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J Appl Physiol 95: 373-384, 2003. First published March 21, 2003; doi:10.1152/japplphysiol.00060.2003
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Fluctuations in acceleration during voluntary contractions lead to greater impairment of movement accuracy in old adults

Evangelos A. Christou, Minoru Shinohara, and Roger M. Enoka

Department of Kinesiology and Applied Physiology, University of Colorado at Boulder, Boulder, Colorado 80309

Submitted 22 January 2003 ; accepted in final form 14 March 2003


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
The purpose of the study was to assess the effect of movement velocity on the relation between fluctuations in acceleration and the ability to achieve a target velocity during voluntary contractions performed by young (29.5 ± 4.3 yr) and old (74.9 ± 6.2 yr) adults. Subjects performed concentric and eccentric contractions with the first dorsal interosseus muscle while lifting a submaximal load (15% of maximum) at six movement velocities (0.03–1.16 rad/s). Fluctuations in acceleration, the accuracy of matching the target velocity, and electromyographic (EMG) activity were determined from three trials for each contraction type and movement velocity. The fluctuations in acceleration increased with movement velocity for both concentric and eccentric contractions, but they were greatest during fast eccentric contractions (~135%) when there was stronger modulation of acceleration in the 5- to 10-Hz bandwidth. Nonetheless, EMG amplitude for first dorsal interosseus increased with movement velocity only for concentric and not eccentric contractions. Consistent with the minimum variance theory, movement accuracy was related to the fluctuations in acceleration for both types of contractions in all subjects. For a given level of fluctuations in acceleration, however, old subjects were three times less accurate than young subjects. Although the EMG amplitude at each speed was similar for young and old adults, only the young adults modulated the power in the EMG spectrum with speed. Thus the fluctuations in acceleration during voluntary contractions had a more pronounced effect on movement accuracy for old adults compared with young adults, probably due to factors that influenced the frequency-domain characteristics of the EMG.

concentric contraction; eccentric contraction; electromyogram; first dorsal interosseus; frequency spectrum

THE FORCE EXERTED BY A MUSCLE during a voluntary contraction is not constant, but rather it fluctuates about an average value (2, 15, 25, 33, 36). The neural mechanisms most responsible for the fluctuations in the force exerted by hand muscles appear to be the regularity with which motoneurons discharge action potentials and the common modulation of motor unit discharge in the agonist and antagonist muscles (7, 10, 13, 16, 41). Fluctuations in muscle force impose a significant constraint on the ability of the nervous system to control movement by influencing the capacity to exert a desired force and to achieve an intended trajectory (17, 18, 43).

The minimum variance theory postulates that the central nervous system attenuates this constraint during the performance of goal-directed movements by selecting activation strategies that minimize the variance in the trajectory of the movement (18, 43). One prediction of this theory is that the accuracy of goal-directed movements should decline as the amplitude of the force fluctuations increases. Therefore, the accuracy of goal-directed movements should vary with changes in movement velocity (41), the type of muscle contraction performed (2, 3, 5), and the age of the individual (1, 12, 15, 23, 38).

The purpose of the study was to assess the effect of movement velocity on the fluctuations in acceleration and the ability to achieve a target velocity when young and old adults performed anisometric contractions with the first dorsal interosseus muscle. The results were consistent with the prediction of the minimum variance theory that movement accuracy declines with an increase in the fluctuations of acceleration; nonetheless, the relations differed for young and old adults. Some of these results have been presented previously in abstract form (4).


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
Ten young adults (29.5 ± 4.3 yr; 5 men and 5 women) and nine old adults (74.9 ± 6.2 yr; 4 men and 5 women) volunteered to participate in the study. All subjects were right handed, reported no neurological impairments and no use of medications known to influence the assessment of neuromuscular function, and performed no more than 5 h of exercise per week at a moderate to a high intensity. Subjects provided written, informed consent before participating in the study, and the Human Research Committee at the University of Colorado in Boulder approved the protocol.

Experimental arrangement. Each subject was seated facing an oscilloscope, which was positioned 1.6 m in front of the subject at eye level. The interphalangeal joints of the left index finger were kept extended by an individualized plastic splint that covered the lateral and ventral surfaces of the index finger. The left arm was abducted by 0.785 rad, and the elbow joint was flexed to a right angle, with the hand and forearm prone and resting on a platform (21, 24). The elbow and forearm were immobilized by using a vacuum foam pad (Versaform pillow, Tumble Forms, Canada), the hand was restrained by a brace for the thumb to maintain an angle of 1.57 rad between the first and second metacarpals, and a brace prevented flexion at the interphalangeal joints of the index finger.

Abduction of the index finger at about the first metacarpophalangeal joint ranged from 0 (neutral position) to 0.175 rad and was detected with a linear variable differential transducer (Novotechnik, Stuttgart, Germany). Acceleration in a horizontal abduction-adduction plane was measured with a piezoresistive accelerometer (model 7265A-HS, Endevco; mass = 6 g; linear range of acceleration response: ±196.2 m/s2; frequency response = 0–500 Hz) that was attached to the lateral side of the proximal interphalangeal joint of the index finger (Fig. 1A). Acceleration was sampled at 500 Hz.



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  		Fig. 1. Schematic drawing of the task and representative data for the velocity-matching task during eccentric and concentric contractions. A: arrangement of the left index finger. B: position trace (solid line) and the target velocity (dotted line) during eccentric and concentric contractions performed by a young subject at a moderate velocity (0.12 rad/s). The visual feedback provided to the subject after each trial was similar to traces shown in B. LVDT, linear variable differential transducer.

 

Electromyographic (EMG) activity of the first dorsal interosseus muscle, which is the prime mover for abduction of the index finger, was measured with silver-silver chloride electrodes (4-mm diameter) that were attached to the skin. One electrode was placed over the belly of the first dorsal interosseus muscle (distal to the innervation zone) and was referred to another electrode placed over the metacarpophalangeal joint. A third electrode, which served as the reference, was placed over the distal head of the ulna. The EMG signals were amplified (x1,000) with an isolated bioamplifier (S-series, Coulbourn), passed through a band-pass filter (20–800 Hz; S-series, Coulbourn), and sampled at 2 kHz (1401 plus, Cambridge Electronic Design). The amplitude of the EMG signal was expressed as the average rectified EMG (AEMG) from the middle one-third of each trial (Fig. 1B).

Experimental protocol. Each subject participated in a single experiment and performed two tasks with the index finger of the left hand: 1) one-repetition maximum (1-RM) and 2) velocity-matching trials with a submaximal load. The 1-RM load was defined as the maximal load that could be lifted by abducting the index finger over the 0.17-rad range of motion. The initial load was 0.5 kg, and increments of 250 g were added until the subjects were not able to lift the load. At that point, adjustments were made down to the 5-g level until the maximal load that could be lifted by a subject was identified. A rest of ~2 min was given to the subjects between the increments in load. The 1-RM load was determined with slow contractions at an average velocity of 0.03 rad/s.

The velocity-matching trials were performed with a 15% 1-RM load over a 0.17-rad range of motion in the abduction-adduction plane. The inertial load, which was attached to a splint on the index finger at the level of the proximal interphalangeal joint (Fig. 1A), opposed abduction of the index finger. Each subject raised the load with a concentric contraction of the first dorsal interosseus muscle and lowered it with an eccentric contraction of the same muscle. The concentric and eccentric contractions were performed at six different velocities (0.03, 0.06, 0.12, 0.29, 0.58, and 1.16 rad/s), which corresponded to movement durations of ~6, 3, 1.5, 0.6, 0.3, and 0.15 s, respectively. The velocity of 1.16 rad/s was not maximal for either group of subjects. Before each movement, the subject supported the load with an isometric contraction; thus both the concentric and eccentric contractions were preceded by an isometric contraction (as indicated by the dotted horizontal line at the beginning of each contraction in Fig. 1B). For the velocity-matching task (Fig. 1B), each participant was instructed to match a line displayed on an oscilloscope by controlling movement velocity of the index finger. To become familiar with each criterion velocity, the subject performed several practice trials (<10 trials) at each velocity before data collection. For the first few practice trials, subjects received both visual (joint angle) and verbal feedback. However, subjects were given visual feedback (Fig. 1B) only after the completion of each trial during the last practice trials and all data collection trials. The subject continued performing trials until the average velocity was within ±15% of the target velocity for the three trials. Rest periods of 10 s were given between trials and 120 s between target velocities. The order of the 12 conditions (2 contraction types and 6 contraction velocities) was assigned randomly for each subject.

Data analysis. The dependent variable for the 1-RM task was the maximal load lifted (in kg). The dependent variables for the velocity-matching task were 1) the number of trials required by each subject to achieve the criterion velocity; 2) the fluctuations in acceleration in each trial, quantified as the standard deviation of acceleration; 3) first dorsal interosseus activation, expressed as the AEMG for each contraction; 4) velocity accuracy, quantified as the standard deviation in the velocity across trials (similar to velocity error and strongly associated with end-point variability); and 5) the trial-to-trial variability, denoted as the standard deviation and coefficient of variation for acceleration across trials. To exclude the initial increase in velocity and thus measure the constant-velocity region of each contraction, all dependent variables (with the exception of the number of trials) were calculated from the middle one-third of each accepted trial (Fig. 1).

The acceleration data for the index finger and the EMG signal from the first dorsal interosseus muscle were analyzed in both the time and the frequency domains. The power spectrum for acceleration has been associated with the discharge pattern of the motor units (16, 20), whereas the EMG spectrum has been used to characterize changes in the activation signal sent by the nervous system to the muscle. Preliminary analyses indicated no significant differences (P > 0.05) in the frequency content of the acceleration and interference EMG (absolute power, median frequency, and the frequency where peak power occurred) for the three trials at a given velocity performed by each subject. Thus the frequency content of the acceleration and surface EMG was quantified from the trial that had the lowest fluctuations in acceleration. A Fourier analysis was performed on the two signals for this trial, and autospectral analysis of the acceleration and EMG signal was obtained by using Welch's averaged periodogram method (MATLAB 6.1). The length of the data segment was equal to the total time of each contraction (ranging from 0.15 to 6 s). The window size for the acceleration signal (sampling frequency of 500 Hz) was 256 for all contractions, except for the fastest velocity (1.16 rad/s) when it was 128. The resolution for acceleration was 0.976 Hz for contractions ranging from 0.03–0.58 rad/s and 3.91 Hz for the fastest contraction (1.16 rad/s). The window size for the EMG signal (sampling frequency of 2 kHz) was 512 for all contractions, which provided a resolution of 4.88 Hz. For statistical comparisons, frequency data were averaged over 5-Hz intervals for acceleration and 25-Hz intervals for EMG. The percent power in the signal for each averaged interval was expressed as a proportion of the total power in the spectrum. The dependent variables for the spectral analysis were the median frequency, the frequency at which the peak power occurred, and the absolute and relative (%) power in the averaged bins.

The dependent variables for the velocity-matching task and the frequency at peak power were compared with a three-factor ANOVA (2 age groups x 2 contraction types x 6 velocities) with repeated measures on contraction type and velocity (SPSS version 9.0). Linear regression analyses were used to examine the relationship between the fluctuations in acceleration and the accuracy of movement velocity. The dependent variables for the spectral analysis were compared with a four-factor ANOVA (2 age groups x 2 contraction types x 6 velocities x 10 frequency bins). Multiple regression analyses were used to examine the contribution of each frequency bin in acceleration and EMG to the increased fluctuations in acceleration as movement speed increased. The {alpha} level for all statistical tests was set at 0.05, and paired contrasts (t-tests with Bonferroni corrections) were used to locate differences between age groups and contractions when ANOVAs yielded significant interactions. Data are indicated as means ± SD in the text and tables and as means ± SE in the figures.


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 
The old and young subjects were of similar height (1.69 ± 0.09 m), but the young group (69.7 ± 19.7 kg) had a greater body mass than the old group (63.8 ± 10.6 kg; P < 0.05). The 1-RM load lifted with the left index finger was 40% less for the old subjects (1.39 ± 0.54 vs. 2.30 ± 0.57 kg), and the men were 22% stronger than the women in the young group (2.58 ± 0.51 vs. 2.02 ± 0.53 kg) and 28% stronger than the women in the old group (1.65 ± 0.62 vs. 1.18 ± 0.41 kg).

Concentric and eccentric contractions. For each anisometric contraction, the subject was required to match the rate of change in the angle of the metacarpophalangeal joint to a target velocity (slope of a position-time trace) that was displayed on an oscilloscope (Fig. 1B). The fluctuations in acceleration during the middle one-third of each contraction were quantified as the average standard deviation of acceleration for the three trials that matched the criterion velocity. The number of trials required to achieve the target velocity (Table 1) was similar for concentric (6.49 ± 4.21) and eccentric (5.03 ± 2.08) contractions at the three slowest velocities but greater for eccentric contractions (12.4 ± 7.54) compared with concentric contractions (7.51 ± 4.21; P < 0.05) at the three fastest velocities. The data were collapsed across sex due to the absence of significant differences in the standard deviation of acceleration between men (39.9 ± 25.5 cm/s2) and women (30.2 ± 19.1 cm/s2; P > 0.05).


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  		Table 1. Number of trials required by the young and old subjects to match the target velocity

 

The standard deviation of acceleration increased with movement velocity (Fig. 2) for both concentric and eccentric contractions (Fig. 3), and similarly for young and old subjects. The standard deviation of acceleration, however, was significantly greater for eccentric contractions (39.3 ± 25.1 cm/s2; P < 0.05) compared with concentric contractions (30.3 ± 19.5 cm/s2). The difference in the standard deviation of acceleration between concentric and eccentric contractions increased with movement velocity (P < 0.05). Despite these monotonic increases in the standard deviation of acceleration with velocity for both the concentric and eccentric contractions, the AEMG of first dorsal interosseus increased with movement velocity only during the concentric contractions and did not change (P > 0.1) with velocity for the eccentric contractions (Figs. 2 and 3).



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  		Fig. 2. Representative data for electromyogram (EMG) and acceleration during eccentric and concentric contractions at 3 movement velocities (A–C). At each velocity, traces show rectified EMG (top) and acceleration (bottom) during eccentric (left) and concentric (right) contractions by a young subject at the slowest (0.03 rad/s; A), middle (0.12 rad/s; B), and fastest (1.16 rad/s; C) velocities. Each eccentric and concentric contraction began from an isometric contraction. The amplitude of the EMG was lower during eccentric contractions compared with concentric contractions, and it increased with movement velocity for concentric contractions but not for eccentric contractions. Fluctuations in acceleration were greater during eccentric contractions and increased with movement velocity for both contraction types.

 


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  		Fig. 3. The standard deviation (SD) of index finger acceleration and the average EMG (AEMG) for first dorsal interosseus during eccentric and concentric contractions at 6 movement velocities. The SD of acceleration increased with movement velocity for both types of contractions, especially at the 3 fastest eccentric contractions. AEMG during eccentric contractions was lower compared with concentric contractions at all velocities. Furthermore, AEMG increased with velocity during concentric contractions but did not change during eccentric contractions. *P < 0.05 compared with concentric contractions.

 

Young and old adults. The standard deviation of index finger acceleration was greater for young adults (43.9 ± 23.3 cm/s2) compared with old adults (24.6 ± 17.5 cm/s2) when averaged across velocity for the concentric and eccentric contractions (P < 0.05; Table 2), even though young subjects lifted almost twice as much load (2.30 ± 0.57 kg) as the old subjects (1.39 ± 0.54 kg). The standard deviation of acceleration, however, was not related to the magnitude of the load (r2 = 0.041, P > 0.05). Despite the greater standard deviation of acceleration for the young subjects, the ability to achieve the target velocity at each movement velocity (velocity accuracy) was not different between young and old adults (P > 0.05). For example, the standard deviation of velocity for the three trials at an intermediate velocity (0.12 rad/s) was 0.73 ± 0.52 rad/s for the young subjects compared with 0.89 ± 0.54 rad/s for the old subjects.


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  		Table 2. Standard deviation of index finger acceleration (em/s2) for the 6 movement velocities performed by young and old subjects

 

The average number of trials needed by the old subjects (8.9 ± 0. 6) to achieve the target velocity was greater (P < 0.05) than that for the young subjects (7.0 ± 0.5). The variability in the standard deviation of index finger acceleration across trials, which was quantified as the coefficient of variation during the middle one-third of each trial, was similar for young (21.4 ± 12.5%) and old (24.5 ± 15.4%) adults during concentric contractions but was greater for eccentric contractions performed by old adults (32.4 ± 23.1%) compared with young adults (21.9 ± 13.4%). Furthermore, the coefficient of variation was greater for old adults (47.1 ± 20.1%) compared with young adults (29.9 ± 9.8%) at the fastest velocity when the two contractions were pooled.

Fluctuations in acceleration and movement accuracy. Movement accuracy for the two age groups and the two types of contractions was quantified as the variability in the average movement velocity across trials (standard deviation of velocity). The standard deviation of velocity was positively related to the standard deviation of acceleration for both the young and old adults (Fig. 4A). The slope of the regression line, however, was approximately three times greater for the old adults (Table 3), which indicated that the old adults were much less accurate than the young adults for the same degree of fluctuations in index finger acceleration. Because the standard deviation of acceleration increased with movement velocity (Fig. 3 and Table 2), the difference in accuracy between young and old adults was greatest at the fast movement velocities.



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  		Fig. 4. Relations between the fluctuations in acceleration and movement accuracy. Each data point indicates means ± SE for acceleration SD (x-axis) and either the variability in the average velocity across trials (y-axis in A) or the trial-to-trial variability in the acceleration fluctuations (ordinate in B). Fluctuations in index finger acceleration (SD) are grouped into 10 cm/s2 bins for clarity of presentation. A: ability to achieve the target velocity (velocity SD) consistently decreased as fluctuations in acceleration increased for both young and old adults. The relation was similar for concentric and eccentric contractions but differed for young (solid line) and old (dashed line) adults (see Table 3 for slope differences). Similarly, movement accuracy across trials (SD of the acceleration SD) decreased as the fluctuations in index finger acceleration increased for both young and old adults. B: the relation was similar for concentric (thick solid line) and eccentric (thick dashed line) contractions for the young adults and the concentric contractions of the old adults (thin solid line) but had a greater slope for the eccentric contractions performed by old adults (thin dashed line; see Table 3 for slope differences).

 

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  		Table 3. Linear regression analysis of the association between the fluctuations in index finger acceleration and movement accuracy

 

The fluctuations in acceleration were also significantly associated with the variability in the acceleration fluctuations across trials (standard deviation of the acceleration standard deviation; Fig. 4B). The positive relation indicated that increases in the mean standard deviation of acceleration for the three trials of each condition were associated with an increase in the variability of the fluctuations in acceleration across the three trials. The slopes of these relations were similar for the concentric and eccentric contractions of the young subjects and the concentric contractions of the old subjects (Table 3). In contrast, variability in the standard deviation of acceleration across trials increased more rapidly with movement velocity for the eccentric contractions performed by old adults (Table 3).

Frequency content of index finger acceleration and EMG. To identify the cause of the differences in the ability of young and old subjects to perform velocity-matching anisometric contractions, both the index finger acceleration and the first dorsal interosseus EMG data were examined in the frequency domain. Because such analyses are typically performed on the rectified EMG, despite the distortion introduced by the rectification process (see DISCUSSION), the analysis was performed on both the interference and rectified EMG signals. The power spectra for these signals were first characterized by the median frequency and the frequency at which the peak power occurred, and then the spectra were compared.

The median frequency for acceleration was similar for the two age groups (young = 7.81 ± 3.02 Hz; old = 8.22 ± 3.21 Hz) and the two contraction types (concentric = 8.2 ± 3.25 Hz; eccentric = 7.74 ± 2.95 Hz) (Fig. 5A). The median frequency decreased significantly (P < 0.05) with movement velocity; for example, it declined from 10.6 ± 2.9 Hz at the slowest velocity (0.03 rad/s) to 7.14 ± 2.71 Hz at a faster velocity (0.58 rad/s). Peak power in acceleration occurred consistently in the 5- to 10-Hz bin for both age groups and contraction types. The young subjects exhibited greater power [14.6 ± 16.6 (cm/s2)2] than the old subjects [4.83 ± 6.81 (cm/s2)2; P <0.001] at low frequencies (0–15 Hz). Similarly, peak power in acceleration was greater for eccentric contractions [16.1 ± 21.7 (cm/s2)2] compared with concentric contractions [3.88 ± 6.1 (cm/s2)2] at low frequencies (0–15 Hz) for both age groups (P < 0.001). Accordingly, the greatest percentage of total power in the acceleration signal consistently occurred at 5–10 Hz for all velocities, both contraction types, and both age groups (Fig. 6). Eccentric contractions contained a greater percent power in the 5- to 10-Hz bin compared with concentric contractions at the four fastest movement velocities (P < 0.001).



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  		Fig. 5. Representative data for power in index finger acceleration (A), interference EMG (B), and rectified EMG (C). Each trace represents the average of all young (left) and old (right) subjects during concentric (thick trace) and eccentric contractions (thin trace) at an intermediate velocity (0.12 rad/s). A: power in index finger acceleration was greater for young adults compared with old adults and for eccentric contractions compared with concentric contractions. The frequency content of the interference EMG was different for young and old adults in both contractions (B); however, this difference was eliminated when the interference EMG was rectified (C).

 


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  		Fig. 6. Percent power at different frequencies in index finger acceleration during eccentric and concentric contractions for each of the 6 movement velocities (A–F). Each data point indicates the percent power in a 5-Hz bin relative to the total power in the spectrum of the acceleration record for the young and old subjects combined. The 5-Hz bins on the abscissa are plotted at the middle of the bin. *P < 0.05 between concentric and eccentric contractions.

 

The median frequency for the interference EMG was significantly greater (P < 0.001) for old adults compared with young adults for concentric contractions (95.8 ± 21.6 vs. 73.3 ± 19.3 Hz, respectively) and eccentric contractions (94.2 ± 18.1 vs. 73.3 ± 14.4 Hz, respectively) (Fig. 5B). Furthermore, the median frequency remained constant with velocity for old adults during eccentric contractions (96.0 ± 18.6 to 106.9 ± 28.5 Hz) but decreased significantly for young adults (0.03 rad/s = 76.6 ± 13.4 Hz; 1.16 rad/s = 56.6 ± 16.0 Hz). The frequency at which peak power occurred for the interference EMG was different for young (53.1 ± 19.9 Hz) and old (83.4 ± 19.9 Hz) adults (P < 0.001), but it was similar for concentric (68.4 ± 26.5 Hz) and eccentric contractions (68.1 ± 16.5 Hz) and remained constant with changes in velocity (64.1 ± 24.6 to 76.8 ± 36.2 Hz).

In contrast, the median frequency for the rectified EMG occurred at a similar frequency for young (56.9 ± 19.3 Hz) and old (60.4 ± 17.7 Hz) adults (P > 0.1) (Fig. 5C), differed for concentric (65.3 ± 18.4 Hz) and eccentric contractions (51.8 ± 18.9 Hz), and it increased with movement velocity (51.4 ± 13.3 to 79.4 ± 32.7 Hz; P < 0.001). Furthermore, the peak power for the rectified EMG occurred at a similar frequency for the two age groups (young = 20.4 ± 6.2 Hz; old = 20.4 ± 6.2 Hz; P > 0.1) but at a higher frequency for concentric (25.4 ± 12.1 Hz) compared with eccentric contractions (15.4 ± 5.9 Hz), and it increased with movement velocity (0.03 rad/s = 15.0 ± 3.6 Hz; 0.581 rad/s = 21.7 ± 7.8 Hz; P < 0.001).

Similar to the AEMG findings, the power in the interference EMG signal increased with velocity for concentric contractions (P < 0.001) but did not change with velocity for eccentric contractions (P > 0.05) (Fig. 3). Thus the differences in peak power between the two contraction types were greater at the fastest velocity (1.16 rad/s: concentric = 2.55 ± 3.41 mV2; eccentric = 0.12 ± 0.10 mV2) compared with the slowest velocity (0.03 rad/s: concentric = 0.21 ± 0.13 mV2; eccentric = 0.12 ± 0.10 mV2). Peak power in the interference EMG occurred at low frequencies (25–50 Hz) for young adults but at higher frequencies and with a broader spectrum (50–125 Hz) for the old adults (Fig. 7A). Differences in power at low frequencies between young and old adults increased with velocity; however, these differences were only significant (P < 0.001) for concentric contractions. The distribution of percent power in the interference EMG was similar for the two contractions types but differed between young and old adults (P < 0.001). For both contraction types, young adults had greater percent power in the 25- to 50-Hz bin, whereas old adults had greater percent power at 125–200 Hz (Fig. 7B). Increases in movement velocity were associated with increased percent power in the 25- to 50-Hz range and decreased energy in the 100- to 200-Hz range for young subjects, but there was no change in the distribution of power for the old subjects (Fig. 8).



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  		Fig. 7. Absolute and relative power in the frequency spectrum for the first dorsal interosseus EMG of young and old adults during concentric and eccentric contractions. A: distribution of power in the interference EMG of first dorsal interosseus across the frequency spectrum for concentric compared with eccentric contractions in both age groups. Each data point indicates the absolute power in a 25-Hz bin averaged across movement velocities, with the data plotted in the middle of each 25-Hz bin. B: percent power in the interference EMG signal in each bin relative to the total power in the spectrum. *P < 0.05 between young and old subjects.

 


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  		Fig. 8. Percent power at different frequencies in first dorsal interosseus EMG for young and old adults for the 6 movement velocities (A–F). The frequency characteristics of the percent power in the interference EMG of the first dorsal interosseus muscle differed for young and old adults. Young adults had greater relative power at lower frequencies (25–75 Hz) compared with the old adults (100–200 Hz), who exhibited a broader peak (25–125 vs. 25–75 Hz, old vs. young adults). In addition, young adults increased the percent power at lower frequencies (25–75 Hz) and decreased the percent power at higher frequencies (100–200 Hz) with increases in movement velocity, whereas old adults did not modulate the distribution of power across the spectrum in the interference EMG. Data are plotted in the middle of the 25-Hz bins. *P < 0.05 between young and old subjects.

 

Associations of acceleration and EMG spectra with movement accuracy. Given these frequency characteristics of the acceleration and EMG signals, the analysis compared the spectra to identify factors that influenced differences in the ability to perform the velocity-matching task. There was a significant relation between the frequency spectrum of the acceleration signal and fluctuations in acceleration. For both concentric (r2 = 0.11, P < 0.001) and eccentric (r2 = 0.20, P < 0.001) contractions, greater fluctuations in acceleration were associated with a decrease in the median frequency of acceleration (Fig. 9A). Similar findings were observed for the young (r2 = 0.24, P < 0.001) and old (r2 = 0.09, P < 0.01) adults. Furthermore, greater fluctuations in acceleration were associated with a significant decrease in the median frequency of the interference EMG (r2 = 0.15, P < 0.001) but not the median frequency of the rectified EMG signal (r2 = 0.01, P > 0.1). The greater fluctuations in acceleration were accompanied by decreases in the median frequency of the interference EMG during both concentric (r2 = 0.13, P < 0.001) and eccentric (r2 = 0.18, P < 0.001) contractions. Similar associations were observed between fluctuations in acceleration and the frequency at which peak power occurred.



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  		Fig. 9. Relations between fluctuations in index finger acceleration and median frequency in acceleration (A) and interference EMG (B). Each data point indicates means ± SE for acceleration SD (x-axis) and either the variability in the median frequency of acceleration (y-axis in A) or the median frequency for interference EMG (y-axis in B). Fluctuations in index finger acceleration (SD) are grouped into 10-cm/s2 bins for clarity of presentation. Greater fluctuations in index finger acceleration (SD) were associated with decreases in the median frequency of acceleration (A) and interference EMG (B). Relations were similar for concentric and eccentric contractions.

 

Variation in the fluctuations in acceleration across contraction type and age were associated with different features of the spectra for acceleration and interference EMG. For example, greater fluctuations in acceleration were associated with a lower percent power in the 15- to 20-Hz bin of acceleration for concentric contractions (r2 = 0.22, P < 0.001) but with a lower percent power in the 20- to 25-Hz bin and a greater percent power in the 0- to 5-Hz bin for eccentric contractions (r2 = 0.24, P < 0.001). Similarly for the interference EMG, greater fluctuations in acceleration were accompanied by a greater percent power in the 25- to 50-Hz bin during concentric contractions (r2 = 0.12, P < 0.001) but a lower percent power in the 100- to 175-Hz bin during eccentric contractions (r2 = 0.27, P < 0.001). The significant relations for the two age groups included a lower percent power in the 15- to 25-Hz bin of acceleration and greater fluctuations in acceleration for young adults (r2 = 0.30, P < 0.001) compared with lower percent power in the 10- to 20-Hz bin and greater fluctuations in acceleration for the old adults (r2 = 0.19, P < 0.001). Similarly for the interference EMG, greater fluctuations in acceleration were associated with a lower percent power in the 100- to 125-Hz bin for young adults (r2 = 0.08, P < 0.01) but with a greater percent power in 0- to 25-Hz bin and a lower percent power in the 225- to 250-Hz and 150- to 175-Hz bins for old adults (r2 = 0.19, P < 0.001).


   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
ACKNOWLEDGMENTS
 REFERENCES
 
The study produced five novel findings on the association between movement velocity and the ability to achieve a target velocity during concentric and eccentric contractions performed with the first dorsal interosseus muscle by young and old adults. First, the fluctuations in acceleration increased with movement speed during concentric and eccentric contractions for both groups of subjects. Second, the fluctuations in acceleration were greater during eccentric contractions compared with concentric contractions, especially at faster movements. Third, there was a significant association between the fluctuations in acceleration and movement accuracy for both contraction types, as suggested by the minimum variance theory, but the relation differed for young and old adults. Fourth, the increase in acceleration fluctuations during fast eccentric contractions was associated with an increase in power in the 5- to 10-Hz bin of the spectrum for index finger acceleration. Although fluctuations in acceleration and AEMG were not associated during eccentric contractions, greater fluctuations in acceleration were associated with a decline in the median frequency of acceleration and interference EMG. Fifth, the frequency content of the EMG signal differed for young and old adults, including modulation of power in the frequency content of the EMG with changes in speed for the young adults but not the old adults.

Concentric and eccentric contractions. Although the decline in accuracy with movement speed has been of interest for some time (44), the present study is the first to provide evidence that the speed-accuracy relation also holds for eccentric contractions. According to the minimum variance theory (18, 43), the decrease in movement accuracy for faster movements is a consequence of greater fluctuations in acceleration with an increase in the average mechanical power produced during muscle contractions. The present results are consistent with this theory for both concentric and eccentric contractions (Fig. 4A).

The greatest difference in the standard deviation of acceleration between concentric and eccentric contractions occurred at the fastest movement because of an enhanced contribution to the fluctuations in index finger acceleration in the 0- to 15-Hz bandwidth (peak 5–10 Hz) (27, 39, 41). This effect increased with movement speed (41) for both types of contractions. For eccentric contractions, however, the modulation at 5–10 Hz was greater at the four fastest contractions (0.117–1.163 rad/s) compared with concentric contractions (Fig. 6), which likely explains the increased fluctuations in acceleration during the fast eccentric contractions (Fig. 3).

Some experimental evidence suggests that increases in the fluctuations in acceleration during concentric contractions are accompanied by an increase in the average EMG (41). In contrast, the greater fluctuations in acceleration for the eccentric contractions in the present study were not associated with greater muscle activity at any given movement speed. In general, the lesser EMG during an eccentric contraction when lowering a given load (6, 42) is attributed to a lower discharge rate and the recruitment of fewer motor units (6, 23, 34). The reduction in discharge rate likely includes an increased variability in discharge (12, 23, 29, 30), which can decrease twitch fusion and increase the fluctuations in the forces exerted by individual motor units (12, 14). Some evidence indicates that discharge rate variability of the motor units and fluctuations in motor output increase with movement speed for both concentric (40, 41) and eccentric contractions (22). Therefore, the greater relative increase in acceleration fluctuations during the eccentric contractions may be due to increased discharge rate variability of the involved motor units. Furthermore, there is evidence that synchronization of motor units in the first dorsal interosseus is greater during eccentric compared with concentric contractions (32), which can potentially increase the fluctuations in acceleration (37, 47). Alternatively, the fluctuations in acceleration might be a consequence of the common modulation of motor unit discharge (16, 20).

Although the modulation of power in the frequency domain was similar for concentric and eccentric contractions, fluctuations in acceleration were associated with different components of the interference EMG spectra for the two contractions. Greater fluctuations in acceleration, for example, were associated with increased percent power at low frequencies during concentric contractions (25–50 Hz) but decreased percent power at high frequencies during eccentric contractions (100–175 Hz). Both of these associations contributed significantly to an increase in the percent power at low frequencies (0–5 Hz) in the acceleration spectrum. The percent power in the 0- to 10-Hz frequency spectra of acceleration increased with movement speed, which was associated with greater fluctuations in acceleration (Fig. 6). Thus it appears that the frequency content of the interference EMG for concentric and eccentric contractions contributed differently to the low-frequency content of acceleration and thus fluctuations in acceleration.

Movement accuracy of young and old adults. The standard deviation of acceleration for a given movement speed was greater for young subjects compared with old subjects. Despite this difference, the ability to achieve the target velocity was similar for young and old adults at each speed. Nonetheless, the old subjects were three times less accurate (standard deviation of velocity) than the young subjects when exhibiting the same level of fluctuations in acceleration (standard deviation of acceleration). Because old adults required ~30% more trials to achieve the target velocity within the 15% acceptable error, accuracy with the velocity-matching task was less in old adults when the comparison was based on a similar number of trials. Consequently, the difference in the slope of the association between movement accuracy and fluctuations in index finger acceleration (Fig. 4A) between young and old adults would be greater for the same absolute number of trials.

Increases in movement speed appear to involve substantial modulation of the activation signal sent to the muscle (40, 41). Although EMG amplitude at each speed was similar for young and old adults, the frequency content of the EMG signal differed. Modulation of the interference EMG occurred over a broader bandwidth and at higher frequencies for old adults (50–150 Hz) compared with young adults (25–100 Hz), and this difference was augmented with an increase in movement speed. The relative power in the EMG increased with movement speed at 25–50 Hz and decreased at higher frequencies for young adults, whereas the distribution of percent power did not change with speed for the old adults. Furthermore, greater fluctuations in acceleration were associated with decreases in percent power of the interference EMG from 100 to 125 Hz for young adults, whereas the association largely involved increases in percent power from 0 to 25 Hz for old adults.

The differential modulation of power in the interference EMG with speed may have impaired the ability of the old individuals to accurately match the target velocity despite lesser fluctuations in index finger acceleration. For example, in-phase modulation of percent power in the interference EMG of the agonist and antagonist muscles would increase coactivation, thereby stiffening the joint and reducing the fluctuations in acceleration (19, 31). There is evidence that old adults exhibit increased coactivation during slow abduction-adduction movements of the index finger (1, 24, 35). Furthermore, the broader peak in the power spectrum for the old adults (50–125 Hz vs. 25–50 Hz) likely reduced phase differences between the frequency components of the signal (28) and resulted in less alternating activation between the agonist and antagonist muscles. Thus the altered temporal activation of the agonist and antagonist muscles in old adults can consequently impair the ability of an old individual to accelerate the limb segment and accurately match a target velocity (9).

The results of this study also indicated that the old subjects had greater variability in the standard deviation of acceleration across trials (trial-to-trial variability). The greatest trial-to-trial variability in the ability to achieve the target velocity for the old adults occurred during the eccentric contractions. The reduced ability of old adults to reproduce a target velocity during fast movements (Fig. 3B), which are influenced the least by peripheral feedback (8), may suggest an impaired motor program (motor command and excitation of the motoneuron pool). A similar conclusion was reached in previous studies that used larger muscles and different tasks. For example, when young and old adults performed fast isometric (2) or anisometric (3) contractions with the quadriceps femoris muscle (400 ms in duration), the ability of old adults to reproduce a parabolic force-time profile was significantly impaired. Furthermore, when young and old adults executed rapid aiming movements with the arm, the old adults exhibited less smooth trajectories (45) and greater trial-to-trial variability in the reaction time (46).

Interference and rectified EMG. Although the force fluctuations that occur during a muscle contraction depend on the behavior of the involved motor units (12), sampling limitations hinder a detailed examination of this association at the level of single motor units. As an alternative, the surface EMG can be used to assess the activity of motor unit populations (16), usually involving a frequency analysis of the rectified and filtered EMG signal (demodulated EMG) due to the strong association between the demodulated EMG and force during an isometric contraction (11, 26). Although the frequency content of the rectified EMG and acceleration signal appear to be modulated in parallel during position-holding contractions (16), the present study focused on the interference EMG for four reasons. First, the association between force and EMG observed during isometric contractions was absent during anisometric contractions (Fig. 2). Second, evaluation of the interference EMG with the high-pass filter set at 1 Hz indicated that the relative power below 20 Hz was negligible in a number of tasks (maximum voluntary contraction = 0.39 ± 0.01%; isometric contractions at 10% maximum voluntary contraction = 2.7 ± 0.5%; slow anisometric contractions with a light load = 3.0 ± 1.3%; fast anisometric contractions with a light load = 3.7 ± 1.8%; E. A. Christou, K. G. Keenan, and R. M. Enoka, unpublished observations). Therefore, the difference in the location of the peak energy between the interference EMG (young: 30–70 Hz; old: 60–100 Hz) and acceleration (5–15 Hz) was not due to the 20-Hz setting on the high-pass filter in the present study. Third, although rectification increased the relative power in the 5- to 15-Hz range from 0.2–1.0 to 6–12%, the peak relative power for the rectified EMG occurred at frequencies from 20 to 40 Hz (12–22%). Fourth, the frequency content of the interference EMG, but not the rectified EMG, was significantly associated with fluctuations in acceleration. Greater fluctuations in acceleration were associated with lower median and peak-power frequencies in the interference EMG (Fig. 8).

In summary, increases in movement speed were accompanied by increased fluctuations in index finger acceleration, especially during eccentric contractions. The increase in acceleration fluctuations with movement speed was associated with a stronger modulation of acceleration at 5–10 Hz during eccentric contractions. Consistent with the minimum variance theory (18, 43), the fluctuations in acceleration impaired the ability of young and old adults to achieve the target velocity during anisometric contractions with the first dorsal interosseus muscle at various prescribed movement speeds. The association between fluctuations in acceleration and accuracy, however, was three times greater in old adults compared with young adults. The reduced ability of old adults to achieve a desired limb trajectory was associated with differences between young and old adults in the interference EMG frequency spectrum for the agonist muscle.


   ACKNOWLEDGMENTS
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
REFERENCES
 
The authors thank Anna M. Taylor for assistance with the frequency analysis and, with John G. Semmler, for comments on a draft of the manuscript.

This study was supported by National Institute on Aging Grant AG-09000 (to R. M. Enoka).


   FOOTNOTES
 

Address for reprint requests and other correspondence: E. A. Christou, Dept. of Kinesiology and Applied Physiology, Univ. of Colorado, Boulder, CO, 80309-0354 (E-mail: echristo{at}colorado.edu).

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.


   REFERENCES
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 RESULTS
 DISCUSSION
 ACKNOWLEDGMENTS
 REFERENCES
 

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