Finger-Tapping Test

Ward, Tracey; Bernier, Raphael; Mukerji, Cora; McPartland, James C.; Johnson, Ellen; Nevers, Maureen; Frazier, Thomas; Howlin, Patricia; Savage, Sarah; Zane, Thomas; Lanner, Traci; Myers, Michelle; VanBergeijk, Ernst; Huestis, Samantha; Doehring, Peter; Voorst, Guus; Macy, Kelly; Kwon, Jennifer M.; McNulty, Edward; Chapman, S. Michael; Crowley, Michael J.; Bean, Allison; Scahill, Lawrence David; Wing, Lorna; Catania, A. Charles; Thorne, John; Kini, Usha; Moyle, Maura; Plowgian, Claire; Case-Smith, Jane; Schmitt, Lauren; Lewis, Moira; Weiss, Mary Jane; Gaag, Jan Van der Rutger; Bonazinga, Laura; Paul, Diane R.; Happé, Francesca; Doyle, Carolyn A.; Perri, Kate S.; Moran, Marcel; Stigler, Kimberly A.; McDougle, Christopher J.; Hyman, Susan; John, Margaret St.; Hessl, David; Schneider, Andrea; Katon, Juli; Hurst, Hillary; Bauminger‐Zviely, Nirit; Hadjikhani, Nouchine; Rinehart, Nicole; Enticott, Peter G.; Bradshaw, John L.; Molteni, John; Palmieri, Mark; Prelock, Patricia; Müller, Ralph‐Axel; LaRue, Robert; Egan, Shaunessy; Hendricks, Dawn; Holman, Katherin C.; D’Eramo, Kristen; Faja, Susan; Perszyk, Danielle

doi:10.1007/978-1-4419-1698-3_343

Cited by 2 publications

(2 citation statements)

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“…With the development of technology, some methods can be simplified and easily used on conventional devices like personal computer or mobile phone. One such method is -FTT [22]. Of course, they give a fairly large error [23], but due to the fact that they are mobile, it is possible to collect a lot of data, which makes it possible to use machine learning models for various problems [24].…”

Section: Literature Analysismentioning

confidence: 99%

Modeling of Psychomotor Reactions of a Person Based on Modification of the Tapping Test

Mochurad¹,

Hladun²

2021

IJC

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The paper considers the method for analysis of a psychophysical state of a person on psychomotor indicators – finger tapping test. The app for mobile phone that generalizes the classic tapping test is developed for experiments. Developed tool allows collecting samples and analyzing them like individual experiments and like dataset as a whole. The data based on statistical methods and optimization of hyperparameters is investigated for anomalies, and an algorithm for reducing their number is developed. The machine learning model is used to predict different features of the dataset. These experiments demonstrate the data structure obtained using finger tapping test. As a result, we gained knowledge of how to conduct experiments for better generalization of the model in future. A method for removing anomalies is developed and it can be used in further research to increase an accuracy of the model. Developed model is a multilayer recurrent neural network that works well with the classification of time series. Error of model learning on a synthetic dataset is 1.5% and on a real data from similar distribution is 5%.

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Section: Literature Analysismentioning

confidence: 99%

Modeling of Psychomotor Reactions of a Person Based on Modification of the Tapping Test

Mochurad¹,

Hladun²

2021

IJC

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“…One way to determine such deficits is through the use of motor performance tests such as the Finger Tapping Test (FTT). This test belongs to a group of neuropsychological tests measuring motor functioning, specifically motor speed and hand coordination (Ward et al, 2013). The low performance on this test can indicate some clinical conditions such as brain injury, neurodegenerative diseases, neurodevelopmental disorders etc.. For example, children with conditions such as Attention Deficit Hyperactivity often fail to meet age-appropriate norms for motor control and timed repetitive movements (Gilbert, Isaacs, Augusta, Macneil, & Mostofsky, 2011).…”

Section: Introductionmentioning

confidence: 99%

The Effects of Age and Gender on Finger Tapping Speed in Preschool Children

Memišević¹,

Mahmutović²,

Pasalic³

et al. 2017

Acta Neuropsychologica

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Background: The assessment of children’s motor control is very important in detecting potential motor deficits. The Finger Tapping Test (FTT) is a widely used test in various clinical and non-clinical populations. FTT is a neuropsychological test designed to measure motor control. Age and gender are significant pre - dictors of finger tapping speed in school-aged children. The goal of the present study was to determine the effects of age and gender on finger tapping speed in preschool children. Material/Methods: The sample for this study included 111 preschool children, aged 3 to 6 years (mean age- 4.6; SD- 0.9), of both genders (59 boys, 52 girls). As a measure of finger tapping speed we used the Finger Tapping Test from the Psychology Experi -ment Building Language (PEBL). Results: The results of this study found a significant effect of age on finger tapping speed. Contrary to the existing studies, there was no gender effect on the tapping speed in preschoolers. A one way analysis of variance showed that older children performed significantly better than younger children Conclusions:There is a linear trend of improved performance on FTT with an increasing age. The child’s gender was not a significant predictor of FTT for preschool children. Motor control and speed can be improved through exercise.

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Finger-Tapping Test

Cited by 2 publications

References 0 publications

Modeling of Psychomotor Reactions of a Person Based on Modification of the Tapping Test

Modeling of Psychomotor Reactions of a Person Based on Modification of the Tapping Test

The Effects of Age and Gender on Finger Tapping Speed in Preschool Children

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