Relationship between reaction time and speed of movement among different age group of teen age school going children
Author[s]: Habib SK and Ashoke Kumar Biswas
Abstract: Reaction time denotes the elapsed time between the presentation of a stimulus and the subsequent behavioural response. “Reaction time is the period from the stimulus to beginning of the over response”. In other words “time from the stimulus to the beginning of movement”. Reaction time is the elapses from the occurrence of the stimulus of the to act to the beginning of the muscle movement.
Method: The study was from the Patha Bhavana of Visva-Bharati University. A total 40 students were selected from different teen age group as subject. 40 subjects were divided into two group each group i.e. one group was 13-15 years and other group was 16-18 years. Again this group has further divided into two groups, one groups is Boys and another groups is Girls.
Criterion measure: Reaction time measured by Nelson Foot Reaction Time and Speed of movement measured by Nelson Hand Reaction Time, those subjects were measured in seconds with the help of Stick drop test.
Statistics: Mean, Standard Deviation and Correlation Coefficient were used. Level of Significance was set at 0.05.
Result: The mean, Standard deviation and correlation coefficient of Reaction time and Speed of movement of 13-15 years Boys 0.190±0.005, 0.193±0.007 and r value 0.2622. And Girls 0.202±0.005, 0.202±0.008 and r value 0.812 seconds respectively. While mean, Standard deviation and correlation coefficient of Reaction time and Speed of movement of 16-18 years Boys 0.189±0.005, 0.188±0.006 and r value 0.977. And Girls 0.205±0.005, 0.204±0.003 and r value 0.604 seconds respectively.
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Habib SK, Ashoke Kumar Biswas. Relationship between reaction time and speed of movement among different age group of teen age school going children. Int J Phys Educ Sports Health 2017;4[5]:93-95.
Address for reprint requests and other correspondence: E. Christou, Dept. of Applied Physiology and Kinesiology, Univ. of Florida, Room 100, Florida Gym Stadium RD, Gainesville, FL 32611-8205 [e-mail: ude.lfu@uotsirhcae].
Received 2018 May 15; Revised 2018 Jun 22; Accepted 2018 Jun 26.
Copyright © 2018 the American Physiological Society
Abstract
Reaction time [RT] is the time interval between the appearance of a stimulus and initiation of a motor response. Within RT, two processes occur, selection of motor goals and motor planning. An unresolved question is whether perturbation to the motor planning component of RT slows the response and alters the voluntary activation of muscle. The purpose of this study was to determine how the modulation of muscle activity during an RT response changes with motor plan perturbation. Twenty-four young adults [20.5 ±1.1 yr, 13 women] performed 15 trials of an isometric RT task with ankle dorsiflexion using a sinusoidal anticipatory strategy [10–20% maximum voluntary contraction]. We compared the processing part of the RT and modulation of muscle activity from 10 to 60 Hz of the tibialis anterior [primary agonist] when the stimulus appeared at the trough or at the peak of the sinusoidal task. We found that RT [P = 0.003] was longer when the stimulus occurred at the peak compared with the trough. During the time of the reaction, the electromyography [EMG] power from 10 to 35 Hz was less at the peak than the trough [P = 0.019], whereas the EMG power from 35 to 60 Hz was similar between the peak and trough [P = 0.92]. These results suggest that perturbation to motor planning lengthens the processing part of RT and alters the voluntary activation of the muscle by decreasing the relative amount of power from 10 to 35 Hz.
NEW & NOTEWORTHY We aimed to determine whether perturbation to motor planning would alter the speed and muscle activity of the response. We compared trials when a stimulus appeared at the peak or trough of an oscillatory reaction time task. When the stimulus occurred at the trough, participants responded faster, with greater force, and less EMG power from 10-35 Hz. We provide evidence that motor planning perturbation slows the response and alters the voluntary activity of the muscle.
Keywords: electromyography, motor neuron pool modulation, reaction time
INTRODUCTION
Reaction time [RT] is the short time interval between the appearance of a stimulus and initiation of a motor response. The present belief is that within this time two important processes take place, namely selection of motor goals [perception of what needs to be achieved] and motor planning [how it needs to be achieved] [Wong et al. 2015]. Although challenging any of these two processes can lengthen RT, most studies have challenged the perceptual process. An important but unresolved question is whether challenging the motor planning process slows the response and alters the voluntary drive to the muscle. Here, we determine how the modulation of muscle activity, a proxy of the voluntary muscle activation [Brown 2000; Neto and Christou 2010; Salenius et al. 1997], changes with motor plan perturbation. To accomplish this, we use a RT task in which subjects anticipate a visual stimulus while exerting a sinusoidal force task. We compare RT and modulation of muscle activity when the stimulus appears at the trough or at the peak of the sinusoidal task. We hypothesize that, when the stimulus occurs at the peak of the sinusoid, it will perturb motor planning [anticipatory motor plan is incompatible with the response] and induce a longer RT and an altered modulation of muscle activity.
RT tasks are common experimental paradigms to understand changes in cognitive processing. A common manipulation to lengthen the RT is to challenge the perceptual process of the task [Wong et al. 2015]. Previous paradigms include choice RT tasks [Hyman 1953; Schmidt et al. 1988; Smith 1968; Woods et al. 2015], stimuli selection based on saliency [Theeuwes et al. 1998], and performance of two or more tasks concurrently [dual tasking; Bekkering et al. 1994]. To date, it remains unclear how challenging the motor planning process would affect the RT and muscle activity.
In this study, we are focusing on challenging the motor planning component of the RT. In anticipation of the visual stimulus, participants performed a sinusoidal force. Although the stimulus can occur at any point of the sinusoidal force, it is compatible with the response requirements when the stimulus appears at the trough. When it appears at the trough, the anticipation motor plan and response require a force increase. In contrast, when the stimulus occurs at the peak, the anticipation motor plan and response are incompatible because the anticipation motor plan is to decrease force, whereas the response requires an increase in force. Thus we expect that, when the stimulus occurs at the peak of the sinusoidal force, the RT will be longer.
Changes to the voluntary muscle activity in response to challenging the motor planning process remain largely unknown. Previous studies have used the modulation of whole muscle activity as a proxy to understand the voluntary activation of muscle [Brown 2000; Neto and Christou 2010; Salenius et al. 1997]. There is evidence that greater modulation of the interference electromyography [EMG] from 10 to 60 Hz is associated with increased voluntary drive [Neto and Christou 2010]. For example, a voluntary increase in force from 15 to 50% maximum increased the interference EMG power from 10 to 60 Hz but not the power from 60 to 300 Hz [Neto and Christou 2010]. Thus greater modulation of 10–60 Hz in the surface EMG is related to a voluntary excitation of the spinal motor neuron pool from higher centers to achieve a stronger contraction. The power from 10 to 35 Hz, termed beta band [Berger 1930], is associated with steadier movements and often referred to as the antikinetic band [Engel and Fries 2010]. In contrast, the power from 35 to 60 Hz, termed gamma band [Berger 1930], has been associated with movement initiation [Baker et al. 1999; Conway et al. 1995; Halliday et al. 1998; Kilner et al. 2000; Omlor et al. 2007]. Therefore, we expect the voluntary muscle activation for a faster RT to attenuate power in the beta band and increase power in the gamma band.
In this study, we examined whether perturbing the motor plan lengthens the processing time and alters the voluntary muscle activation. To achieve this, we compared trials where the stimulus appeared at the peak or trough of a sinusoidal task. We examined processing time with the length of the premotor component of RT [Botwinick and Thompson 1966; Schmidt et al. 1988] and voluntary drive with the modulation of muscle activity [Brown 2000; Neto and Christou 2010; Salenius et al. 1997] during the RT task. We hypothesized that stimulus appearance at the peak [incompatible intention and response requirements] compared with the trough would result in a longer processing time and an altered modulation of the muscle by decreasing power from 10 to 35 Hz and increasing power from 35 to 60 Hz.
METHODS
Participants
Twenty-four young adults [20.5 ± 1.1, 13 women] volunteered to participate in this study. All participants reported being healthy without any known neurological or orthopedic disorders. On average, participants had a body mass index of 22.5 ± 2.4 and a Montreal Cognitive Assessment score of 28.1 ± 1.4 [Nasreddine et al. 2005]. All participants were right handed and right footed as assessed with the Edinburgh Handedness Inventory [Oldfield 1971] and the Waterloo Footedness Questionnaire [Elias and Bryden 1998], respectively. The Institutional Review Board at the University of Florida approved the procedures, and participants signed a written, informed consent before participating in the study.
Experimental Approach
Participants performed one testing session that lasted ~1 h. This session involved performing a sinusoidal anticipatory RT task. Participants performed the following: 1] familiarization of the experimental procedure that included a verbal explanation and practice trials of the RT task, 2] maximum voluntary contraction [MVC] task with ankle dorsiflexion, 3] 15 trials of the RT task, and 4] repetition of the MVC task.
Experimental Arrangement
Experimental setup and apparatus.
Each participant sat comfortably in an upright position and faced a 32-inch monitor [SyncMasterTM 320MP-2; Samsung Electronics America, Ridgefield Park, NJ] that was located 1.25 m away at eye level. The monitor displayed the targeted force, the force produced by ankle dorsiflexion, and the stimulus using a custom-written program in Matlab [MathWorks, Natick, MA]. All participants affirmed that they could see the display clearly. Participants flexed the left hip joint to ∼90°, abducted by ∼10°, and flexed the knee to ∼90°. The left foot rested on a customized foot device with an adjustable footplate and secured by straps over the metatarsals to ensure a secure position and an isolated dorsiflexion of the ankle [Fig. 1A]. The initial ankle position was ∼90° of ankle dorsiflexion. All participants performed the RT tasks with their nondominant foot [i.e., the left] to introduce greater novelty to the task [Sainburg 2002].
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Fig. 1.
A: schematic drawing of the experimental set up and arrangement of the left foot for 1 participant. The left foot was placed and rested on a customized foot device with an adjustable footplate and secured by a strap over the metatarsals. Participants performed a sinusoidal reaction time task with ankle dorsiflexion. B: representation for 1 participant of the reaction time task at 3 different time points. Participants were presented with unanticipated visual stimulus in the middle of the screen while performing a sinusoidal isometric force-tracking task. This stimulus appeared with illumination of a green background. Participants were asked to respond to the stimulus as quickly as possible by dorsiflexing the ankle with adequate force to show the reaction clearly. The duration of the task was 37 s. Left: anticipatory strategy [type of force control before the stimulus]. Middle: moment when the stimulus first occurs. Right: reaction of the participant.
Force measurements.
We quantified the force exerted during the MVC and RT task with a force transducer [model MB-100; Interface, Scottsdale, AZ] placed in parallel with the direction on the customized foot device. This allowed us to analyze the ankle dorsiflexion force vector that was perpendicular to the transducer. The ankle force signals were amplified 100 times [Bridge-8; World Precision Instruments, Sarasota, FL], sampled at 1,000 Hz with a Power 1401 A/D card and a NI-DAQ card [model USB6210; National Instruments, Austin, TX], and stored on a personal computer.
EMG measurements.
To identify the onset of muscle activity during the RT task, we recorded the muscle activity of the primary ankle dorsiflexor [tibialis anterior, TA] with surface EMG [Bagnoli EMG system; Delsys, Boston, MA]. We placed the recording electrodes on the skin and in line with the muscle fibers of the TA at the proximal third between the head of the fibula and the medial malleolus to avoid the innervation zone of the muscle [Corti et al. 2015]. We placed the reference electrode over the patella. The EMG signals were amplified 1,000 times, sampled at 1,000 Hz with a Power 1401 A/D card and a NI-DAQ card, and stored on a personal computer.
MVC task.
We identified the MVC for ankle dorsiflexion force before and after the RT tasks. Participants increased their ankle dorsiflexion force to their maximum and maintained it for 3 s. Participants exerted three to five MVCs until two MVC values were within 5% of each other. There was 1 min of rest between trials to minimize fatigue. We repeated the MVC task at the end of the experiment to assess whether the experimental task induced fatigue.
RT task.
The RT task consisted of a sinusoidal anticipatory force control [~15 s] before a reaction to an unanticipated visual stimulus. We instructed participants to increase and decrease their ankle dorsiflexion force within a target area [15 ± 5% MVC] at their own preferred frequency and amplitude. We displayed the target area as two red horizontal lines over a white background in the middle of the monitor and the force produced by the participant as a blue line progressing with time from left to right [Fig. 1B] at a rate of 0.02 m/s. We kept the visual gain constant at 1.2° [visual angle] [Vaillancourt et al. 2006].
The visual stimulus consisted of a transient change in background color, from white to green, that lasted for 1 s [Fig. 1B]. We instructed the participants to respond to the stimulus as quickly as possible by increasing their ankle dorsiflexion with sufficient force to show the reaction clearly. Each trial lasted 37 s, comprised of the following phases: 1] 4 s of rest, 2] 1.5 s of a ramp to increase force to the target, 3] 3 s of maintaining a constant force of 15% MVC, 4] 20 s of exerting a sinusoidal force task, 5] 3 s of maintaining a constant force of 15% MVC, 6] 1.5 s of a ramp to decrease force to resting levels, and 7] 4 s of rest [Fig. 1B]. Participants performed 15 trials for each condition. For 12 out of the 15 trials, we randomly presented the stimulus between 22 and 25 s. For the other three trials, the stimulus was presented at 13.5 s. We did this to prevent participants from predicting an occurrence of the stimulus around the 22-s mark.
Data Analysis
We recorded the force and EMG signals analyzed using a custom-written program in Matlab. In the analysis, we included only the 12 trials that occurred from 22 to 25 s. Before data analysis, the program low-pass filtered the raw force signal at 20 Hz with a fourth-order [bidirectional] Butterworth filter and detrended. Detrending the force signal removed the linear trend from the data and eliminated any drift. We identified force onset as the first time point in which the force exceeded 2 SD of the mean force around the stimulus onset [200 ms before stimulus and 100 ms after stimulus; Fig. 2]. Moreover, the EMG signals were detrended, rectified, and low-pass filtered at 6 Hz. We used this processing to identify the onset of EMG associated with the reaction to the stimulus. We identified EMG onset as the first time point in which the low-pass filtered EMG was >2 SD of the mean EMG around the stimulus onset [200 ms before stimulus and 100 ms after stimulus; Fig. 2, dashed box]. We identified EMG end as the first time point in which the low-pass filtered EMG was