ArticleInternational journal of environmental research and public health2021
Evaluating Therapeutic Effects of ADHD Medication Objectively by Movement Quantification with a Video-Based Skeleton Analysis.
Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- ADHD identification from real-life recorded video.Scientific reports · 2026Article
- Objective and automatic assessment approach for diagnosing attention-deficit/hyperactivity disorder based on skeleton detection and classification analysis in outpatient videos.Child and adolescent psychiatry and mental health · 2024Article
- Clinical reliability and validity of a video-based markerless gait evaluation method.Frontiers in pediatrics · 2023Article
- Adjuvant Therapy for Attention in Children with ADHD Using Game-Type Digital Therapy.International journal of environmental research and public health · 2022Article
- Automatic Personality Assessment through Movement Analysis.Sensors (Basel, Switzerland) · 2022Article
- Design of a Diagnostic System for Patient Recovery Based on Deep Learning Image Processing: For the Prevention of Bedsores and Leg Rehabilitation.Diagnostics (Basel, Switzerland) · 2022Article
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Authors and funding
7 authors.
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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.
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