Environments · doi:10.1145/2674061.2674080 · Cited by 69 · see citing works
Self-citationKinematic assessment of stereotypy in spontaneous movements in infants
Karch, D., Kang, K., Wochner, K., Philippi, H., Hadders‐Algra, M., Pietz, J., & Dickhaus, H. (2012) · Gait & Posture · doi:10.1016/j.gaitpost.2012.03.017 · Cited by 64 · see citing works
Computer‐based analysis of general movements reveals stereotypies predicting cerebral palsy
Philippi, H., Karch, D., Kang, K., Wochner, K., Pietz, J., Dickhaus, H., & Hadders‐Algra, M. (2014) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.12477 · Cited by 62 · see citing works
Quantification of the segmental kinematics of spontaneous infant movements
Karch, D., Kim, K.-S., Wochner, K., Pietz, J., Dickhaus, H., & Philippi, H. (2008) · Journal of Biomechanics · doi:10.1016/j.jbiomech.2008.06.033 · Cited by 58 · see citing works
GymSkill: A personal trainer for physical exercises
Moller, A., Roalter, L., Diewald, S., Scherr, J., Kranz, M., Hammerla, N., Olivier, P. L., & Plötz, T. (2012) · IEEE International Conference on Pervasive Computing and Communications · doi:10.1109/percom.2012.6199869 · Cited by 58 · see citing works
Self-citationOhgi, S., Morita, S., Loo, K. K., & Mizuike, C. (2008) · Physical Therapy · doi:10.2522/ptj.20070171 · Cited by 57 · see citing works
Assessment of Infant Movement With a Compact Wireless Accelerometer System
Gravem, D., Singh, M., Chen, C., Rich, J., Vaughan, J., Goldberg, K. Y., Waffarn, F., Chou, P. H., Cooper, D. M., Reinkensmeyer, D. J., et al. (2012) · Journal of Medical Devices · doi:10.1115/1.4006129 · Cited by 56 · see citing works
Kanemaru, N., Watanabe, H., Kihara, H., Nakano, H., Takaya, R., Nakamura, T., Nakano, J., Taga, G., & Konishi, Y. (2013) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.12156 · Cited by 55 · see citing works
Waldmeier, S., Grunt, S., Delgado‐Eckert, E., Latzin, P., Steinlin, M. I., Fuhrer, K., & Frey, U. (2013) · Experimental Brain Research · doi:10.1007/s00221-013-3504-6 · Cited by 53 · see citing works
Plötz, T., Chen, C., Hammerla, N., & Abowd, G. D. (2012) · International Symposium on Wearable Computers · doi:10.1109/iswc.2012.15 · Cited by 51 · see citing works
Self-citationA Dynamical Systems Analysis of Spontaneous Movements in Newborn Infants
Ohgi, S., Morita, S., Loo, K. K., & Mizuike, C. (2007) · Journal of Motor Behavior · doi:10.3200/jmbr.39.3.203-214 · Cited by 49 · see citing works
Jerky spontaneous movements at term age in preterm infants who later developed cerebral palsy
Kanemaru, N., Watanabe, H., Kihara, H., Nakano, H., Nakamura, T., Nakano, J., Taga, G., & Konishi, Y. (2014) · Early Human Development · doi:10.1016/j.earlhumdev.2014.05.004 · Cited by 49 · see citing works
Bettadapura, V., Schindler, G., Plötz, T., & Essa, I. A. (2013) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2013.338 · Cited by 49 · see citing works
Self-citationChoquette, S., Hamel, M., & Boissy, P. (2008) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-5-20 · Cited by 43 · see citing works
Kanemaru, N., Watanabe, H., & Taga, G. (2012) · Experimental Brain Research · doi:10.1007/s00221-012-3001-3 · Cited by 40 · see citing works
Fan, M., Gravem, D., Cooper, D. M., & Patterson, D. J. (2012) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2370216.2370278 · Cited by 29 · see citing works
Cervical accelerometry in preterm infants
Reynolds, E. W., Vice, F. L., Bosma, J. F., & Gewolb, I. H. (2002) · Developmental Medicine & Child Neurology · doi:10.1017/s0012162201002626 · Cited by 29 · see citing works
Dißelhorst-Klug, C., Heinze, F., Breitbach‐Faller, N., Schmitz‐Rode, T., & Rau, G. (2012) · Experimental Brain Research · doi:10.1007/s00221-012-3015-x · Cited by 27 · see citing works
Shevell, A. H., & Shevell, M. I. (2013) · Journal of Child Neurology · doi:10.1177/0883073812471430 · Cited by 23 · see citing works
Movement outcomes of infants born moderate and late preterm
Odd, D., Lingam, R., Emond, A. M., & Whitelaw, A. (2013) · Acta Paediatrica · doi:10.1111/apa.12320 · Cited by 22 · see citing works
Anomaly Detection and Knowledge Transfer in Automatic Sports Video Annotation
Almajai, I., Yan, F., de Campos, T. E., Khan, A., Christmas, W. J., Windridge, D., & Kittler, J. (2011) · Studies in computational intelligence · doi:10.1007/978-3-642-24034-8_9 · Cited by 19 · see citing works
Self-citationAutomatic correction of annotation boundaries in activity datasets by class separation maximization
Kirkham, R., Khan, A., Bhattacharya, S., Hammerla, N. Y., Mellor, S., Roggen, D., & Ploetz, T. (2013) · Ubiquitous Computing · doi:10.1145/2494091.2495988 · Cited by 18 · see citing works
Self-citationKhan, A., Windridge, D., & Kittler, J. (2014) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2014.2299955 · Cited by 17 · see citing works
Self-citationENIGMA – Enhanced interactive general movement assessment
BERGE, P., Adde, L., Espinosa, G., & Stavdahl, Ø. (2007) · Expert Systems with Applications · doi:10.1016/j.eswa.2007.05.024 · Cited by 15 · see citing works
Ball event recognition using hmm for automatic tennis annotation
Almajai, I., Kittler, J., de Campos, T. E., Christmas, W. J., Yan, F., Windridge, D., & Khan, A. (2010) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2010.5652415 · Cited by 15 · see citing works
Self-citationA framework for automatic sports video annotation with anomaly detection and transfer learning
Campos, T., Khan, A., Yan, F., Davar, N. F., Windridge, D., Kittler, J., & Christmas, W. J. (2013) · Surrey Research Insight Open Access (The University of Surrey) · Cited by 10 · see citing works
Self-citationOrigins of origins of motor control
Thelen, E. (1995) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00041030 · Cited by 9 · see citing works
How do we use the assessment of general movements in clinical practice?
Spittle, A. J. (2011) · Developmental Medicine & Child Neurology · doi:10.1111/j.1469-8749.2011.04034.x · Cited by 9 · see citing works
Gesture stroke recognition using computer vision and linear accelerometer
Huang, E.-W., & Fu, L. (2008) · International Conference on Automatic Face and Gesture Recognition · doi:10.1109/afgr.2008.4813355 · Cited by 9 · see citing works
Lattice-Based Anomaly Rectification for Sport Video Annotation
Khan, A., Windridge, D., de Campos, T. E., Kittler, J., & Christmas, W. J. (2010) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2010.1063 · Cited by 5 · see citing works
Self-citationComputer‐based analysis of general movements reveals stereotypies predicting cerebral palsy
Pierrat, V. (2014) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.12528 · Cited by 3 · see citing works
A wearable accelerometer based platform to encourage physical activity for the eld-erly
de Morais, W. O., Sant'Anna, A. D., & Wickström, N. (2008) · Gerontechnology · doi:10.4017/gt.2008.07.02.118.00 · Cited by 3 · see citing works
Flagged first, then by citations
2 of the 73 references couldn’t be matched to a known paper.
Research works printed but not linked: 3
- [63]Adde L Helbostad JL Jensenius AR Taraldsen G Støen R. Using computer-based video analysis in the study of fidgety movements. Early Hum Dev (2009) 85(9): 541– 7. 10.1016/j.earlhumdev.2009.05.003 19464127 · DOI
- [70]Rahmanpour P Features for Movement based Prediction of Cerebral Palsy [MSc Thesis]. Trondheim: Norwegian University of Science and Technology (2009).
- [74]Yang J Honavar V Feature Subset Selection Using a Genetic Algorithm. Feature Extraction, Construction and Selection. The Springer International Series in Engineering and Computer Science. 453. Springer (1998). p. 117– 36.
Cited by
Sorted by citations
Einspieler, C., Bos, A. F., Libertus, M. E., & Marschik, P. B. (2016) · Frontiers in Psychology · doi:10.3389/fpsyg.2016.00406 · Cited by 202 · see citing works
Optimising sampling rates for accelerometer-based human activity recognition
Khan, A., Hammerla, N., Mellor, S., & Plötz, T. (2016) · Pattern Recognition Letters · doi:10.1016/j.patrec.2016.01.001 · Cited by 171 · see citing works
Self-citationVelde, A. T., Morgan, C., Novak, I., Tantsis, E. M., & Badawi, N. A. (2019) · Journal of Clinical Medicine · doi:10.3390/jcm8101599 · Cited by 170 · see citing works
Silva, N., Zhang, D., Kulvičius, T., Gail, A., Barreiros, C., Lindstaedt, S., Kraft, M., Bölte, S., Poustka, L., Nielsen‐Saines, K., et al. (2021) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2021.103854 · Cited by 137 · see citing works
Einspieler, C., Marschik, P. B., Pansy, J., Scheuchenegger, A., Krieber, M., Yang, H., Borszewska-Kornacka, M. K., Rowinska, E., Soloveichick, M., & Bos, A. F. (2015) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.12923 · Cited by 130 · see citing works
A Review of Automated Pain Assessment in Infants: Features, Classification Tasks, and Databases
Zamzmi, G., Kasturi, R., Goldgof, D. B., Zhi, R., Ashmeade, T. L., & Sun, Y. (2017) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2017.2777907 · Cited by 122 · see citing works
Computer Vision to Automatically Assess Infant Neuromotor Risk
Chambers, C., Seethapathi, N., Saluja, R., Loeb, H. S., Pierce, S. R., Bogen, D. K., Prosser, L. A., Johnson, M. J., & Kording, K. P. (2020) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2020.3029121 · Cited by 121 · see citing works
Ihlen, E. A. F., Støen, R. Ø., Boswell, L., de Regnier, R.-A. O., Fjørtoft, T., Gaebler-Spira, D. J., Labori, C., Loennecken, M. C., Msall, M. E., Møinichen, U. I., et al. (2019) · Journal of Clinical Medicine · doi:10.3390/jcm9010005 · Cited by 117 · see citing works
A Review of Wearable Sensor Systems for Monitoring Body Movements of Neonates
Chen, H., Xue, M., Mei, Z., Oetomo, S. B., & Chen, W. (2016) · Sensors · doi:10.3390/s16122134 · Cited by 107 · see citing works
The BEE-PRI Study Group, Marschik, P. B., Pokorny, F. B., Peharz, R., Zhang, D., O’Muircheartaigh, J., Roeyers, H., Bölte, S., Spittle, A. J., Urlesberger, B., et al. (2017) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-017-0748-8 · Cited by 96 · see citing works
Groos, D., Adde, L., Aubert, S., Boswell, L., de Regnier, R.-A. O., Fjørtoft, T., Gaebler-Spira, D. J., Haukeland, A., Loennecken, M. C., Msall, M. E., et al. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.21325 · Cited by 87 · see citing works
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Hesse, N., Bodensteiner, C., Arens, M., Hofmann, U., Weinberger, R., & Schroeder, A. S. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-11024-6_3 · Cited by 86 · see citing works
Abnormal Infant Movements Classification With Deep Learning on Pose-Based Features
McCay, K. D., Ho, E. S. L., Shum, H. P. H., Fehringer, G., Marcroft, C., & Embleton, N. D. (2020) · IEEE Access · doi:10.1109/access.2020.2980269 · Cited by 78 · see citing works
Self-citationSakkos, D., McCay, K. D., Marcroft, C., Embleton, N. D., Chattopadhyay, S., & Ho, E. S. L. (2021) · IEEE Access · doi:10.1109/access.2021.3093469 · Cited by 78 · see citing works
Self-citationLearning an Infant Body Model from RGB-D Data for Accurate Full Body Motion Analysis
Hesse, N., Pujades, S., Romero, J., Black, M. J., Bodensteiner, C., Arens, M., Hofmann, U., Tacke, U., Hadders‐Algra, M., Weinberger, R., et al. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00928-1_89 · Cited by 74 · see citing works
Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences
Hesse, N., Pujades, S., Black, M. J., Arens, M., Hofmann, U., & Schroeder, A. S. (2019) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2917908 · Cited by 71 · see citing works
AI Approaches towards Prechtl’s Assessment of General Movements: A Systematic Literature Review
Irshad, M. T., Nisar, M. A., Gouverneur, P., Rapp, M., & Grzegorzek, M. (2020) · Sensors · doi:10.3390/s20185321 · Cited by 68 · see citing works
Khan, A., Mellor, S., Berlin, E., Thompson, R. J., McNaney, R., Olivier, P. L., & Plötz, T. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2750858.2807534 · Cited by 67 · see citing works
Self-citationDetection of Atypical and Typical Infant Movements using Computer-based Video Analysis
Orlandi, S., Raghuram, K., Smith, C. R., Mansueto, D., Church, P., Shah, V. S., Luther, M., & Chau, T. T. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8513078 · Cited by 65 · see citing works
Jeong, H., Kwak, S. S., Sohn, S., Lee, J. Y., Lee, Y. J., O’Brien, M. K., Park, Y., Avila, R., Kim, J.-T., Yoo, J.-Y., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2104925118 · Cited by 59 · see citing works
Computer-based video analysis identifies infants with absence of fidgety movements
on behalf of the CIMA Norway Study Group, Støen, R. Ø., Songstad, N. T., Silberg, I. E., Fjørtoft, T., Jensenius, A. R., & Adde, L. (2017) · Pediatric Research · doi:10.1038/pr.2017.121 · Cited by 56 · see citing works
McCay, K. D., Hu, P., Shum, H. P. H., Woo, W. L., Marcroft, C., Embleton, N. D., Munteanu, A., & Ho, E. S. L. (2021) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2021.3138185 · Cited by 55 · see citing works
Self-citationMarchi, V., Hakala, A., Knight, A., D'Acunto, F., Scattoni, M. L., Guzzetta, A., & Vanhatalo, S. (2019) · Acta Paediatrica · doi:10.1111/apa.14781 · Cited by 55 · see citing works
In-Motion-App for remote General Movement Assessment: a multi-site observational study
Adde, L., Brown, A., den Broeck, C. V., DeCoen, K., Eriksen, B. H., Fjørtoft, T., Groos, D., Ihlen, E. A. F., Osland, S., Pascal, A., et al. (2021) · BMJ Open · doi:10.1136/bmjopen-2020-042147 · Cited by 51 · see citing works
Gao, Q., Yao, S., Tian, Y., Zhang, C., Zhao, T., Wu, D., Yu, G., & Lu, H. J. (2023) · Nature Communications · doi:10.1038/s41467-023-44141-x · Cited by 50 · see citing works
Frequency Analysis and Feature Reduction Method for Prediction of Cerebral Palsy in Young Infants
Rahmati, H., Martens, H. A., Aamo, O. M., Stavdahl, Ø., Støen, R. Ø., & Adde, L. (2016) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2016.2539390 · Cited by 50 · see citing works
Gao, Y., Long, Y., Guan, Y., Basu, A., Baggaley, J., & Ploetz, T. (2019) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies · doi:10.1145/3314399 · Cited by 49 · see citing works
Self-citationTrujillo-Priego, I. A., Lane, C. J., Vanderbilt, D. L., Deng, W., Loeb, G. E., Shida-Tokeshi, J., & Smith, B. A. (2017) · Technologies · doi:10.3390/technologies5030039 · Cited by 49 · see citing works
Leo, M., Bernava, G. M., Carcagnì, P., & Distante, C. (2022) · Sensors · doi:10.3390/s22030866 · Cited by 48 · see citing works
Raghuram, K., Orlandi, S., Church, P., Chau, T. T., Uleryk, E. M., Pechlivanoglou, P., & Shah, V. S. (2021) · Developmental Medicine & Child Neurology · doi:10.1111/dmcn.14800 · Cited by 48 · see citing works
Abrishami, M. S., Nocera, L., Mert, M., Trujillo-Priego, I. A., Purushotham, S., Shahabi, C., & Smith, B. A. (2019) · IEEE Journal of Translational Engineering in Health and Medicine · doi:10.1109/jtehm.2019.2893223 · Cited by 46 · see citing works
A Ballistographic Approach for Continuous and Non-Obtrusive Monitoring of Movement in Neonates
Joshi, R., Bierling, B. L., Long, X., Weijers, J., Feijs, L., Van Pul, C., & Andriessen, P. (2018) · IEEE Journal of Translational Engineering in Health and Medicine · doi:10.1109/jtehm.2018.2875703 · Cited by 43 · see citing works
Shin, H. I., Shin, H., Bang, M. S., Kim, D., Shin, S. H., Kim, E., Kim, Y., Lee, E. S., Park, S. G., Ji, H. M., et al. (2022) · Scientific Reports · doi:10.1038/s41598-022-07139-x · Cited by 39 · see citing works
Design and Validation of Rule-Based Expert System by Using Kinect V2 for Real-Time Athlete Support
Örücü, S., & Selek, M. (2020) · Applied Sciences · doi:10.3390/app10020611 · Cited by 38 · see citing works
Caruso, A., Gila, L., Fulceri, F., Salvitti, T., Micai, M., Baccinelli, W., Bulgheroni, M., & Scattoni, M. L. (2020) · Brain Sciences · doi:10.3390/brainsci10060379 · Cited by 38 · see citing works
Characteristics of general movements in preterm infants assessed by computer-based video analysis
Adde, L., Yang, H., Sæther, R., Jensenius, A. R., Ihlen, E. A. F., Cao, J., & Støen, R. Ø. (2017) · Physiotherapy Theory and Practice · doi:10.1080/09593985.2017.1391908 · Cited by 35 · see citing works
Establishing Pose Based Features Using Histograms for the Detection of Abnormal Infant Movements
McCay, K. D., Ho, E. S. L., Marcroft, C., & Embleton, N. D. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8857680 · Cited by 35 · see citing works
Self-citationBassi, M., Grobberio, M., Negri, L., Cilia, S., Minacapelli, E., Niccolai, C., Pattini, M., Pietrolongo, E., Quartuccio, M. E., Viterbo, R. G., et al. (2019) · Journal of Clinical Psychology in Medical Settings · doi:10.1007/s10880-019-09692-6 · Cited by 34 · see citing works
Multivariate Analysis and Machine Learning in Cerebral Palsy Research
Zhang, J. (2017) · Frontiers in Neurology · doi:10.3389/fneur.2017.00715 · Cited by 33 · see citing works
Early movement restriction leads to enduring disorders in muscle and locomotion
Delcour, M., Massicotte, V. S., Russier, M., Bras, H., Peyronnet, J., Canu, M., Cayetanot, F., Barbe, M. F., & Coq, J. (2018) · Brain Pathology · doi:10.1111/bpa.12594 · Cited by 31 · see citing works
Baccinelli, W., Bulgheroni, M., Simonetti, V., Fulceri, F., Caruso, A., Gila, L., & Scattoni, M. L. (2020) · Brain Sciences · doi:10.3390/brainsci10040203 · Cited by 29 · see citing works
Doi, H., Iijima, N., Furui, A., Soh, Z., Yonei, R., Shinohara, K., Iriguchi, M., Shimatani, K., & Tsuji, T. (2022) · Scientific Reports · doi:10.1038/s41598-022-21308-y · Cited by 29 · see citing works
Semi-supervised body parsing and pose estimation for enhancing infant general movement assessment
Ni, H., Xue, Y., Ma, L., Zhang, Q., Li, X., & Huang, X. (2022) · Medical Image Analysis · doi:10.1016/j.media.2022.102654 · Cited by 28 · see citing works
BabyPose: Real-Time Decoding of Baby’s Non-Verbal Communication Using 2D Video-Based Pose Estimation
Yurtsever, M. M. E., & Eken, S. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3183502 · Cited by 27 · see citing works
Detection of Infantile Movement Disorders in Video Data Using Deformable Part-Based Model
Khan, M. H., Schneider, M., Farid, M. S., & Grzegorzek, M. (2018) · Sensors · doi:10.3390/s18103202 · Cited by 27 · see citing works
Audio- and video-based estimation of the sleep stages of newborns in Neonatal Intensive Care Unit
Cabon, S., Porée, F., Simon, A., Met-Montot, B., Pladys, P., Rosec, O., Nardi, N., & Carrault, G. (2019) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2019.04.011 · Cited by 27 · see citing works
Mobile Solutions for Clinical Surveillance and Evaluation in Infancy—General Movement Apps
Marschik, P. B., Kwong, A., Silva, N., Olsen, J. E., Schulte‐Rüther, M., Bölte, S., Örtqvist, M., Eeles, A. L., Poustka, L., Einspieler, C., et al. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12103576 · Cited by 26 · see citing works
Li, M., Wei, F., Li, Y., Zhang, S., & Xu, G. (2020) · IEEE Sensors Journal · doi:10.1109/jsen.2020.3037121 · Cited by 25 · see citing works
Spontaneous movements in the newborns: a tool of quantitative video analysis of preterm babies
Tacchino, C. M., Impagliazzo, M., Maggi, E., Bertamino, M., Blanchi, I., Campone, F., Durand, P., Fato, M., Giannoni, P., Iandolo, R., et al. (2020) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2020.105838 · Cited by 24 · see citing works
Infant movement classification through pressure distribution analysis
Kulvičius, T., Zhang, D., Nielsen‐Saines, K., Bölte, S., Kraft, M., Einspieler, C., Poustka, L., Wörgötter, F., & Marschik, P. B. (2023) · Communications Medicine · doi:10.1038/s43856-023-00342-5 · Cited by 24 · see citing works
Valle, S. C., Støen, R. Ø., Sæther, R., Jensenius, A. R., & Adde, L. (2015) · Early Human Development · doi:10.1016/j.earlhumdev.2015.07.001 · Cited by 24 · see citing works
The general movement assessment in non-European low- and middle-income countries
Tomantschger, I., Herrero, D., Einspieler, C., Moriyama, C. H., Voos, M. C., & Marschik, P. B. (2018) · Revista de Saúde Pública · doi:10.11606/s1518-8787.2018052000332 · Cited by 24 · see citing works
Deep-learning for automated markerless tracking of infants general movements
Abbasi, H., Mollet, S. R., Williams, S. A., Lim, L., BATTIN, M. R., Besier, T. F., & McMorland, A. J. C. (2023) · International Journal of Information Technology · doi:10.1007/s41870-023-01497-z · Cited by 21 · see citing works
Ouss, L., Normand, M. L., Bailly, K., Gille, M. L., Gosme, C., Simas, R., Wenke, J., Jeudon, X., Thepot, S., Silva, T. D., et al. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.00083 · Cited by 20 · see citing works
Raghuram, K., Orlandi, S., Church, P., Luther, M., Kiss, A., & Shah, V. S. (2022) · Children · doi:10.3390/children9060843 · Cited by 20 · see citing works
General movement assessment by machine learning: why is it so difficult?
Schmidt, W., Regan, M., Fahey, M., & Papliński, A. P. (2019) · Journal of Medical Artificial Intelligence · doi:10.21037/jmai.2019.06.02 · Cited by 19 · see citing works
Thompson, R. J., Kyriazakis, I., Holden, A., Olivier, P. L., & Plötz, T. (2015) · ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) · doi:10.1145/2750858.2807536 · Cited by 19 · see citing works
Self-citationHoyt, C. R., Brown, S., Sherman, S. K., Wood-Smith, M., Van, A. N., Ortega, M., Nguyen, A. L., Lang, C. E., Schlaggar, B. L., & Dosenbach, N. U. F. (2019) · Research in Developmental Disabilities · doi:10.1016/j.ridd.2019.103546 · Cited by 20 · see citing works
Adde, L., Thomas, N., John, H. B., Oommen, S. P., Vågen, R. T., Fjørtoft, T., Jensenius, A. R., & Støen, R. Ø. (2016) · European Journal of Paediatric Neurology · doi:10.1016/j.ejpn.2016.07.019 · Cited by 19 · see citing works
Deng, W., O’Brien, M. K., Andersen, R. A., Rai, R., Jones, E. F., & Jayaraman, A. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01450-3 · Cited by 17 · see citing works
Automatic infant 2D pose estimation from videos: Comparing seven deep neural network methods
Gama, F., Mísař, M., Navara, L., Popescu, S. T., & Hoffmann, M. (2025) · Behavior Research Methods · doi:10.3758/s13428-025-02816-x · Cited by 17 · see citing works
Improving Outcomes in Cerebral Palsy with Early Intervention: New Translational Approaches
Basu, A. P., & Clowry, G. J. (2015) · Frontiers in Neurology · doi:10.3389/fneur.2015.00024 · Cited by 17 · see citing works
Redd, C. B., Barber, L. A., Boyd, R. N., Varnfield, M., & Karunanithi, M. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8857377 · Cited by 17 · see citing works
Movement analysis in early infancy: Towards a motion biomarker of age
Marchi, V., Belmonti, V., Cecchi, F., Coluccini, M., Ghirri, P., Grassi, A., Sabatini, A. M., & Guzzetta, A. (2020) · Early Human Development · doi:10.1016/j.earlhumdev.2019.104942 · Cited by 17 · see citing works
A video/IMU hybrid system for movement estimation in infants
Machireddy, A., van Santen, J. P. H., Wilson, J. L., Myers, J., Hadders‐Algra, M., & Song, X. B. (2017) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2017.8036928 · Cited by 17 · see citing works
Wu, Q., Qin, P., Kuang, J., Wei, F., Li, Z., Bian, R., Han, C., & Xu, G. (2023) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2023.3255639 · Cited by 16 · see citing works
Machine-based Multimodal Pain Assessment Tool for Infants: A ReviewPreprint
Zamzmi, G., Goldgof, D. B., Kasturi, R., Sun, Y., & Ashmeade, T. L. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1607.00331 · Cited by 23 · see citing works
Ouss, L., Palestra, G., Saint‐Georges, C., Gille, M. L., Afshar, M., Pellerin, H., Bailly, K., Chétouani, M., Robel, L., Golse, B., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-0743-8 · Cited by 16 · see citing works
Computer Vision Tasks for Ambient Intelligence in Children’s Health
Germanese, D., Colantonio, S., Coco, M. D., Carcagnì, P., & Leo, M. (2023) · Information · doi:10.3390/info14100548 · Cited by 15 · see citing works
Wu, Q., Xu, G., Wei, F., Kuang, J., Zhang, X., Chen, L., & Zhang, S. (2021) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2021.3125980 · Cited by 14 · see citing works
Mobile payment recognition technology based on face detection algorithm
Du, M. (2018) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.4655 · Cited by 14 · see citing works
Balta, D., Kuo, H., Wang, J., Porco, I. G., Morozova, O., Schladen, M. M., Cereatti, A., Lum, P. S., & Croce, U. D. (2022) · Sensors · doi:10.3390/s22197426 · Cited by 13 · see citing works
Markerless Motion Analysis for Early Detection of Infantile Movement Disorders
Hesse, N., Schroeder, A. S., Müller‐Felber, W., Bodensteiner, C., Arens, M., & Hofmann, U. (2017) · World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany · doi:10.1007/978-981-10-5122-7_50 · Cited by 13 · see citing works
Bultmann, C.-S., Orlikowsky, T. W., Häusler, M., Trepels‐Kottek, S., Dißelhorst-Klug, C., & Schoberer, M. (2019) · Early Human Development · doi:10.1016/j.earlhumdev.2019.01.002 · Cited by 13 · see citing works
McCay, K. D., Ho, E. S. L., Sakkos, D., Woo, W. L., Marcroft, C., Dulson, P., & Embleton, N. D. (2021) · IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI ...) · doi:10.1109/bhi50953.2021.9508603 · Cited by 12 · see citing works
Self-citationContinuous sensing and quantification of body motion in infants: A systematic review
Peng, Z. Q., Kommers, D. R., Liang, R.-H., Long, X., Cottaar, W., Niemarkt, H. J., Andriessen, P., & van Pul, C. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e18234 · Cited by 12 · see citing works
Measuring Physical Activity and Sedentary Behavior in Youth with Type 2 Diabetes
Rockette‐Wagner, B., Storti, K. L., Edelstein, S. L., Delahanty, L. M., Galvin, B., Jackson, A., & Kriska, A. M. (2016) · Childhood Obesity · doi:10.1089/chi.2015.0151 · Cited by 12 · see citing works
Review: Emerging Trends in Healthcare Adoption of Wireless Body Area Networks
Rangarajan, A. (2016) · Biomedical Instrumentation & Technology · doi:10.2345/0899-8205-50.4.264 · Cited by 11 · see citing works
Preterm infant general movements assessment via representation learning
Gong, X., Li, X., Ma, L., Tong, W., Shi, F., Hu, M., Zhang, X.-P. S., Yu, G., & Yang, C. (2022) · Displays · doi:10.1016/j.displa.2022.102308 · Cited by 11 · see citing works
Shin, H. I., Park, M. W., & Lee, W. H. (2023) · Korean Journal of Pediatrics · doi:10.3345/cep.2022.01235 · Cited by 10 · see citing works
Towards automatic assessment of atypical early motor development?
Ossmy, O., Donati, G., Kaur, A., Sotoodeh, M. S., & Forrester, G. S. (2025) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2025.111311 · Cited by 9 · see citing works
Movements analysis of preterm infants by using depth sensor
Cenci, A., Liciotti, D., Frontoni, E., Zingaretti, P., & Carnielli, V. P. (2017) · doi:10.1145/3109761.3109773 · Cited by 9 · see citing works
An Automated Approach for General Movement Assessment: A Pilot Study
Fontana, C., Ottaviani, V., Veneroni, C., Sforza, S. E., Pesenti, N., Mosca, F., Picciolini, O., Fumagalli, M., & Dellacà, R. L. (2021) · Frontiers in Pediatrics · doi:10.3389/fped.2021.720502 · Cited by 9 · see citing works
Wu, Y., van Rijssen, I. M., Buurman, M. T., Dijkstra, L., Hamer, E. G., & Hadders‐Algra, M. (2020) · Acta Paediatrica · doi:10.1111/apa.15300 · Cited by 7 · see citing works
Çelik, H. İ., Yıldız, A., Yıldız, R., Mutlu, A., Soylu, A. R., Gücüyener, K., Çamurdan, A. D., Koç, E., Önal, E. E., & Elbasan, B. (2023) · The Italian Journal of Pediatrics/Italian journal of pediatrics · doi:10.1186/s13052-023-01568-8 · Cited by 5 · see citing works
Monitoring preterm infants' body movement to improve developmental care for their health
Shimizu, A., Ishii, A., & Okada, S. (2017) · IEEE Global Conference on Consumer Electronics (GCCE) · doi:10.1109/gcce.2017.8229426 · Cited by 5 · see citing works
Video-based Body Parsing for Neonatal Body-parts Actigraphy: A Clinical Study in NICU
Zeng, Y., Pan, L., Song, X., Wang, Q., Yang, J., Lu, H., & Wang, W. (2024) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc53108.2024.10781960 · Cited by 5 · see citing works
Ben‐Sasson, A., Ben‐Sasson, E., Jacobs, K., & Malinovitch, R. (2020) · Health and Technology · doi:10.1007/s12553-020-00457-y · Cited by 5 · see citing works
SiamParseNet: Joint Body Parsing and Label Propagation in Infant Movement Videos
Ni, H., Xue, Y., Zhang, Q., & Huang, X. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-59719-1_39 · Cited by 5 · see citing works
Cost-effective Video-based Poor Repertoire Detection for Preterm Infant General Movement Analysis
Tong, W., Yang, C., Xiao, L., Shi, F., & Zhai, G. (2022) · International Conference on Image and Graphics Processing (ICIGP) · doi:10.1145/3512388.3512396 · Cited by 5 · see citing works
Parisi, C., Hesse, N., Tacke, U., Pujades, S., Blaschek, A., Hadders‐Algra, M., Black, M. J., Heinen, F., Müller‐Felber, W., & Schroeder, A. S. (2020) · Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz · doi:10.1007/s00103-020-03163-2 · Cited by 5 · see citing works
Frequency-based features for early cerebral palsy prediction
Rahmati, H., Martens, H. A., Aamo, O. M., Stavdahl, Ø., Støen, R. Ø., & Adde, L. (2015) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2015.7319560 · Cited by 5 · see citing works
Warning signs for identifying neurodevelopmental disorders: a systematic literature review
de Araújo, L. A. (2026) · Jornal de Pediatria · doi:10.1016/j.jped.2025.101478 · Cited by 8 · see citing works
Tafur, B., Weiss, S. M., & Mahmoud, M. (2023) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3610661.3616238 · Cited by 4 · see citing works
Automatic pose estimation in newborn infants: Lessons from the Baby Grow study
Sotoodeh, M. S., Ossmy, O., Donati, G., Hall, J., Rowan, H., & Forrester, G. S. (2026) · Behavior Research Methods · doi:10.3758/s13428-026-02943-z · Cited by 4 · see citing works
Balta, D., Kuo, H., Wang, J. Z., Porco, I. G., Schladen, M. M., Cereatti, A., Lum, P. S., & Croce, U. D. (2022) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc48229.2022.9871928 · Cited by 4 · see citing works
Design and Construct Validity of a Postural Control Test for Pre-Term Infants
Kniaziew-Gomoluch, K., Szopa, A., Kidoń, Z., Siwiec, A., & Domagalska–Szopa, M. (2022) · Diagnostics · doi:10.3390/diagnostics13010096 · Cited by 4 · see citing works
Peng, Z. Q., Zhao, Y., Kommers, D. R., van den Boom, H., Liang, R.-H., Long, X., Niemarkt, H. J., Andriessen, P., & van Pul, C. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3369135 · Cited by 4 · see citing works
The Motion Capture as Behavior Analyzing Method of Spontaneous Motor Activity in Human Infants
Gajniyarov, I., Mikhailov, I., Starodubtsev, I., Obabkov, I., Lvova, O. A., Suleymanova, E., & Антипина, И. (2019) · International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON) · doi:10.1109/sibircon48586.2019.8958041 · Cited by 4 · see citing works
Jardine, L. A., Mausling, R., Caldararo, D., Colditz, P. B., & Davies, M. W. (2022) · Early Human Development · doi:10.1016/j.earlhumdev.2022.105685 · Cited by 4 · see citing works
- Authors
- Marcroft, C., Khan, A., Embleton, N. D., Trenell, M., & Plötz, T.
- Affiliations
- Royal Victoria Infirmary (GB)
- Newcastle University (GB)
- Corresponding author
- Marcroft, Claire
- Venue
- Frontiers in Neurology
- Publisher
- Frontiers Media SA
- Published
- 2015-01-09
- Volume
- 5
- Pages
- 284-284
- ISSN
- 1664-2295 (ISSN-L)
- PMC
- PMC4288331
- OpenAlex
- W2076572096
- Cited by
- 146
- References
- 73
- Citations by year
- 2026: 6 · 2025: 7 · 2024: 11 · 2023: 15 · 2022: 18 · 2021: 13 · 2020: 18 · 2019: 19 · 2018: 9 · 2017: 12 · 2016: 10 · 2015: 8
- FWCI
- 1.79
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Neurology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Newcastle University ePrints (Newcastle Univesity) (cc-by)
- Funders
- National Institute for Health and Care Research (SRF-2011-04-017)
- Research Councils UK
- Medical Research Council (MR/K006312/1)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Cerebral Palsy and Movement Disorders
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Infant Development and Preterm Care
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Neonatal and fetal brain pathology
- Keywords
- motion recognition, high-risk infants, preterm infants, cerebral palsy, motion sensors, machine learning, early risk detection, infant motor development
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