The future of General Movement Assessment: The role of computer vision and machine learning - A scoping review

doi:10.1016/j.ridd.2021.103854

. 2021 Mar:110:103854.

doi: 10.1016/j.ridd.2021.103854. Epub 2021 Feb 8.

The future of General Movement Assessment: The role of computer vision and machine learning - A scoping review

Affiliations

¹ iDN - Interdisciplinary Developmental Neuroscience, Division of Phoniatrics, Medical University of Graz, Graz, Austria; Know-Center GmbH, Graz, Austria.
² iDN - Interdisciplinary Developmental Neuroscience, Division of Phoniatrics, Medical University of Graz, Graz, Austria; Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany; Leibniz-ScienceCampus Primate Cognition, Göttingen, Germany.
³ Department for Computational Neuroscience, Third Institute of Physics-Biophysics, Georg-August-University of Göttingen, Göttingen, Germany.
⁴ Leibniz-ScienceCampus Primate Cognition, Göttingen, Germany; German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany.
⁵ Know-Center GmbH, Graz, Austria; Institute of Interactive Systems and Data Science, Graz University of Technology, Graz, Austria.
⁶ Department of Medical Engineering, Technical University Berlin, Berlin, Germany.
⁷ Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden; Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden; Curtin Autism Research Group, School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia, Australia.
⁸ Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany; Leibniz-ScienceCampus Primate Cognition, Göttingen, Germany.
⁹ Division of Pediatric Infectious Diseases, David Geffen UCLA School of Medicine, USA.
¹⁰ Leibniz-ScienceCampus Primate Cognition, Göttingen, Germany; Department for Computational Neuroscience, Third Institute of Physics-Biophysics, Georg-August-University of Göttingen, Göttingen, Germany; Institute of Physics, Department for Computational Neuroscience at the Bernstein Center Göttingen, Georg-August-University of Göttingen, Göttingen, Germany.
¹¹ iDN - Interdisciplinary Developmental Neuroscience, Division of Phoniatrics, Medical University of Graz, Graz, Austria.
¹² iDN - Interdisciplinary Developmental Neuroscience, Division of Phoniatrics, Medical University of Graz, Graz, Austria; Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany; Leibniz-ScienceCampus Primate Cognition, Göttingen, Germany; Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden. Electronic address: peter.marschik@med.uni-goettingen.de.

PMID: 33571849
PMCID: PMC7910279
DOI: 10.1016/j.ridd.2021.103854

The future of General Movement Assessment: The role of computer vision and machine learning - A scoping review

Nelson Silva et al. Res Dev Disabil. 2021 Mar.

. 2021 Mar:110:103854.

doi: 10.1016/j.ridd.2021.103854. Epub 2021 Feb 8.

Authors

Affiliations

¹ iDN - Interdisciplinary Developmental Neuroscience, Division of Phoniatrics, Medical University of Graz, Graz, Austria; Know-Center GmbH, Graz, Austria.
² iDN - Interdisciplinary Developmental Neuroscience, Division of Phoniatrics, Medical University of Graz, Graz, Austria; Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany; Leibniz-ScienceCampus Primate Cognition, Göttingen, Germany.
³ Department for Computational Neuroscience, Third Institute of Physics-Biophysics, Georg-August-University of Göttingen, Göttingen, Germany.
⁴ Leibniz-ScienceCampus Primate Cognition, Göttingen, Germany; German Primate Center - Leibniz Institute for Primate Research, Göttingen, Germany.
⁵ Know-Center GmbH, Graz, Austria; Institute of Interactive Systems and Data Science, Graz University of Technology, Graz, Austria.
⁶ Department of Medical Engineering, Technical University Berlin, Berlin, Germany.
⁷ Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden; Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden; Curtin Autism Research Group, School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia, Australia.
⁸ Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany; Leibniz-ScienceCampus Primate Cognition, Göttingen, Germany.
⁹ Division of Pediatric Infectious Diseases, David Geffen UCLA School of Medicine, USA.
¹⁰ Leibniz-ScienceCampus Primate Cognition, Göttingen, Germany; Department for Computational Neuroscience, Third Institute of Physics-Biophysics, Georg-August-University of Göttingen, Göttingen, Germany; Institute of Physics, Department for Computational Neuroscience at the Bernstein Center Göttingen, Georg-August-University of Göttingen, Göttingen, Germany.
¹¹ iDN - Interdisciplinary Developmental Neuroscience, Division of Phoniatrics, Medical University of Graz, Graz, Austria.
¹² iDN - Interdisciplinary Developmental Neuroscience, Division of Phoniatrics, Medical University of Graz, Graz, Austria; Child and Adolescent Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany; Leibniz-ScienceCampus Primate Cognition, Göttingen, Germany; Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden. Electronic address: peter.marschik@med.uni-goettingen.de.

PMID: 33571849
PMCID: PMC7910279
DOI: 10.1016/j.ridd.2021.103854

Abstract

Background: The clinical and scientific value of Prechtl general movement assessment (GMA) has been increasingly recognised, which has extended beyond the detection of cerebral palsy throughout the years. With advancing computer science, a surging interest in developing automated GMA emerges.

Aims: In this scoping review, we focused on video-based approaches, since it remains authentic to the non-intrusive principle of the classic GMA. Specifically, we aimed to provide an overview of recent video-based approaches targeting GMs; identify their techniques for movement detection and classification; examine if the technological solutions conform to the fundamental concepts of GMA; and discuss the challenges of developing automated GMA.

Methods and procedures: We performed a systematic search for computer vision-based studies on GMs.

Outcomes and results: We identified 40 peer-reviewed articles, most (n = 30) were published between 2017 and 2020. A wide variety of sensing, tracking, detection, and classification tools for computer vision-based GMA were found. Only a small portion of these studies applied deep learning approaches. A comprehensive comparison between data acquisition and sensing setups across the reviewed studies, highlighting limitations and advantages of each modality in performing automated GMA is provided.

Conclusions and implications: A "method-of-choice" for automated GMA does not exist. Besides creating large datasets, understanding the fundamental concepts and prerequisites of GMA is necessary for developing automated solutions. Future research shall look beyond the narrow field of detecting cerebral palsy and open up to the full potential of applying GMA to enable an even broader application.

Keywords: Augmented general movement assessment; Automation; Cerebral palsy; Computer vision; Deep learning; Developmental disorder; Early detection; General movements; Infancy; Machine learning; Neurodevelopment; Pose estimation.

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Conflict of interest statement

We declare that there are no conflicts of interest, guiding this research work.

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Literature search and screening procedure.

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References

1. Alcantarilla, P., Bartoli, A., & Davison, A. (2012, October 7). KAZE features. 10.1007/978-3-642-33783-3_16. - DOI
1. Ali J., Charman T., Johnson M.H., Jones E.J.H., BASIS/STAARS Team Early motor differences in infants at elevated likelihood of autism spectrum disorder and/or attention deficit hyperactivity disorder. Journal of Autism and Developmental Disorders. 2020;50(12):4367–4384. doi: 10.1007/s10803-020-04489-1. - DOI - PMC - PubMed
1. Beck F., Koch S., Weiskopf D. Visual analysis and dissemination of scientific literature collections with SurVis. IEEE Transactions on Visualization and Computer Graphics. 2016;22(1):180–189. doi: 10.1109/TVCG.2015.2467757. - DOI - PubMed
1. Beleites C., Neugebauer U., Bocklitz T., Krafft C., Popp J. Sample size planning for classification models. Analytica Chimica Acta. 2013;760:25–33. doi: 10.1016/j.aca.2012.11.007. - DOI - PubMed
1. Bölte S., Bartl-Pokorny K.D., Jonsson U., Berggren S., Zhang D., Kostrzewa E.…Marschik P.B. How can clinicians detect and treat autism early? Methodological trends of technology use in research. Acta Paediatrica (Oslo, Norway : 1992) Supplement. 2016;105(2):137–144. doi: 10.1111/apa.13243. - DOI - PMC - PubMed

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[1] Alcantarilla, P., Bartoli, A., & Davison, A. (2012, October 7). KAZE features. 10.1007/978-3-642-33783-3_16. - DOI

[2] Alcantarilla, P., Bartoli, A., & Davison, A. (2012, October 7). KAZE features. 10.1007/978-3-642-33783-3_16. - DOI

[3] Ali J., Charman T., Johnson M.H., Jones E.J.H., BASIS/STAARS Team Early motor differences in infants at elevated likelihood of autism spectrum disorder and/or attention deficit hyperactivity disorder. Journal of Autism and Developmental Disorders. 2020;50(12):4367–4384. doi: 10.1007/s10803-020-04489-1. - DOI - PMC - PubMed

[4] Ali J., Charman T., Johnson M.H., Jones E.J.H., BASIS/STAARS Team Early motor differences in infants at elevated likelihood of autism spectrum disorder and/or attention deficit hyperactivity disorder. Journal of Autism and Developmental Disorders. 2020;50(12):4367–4384. doi: 10.1007/s10803-020-04489-1. - DOI - PMC - PubMed

[5] Beck F., Koch S., Weiskopf D. Visual analysis and dissemination of scientific literature collections with SurVis. IEEE Transactions on Visualization and Computer Graphics. 2016;22(1):180–189. doi: 10.1109/TVCG.2015.2467757. - DOI - PubMed

[6] Beck F., Koch S., Weiskopf D. Visual analysis and dissemination of scientific literature collections with SurVis. IEEE Transactions on Visualization and Computer Graphics. 2016;22(1):180–189. doi: 10.1109/TVCG.2015.2467757. - DOI - PubMed

[7] Beleites C., Neugebauer U., Bocklitz T., Krafft C., Popp J. Sample size planning for classification models. Analytica Chimica Acta. 2013;760:25–33. doi: 10.1016/j.aca.2012.11.007. - DOI - PubMed

[8] Beleites C., Neugebauer U., Bocklitz T., Krafft C., Popp J. Sample size planning for classification models. Analytica Chimica Acta. 2013;760:25–33. doi: 10.1016/j.aca.2012.11.007. - DOI - PubMed

[9] Bölte S., Bartl-Pokorny K.D., Jonsson U., Berggren S., Zhang D., Kostrzewa E.…Marschik P.B. How can clinicians detect and treat autism early? Methodological trends of technology use in research. Acta Paediatrica (Oslo, Norway : 1992) Supplement. 2016;105(2):137–144. doi: 10.1111/apa.13243. - DOI - PMC - PubMed

[10] Bölte S., Bartl-Pokorny K.D., Jonsson U., Berggren S., Zhang D., Kostrzewa E.…Marschik P.B. How can clinicians detect and treat autism early? Methodological trends of technology use in research. Acta Paediatrica (Oslo, Norway : 1992) Supplement. 2016;105(2):137–144. doi: 10.1111/apa.13243. - DOI - PMC - PubMed

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The future of General Movement Assessment: The role of computer vision and machine learning - A scoping review

Affiliations

The future of General Movement Assessment: The role of computer vision and machine learning - A scoping review

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

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Cited by

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Abstract

Conflict of interest statement

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