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Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos

Abstract: 

Research has shown that caregivers implementing
pivotal response treatment (PRT) with their child with autism
spectrum disorder (ASD) helps the child develop social and
communication skills. Evaluation of caregiver fidelity to PRT in
training programs and research studies relies on the evaluation
of video probes depicting the caregiver interacting with his
or her child. These video probes are reviewed by behavior
analysts and are dependent on manual processing to extract
data metrics. Using multimodal data processing techniques and
machine learning could alleviate the human cost of evaluating
the video probes by automating data analysis tasks.

Creating an ’Opportunity to Respond’ is one of the categories
used to evaluate caregiver fidelity to PRT implementation. A
caregiver is determined to have successfully demonstrated creating
an opportunity to respond when they have delivered an
appropriate instruction while she or he has the child’s attention.
Automatically determining when the caregiver has correctly
provided an opportunity to respond requires classifying the audio
and video data from the probes. Combining the modalities into a
single classification task can be undertaken using feature fusion
or decision fusion methods. Two decision fusion configurations,
and a feature fusion model were evaluated. The decision fusion
models achieved higher accuracy, however the feature fusion
model had a higher average

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Paper Details

Authors:
Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan
Submitted On:
11 November 2019 - 8:34pm
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Troy McDaniel
Paper Code:
1570568459
Document Year:
2019
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Document Files

GlobalSIP_Presentation.pptx

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[1] Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan, "Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4946. Accessed: Dec. 12, 2019.
@article{4946-19,
url = {http://sigport.org/4946},
author = {Corey Heath; Hemanth Venkateswara; Troy McDaniel; Sethuraman Panchanathan },
publisher = {IEEE SigPort},
title = {Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos},
year = {2019} }
TY - EJOUR
T1 - Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos
AU - Corey Heath; Hemanth Venkateswara; Troy McDaniel; Sethuraman Panchanathan
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4946
ER -
Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan. (2019). Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos. IEEE SigPort. http://sigport.org/4946
Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan, 2019. Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos. Available at: http://sigport.org/4946.
Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan. (2019). "Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos." Web.
1. Corey Heath, Hemanth Venkateswara, Troy McDaniel, Sethuraman Panchanathan. Using Multimodal Data for Automated Fidelity Evaluation in Pivotal Response Treatment Videos [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4946