Advanced analysis of finger-tapping performance: A preliminary study

Abstract

The finger-tapping (FT) test has been used for almost a century to evaluate muscle control and motor ability in the upper extremities (1). This task is frequently used to quantitatively evaluate patients with Parkinson's disease (1), ataxia (2), Alzheimer's disease (3), and Korsakoff syndrome (4), as well as in individuals who have suffered an acute stroke (5). Moreover, the finger-tapping test is widely used to evaluate motor function in the upper limbs (6-8) and the relationship between hand preference and hand skill (9) in healthy individuals and to assess hand skill and coordination (10-12) for occupations in which the hands are essential. The finger-tapping test is also used for psychomotor evaluations (13)(14)(15)(16)(17)(18)(19)(20).The movement involved in single-finger tapping is complex and is affected by visual and auditory stimuli, emotional and physical health, and factors that impact the skeletal and nervous systems. The characterisation of finger-tapping by an average tapping interval or by a tapping rate can only provide a limited amount of information. However, constructing a mathematical function that has the best fit to a series of data points obtained for a complex movement possibly helps to understand the nature of the movement.Various techniques have been used to record the number of tappings in a certain test period and the average time passed between tappings (intertap-interval) in the fingertapping test, including a mechanical counter, an electronic switch, a telegraph key, and a computer keyboard associated with word processing software (7,8). However, the time resolution of these systems is either low or unpredictable. The ability of a system to determine only an average intertap-interval or a tapping speed for a complicated movement results in poor time resolution and carries no information on the time course of the movement. Previous studies on this topic have not considered the temporal changes that occur between consecutive tapping. Therefore, the present study evaluated the time course of average intertap-interval values and the patterns of variation in both the right and left hands of right-handed subjects using the TanTong Finger-Tap system (21,22 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.

The Impacts of Central Fatigue on the Polyphasic Nature of Tapping Performance

“…An unexpected performance increase in the last period (PERIOD-3) of MVRM is consistent with the earlier studies (15)(16)(17) where it was named as "Late adaptation pahase", "Super effort period" and "Ha gayret phenomenon" in (Figure 2). The latter stands for "win or die" circumstances and emphasizes on the impact of internal motivation that may smartly modulates the performance in unexpected situations (Limbic System in Figure 1).…”

“…This period of MVRM was defined as "early adaptation phase" (15), "early stage of learning" or "cognitive stage" (18) in the literature ( Figure 2). As the names imply this period consists of environmental adaptation, development of schema with practice and integration of sensory information.…”

“…MVRM for index finger was conducted using the digital FT task test system (15,16,24). The system records Inter Tap Intervals (ITI), which is the time difference between consecutive taps, in ms resolution by making use of the time-stamp counter of microprocessor and saves data array on the hard drive of a computer for later analysis.…”

“…Our earlier studies (15,16) employing a lower technology method of fingertapping (FT) task test suggest that the performance of maximal voluntary repetitive movements (MVRM) has polyphasic nature and the temporal analysis may reflect the dynamics and/or energetic states of the muscle involved in the movement (Figure 2). It may be hypothesized that under induced fatigue condition the MVRM may also mimic the dynamics of fatigue and therefore, may be used in evaluating the origin of fatigue phenomenon.…”

“…PC6.0 is the time at which anaerobic glycolytic systems' output reaches its maximum. "HGx.x" represents the onset time (x.x) of "Ha gayret phenomenon (adopted after the studies of 13,[15][16][17][18][19].…”