TY - GEN
T1 - A scalable app for measuring autism risk behaviors in young children
T2 - 5th EAI International Conference on Wireless Mobile Communication and Healthcare - Transforming Healthcare through Innovations in Mobile and Wireless Technologies, MOBIHEALTH 2015
AU - Hashemi, Jordan
AU - Campbell, Kathleen
AU - Carpenter, Kimberly L.H.
AU - Harris, Adrianne
AU - Qiu, Qiang
AU - Tepper, Mariano
AU - Espinosa, Steven
AU - Borg, Jana Schaich
AU - Marsan, Samuel
AU - Calderbank, Robert
AU - Baker, Jeffery P.
AU - Egger, Helen L.
AU - Dawson, Geraldine
AU - Sapiro, Guillermo
N1 - Publisher Copyright:
Copyright © 2015 ICST.
PY - 2015/12/22
Y1 - 2015/12/22
N2 - In spite of recent advances in the genetics and neuroscience of early childhood mental health, behavioral observation is still the gold standard in screening, diagnosis, and outcome assessment. Unfortunately, clinical observation is often sub-jective, needs significant rater training, does not capture data from participants in their natural environment, and is not scalable for use in large populations or for longitu-dinal monitoring. To address these challenges, we devel-oped and tested a self-contained app designed to measure toddlers' social communication behaviors in a primary care, school, or home setting. Twenty 16-30 month old children with and without autism participated in this study. Tod-dlers watched the developmentally-Appropriate visual stim-uli on an iPad in a pediatric clinic and in our lab while the iPad camera simultaneously recorded video of the child's behaviors. Automated computer vision algorithms coded emotions and social referencing to quantify autism risk be-haviors. We validated our automatic computer coding by comparing the computer-generated analysis of facial expres-sion and social referencing to human coding of these behav-iors. We report our method and propose the development and testing of measures of young children's behaviors as the first step toward development of a novel, fully integrated, low-cost, scalable screening tool for autism and other neu-rodevelopmental disorders of early childhood.
AB - In spite of recent advances in the genetics and neuroscience of early childhood mental health, behavioral observation is still the gold standard in screening, diagnosis, and outcome assessment. Unfortunately, clinical observation is often sub-jective, needs significant rater training, does not capture data from participants in their natural environment, and is not scalable for use in large populations or for longitu-dinal monitoring. To address these challenges, we devel-oped and tested a self-contained app designed to measure toddlers' social communication behaviors in a primary care, school, or home setting. Twenty 16-30 month old children with and without autism participated in this study. Tod-dlers watched the developmentally-Appropriate visual stim-uli on an iPad in a pediatric clinic and in our lab while the iPad camera simultaneously recorded video of the child's behaviors. Automated computer vision algorithms coded emotions and social referencing to quantify autism risk be-haviors. We validated our automatic computer coding by comparing the computer-generated analysis of facial expres-sion and social referencing to human coding of these behav-iors. We report our method and propose the development and testing of measures of young children's behaviors as the first step toward development of a novel, fully integrated, low-cost, scalable screening tool for autism and other neu-rodevelopmental disorders of early childhood.
KW - Autism
KW - Automatic behavioral coding
KW - Facial affect coding system
KW - Integrated app
KW - Natural environments.
KW - Scalability
UR - http://www.scopus.com/inward/record.url?scp=85035020867&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85035020867&partnerID=8YFLogxK
U2 - 10.4108/eai.14-10-2015.2261939
DO - 10.4108/eai.14-10-2015.2261939
M3 - Conference contribution
AN - SCOPUS:85035020867
T3 - MOBIHEALTH 2015 - 5th EAI International Conference on Wireless Mobile Communication and Healthcare - Transforming Healthcare through Innovations in Mobile and Wireless Technologies
BT - MOBIHEALTH 2015 - 5th EAI International Conference on Wireless Mobile Communication and Healthcare - Transforming Healthcare through Innovations in Mobile and Wireless Technologies
A2 - Alomainy, Akram
A2 - Hao, Yang
A2 - Whittow, William
A2 - Nikita, Konstantina S.
A2 - Parini, Clive G.
PB - ICST
Y2 - 14 October 2015 through 16 October 2015
ER -