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Robot-Assisted ADHD Screening in Diagnostic Process

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Abstract

This paper presents a novel approach to screening children with ADHD, one of the most prevalent childhood disorders. We have designed the robot-assisted, game-like test that directly reflects children’s behavior on measuring ADHD symptoms. Using the sensors in the robot system, most of the children’s behavior is automatically measured during the entire course of the test. We collected real data by carrying out tests to 326 children from 3rd to 4th grades in the field. A unified frame that classifies multiple categories of ADHD, ADHD-at-Risk and normal has been set up to investigate a wide spectrum of classifiers and their optimal hyper-parameters. The results of the data analysis show highly confident ADHD classification, up to 97% (F1 score). It could be a practical tool for clinicians and special teachers to use in the diagnosis of childhood ADHD.

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Acknowledgements

This work was supported by the Technology Innovation Program (10048451), funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea).

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Author notes

  1. Injun Park

    Present address: University of Seoul, Seoul, Republic of Korea

Authors and Affiliations

  1. School of Mechanical Engineering, Sungkyunkwan University, Suwon, Republic of Korea

    Mun-Taek Choi & Jinseob Yeom

  2. Institute of Special Education, Rehabilitation Science, Daegu University, Daegu, Republic of Korea

    Yunhee Shin

  3. Robocare Co., Pangyo, Republic of Korea

    Injun Park

Authors
  1. Mun-Taek Choi
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  2. Jinseob Yeom
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  3. Yunhee Shin
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  4. Injun Park
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Correspondence to Mun-Taek Choi.

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Choi, MT., Yeom, J., Shin, Y. et al. Robot-Assisted ADHD Screening in Diagnostic Process. J Intell Robot Syst 95, 351–363 (2019). https://doi.org/10.1007/s10846-018-0890-9

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