ArticleScientific data2024
Dataset of Smartphone-Based Finger Tapping Test.
Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Distinct finger-tapping feature in progressive supranuclear palsy correlates with motor function and brain atrophy.NPJ Parkinson's disease · 2026Article
- Upper extremity motor improvement after carotid endarterectomy associated with postoperative recovery in cerebral perfusion and cortical neurotransmitter receptor function.Neurosurgical review · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The finger tapping test (FTT) is a neuropsychological test that measures motor speed and coordination. It involves tapping a designated surface with a specific finger as quickly as possible for a certain duration. Touchscreen of smartphones has been used as interface to record the tap, what enables to extract information about the taps. The present study represents an initiative of construction for a national Database of Smartphone-Based FTT, which includes data from 176 healthy male and female adults ranging in age from 18 to 74 years. Participants were asked to perform the FTT using one or both hands, tapping on a central area of a smartphone as many times as possible within a 30-second interval. Data were extracted using an Android application, encompassing details such as touch timing, spatial coordinates, sex, smartphone model, hand used, and age. A Python-developed web visualization tool for individual and averaged analysis. This database serves as informative foundation for a healthy adult sample and supports further exploration and international comparative analyses of FTT performance.
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Registered trials
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