research-article

Predicting ADHD Risk from Touch Interaction Data

Authors:

Ann-Christine Ehlis,

Peter GerjetsAuthors Info & Claims

ICMI '18: Proceedings of the 20th ACM International Conference on Multimodal Interaction

Pages 446 - 454

https://doi.org/10.1145/3242969.3242986

Published: 02 October 2018 Publication History

Abstract

This paper presents a novel approach for automatic prediction of risk of ADHD in schoolchildren based on touch interaction data. We performed a study with 129 fourth-grade students solving math problems on a multiple-choice interface to obtain a large dataset of touch trajectories. Using Support Vector Machines, we analyzed the predictive power of such data for ADHD scales. For regression of overall ADHD scores, we achieve a mean squared error of 0.0962 on a four-point scale (R² = 0.5667). Classification accuracy for increased ADHD risk (upper vs. lower third of collected scores) is 91.1%.

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Cited By

Cibrian FMin LArnold V(2024)Towards a Multimodal Approach for Assessing ADHD Hyperactivity BehaviorsProceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2024)10.1007/978-3-031-77571-0_1(3-14)Online publication date: 21-Dec-2024
https://doi.org/10.1007/978-3-031-77571-0_1
Kalanadhabhatta MGanesan DRahman T(2023)Towards Accurate and Scalable Mental Health Screening Technologies for Young ChildrenAdjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing10.1145/3594739.3610763(225-229)Online publication date: 8-Oct-2023
https://dl.acm.org/doi/10.1145/3594739.3610763
Zhang HLiu YZhu SFang X(2023)Prototype Design of Wearable Multimodal Interaction Based on Preliminary Screening for ADHD in Children in Preschool AgeProceedings of the 22nd Annual ACM Interaction Design and Children Conference10.1145/3585088.3593898(672-676)Online publication date: 19-Jun-2023
https://dl.acm.org/doi/10.1145/3585088.3593898
Show More Cited By

Index Terms

Predicting ADHD Risk from Touch Interaction Data
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User models
      2. User studies
    2. Interaction devices
      1. Touch screens

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cover image ACM Other conferences

ICMI '18: Proceedings of the 20th ACM International Conference on Multimodal Interaction

October 2018

687 pages

ISBN:9781450356923

DOI:10.1145/3242969

General Chairs:
Sidney K. D'Mello
University of Illinois, USA
,
Panayiotis (Panos) Georgiou
University of Southern California, USA
,
Stefan Scherer
University of Southern California, USA
,
Program Chairs:
Emily Mower Provost
University of Michigan, USA
,
Mohammad Soleymani
University of Southern California, USA
,
Marcelo Worsley
Northwestern University, USA

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGCHI: Specialist Interest Group in Computer-Human Interaction of the ACM

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 October 2018

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LEAD Graduate School and Research Network

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ICMI '18

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SIGCHI

ICMI '18: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION

October 16 - 20, 2018

CO, Boulder, USA

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ICMI '18 Paper Acceptance Rate 63 of 149 submissions, 42%;

Overall Acceptance Rate 453 of 1,080 submissions, 42%

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Cited By

Cibrian FMin LArnold V(2024)Towards a Multimodal Approach for Assessing ADHD Hyperactivity BehaviorsProceedings of the International Conference on Ubiquitous Computing and Ambient Intelligence (UCAmI 2024)10.1007/978-3-031-77571-0_1(3-14)Online publication date: 21-Dec-2024
https://doi.org/10.1007/978-3-031-77571-0_1
Kalanadhabhatta MGanesan DRahman T(2023)Towards Accurate and Scalable Mental Health Screening Technologies for Young ChildrenAdjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing10.1145/3594739.3610763(225-229)Online publication date: 8-Oct-2023
https://dl.acm.org/doi/10.1145/3594739.3610763
Zhang HLiu YZhu SFang X(2023)Prototype Design of Wearable Multimodal Interaction Based on Preliminary Screening for ADHD in Children in Preschool AgeProceedings of the 22nd Annual ACM Interaction Design and Children Conference10.1145/3585088.3593898(672-676)Online publication date: 19-Jun-2023
https://dl.acm.org/doi/10.1145/3585088.3593898
Jones DGhasemi SGračanin DAzab M(2023)Privacy, Safety, and Security in Extended Reality: User Experience Challenges for Neurodiverse UsersHCI for Cybersecurity, Privacy and Trust10.1007/978-3-031-35822-7_33(511-528)Online publication date: 9-Jul-2023
https://doi.org/10.1007/978-3-031-35822-7_33
Kalanadhabhatta MSantana AZhang ZGanesan DGrabell ARahman T(2022)EarlyScreenProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35345836:2(1-39)Online publication date: 7-Jul-2022
https://dl.acm.org/doi/10.1145/3534583
Stefanidi ESchöning JFeger SMarshall PRogers YNiess J(2022)Designing for Care Ecosystems: a Literature Review of Technologies for Children with ADHDProceedings of the 21st Annual ACM Interaction Design and Children Conference10.1145/3501712.3529746(13-25)Online publication date: 27-Jun-2022
https://dl.acm.org/doi/10.1145/3501712.3529746
Spiel KHornecker EWilliams RGood J(2022)ADHD and Technology Research – Investigated by Neurodivergent ReadersProceedings of the 2022 CHI Conference on Human Factors in Computing Systems10.1145/3491102.3517592(1-21)Online publication date: 29-Apr-2022
https://dl.acm.org/doi/10.1145/3491102.3517592
Baayen RFasiolo MWood SChuang Y(2022)A note on the modeling of the effects of experimental time in psycholinguistic experimentsThe Mental Lexicon10.1075/ml.21012.baa17:2(178-212)Online publication date: 4-Apr-2022
https://doi.org/10.1075/ml.21012.baa

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