Ethem GELİR, Erhan KIZILTAN, Fürüzan KÖKTÜRK, Çağatay BARUT

Advanced analysis of finger-tapping performance: A preliminary study

Background: The finger-tapping test is a commonly employed quantitative assessment tool used to measure motor performance in the upper extremities. This task is a complex motion that is affected by external stimuli, mood and health status. The complexity of this task is difficult to explain with a single average intertap-interval value (time difference between successive tappings) which only provides general information and neglects the temporal effects of the aforementioned factors. Aims: This study evaluated the time course of average intertap-interval values and the patterns of variation in both the right and left hands of righthanded subjects using a computer-based finger-tapping system. Study Design: Cross sectional study. Methods: Thirty eight male individuals aged between 20 and 28 years (Mean±SD = 22.24±1.65) participated in the study. Participants were asked to perform single-finger-tapping test for 10 seconds of test period. Only the results of right-handed (RH) 35 participants were considered in this study. The test records the time of tapping and saves data as the time difference between successive tappings for further analysis. The average number of tappings and the temporal fluctuation patterns of the intertap-intervals were calculated and compared. The variations in the intertap-interval were evaluated with the best curve fit method. Results: An average tapping speed or tapping rate can reliably be defined for a single-finger tapping test by analysing the graphically presented data of the number of tappings within the test period. However, a different presentation of the same data, namely the intertap-interval values, shows temporal variation as the number of tapping increases. Curve fitting applications indicate that the variation has a biphasic nature. Conclusion: The measures obtained in this study reflect the complex nature of the finger-tapping task and are suggested to provide reliable information regarding hand performance. Moreover, the equation reflects both the variations in and the general patterns associated with the task.

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1. Jobbágy A, Harcos P, Karoly R, Fazekas G. Analysis of finger-tap- ping movement. J Neurosci Methods 2005;141:29-39. [CrossRef]
2. Notermans NC, van Dijk GW, van der Graaf Y, van Gijn J, Wokke JH. Measuring ataxia: quantification based on the standard neurological examination. J Neurol Neurosurg Psychiatry 1994;57:22-6. [CrossRef]
3. Ott BR, Ellias SA, Lannon MC. Quantitative assessment of movement in Alzheimer’s disease. J Geriatr Psychiatry Neurol 1995;8:71-5.
4. Welch LW, Cunningham AT, Eckardt MJ, Martin PR. Fine motor speed deficits in alcoholic Korsakoff’s syndrome. Alcohol Clin Exp Res 1997;21:134-9. [CrossRef]
5. Heller A, Wade DT, Wood VA, Sunderland A, Hewer RL, Ward E. Arm function after stroke: measurement and recovery over the first three months. J Neurol Neurosurg Psychiatry 1987;50:714-9. [CrossRef]
6. Giovannoni G, van Schalkwyk J, Fritz VU, Lees AJ. Bradykinesia akinesia in co-ordination test (BRAIN TEST): an objective com- puterised assessment of upper limb motor function. J Neurol Neurosurg Psychiatry 1999;67:624-9. [CrossRef]
7. Couins MS, Corrow C, Finn M, Salome JD. Temporal measures of human finger tapping: effects of age. Pharmacol Biochem Behav 1998;59:445-9. [CrossRef]
8. Aoki T, Kinoshita H. Temporal and force characteristics of fast double-finger, single-finger and hand tapping. Ergonomics 2001;44:368-83. [CrossRef]
9. Nalcaci E, Kalaycioglu C, Cicek M, Genc Y. The relationship between handedness and fine motor performance. Cortex 2001;37:493-500. [CrossRef]
10. Jancke L, Schlaug G, Steinmetz H. Hand skill asymmetry in professional musicians. Brain Cogn 1997;34:424-32. [CrossRef]
11. Rehman AJ. Hanbook of Human Performance Measures and Crew Requirements for Flightdeck Research. Atlantic City: US Deparment of Transportation, Federal Aviation Administration; 1995.
12. Dolbec J, Mergler D, Sousa Passos C-J, Sousa de Morais S, Lebel J. Methylmercury exposure affects motor performance of a riverine population of the TapajoÂ s river, Brazilian Amazon. Int Arch Occup Environ Health 2000;73:195-203. [CrossRef]
13. Bowler RM, Gysens S, Diamond E, Nakagawa S, Drezgic M, Roels HA. Manganese exposure: Neuropsychological and neurological symptoms and effects in welders. NeuroToxicology 2006;27: 315-26. [CrossRef] Barut et al. Analysis of Finger Tapping Performance
14. Bowler RM, Roels HA, Nakagawa S, Drezgic M, Diamond E, Park R, et al. Dose-effect relations between manganese exposure and neurological, neuropsychological and pulmonary function in confined space bridge welders. Occup Environ Med 2007;64:167-77. [CrossRef]
15. Daniell WE, Claypoole KH, Checkoway H, Smith-Weller T, Dager SR, Townes BD, et al. Neuropsychological function in retired workers with previous long-term occupational exposure to solvents. Occup Environ Med 1999;56:93-105. [CrossRef]
16. Bowler RM, Gysens S, Hartney C. Neuropsychological effects of ethylene dichloride exposure. Neurotoxicology 2003;24:553-62. [CrossRef]
17. Bowler RM, Gysens S, Diamond E, Booty A, Hartney C, Roels HA. Neurophysiological sequelae of exposure to welding fumes in a group of occupationally exposed man. Int J Hyg Environ Health 2003;206:517-29. [CrossRef]
18. Bowler RM, Lezak M, Booty A, Hartney C, Mergler D, Levin J, et al. Neuropsychological dysfunction, mood disturbance, and emotional status of munitions workers. Appl Neuropsychol 2001;8:74-90. [CrossRef]
19. Akila R, Stollery BT, Riihimaki V. Decrements in cognitive perfor- mance in metal inert gas welders exposed to aluminium. Occup Environ Med 1999;56:632-9. [CrossRef]
20. Godderisa L, Braeckmanb L, Vanhoorneb M, Viaenea M. Neurobehavioral and clinical effects in workers exposed to CS2. Int J Hyg Environ Health 2006;209:139-50. [CrossRef]
21. Kızıltan E, Barut Ç, Gelir E. A high-precision, low cost system for evaluating finger-tapping tasks. Int J Neurosci 2006;116:1471-80. [CrossRef]
22. Kızıltan E, Barut Ç, Gelir E. Parmak vuru performansını değerlendirmek için hassas ve düşük maliyetli bir sistem. 12. Ulusal Ergonomi Kongresi Bildiriler Kitabı, 16-18 Kasım 2006; Ankara. Ankara: Gazi Üniversitesi; 2006. s. 14-18.
23. Brown SG, Roy EA, Rohr LE, Bryden PJ. Using hand performance measures to predict handedness. Laterality 2006;11:1-14. [CrossRef]
24. Meyer A, Sagvolden T. Fine motor skills in South African children with symptoms of ADHA: influence of subtype, gender, age, and hand dominance. Behav Brain Funct 2006;2:33. [CrossRef]
25. Kauranen K, Vuotikka P, Hakala M. Motor performance of the hand in patients with rheumatoid arthritis. Ann Rheum Dis 2000;59:812-6. [CrossRef]
26. Aoki T, Furuya S, Kinoshita H. Finger-Tapping ability in male and female pianists and nonmusician controls. Motor Control 2005;9:23-39.