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Combining functional near-infrared spectroscopy and EEG measurements for the diagnosis of attention-deficit hyperactivity disorder

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Abstract

Recently multimodal neuroimaging which combines signals from different brain modalities has started to be considered as a potential to improve the accuracy of diagnosis. The current study aimed to explore a new method for discriminating attention-deficit hyperactivity disorder (ADHD) patients and control group by means of simultaneous measurement of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Twenty-three pre-medicated combined type ADHD children and 21 healthy children were included in the study. Nonlinear brain dynamics of subjects were obtained from EEG signal using Higuchi fractal dimensions and Lempel–Ziv complexity, latency and amplitude values of P3 wave obtained from auditory evoked potentials and frontal cortex hemodynamic responses calculated from fNIRS. Lower complexity values, prolonged P3 latency and reduced P3 amplitude values were found in ADHD children. fNIRS indicated that the control subjects exhibited higher right prefrontal activation than ADHD children. Features are analyzed, looking for the best classification accuracy and finally machine learning techniques, namely Support Vector Machines, Naïve Bayes and Multilayer Perception Neural Network, are introduced for EEG signals alone and for combination of fNIRS and EEG signals. Naive Bayes provided the best classification with an accuracy rate of 79.54% and 93.18%, using EEG and EEG-fNIRS systems, respectively. Our findings demonstrate that utilization of information by combining features obtained from fNIRS and EEG improves the classification accuracy. As a conclusion, our method has indicated that EEG-fNIRS multimodal neuroimaging is a promising method for ADHD objective diagnosis.

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Acknowledgements

This study was supported by the TUBITAK under Project Number 114S47.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Engineering Faculty, Erciyes University, 38039, Kayseri, Turkey

    Ayşegül Güven, Miray Altınkaynak & Turgay Batbat

  2. Department of Physiology, Medical Faculty, Başkent University, 06790, Ankara, Turkey

    Nazan Dolu

  3. Electrical and Computer Engineering Department, Villanova University, Villanova, 19085, USA

    Meltem İzzetoğlu

  4. Department of Physiology, Medical Faculty, Altınbaş University, 34218, Istanbul, Turkey

    Ferhat Pektaş

  5. Department of Child and Adolescent Psychiatry, Medical Faculty, Erciyes University, 38039, Kayseri, Turkey

    Sevgi Özmen & Esra Demirci

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  1. Ayşegül Güven
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  2. Miray Altınkaynak
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Güven, A., Altınkaynak, M., Dolu, N. et al. Combining functional near-infrared spectroscopy and EEG measurements for the diagnosis of attention-deficit hyperactivity disorder. Neural Comput & Applic 32, 8367–8380 (2020). https://doi.org/10.1007/s00521-019-04294-7

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