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Journal of Autism and Developmental Disorders

Gepubliceerd in:

26-03-2020 | Original Paper

Detecting and Classifying Self-injurious Behavior in Autism Spectrum Disorder Using Machine Learning Techniques

Auteurs: Kristine D. Cantin-Garside, Zhenyu Kong, Susan W. White, Ligia Antezana, Sunwook Kim, Maury A. Nussbaum

Gepubliceerd in: Journal of Autism and Developmental Disorders | Uitgave 11/2020

Abstract

Traditional self-injurious behavior (SIB) management can place compliance demands on the caregiver and have low ecological validity and accuracy. To support an SIB monitoring system for autism spectrum disorder (ASD), we evaluated machine learning methods for detecting and distinguishing diverse SIB types. SIB episodes were captured with body-worn accelerometers from children with ASD and SIB. The highest detection accuracy was found with k-nearest neighbors and support vector machines (up to 99.1% for individuals and 94.6% for grouped participants), and classification efficiency was quite high (offline processing at ~ 0.1 ms/observation). Our results provide an initial step toward creating a continuous and objective smart SIB monitoring system, which could in turn facilitate the future care of a pervasive concern in ASD.

vorige artikel Executive Function in High-Functioning Autism Spectrum Disorder: A Meta-analysis of fMRI Studies

volgende artikel Resilience in Familial Caregivers of Children with Developmental Disabilities: A Meta-analysis

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Albinali, F., Goodwin, M. S., & Intille, S. S. (2009). Recognizing stereotypical motor movements in the laboratory and classroom: A case study with children on the autism spectrum. Paper presented at the Proceedings of the 11th international conference on Ubiquitous computing.

Allen, K. D., & Warzak, W. J. (2000). The problem of parental nonadherence in clinical behavior analysis: Effective treatment is not enough. Journal of Applied Behavior Analysis, 33(3), 373–391. https://doi.org/10.1901/jaba.2000.33-373.CrossRefPubMedPubMedCentral

Amaral, D. G., Schumann, C. M., & Nordahl, C. W. (2008). Neuroanatomy of autism. Trends in Neurosciences, 31(3), 137–145. https://doi.org/10.1016/j.tins.2007.12.005.CrossRefPubMed

Banaee, H., Ahmed, M., & Loutfi, A. J. S. (2013). Data mining for wearable sensors in health monitoring systems: A review of recent trends and challenges. Sensors, 13(12), 17472–17500.CrossRefPubMedPubMedCentral

Bastani, K., Kim, S., Kong, Z. J., Nussbaum, M. A., & Huang, W. (2016a). Online classification and sensor selection optimization with applications to human material handling tasks using wearable sensing technologies. IEEE Transactions on Human-Machine Systems, 46(4), 485–497. https://doi.org/10.1109/THMS.2016.2537747.CrossRef

Bastani, K., Rao, P. K., & Kong, Z. (2016b). An online sparse estimation-based classification approach for real-time monitoring in advanced manufacturing processes from heterogeneous sensor data. IIE Transactions, 48(7), 579. https://doi.org/10.1080/0740817X.2015.1122254.CrossRef

Bellini, S., & Akullian, J. (2007). A meta-analysis of video modeling and video self-modeling interventions for children and adolescents with autism spectrum disorders. Exceptional Children, 73(3), 264–287.CrossRef

Bone, D., Goodwin, M. S., Black, M. P., Lee, C.-C., Audhkhasi, K., & Narayanan, S. (2015). Applying machine learning to facilitate autism diagnostics: Pitfalls and promises. Journal of Autism and Developmental Disorders, 45(5), 1121–1136. https://doi.org/10.1007/s10803-014-2268-6.CrossRefPubMedPubMedCentral

Bulling, A., Blanke, U., & Schiele, B. (2014). A tutorial on human activity recognition using body-worn inertial sensors. ACM Computing Surveys (CSUR), 46(3), 33.CrossRef

Cabibihan, J.-J., Javed, H., Aldosari, M., Frazier, T., & Elbashir, H. (2017). Sensing technologies for autism spectrum disorder screening and intervention. Sensors, 17(1), 46.CrossRef

Cantin-Garside, K., Valdez, R. S., Nussbaum, M. A., White, S., Kim, S., Kim, C. D., et al. (2018). Exploring challenges of monitoring technology and self-injurious behavior in autism spectrum disorder. Paper presented at the Proceedings of the Human Factors and Ergonomics Society Annual Meeting.

Chen, Y.-H., Rodgers, J., & McConachie, H. (2009). Restricted and repetitive behaviours, sensory processing and cognitive style in children with Autism Spectrum Disorders. Journal of Autism and Developmental Disorders, 39(4), 635–642. https://doi.org/10.1007/s10803-008-0663-6.CrossRefPubMed

Coronato, A., De Pietro, G., & Paragliola, G. (2014). A situation-aware system for the detection of motion disorders of patients with Autism Spectrum Disorders. Expert Systems with Applications, 41(17), 7868–7877.CrossRef

Dracobly, J. D., Dozier, C. L., Briggs, A. M., & Juanico, J. F. (2018). Reliability and validity of indirect assessment outcomes: Experts versus caregivers. Learning and Motivation, 62, 77–90. https://doi.org/10.1016/j.lmot.2017.02.007.CrossRefPubMed

Dunlap, G., Newton, J. S., Fox, L., Benito, N., & Vaughn, B. (2001). Family involvement in functional assessment and positive behavior support. Focus on autism and other developmental disabilities, 16(4), 215–221.CrossRef

Gaonkar, B., & Davatzikos, C. (2013). Analytic estimation of statistical significance maps for support vector machine based multi-variate image analysis and classification. NeuroImage, 78, 270–283. https://doi.org/10.1016/j.neuroimage.2013.03.066.CrossRefPubMed

Garside, K. D. C. (2019). Behavioral monitoring to identify self-injurious behavior among children with autism spectrum disorder. Unpublished PhD Dissertation. Department of Industrial and Systems Engineering, Virginia Tech.

Goncalves, N., Rodrigues, J. L., Costa, S., & Soares, F. (2012a). Preliminary study on determining stereotypical motor movements. Conference Proceedings of IEEE Engineering in Medicine and Biology Society, 2012, 1598–1601.

Goncalves, N., Rodrigues, J. L., Costa, S., & Soares, F. (2012). Automatic detection of stereotyped hand flapping movements: Two different approaches. In IEEE RO-MAN: The 21st IEEE international symposium on robot and human interactive communication (pp. 392–397).

Goodwin, M., Haghighi, M., Tang, Q., Akcakaya, M., Erdogmus, D., & Intille, S. (2014). Moving towards a real-time system for automatically recognizing stereotypical motor movements in individuals on the autism spectrum using wireless accelerometry. In UbiComp '14: Proceedings of the 2014 ACM international joint conference on pervasive and ubiquitous computing.

Goodwin, M. S., Intille, S. S., Albinali, F., & Velicer, W. F. (2011). Automated detection of stereotypical motor movements. Journal of Autism and Developmental Disorders, 41(6), 770–782. https://doi.org/10.1007/s10803-010-1102-z.CrossRefPubMed

Goodwin, M. S., Intille, S. S., Velicer, W. F., & Groden, J. (2008). Sensor-enabled detection of stereotypical motor movements in persons with autism spectrum disorder. Paper presented at the proceedings of the 7th international conference on Interaction design and children.

Gowen, E., & Hamilton, A. (2013). Motor abilities in autism: A review using a computational context. Journal of Autism and Developmental Disorders, 43(2), 323. https://doi.org/10.1007/sl0803-012-1574-0.CrossRefPubMed

Großekathöfer, U., Manyakov, N. V., Mihajlović, V., Pandina, G., Skalkin, A., Ness, S., et al. (2017). Automated detection of stereotypical motor movements in Autism Spectrum Disorder using recurrence quantification analysis. Frontiers in Neuroinformatics, 11, 9. https://doi.org/10.3389/fninf.2017.00009.CrossRefPubMedPubMedCentral

Hill, A. P., Zuckerman, K. E., Hagen, A. D., Kriz, D. J., Duvall, S. W., van Santen, J., et al. (2014). Aggressive behavior problems in children with Autism Spectrum Disorders: Prevalence and correlates in a large clinical sample. Research in Autism Spectrum Disorders, 8(9), 1121–1133. https://doi.org/10.1016/j.rasd.2014.05.006.CrossRefPubMedPubMedCentral

Iwata, B. A., Pace, G. M., Dorsey, M. F., Zarcone, J. R., Vollmer, T. R., Smith, R. G., et al. (1994). The functions of self-injurious behavior: An experimental-epidemiological analysis. Journal Of Applied Behavior Analysis, 27(2), 215–240. https://doi.org/10.1901/Jaba.1994.27-215.CrossRefPubMedPubMedCentral

Johnson, C. R., Butter, E. M., Handen, B. L., Sukhodolsky, D. G., Mulick, J., Lecavalier, L., et al. (2009). Standardised Observation Analogue Procedure (SOAP) for assessing parent and child behaviours in clinical trials. Journal of Intellectual Developmental Disability, 34(3), 230–238. https://doi.org/10.1080/13668250903074471.CrossRefPubMedPubMedCentral

Kalb, L. G., Vasa, R. A., Ballard, E. D., Woods, S., Goldstein, M., & Wilcox, H. C. (2016). Epidemiology of injury-related emergency department visits in the us among youth with autism spectrum disorder. Journal of Autism and Developmental Disorders, 46(8), 2756–2763. https://doi.org/10.1007/s10803-016-2820-7.CrossRefPubMedPubMedCentral

Kanne, S. M., & Mazurek, M. O. (2011). Aggression in children and adolescents with asd: Prevalence and risk factors. Journal of Autism and Developmental Disorders, 41(7), 926–937. https://doi.org/10.1007/s10803-010-1118-4.CrossRefPubMed

Kim, S., & Nussbaum, M. A. (2014). An evaluation of classification algorithms for manual material handling tasks based on data obtained using wearable technologies. Ergonomics, 57(7), 1040–1051. https://doi.org/10.1080/00140139.2014.907450.CrossRefPubMed

Kirby, A. V., Boyd, B. A., Williams, K. L., Faldowski, R. A., & Baranek, G. T. (2016). Sensory and repetitive behaviors among children with autism spectrum disorder at home. Autism, 21, 142–154.CrossRefPubMedPubMedCentral

Kurtz, P. F., Chin, M. D., Huete, J. M., Tarbox, R. S., O'Connor, J. T., Paclawskyj, T. R., et al. (2003). Functional analysis and treatment of self-injurious behavior in young children: A summary of 30 cases. Journal of Applied Behavior Analysis, 36(2), 205–219.CrossRefPubMedPubMedCentral

Lam, K. S., & Aman, M. G. (2007). The Repetitive Behavior Scale-Revised: Independent validation in individuals with autism spectrum disorders. Journal of Autism and Developmental Disorders, 37(5), 855–866.CrossRefPubMed

Lord, C., Rutter, M., DiLavore, P., Risi, S., Gotham, K., & Bishop, S. (2012). Autism diagnostic observation schedule–2nd edition (ADOS-2). Los Angeles, CA: Western Psychological Corporation.

Marcu, G., Tassini, K., Carlson, Q., Goodwyn, J., Rivkin, G., Schaefer, K. J., et al. (2013). Why do they still use paper?: Understanding data collection and use in Autism education. Paper presented at the proceedings of the sigchi conference on human factors in computing systems, Paris, France.

McLeod, A., Bochniewicz, E. M., Lum, P. S., Holley, R. J., Emmer, G., & Dromerick, A. W. (2016). Using wearable sensors and machine learning models to separate functional upper extremity use from walking-associated arm movements. Archives of Physical Medicine and Rehabilitation, 97(2), 224.CrossRefPubMed

Miller, J. D., Beazer, M. S., & Hahn, M. E. (2013). Myoelectric walking mode classification for transtibial amputees. IEEE Transactions on Biomedical Engineering, 60(10), 2745–2750. https://doi.org/10.1109/TBME.2013.2264466.CrossRefPubMed

Min, C.-H. (2017). Automatic detection and labeling of self-stimulatory behavioral patterns in children with Autism Spectrum Disorder. Paper presented at the Engineering in Medicine and Biology Society (EMBC), 2017 39th annual international conference of the IEEE.

Min, C.-H., & Tewfik, A. H. (2010). Automatic characterization and detection of behavioral patterns using linear predictive coding of accelerometer sensor data. Paper presented at the Engineering in Medicine and Biology Society (EMBC), 2010 annual international conference of the IEEE.

Min, C.-H., Tewfik, A. H., Kim, Y., & Menard, R. (2009). Optimal sensor location for body sensor network to detect self-stimulatory behaviors of children with autism spectrum disorder. Conference Proceedings of IEEE Engineering in Medicine and Biology Society., 2009, 3489–3492.

Minshawi, N. F., Hurwitz, S., Fodstad, J. C., Biebl, S., Morriss, D. H., & McDougle, C. J. (2014). The association between self-injurious behaviors and autism spectrum disorders. Psychology Research and Behavior Management, 7, 125–136. https://doi.org/10.2147/PRBM.S44635.CrossRefPubMedPubMedCentral

Mittek, M. M., Carlson, J. D., Mora-Becerra, F., Psota, E. T., & Perez, L. D. (2015). In-home behavioral monitoring using simultaneous localization and activity detection. Biomedical Sciences Instrumentation, 51, 289.PubMed

Moreau, A., Anderer, P., Ross, M., Cerny, A., Almazan, T. H., & Peterson, B. (2018). Detection of nocturnal scratching movements in patients with atopic dermatitis using accelerometers and recurrent neural networks. IEEE Journal of Biomedical and Health Informatics, 22(4), 1011–1018. https://doi.org/10.1109/JBHI.2017.2710798.CrossRefPubMed

Ozdenizci, O., Cumpanasoiu, C., Mazefsky, C., Siegel, M., Erdogmus, D., Ioannidis, S., et al. (2018). Time-series prediction of proximal aggression onset in minimally-verbal youth with autism spectrum disorder using physiological biosignals. arXiv:1809.09948.

Pace, G. M., Iwata, B. A., Edwards, G. L., & McCosh, K. C. (1986). Stimulus fading and transfer in the treatment of self-restraint and self-injurious behavior. Journal of Applied Behavior Analysis, 19(4), 381–389.CrossRefPubMedPubMedCentral

Pelios, L., Morren, J., Tesch, D., & Axelrod, S. (1999). The impact of functional analysis methodology on treatment choice for self-injurious and aggressive behavior. Journal of Applied Behavior Analysis, 32(2), 185–195.CrossRefPubMedPubMedCentral

Plötz, T., Hammerla, N. Y., & Olivier, P. (2011). Feature learning for activity recognition in ubiquitous computing. Paper presented at the IJCAI proceedings-international joint conference on artificial intelligence.

Plötz, T., Hammerla, N. Y., Rozga, A., Reavis, A., Call, N., & Abowd, G. D. (2012). Automatic assessment of problem behavior in individuals with developmental disabilities. Paper presented at the proceedings of the 2012 ACM conference on ubiquitous computing.

Poliker, R. (2006). Pattern recognition. In Wiley Encyclopedia of biomedical engineering. Wiley.

Preece, S. J., Goulermas, J. Y., Kenney, L. P., Howard, D., Meijer, K., & Crompton, R. (2009). Activity identification using body-mounted sensors—A review of classification techniques. Physiological Measurement, 30(4), R1.CrossRefPubMed

Pugliese, C. E., Kenworthy, L., Bal, V. H., Wallace, G. L., Yerys, B. E., Maddox, B. B., et al. (2015). Replication and comparison of the newly proposed ADOS-2, module 4 algorithm in ASD without ID: A multi-site study. Journal of Autism and Developmental Disorders, 45(12), 3919–3931. https://doi.org/10.1007/s10803-015-2586-3.CrossRefPubMedPubMedCentral

Rad, N. M., Furlanello, C., & Kessler, F. B. (2016). Applying deep learning to stereotypical motor movement detection in autism spectrum disorders. 2016 IEEE 16th international conference on data mining workshops.

Richards, C., Moss, J., Nelson, L., & Oliver, C. (2016). Persistence of self-injurious behaviour in autism spectrum disorder over 3 years: A prospective cohort study of risk markers. J Neurodev Disord, 8, 21. https://doi.org/10.1186/s11689-016-9153-x.CrossRefPubMedPubMedCentral

Roid, G. H., & Miller, L. J. (1997). Leiter international performance scale-revised (Leiter-R). IL Stoelting: Wood Dale.

Rojahn, J., Matson, J. L., Lott, D., Esbensen, A. J., & Smalls, Y. (2001). The Behavior Problems Inventory: An instrument for the assessment of self-injury, stereotyped behavior, and aggression/destruction in individuals with developmental disabilities. Journal of Autism and Developmental Disorders, 31(6), 577–588.CrossRefPubMed

Rooker, G. W., Hausman, N. L., Fisher, A. B., Gregory, M. K., Lawell, J. L., & Hagopian, L. P. (2018). Classification of injuries observed in functional classes of self-injurious behaviour. Journal of Intellectual Disability Research, 62(12), 1086–1096. https://doi.org/10.1111/jir.12535.CrossRefPubMed

Schaeffer, K. M., Hamilton, K. A., & Johnson, W. L. B. (2016). Video self-modeling interventions for students with autism spectrum disorder. Intervention in School and Clinic, 52(1), 17–24.CrossRef

Soares, D. A., Vannest, K. J., & Harrison, J. (2009). Computer aided self-monitoring to increase academic production and reduce self-injurious behavior in a child with autism. Behavioral Interventions, 24(3), 171–183. https://doi.org/10.1002/bin.283.CrossRef

Tarbox, J., Wilke, A. E., Najdowski, A. C., Findel-Pyles, R. S., Balasanyan, S., Caveney, A. C., et al. (2009). Comparing indirect, descriptive, and experimental functional assessments of challenging behavior in children with autism. Journal of Developmental and Physical Disabilities, 21(6), 493–514. https://doi.org/10.1007/s10882-009-9154-8.CrossRef

Taylor, L., Oliver, C., & Murphy, G. (2011). The chronicity of self-injurious behaviour: A long-term follow-up of a total population study. Journal of Applied Research in Intellectual Disabilities, 24(2), 105–117. https://doi.org/10.1111/j.1468-3148.2010.00579.x.CrossRef

Trost, S. G., Zheng, Y., & Wong, W.-K. (2014). Machine learning for activity recognition: hip versus wrist data. Physiological Measurement, 35(11), 2183.CrossRefPubMed

Wechsler, D. (2011). WASI-II: Wechsler abbreviated scale of intelligence. San Antonio: PsychCorp.

Williams, S. K., Johnson, C., & Sukhodolsky, D. G. (2005). The role of the school psychologist in the inclusive education of school-age children with autism spectrum disorders. Journal of School Psychology, 43(2), 117–136.CrossRef

Wright, J., Yang, A. Y., Ganesh, A., Sastry, S. S., & Ma, Y. (2009). Robust face recognition via sparse representation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(2), 210–227.CrossRefPubMed

Wu, X., Kumar, V., Ross Quinlan, J., Ghosh, J., Yang, Q., Motoda, H., et al. (2008). Top 10 algorithms in data mining. Knowledge and Information Systems, 14(1), 1–37. https://doi.org/10.1007/s10115-007-0114-2.CrossRef

Zheng, Y.-L., Ding, X.-R., Poon, C. C. Y., Lo, B. P. L., Zhang, H., Zhou, X.-L., et al. (2014). Unobtrusive sensing and wearable devices for health informatics. IEEE Transactions on Biomedical Engineering, 61(5), 1538–1554.CrossRefPubMed

Titel: Detecting and Classifying Self-injurious Behavior in Autism Spectrum Disorder Using Machine Learning Techniques
Auteurs: Kristine D. Cantin-Garside
Zhenyu Kong
Susan W. White
Ligia Antezana
Sunwook Kim
Maury A. Nussbaum
Publicatiedatum: 26-03-2020
Uitgeverij: Springer US
Gepubliceerd in: Journal of Autism and Developmental Disorders / Uitgave 11/2020
Print ISSN: 0162-3257
Elektronisch ISSN: 1573-3432
DOI: https://doi.org/10.1007/s10803-020-04463-x

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Detecting and Classifying Self-injurious Behavior in Autism Spectrum Disorder Using Machine Learning Techniques

Abstract

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