Social Approach in Autism: Modeling Objective Measurements of Child Movement in a Naturalistic Environment

Background. Atypicalities in social approach are thought to be characteristic of children with autism spectrum disorder (ASD), but few studies have quantified the social movement of children with ASD using objective measures. The purpose of this paper is to introduce a new method—computational modeling of radio frequency identification (RFID) child tracking—for studying children with ASD in a naturalistic setting. We present the use of RFID measurements to investigate the velocity and social approach of children with ASD and typically developing (TD) children interacting together in preschool inclusion classrooms during repeated multi-hour observations. Methods. Observations of 14 preschoolers with ASD and 16 TD preschoolers in two inclusion classrooms on a total of 10 days yielded approximately 10 hours of data per child. Objective measurements of position and orientation were collected using four corner-mounted Ubisense ultra-wide sensors, which tracked a right and left tag worn by each child (in a vest) and teacher in the classroom. We calculate angular velocity, velocity, and social approach, and compare ASD and TD children on these parameters using multilevel statistical models. Results. In this initial exploration of the ASD phenotype in situ, children with ASD did not differ from TD children in angular velocity or velocity of movement in the classroom. Rather, pairs of TD children moved toward and away from each other at higher velocities than both pairs of children with ASD and pairs in which one child had ASD and the other child was TD. Children with ASD, however, moved toward and away from teachers at higher velocities than TD children. Limitations. Illustrative data from repeated observations of 30 children in two classrooms are reported. Results are preliminary. Conclusions. Multi-hour, objective measurements in a preschool inclusion classroom indicated that children with ASD did not move through space or turn at higher velocities than other children. Instead, ASD differences were evident in social approach. Children with ASD were slower in approaching peers but quicker in approaching teachers than were TD children. The results suggest the potential of modeling RFID measurements to produce a quantitative understanding of the ASD phenotype in naturalistic social contexts.

[1]  Mubarak Shah,et al.  Deep Affinity Network for Multiple Object Tracking , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Daniel S. Messinger,et al.  Validation of continuous measures of peer social interaction with self- and teacher-reports of friendship and social engagement , 2020, The European journal of developmental psychology.

[3]  Daniel J. Faso,et al.  Outcomes of real-world social interaction for autistic adults paired with autistic compared to typically developing partners , 2019, Autism : the international journal of research and practice.

[4]  S. Jeng,et al.  Multidimensional Developments and Free-Play Movement Tracking in 30- to 36-Month-Old Toddlers With Autism Spectrum Disorder Who Were Full Term. , 2019, Physical therapy.

[5]  Jiri Matas,et al.  CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[6]  O. Donchin,et al.  Quantifying the social symptoms of autism using motion capture , 2019, Scientific Reports.

[7]  Guillermo Sapiro,et al.  Potential for Digital Behavioral Measurement Tools to Transform the Detection and Diagnosis of Autism Spectrum Disorder , 2019, JAMA pediatrics.

[8]  Udo Rudolph,et al.  Continuous measurement of dynamic classroom social interactions , 2019, International journal of behavioral development.

[9]  John Gormley,et al.  Gait Deviations in Children with Autism Spectrum Disorders: A Review , 2015, Autism research and treatment.

[10]  D. Bates,et al.  Fitting Linear Mixed-Effects Models Using lme4 , 2014, 1406.5823.

[11]  James M. Rehg,et al.  Behavioral Imaging and Autism , 2014, IEEE Pervasive Computing.

[12]  J. Gardner,et al.  Rating scale measures are associated with Noldus EthoVision-XT video tracking of behaviors of children on the autism spectrum , 2014, Molecular Autism.

[13]  Matthew F. Moran,et al.  Gait analysis of teenagers and young adults diagnosed with autism and severe verbal communication disorders , 2013, Front. Integr. Neurosci..

[14]  Laurent Mottron,et al.  The autistic spectrum. , 2013, Handbook of clinical neurology.

[15]  Yi Zhang,et al.  Motor impairment in sibling pairs concordant and discordant for autism spectrum disorders , 2012, Autism : the international journal of research and practice.

[16]  Victoria L. Chester,et al.  Gait Symmetry in Children with Autism , 2012, Autism research and treatment.

[17]  C. Hass,et al.  Motor Coordination in Autism Spectrum Disorders: A Synthesis and Meta-Analysis , 2010, Journal of autism and developmental disorders.

[18]  William D. Kearns,et al.  Ultra wideband radio: A novel method for measuring wandering in persons with dementia , 2008 .

[19]  J. Massion,et al.  Goal Directed Locomotion and Balance Control in Autistic Children , 2005, Journal of autism and developmental disorders.

[20]  D. Katz,et al.  American Statistical Association , 2022, The SAGE Encyclopedia of Research Design.

[21]  D. Fein,et al.  Social initiations by autistic children to adults and other children , 1995, Journal of autism and developmental disorders.

[22]  R. Livingston,et al.  An automated electronic method for quantifying spinning (circling) in children with autistic disorder. , 1995, The Journal of neuropsychiatry and clinical neurosciences.

[23]  J. Rabe-Jabłońska,et al.  [Affective disorders in the fourth edition of the classification of mental disorders prepared by the American Psychiatric Association -- diagnostic and statistical manual of mental disorders]. , 1993, Psychiatria polska.

[24]  John M. Franchak,et al.  Development of motor behavior. , 1963, Journal of the American Physical Therapy Association.

[25]  Lull Gf,et al.  THE AMERICAN MEDICAL ASSOCIATION. , 1947, Science.