Optoelectronics method for determining the cobalt involved in symptoms of attention deficit hyperactivity disorder

Tudosie, M; Truta, Elena; Daviţoiu, Ana Maria; Mitu, Ana Mihaela; Bojescu, Alexandra Andrada

doi:10.1109/ecai.2017.8166474

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…The work [30] gesture recognition model allows finding behaviour patterns which are defined by physicians and provides a satisfactory result. The study [31] compared cobalt level in urine sample, result proved that cobalt is not at all responsible for the presence of ADHD disorder. The study [32] uses EEG and wavelet analysis to construct a model which is capable to separate ADHD and non ADHD with 94.74% accuracy.…”

Section: Classification Of Applications Using Feature Selectionmentioning

confidence: 93%

Classification of Attention Deficit Hyperactivity Disorder (ADHD) Considering Diagnosis and Treatment

Sumathi¹,

Cholli²,

Nayak³

2019

IJMECS

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Attention Deficit Hyperactivity Disorder (ADHD) is the most frequent brain disorders in children. Brain is the greatest complicated data processing part in human body. ADHD can begin in childhood age and may extend till adolescent too. ADHD patients activities/actions/behaviour are totally different from non ADHD patients. To solve the problem in early stage is more precious contribution for children life. Otherwise the disorder may cause further destruction in child brain. An activity of ADHD child is: carelessness, impulsive, and feverish. These activities may be common in other children too but for ADHD patients these activities are more severe and more often occurs. ADHD can arise problems at school, home, it may affect children learning ability, and child may not join with others. ADHD is one among many childhood syndromes. The paper summarises the different ADHD diagnosis methods and suggested treatments for the disorder.

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Section: Classification Of Applications Using Feature Selectionmentioning

confidence: 93%