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.
Highlights
We evaluated the therapeutic effect of Attention-deficit/hyperactivity disorder (ADHD) medication and analyzed the movements of patients with ADHD by using the OpenPose system
ADHD diagnosis was made according to the Diagnostic and Statistical
Skeletons, wewe found fourfour feafeatures corresponding to the first autocorrelation coefficients of the original series of tures tures corresponding corresponding to to the the first first autocorrelation autocorrelation coefficients coefficients of of the the original original series series of of four four four skeleton parameters; 11 features each corresponding to the first autocorskeleton parameters; each to autocorrelation skeleton parameters; 11 features features each corresponding corresponding to the the first first autocorrelation relation coefficients of the differenced series and the averaged variances of the original coefficients of series the variances series of coefficients of the the differenced differenced series and and the averaged averaged variances of of the the original original series of 11 series of 11 skeleton demonstrated parameters demonstrated significant
Summary
Attention-deficit/hyperactivity disorder (ADHD) is a common neuropsychiatric disorder; it affects 3–5% of children worldwide [1]. The long-term impact of attentional and hyperactivity problems may lead to difficulties in several dimensions, including conduct disorders, peer relationship difficulties, educational problems and underachievement, employment problems, a lack of involvement in social activities, suicidal behaviors, and criminality [2,3,4,5,6,7,8]. ADHD may affect the patients’ functionality in childhood but may cause social and educational impairments later in life. Early diagnosis and treatment of ADHD is crucial [9].
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