Evaluating Therapeutic Effects of ADHD Medication Objectively by Movement Quantification with a Video-Based Skeleton Analysis

Chen-Sen Ouyang, Yi-Hung Chiu, Ching-Tai Chiang, Rong-Ching Wu, Ying-Tong Lin, Rei-Cheng Yang and Lung-Chang Lin
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Chen-Sen Ouyang: Department of Information Engineering, I-Shou University, Kaohsiung 840, Taiwan
Yi-Hung Chiu: Department of Information Engineering, I-Shou University, Kaohsiung 840, Taiwan
Ching-Tai Chiang: Department of Computer and Communication, National Pingtung University, Pingtung 912, Taiwan
Rong-Ching Wu: Department of Electrical Engineering, I-Shou University, Kaohsiung 840, Taiwan
Ying-Tong Lin: St. Dominic Catholic High School, Kaohsiung 802, Taiwan
Rei-Cheng Yang: Departments of Pediatrics, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan
Lung-Chang Lin: Departments of Pediatrics, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung 807, Taiwan

IJERPH, 2021, vol. 18, issue 17, 1-13

Abstract: Attention-deficit/hyperactivity disorder (ADHD) is the most common neuropsychiatric disorder in children. Several scales are available to evaluate ADHD therapeutic effects, including the Swanson, Nolan, and Pelham (SNAP) questionnaire, the Vanderbilt ADHD Diagnostic Rating Scale, and the visual analog scale. However, these scales are subjective. In the present study, we proposed an objective and automatic approach for evaluating the therapeutic effects of medication in patients with (ADHD). The approach involved using movement quantification of patients’ skeletons detected automatically with OpenPose in outpatient videos. Eleven skeleton parameter series were calculated from the detected skeleton sequence, and the corresponding 33 features were extracted using autocorrelation and variance analysis. This study enrolled 25 patients with ADHD. The outpatient videos were recorded before and after medication treatment. Statistical analysis indicated that four features corresponding to the first autocorrelation coefficients of the original series of four skeleton parameters and 11 features each corresponding to the first autocorrelation coefficients of the differenced series and the averaged variances of the original series of 11 skeleton parameters significantly decreased after the use of methylphenidate, an ADHD medication. The results revealed that the proposed approach can support physicians as an objective and automatic tool for evaluating the therapeutic effects of medication on patients with ADHD.

Keywords: attention-deficit/hyperactivity disorder; skeleton detection; OpenPose; variance; autocorrelation coefficients (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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