Effects of Aging and Tai Chi on Finger-Pointing Toward Stationary and Moving Visual Targets

Article Outline

• Abstract
• Methods
  • Participants
  • Test Procedures
    • Pointing toward a stationary visual signal
    • Pointing toward a moving visual signal
  • Data Recording and Analysis
  • Statistical Analysis
• Results
  • Subjects
  • Test-Retest Reliability
  • Stationary Visual Signal
  • Moving Visual Signal
• Discussion
  • Effects of Aging
    • Pointing toward a stationary visual signal
    • Pointing toward a moving target
  • Effects of Tai Chi Practice
    • Pointing toward a stationary target
    • Pointing toward a moving visual signal
• Conclusions
• Acknowledgment
• References
• Copyright

Abstract 

Kwok JC, Hui-Chan CW, Tsang WW. Effects of aging and Tai Chi on finger-pointing toward stationary and moving visual targets.

Objective

To examine the aging effect on speed and accuracy in finger pointing toward stationary and moving visual targets between young and older healthy subjects and whether or not Tai Chi practitioners perform better than healthy older controls in these tasks.

Design

Cross-sectional study.

Setting

University-based rehabilitation center.

Participants

University students (n=30) (aged 24.2±3.1y), were compared with healthy older control subjects (n=30) (aged 72.3±7.2y) and experienced (n=31) (mean years of practice, 7.1±6.5y) Tai Chi practitioners (aged 70.3±5.9y).

Interventions

Not applicable.

Main Outcome Measures

Subjects pointed with the index finger of their dominant hand from a fixed starting position on a desk to a visual signal (1.2cm diameter dot) appearing on a display unit, as quickly and as accurately as possible. Outcome measures included (1) reaction time—the time from the appearance of the dot to the onset of the anterior deltoid electromyographic response; (2) movement time—the time from onset of the electromyographic response to touching of the dot; and (3) accuracy—the absolute deviation of the subject's finger-pointing location from center of the dot.

Results

Young subjects achieved significantly faster reaction and movement times with significantly better accuracy than older control subjects in all finger-pointing tasks. Tai Chi practitioners attained significantly better accuracy than older controls in pointing to stationary visual signals appearing contralaterally and centrally to their pointing hand. They also demonstrated significantly better accuracy when the target was moving. Accuracy in Tai Chi practitioners was similar to young controls.

Conclusions

Eye-hand coordination in finger-pointing declines with age in time and accuracy domains. However, Tai Chi practitioners attained significantly better accuracy than control subjects similar in age, sex, and physical activity level.

Key Words: Exercise, Rehabilitation

List of Abbreviations: ADLs, activities of daily living, ANOVA, analysis of variance, ICC, intraclass correlation coefficient, LCD, liquid crystal display, MMSE, Mini-Mental State Examination, UE, upper extremity

EYE-HAND COORDINATION is an important perceptual-motor function facilitating goal-directed movements in daily life, for example, reaching for and manipulating objects.¹ Motor coordination can be defined as “the ability to produce a controlled, accurate and rapid movement.”^2(p108) Its deterioration is a major factor in age-related slowdown.², ³, ⁴ In particular, smooth motor coordination is an important prerequisite for adequate UE performance in many related ADLs.³ Accurate arm movements depend not only on visual input but also on proprioceptive information about the current angles of the head, neck, trunk, and arm joints and their respective muscular work.⁵ In an aging population, more and more older adults suffer from poor UE motor coordination.², ⁶ This can influence the performance of their ADLs requiring UE involvement such as feeding, and consequently make them more dependent in their ADLs.² Whether finger-pointing toward stationary and moving visual stimuli becomes slower and less accurate in older than younger healthy subjects remains unclear.

Research studies have demonstrated that some of the age-related declines in mental function and physical fitness could be alleviated through exercise. More specifically, exercise can help older adults achieve faster reaction times, better movement accuracy, and increased muscle strength.⁷, ⁸ Tai Chi is a popular form of exercise among older adults. It involves a series of slow, smooth, and graceful movements with an emphasis on smooth coordination of eyes, head and body, and upper and lower extremities. Because many Tai Chi forms require the practitioners to focus their eyes on their hand movement by means of head and/or trunk rotation,⁹ a question naturally arose: Did Tai Chi practitioners improve their eye-hand coordination when compared with nonpractitioners similar in age and physical activity level? To answer this question, the objectives of our present study were (1) to examine the effect of aging on performance in a finger-pointing task involving stationary and moving visual signals and (2) to compare the performance of these tasks between experienced Tai Chi practitioners and healthy older control subjects.

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Methods 

Participants 

Thirty young university students (aged 24.2±3.1y) were compared with 30 healthy older control subjects (aged 72.3±7.2y) and 31 experienced (mean, 7.1±6.5y of practice) Tai Chi practitioners (aged 70.3±5.9y) in this cross-sectional study. Students who reported regular exercise were recruited from a local university. Control older subjects were recruited from several community elderly centers. They had to have no previous experience in Tai Chi, although some of them took morning walks or did stretching exercises. For inclusion in the Tai Chi study group, subjects had to have recently practiced Tai Chi more than 1.5h·wk⁻¹ for 3 years or more. All the older subjects underwent 4 screening tests. They had to (1) score at least 24 in the MMSE to show that they had no cognitive impairment,¹⁰ using the Chinese version validated by Chiu et al¹¹; (2) attain 20 out of 20 or above in Snellen's visual acuity test with eyeglasses if necessary¹²; (3) demonstrate sufficient active range of motion in their upper limbs to perform the finger-pointing tasks, which required subjects to flex and extend their shoulder, elbow, wrist, and fingers; and (4) complete a modified Minnesota Leisure Time Physical Activity Questionnaire.¹³, ¹⁴, ¹⁵, ¹⁶

Excluding criteria included (1) any eye pathology such as glaucoma or cataract unless it had been corrected and subjects were able to score at least 20 out of 20 in Snellen's acuity test, (2) cognitive impairments revealed by the MMSE, (3) cardiovascular pathologies such as symptomatic cardiovascular diseases or uncontrolled hypertension, (4) any pathology affecting UE function such as stroke, Parkinson's disease, or any disabling neurologic or musculoskeletal disorder, and (5) peripheral neuropathies of the UE or metastatic cancer. The project was approved by the ethics committee of The Hong Kong Polytechnic University, and written informed consent was obtained from all subjects before the study.

Test Procedures 

Previous investigators¹⁷, ¹⁸ have usually used a stylus pen and required subjects to reach the targets located in a horizontal plane. However in real life, people rely on 3-dimensional eye-hand coordination. Pressing a lift button, reaching for a cup, and punching keys on a phone to make phone calls are a few examples. These finger-pointing tasks involved a vertical display unit. In this study, subjects were instructed to perform a pointing task with the index finger of their dominant hand (the hand used for writing or holding chopsticks) as quickly and as accurately as possible from a fixed starting position on a desk to a visual signal appearing on a vertical display unit.^a The visual display unit was fixed on and perpendicular to the supporting surface, with its upper edge at subject's eye level and 36cm from the supporting surface. At the starting point, the subject's index finger rested on the desktop 10cm from the screen. The visual signal was a black dot 1.2cm in diameter. There were 2 testing protocols involving a stationary and a moving visual signal.

Subjects sat on a height-adjustable nonrotating chair with armrests in front of a computer-controlled LCD touch screen^a with their hands resting on a desk and their elbows, hips, knees, and ankles at approximately 90°. The chair height was adjusted so that the upper edge of the visual display unit was at subject's eye level. A mark was positioned at the center of the upper edge of the display unit, and subjects were asked to fix their eyes on it during the testing. Their upper trunk was strapped to the chair with a hook-and-loop fabric fastener belt to prevent trunk movement. This was because finger pointing could involve either trunk and arm movement or arm movement alone.¹⁹ Because only the electromyographic responses of the arm muscles were recorded, it was necessary to prevent trunk movement so that subjects reached for the visual signal only with their arms. After a preparatory auditory “ding” signal, a visual response signal appeared on the screen with a fixed interval of 2 seconds. To deter anticipatory responses to the preparatory “ding” signal, tests in which no visual response signal appeared after the auditory signal were also administered in a random order. Subjects were instructed to point to and touch the dot as quickly and as accurately as possible. To minimize a possible reduction in subject's attention span, recorded encouragements: “fast and accurate,” were delivered by the computer through a set of headphones in the middle of each set of tests regardless of the subject's actual performance.

Subjects used their index finger to point at a stationary visual signal as quickly and as accurately as possible when it appeared on the LCD screen. The LCD monitor was 34cm wide and 27cm tall. It was divided into 1000 sections from left to right and from top to bottom. The visual signal of each trial appeared at 1 of 5 locations: 100,100 (upper left), 100,900 (upper right), 500,500 (center), 900,100 (lower left) and 900,900 (lower right). There were 10 trials per location. The visual signal appearance was randomized across trials for each subject, but the sequence of appearance was the same for all subjects. The average of the data obtained for each location was used to compare the eye-hand coordination performance among the 3 groups. Each subject had a total of 5 familiarization trials (to each of the 5 locations) before recording of their reaction time, movement time, and endpoint accuracy.

At a fixed delay of 2 seconds after the preparatory auditory signal, a moving visual response signal (the same black dot) appeared from the left side of the LCD screen at a fixed coordinate of 500,100 and moved to the right along the same Y coordinate (500) at 12cm·s⁻¹. Similar to the previous test, trials without the moving visual signal appearing after the preparatory signal were also included here to deter anticipatory response. Subjects were given 2 familiarization trials before the actual testing. Ten trials were recorded in each subject for averaging purposes.

Data Recording and Analysis 

A surface electrode was used to record electromyographic activity in the anterior deltoid muscle (prime mover for arm reaching component)²⁰ of each subject's dominant arm. The electrode was positioned with electrolyte gel and adhesive tape and placed in line with the muscle, as recommended by Cram and Kasman.²¹ Electromyographic signals were recorded using active stainless steel surface electrode^b (interelectrode spacing=1.375in [3.493cm]), amplified with a gain of 320 and a total input impedance of more than 100mΩ over a bandwidth of 12Hz to 3000Hz. These signals were sampled at 1000Hz and digitized using an analog/digital converter card,^c then stored for offline analysis. Electromyographic data were processed using the LabView software suite.^c These signals were full-wave rectified and smoothed using a second-order Butterworth low-pass filter with a cutoff frequency of 10Hz. The onset of electromyographic activity (reaction time) was identified as the time when the electromyographic signal deviated more than 3 standard deviations from the baseline. This was determined by using a custom-made LabView software program^c but was visually verified to avoid possible contamination by artifact signal.

Reaction time, movement time, and endpoint accuracy were compared among the 3 groups. Reaction time was defined as the time from the appearance of the dot on the screen to the onset of the anterior deltoid electromyographic response. Movement time was defined in the present study as the time from the onset of the electromyographic response to touching the dot called “endpoint,” which included the time for muscle torque generation to complete the pointing task. By convention, electromyographic movement time is defined as the interval from the onset to the end of the electromyographic signal. Because older adults showed longer biomechanical delay due to the decrease in muscle size and related neuromuscular functions,³ we included the time for generating the muscle torque required to complete the pointing task for comparison of the movement time among the 3 cohorts in this study. Precision in locating the dot on the LCD screen, termed “endpoint accuracy,” was defined as the absolute deviation of the subject's finger-pointing location from the center of the dot.

Statistical Analysis 

To ensure data repeatability, an ICC was used to assess the test-retest repeatability of the outcome measures in the older adults. One-way ANOVA was used to compare the age, height, and arm length among the 3 groups, and sex was compared using a chi-square test. Because the starting position of the hand with respect to the visual display unit was fixed for all participants, the differences in arm length might constitute a covariate in the finger-pointing task. Arm length was thus treated as a covariate in the statistical analysis if a significant difference was found. Arm length was defined as the distance between a subject's acromion and the tip of the middle finger. To compare between the 2 older adult groups, independent t tests were performed on the MMSE scores, and a chi-square test was used to compare their physical activity levels. For the stationary visual signal, multivariate ANOVA was used to compare each of the outcome measures (reaction time, movement time, and endpoint accuracy) among the 3 groups and the 5 locations. If statistically significant differences were found in the multivariate tests, univariate tests were conducted for each of the locations. Post hoc analysis using Bonferroni adjustment was conducted if a significant difference was found in the univariate test. One-way ANOVA was used to compare reaction time, movement time, and endpoint accuracy among the three groups in the task with a moving visual signal. If a statistically significant difference was found in the 1-way ANOVA, post hoc analysis using Bonferroni adjustment was performed. A significance level (α) of .05 was chosen for statistical comparisons.

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Results 

Subjects 

Eighty older subjects volunteered to participate in this study. Two Tai Chi practitioners were excluded because they had less than 3 years of Tai Chi practice. Among the control subjects, 3 were excluded because of their previous Tai Chi experience; 8 were excluded because they had MMSE scores less than 24, and another 6 subjects were excluded because of their inability to score 20 out of 20 or more in Snellen's acuity test.

Table 1 shows a comparison of age, height, and arm length among the 3 groups. One-way ANOVA showed statistically significant differences between the young subjects and the older adults in age, height, and arm length, with no significant difference between the 2 older adult groups in the post hoc analysis. Because the arm length was significantly different, it was treated as a covariate in the multivariate ANOVA and 1-way ANOVA procedures. Chi-square tests showed no significant difference in gender distribution among the 3 groups. Another chi-square test found no statistically significant difference between the 2 older groups in terms of physical activity level (see table 1). Tai Chi practitioners and older controls were thus similar with respect to age, height, arm length, sex, MMSE scores, and physical activity levels.

Table 1. Comparisons of Age, Height, and Arm Length Among Young Control, Older Control, and Older Tai Chi Subjects and of MMSE and Physical Activity Levels Between the 2 Older Groups

	Young Control Subjects	Older Control Subjects	Tai Chi Subjects
	(n=30)	(n=30)	(n=31)	P
Age (y)	24.2±3.1	72.3±7.2†	70.3±5.9†	<.001⁎
Height (m)	1.67±0.08	1.58±0.08†	1.59±0.07†	<.001⁎
Arm length (cm)	70.5±4.3	65.3±5.8†	67.2±4.3†	<.001⁎
Sex (M/F)	15/15	15/15	15/16	.989
MMSE score	–	26.7±2.0	26.6±1.9	.966
Physical activity level				.364
Light < 4 METs	–	n=15	n=10
Moderate 4-5.5 METs	–	n=11	n=16
Heavy > 5.5 METs	–	n=4	n= 5

NOTE. Values are mean ± SD.

Abbreviation: MET, metabolic equivalent.

Test-Retest Reliability 

To test for data repeatability, 6 men (3 Tai Chi subjects) and 14 women (9 Tai Chi subjects) with a mean age of 69.2±7.1 years of the 61 older participants returned to the laboratory 1 week after the first finger-pointing trials for a second assessment. Table 2 shows that ICC values for reaction time, movement time, and endpoint accuracy ranged from .68 to .97, thus showing moderate to very good data repeatability for finger-pointing toward both stationary and moving visual signals.

Table 2. ICC for Each Response Variable in Replicate Tests (n=20).

	Finger-Pointing Toward a Stationary Visual Signal		Finger-Pointing Toward a Moving Visual Signal
	ICC⁎	95% CI	ICC	95% CI
Anterior deltoid electromyographic response
Reaction time	.70	.55–.80	.85	.63–.94
Movement time	.68	.52–.78	.89	.73–.96
Endpoint accuracy	.71	.57–.81	.97	.93–.99

NOTE. Values are mean ± SD.

Abbreviation: CI, confidence interval.

Stationary Visual Signal 

Table 3 shows that young university students achieved significantly faster reaction and movement times, with significantly greater endpoint accuracy than older controls. Although Tai Chi practitioners tended to have faster reaction and movement times than older controls, the difference was not statistically significant. Tai Chi practitioners did, however, show significantly better endpoint accuracy than older controls when the signal appeared contralaterally and centrally in their visual field: in the upper left, center, and lower left locations. Of special interest is that their endpoint accuracy was similar to that of the young subjects (see table 3).

Table 3. Comparison of Anterior Deltoid Reaction Time and Movement Time as Well as Endpoint Accuracy Among Young Control, Older Control, and Older Tai Chi Subjects in Finger-Pointing Toward a Stationary Target at 5 Spatial Locations

	Young Control Subjects	Older Control Subjects	Tai Chi Subjects
	(n=30)	(n=30)	(n=31)	P
Electromyographic reaction time (ms)
Upper left	304.8±46.4	377.0±85.9†	374.9±94.2†	.001⁎
Upper right	309.3±51.9	374.2±69.5†	356.0±72.9†	.001⁎
Center	289.6±45.6	322.2±58.5†	306.0±43.8	.046⁎
Lower left	294.6±40.2	380.7±93.6†	343.7±71.2†	<.001⁎
Lower right	307.1±48.5	349.2±69.8†	330.1±56.8	.027⁎
Electromyographic movement time (ms)
Upper left	669.1±147.2	876.3±186.5†	844.9±139.2†	<.001⁎
Upper right	597.0±122.7	806.1±217.6†	790.4±141.5†	<.001⁎
Center	583.2±118.9	768.7±178.3†	762.3±147.9†	<.001⁎
Lower left	625.7±127.6	822.1±195.5†	784.0±142.9†	<.001⁎
Lower right	524.5±113.5	712.1±173.6†	702.6±137.8†	<.001⁎
End-point accuracy (mm)
Upper left	17.2±7.2	38.6±29.0‡	21.8±12.5	<.001⁎
Upper right	16.8±4.4	25.5±19.9†	19.0±6.4	.024⁎
Center	7.3±2.4	12.8±11.2‡	7.5±3.4	.004⁎
Lower left	12.0±4.5	22.0±16.3‡	13.1±4.5	<.001⁎
Lower right	11.1±4.2	17.0±16.1†	10.9±3.9	.032⁎

NOTE. Values are mean ± SD.

Moving Visual Signal 

Similar to the results for pointing toward a stationary visual signal, young students achieved significantly faster reaction and movement times and also greater endpoint accuracy than older controls (table 4). Although Tai Chi practitioners did not have significantly faster reaction and movement times than older controls, they did show significantly better endpoint accuracy. In fact, their endpoint accuracy was similar to that of young students (see table 4).

Table 4. Comparison of Anterior Deltoid Electromyographic Reaction Time and Movement Time, as Well as Endpoint Accuracy Among Young Control, Older Control, and Older Tai Chi Subjects in Finger-Pointing Toward a Moving Target

NOTE. Values are mean ± SD.

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Discussion 

Effects of Aging 

Our present findings of slower reaction times in older than younger controls were consistent with previous studies.²², ²³, ²⁴ Moreover, their slower reaction times were more prominent in pointing to the contralateral visual field: 23.7% and 29.2% increases in the upper left and lower left locations versus 11.3%, 21.0%, and 13.7% increases in the upper right, center, and lower right locations.

Our findings also show that older adults had significantly longer movement times. Goggin and Meeuwsen²⁵ asked older (67–80y) and younger (22–30y) subjects to reach for different sized targets with an electronic pen in the horizontal plane. They reported that older subjects were significantly slower than younger subjects in reaching for targets of all sizes, and the movement time of older subjects was especially longer when the targets were smaller. Surprisingly, older subjects had less error in overshooting the targets than younger subjects, which the investigators attributed to their desire for better accuracy. The strategy of moving more slowly in order to achieve a better accuracy conforms to Fitts' law,²⁶ which states that movement time is indirectly proportional to target size. In our present testing protocol, the participants were required to touch the visual target as quickly and as accurately as possible. This command demanded fast finger-pointing movement with an accurate stop. Fast finger-pointing movement required the subjects to generate a high-amplitude agonist burst. When the hand approached the target, the subjects were required to arrest the movement by switching off the agonist burst and switching on the antagonist muscles at once. Barry et al²⁷ showed that older subjects had difficulties producing a high-amplitude agonist burst and switching on the antagonist in a speedy manner. This may explain why the older adults in our study showed significantly slower movement times and significantly less endpoint accuracy with all 5 target locations. However, validation of such a possibility would require the recording and analyses of the triphasic electromyographic patterns from agonist and antagonist muscles, which was not done here and warrants further study.

Target reaching often involves targets that are moving, for instance, passing an object to or from another person whose hand is also moving. Indeed, for many people, passing keys or small items of clothing from one hand to the other commonly involves a brief flight phase. Reaching for a moving object requires both spatial and temporal prediction; that is, a person must predict the position of the moving object in order to reach for it at the right time and location.²⁸ Cooke et al²⁹ observed that older adults had faster movement times than younger adults, but only when there was no requirement for accuracy. In our present study, both the reaction time and movement time of the older adults were significantly slower than those of the young university students. This may have resulted from the requirement that the subjects had to touch the visual target as quickly and as accurately as possible. With these constraints, older control subjects were both slower and had poorer accuracy than young students in pointing to a moving visual signal.

Effects of Tai Chi Practice 

With this testing protocol, Tai Chi practitioners showed similar electromyographic reaction times to those of healthy older control subjects in all five locations of the visual signal (see table 3). These results differ from those of our previous study¹⁵ in which subjects were asked to voluntarily weight-shift to eight different spatial positions at their limits of stability within their base of support. Tai Chi practitioners had significantly faster reaction times (0.8±0.1s) than matched controls (1.0±0.3s) in that task. Different neuromuscular control and cognitive factors required of the 2 different tasks—between balance control in the limits of stability test and eye-hand coordination in the finger-pointing task—might explain the different results.

In the present study, Tai Chi practitioners did not achieve faster movement times than the healthy older controls. Previous research has shown that when experienced Tai Chi practitioners performed a task that required moving a stylus from target to target (a total of 10 targets) in a zigzag pattern in the horizontal plane, the time they needed to complete the task was significantly shorter than that of matched controls who were not Tai Chi practitioners.¹⁸ There seems to be a discrepancy between Pei et al's¹⁸ findings and ours, which could be explained by the different protocols adopted in the 2 studies. More specifically, our movement time measure included the biomechanical delay required to generate the muscle torque to complete the pointing task and theirs did not. Furthermore, their protocol required subjects to reach 11 target locations, and the total time might have reflected better eye-hand coordination among the Tai Chi practitioners. However, in our study, subjects were required to touch 1 target only. Although there was a trend toward faster movement time when Tai Chi practitioners reached for contralateral targets (by 3.9% and 4.6% on upper left and lower left locations), they did not display significantly faster movement times than the controls.

Tai Chi practitioners showed significantly better endpoint accuracy than older controls similar in age, gender mix, and physical activity level. Joint proprioception is essential for accurate finger-pointing, and research has shown that subjects with poor proprioception make extensive directional errors in pointing to visual targets.³⁰ Tai Chi puts great emphasis on both exact joint positioning and the direction of movement. Previous studies including ours show that Tai Chi practitioners had developed better joint proprioception, and this might have enhanced their endpoint accuracy.¹⁴, ¹⁵, ³¹, ³², ³³

Pointing to ipsilateral target locations might not provide a challenge sufficient to differentiate between the 2 older groups. During ipsilateral pointing, the responding hand and the hemifield of the visual signal are located on the same side. Both visual and motor responses are processed in the same contralateral brain hemisphere. During contralateral pointing, the visual input is received by the hemisphere contralateral to the stimulus, while the motor response is generated by the other hemisphere. This necessitates interhemisphere transmission of information,³⁴, ³⁵ and the main structural basis for interhemisphere transfer is probably the corpus callosum. Anatomical studies reveal a decrease in size of the corpus callosum with aging. This structural decline is associated with an increased deficit in interhemisphere communication in older adults.³⁶ Moreover, the visual feedback during contralateral pointing is received by the hemisphere contralateral to the target side, while the corrective motor response is generated by the opposite hemisphere. Interhemispheric transmission of information is thus also needed and yields additional response latency in the immediate visual-motor feedback.³⁷ This may also deteriorate in the aging process and affect the endpoint accuracy of the hand. Exercises that involve contralateral arm movements, such as Tai Chi may help to minimize the deteriorating process. Tai Chi styles often involve hand movements crossing the midline of body, like the “waving hands like clouds” and “fair lady works the shuttles” maneuvers.³⁸ Such repeated practice with emphasis on exact joint position and direction¹⁴, ³⁹ may have facilitated eye-hand coordination in responding to a visual target contralateral to the pointing hand.

Tai Chi practitioners showed significantly better endpoint accuracy than older control subjects in pointing toward a moving visual signal (37.7% difference), and their accuracy even reached a level similar to that of young students (7.4% difference) (see table 4). Tai Chi forms like “repulse the monkey”¹⁶ and “cloud hand” maneuvers⁴⁰ require practitioners to move both hands simultaneously in different directions, often with trunk rotation while stepping backward or sideways and with their eyes all the while focused on 1 hand. Practicing such complex drills may have facilitated eye-hand coordination in responding to a moving visual signal. Improved control of arm trajectory in a finger-pointing task might have in turn led to better endpoint accuracy.

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Conclusions 

Strong evidence from clinical³⁹ and laboratory investigations including magnetic resonance imaging⁴¹ has supported the benefits of exercise in improving eye-hand coordination⁷, ⁸ and balance control¹⁶, ⁴² in the aging population. We used a cross-sectional design in the present study. Thus, a causal relation between Tai Chi practice and better finger-pointing has yet to be established through a longitudinal study involving a randomized controlled trial. Because only healthy older adults were examined, the findings cannot be extended to frail older persons or those who have a history of eye problems. Limitations aside, the findings from this cross-sectional study demonstrate that experienced Tai Chi practitioners are significantly more accurate in pointing to both stationary and moving visual signals than older controls similar in age, gender and physical activity level. Of interest is that their performance was similar to that of young university students.

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Acknowledgment 

We thank the older adult centers for permission to recruit their subjects and Bill Purves for his English editorial advice.

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• a 3M Touch Systems; 3M Optical Systems Division, 300 Griffin Brook Park Drive, Methuen, MA 01844.
• b B & L Engineering, 1901 Carnegie Ave, Ste Q, Santa Ana, CA 92705.
• c National Instruments, 11500 N Mopac Expwy, Austin, TX 78759-3504.