The ability of older adults to perform activities of daily living (ADL) declines with age (19). One possible reason for this decline is that older adults may require substantially greater effort than younger adults to perform similar ADL. Effort is a psychophysical construct corresponding to an individual's sense of difficulty (or lack thereof) in achieving a task in a specific way (34). Although most physical tasks can be performed in an infinite number of ways, recent research in biomechanics and motor control suggests that movement choices are not dictated entirely by physical constraints. Rather, an important factor distinguishing movements that are performed from those that are not is the level of effort associated with the movement: movements that are performed generally take less effort than those that are not (33). Because effort can play a significant role in movement selection and human performance (22), increases in sense of effort (SOE) in older versus younger individuals may contribute to decreases in mobility and the ability to perform ADL. This insight suggests that effort is an important variable to be assessed in aging populations because older individuals often have difficulty in performing (or are unable to perform) ADL. Because an increasing percentage of the population is found in older age categories, it is vital to have an understanding of age-related differences in effort during human movement. Although several investigators have asked individuals to rate their SOE while performing different, complex tasks (for reviews, see [4,31]), the majority of these studies have focused primarily on individuals under 60 yr; therefore, our grasp of age-related differences in SOE is not fully understood and there are contradictory findings. Although some studies have reported increased SOE in older individuals during physical activity (e.g., [1,20]), others have reported no differences (e.g., [2,37,39]). In addition, these previous investigations have been directed at the physiological and psychological factors that influence SOE; little research has been performed to examine the effects of aging on the biomechanics of muscular effort.
To quantify age-related differences in muscular effort from a biomechanical perspective, it is necessary to relate judgments of effort to kinematic and/or kinetic variables such as angular velocity (32), mean squared jerk (11), mean torque change (40), and peak work (38). Andrews (3) identified several biomechanical measures that appear to be most directly related to muscular effort, that is, the metabolic cost associated with producing muscle tension in a joint neighborhood; he concluded that instantaneous (peak) and interval (mean) force and torque quantities are appropriate for evaluating muscular effort during static and dynamic movements, respectively. Due to the relationship between force/torque and muscular effort, it is possible to quantify age-related changes in physical work capacity via differences in joint torque production.
The goal of this study was to examine age-related changes in muscular effort during static, single-joint upper-extremity force/torque production tasks. It was hypothesized that older individuals will produce smaller absolute (N·m) and relative [% maximal voluntary contraction (MVC)] joint torques for a given level of muscular effort and demonstrate greater muscular effort than younger individuals during isometric elbow flexion and extension joint actions. If one conceives of an individual's state as a ball in a changing effort landscape, it is necessary to return the ball to a height corresponding to an acceptable level of muscular effort for any task of importance. By quantifying muscular effort in older individuals, it will be possible to establish an effort landscape that can allow for adaptive changes in performance over a wide range of ADL and other functionally significant tasks. In addition, it will be possible to evaluate changes in muscular effort over time as a result of medical interventions or exercise training programs.
Thirty healthy, right hand dominant individuals [15 younger (8 males, 7 females) and 15 older adults (8 males, 7 females)] participated in this study. The subject characteristics are presented in Table 1. This study was approved by the Human Subjects Committee of the University of Kansas Medical Center (KUMC). Before participating in the experiment, all subjects provided written informed consent. All participants were screened to ensure that they were free from cardiovascular/cardiorespiratory, musculoskeletal, and neurological disorders that may have placed them at risk or affected their performance during the required experimental tasks. In addition, the older adults were required to complete the Mini-Mental State Examination (12); individuals with a score of 23 or less were excluded from participation in the study.
Sample size and power.
The differences in torque at each effort level across younger and older healthy adults were tested. Fifteen subjects in each group and an anticipated mean torque difference of 16 Nm will allow the detection of a significance difference in effort levels at P ≤ 0.05. This estimation was based on a pilot study in which a range of 50 Nm torque was observed corresponding to an experimental SD of 12.5 (range/4). A power calculation from this value yielded a 92% power with 15 subjects in each of the two experimental groups using the formula:
Each participant was required to visit the KUMC Georgia Holland Cardiopulmonary and Neuromuscular Research Laboratory for one experimental data collection session. To standardize testing conditions for all subjects, all experimental procedures were administered by the same researcher. Upon arrival at the laboratory, each subject participated in a warm-up activity by performing arm cranking exercise for a duration of 5 min on an upper-body ergometer (Pro II Power Trainer; Scifit Systems, Inc., Tulsa, OK), followed by 5 min of upper-body stretching exercises.
After the warm-up, the subjects were required to perform isometric elbow flexion and extension torque production tasks at both submaximal and maximal effort levels using the dominant (right) upper extremity. The participants were seated in an upright position on a dynamometer (System 3 Pro; Biodex Medical Systems, Inc., Shirley, NY) such that the elbow flexion and extension joint actions occurred in the horizontal plane to eliminate the effects of gravitational forces. The medial epicondyle of the humerus served as the bony landmark for matching the axis of rotation of the elbow joint with the axis of rotation of the dynamometer. In addition, surface electrodes (TeleMyo 900; Noraxon, Inc., Scottsdale, AZ) were placed on the subject's upper arm (biceps brachii and triceps brachii) to record muscle activity levels in the elbow flexor and extensor muscle groups. The participants then went through a brief familiarization protocol with the dynamometer by performing three submaximal effort isometric joint actions followed by three maximal effort isometric joint actions for both elbow flexion and extension tasks. An elbow joint angle of 90° was used for all subjects. The joint torque and surface EMG data were collected using MyoResearch software (Noraxon, Inc.) at 100 and 1000 Hz, respectively. The EMG data were band-pass filtered using a fourth-order zero-lag Butterworth filter with a cutoff frequency of 20-500 Hz, rectified, and integrated over the last 3 s of force production. Calibration of the dynamometer was performed according to the manufacturer's specifications before every session.
After the familiarization trials, maximal voluntary contraction (MVC) strength was determined for both isometric elbow flexion and extension tasks. The subjects were required to produce three elbow flexion and extension MVC trials, alternating between the two joint actions and with 2 min of rest in between each trial. During the MVC trials, the participants were provided with verbal encouragement along with visual feedback from the dynamometer computer monitor to achieve a maximal voluntary effort. Each MVC trial was 6 s in duration; the first 3 s allowed the subjects to ramp up to maximum joint torque production, and the last 3 s were averaged to calculate MVC strength. The mean torque across all three MVC trials was used as an estimate of the individual's MVC strength.
After a 15-min rest period following the MVC strength testing, the participants were required to perform isometric elbow flexion and extension torque production tasks at five different submaximal effort levels. The request to the subject was to perform a voluntary isometric joint action with his/her elbow joint flexors/extensors that produced a level of muscular effort that corresponded to a rating of 1, 3, 5, 7, or 9 on a modified Borg CR-10 scale, where 0 = "no effort" and 10 = "maximal effort" (see Fig. 1). This scale is similar to the one used by Burgess and Jones (5) for evaluating SOE during isometric elbow joint flexion actions. Each effort level was produced for both elbow flexion and extension joint actions. The 10 resulting conditions (2 joint actions × 5 effort levels) were tested in random order, alternating between the two joint actions and with 2 min of rest in between each trial to minimize fatigue. All participants performed one trial of each condition in two rounds. The first round was used for practice and was designed to allow the participants to experience the full range of effort levels during both joint actions. The second round was used for data collection. Once the participant indicated that he/she was ready, the researcher indicated the effort level required for that particular condition, waited for the subject to repeat the effort level, and then initiated the trial. After a "three, two, one, go" sequence of commands, the subject then produced the required effort level (1, 3, 5, 7, or 9) and held it for a duration of 6 s; the last 3 s were averaged to calculate the elbow joint torque.
To assess the effects of age (younger vs older subjects), task (elbow flexion vs extension), and effort level (1, 3, 5, 7, and 9), we performed a three-way factorial ANOVA with repeated measures separately for absolute (N·m) and relative (% MVC) elbow joint torque values as well as muscle cocontraction values. Muscle cocontraction, defined as the simultaneous activation of antagonistic muscles (biceps brachii and triceps brachii), was calculated using the integrated EMG of each muscle and the formula [(less active muscle / more active muscle) × (sum of the integrated activity of both muscles)] (35). If significant differences were identified using ANOVA, post hoc comparisons using unpaired t-tests with a Bonferroni adjustment were used to identify the specific effects of age, task, and effort level. The level of significance was set at an alpha level of P < 0.05. All statistical analysis was performed using SPSS 15.0 software (SPSS Inc., Chicago, IL).
Absolute (N·m) torque.
There was a significant main effect of age on absolute (N·m) elbow joint torque values (F1,28 = 8.80, P < 0.01). For both elbow flexion and extension tasks, the younger subjects produced significantly greater absolute elbow joint torques than the older subjects across all effort levels. During elbow flexion tasks, the joint torques ranged from 7.6 ± 5.4 to 44.4 ± 17.2 N·m and from 4.7 ± 3.3 to 23.5 ± 11.3 N·m (mean ± SD) for the younger and the older subjects, respectively, as the effort level increased from 1 to 9 (see Fig. 2A). During elbow extension tasks, the joint torques ranged from 4.7 ± 3.1 to 25.8 ± 10.9 N·m and from 3.0 ± 2.5 to 13.9 ± 6.3 N·m for the younger and the older subjects, respectively, as the effort level increased from 1 to 9 (see Fig. 2B). The younger subjects were able to produce significantly larger joint torques than the older subjects during both MVC elbow flexion (59.2 ± 24.6 vs 42.3 ± 18.4 N·m, respectively) and extension (36.8 ± 16.3 vs 25.0 ± 11.5 N·m, respectively) tasks. The main effect of task was also significant (F1,28 = 107.53, P < 0.0001). Both the younger and the older subjects produced significantly greater joint torques during elbow flexion than extension tasks across all effort levels. In addition, the main effect for effort level was significant (F5,24 = 35.00, P < 0.0001). For each increase in effort level, both the younger and the older subjects produced significantly greater joint torques during both elbow flexion and extension tasks.
There were several significant interaction effects across the main effects of age, task, and effort level. Across both age groups, the interaction between task and effort level was significant (F5,24 = 16.58, P < 0.0001). Although the younger and the older subjects both produced greater absolute joint torques during elbow flexion versus extension tasks, the difference between the two tasks increased as a function of effort level (a 2.4-N difference at effort level 1 to a 13.2-N difference at effort level 9). Across both tasks, the interaction effect between age and effort level was also significant (F5,24 = 7.15, P < 0.0005). Not only did the younger subjects produce greater absolute joint torques during both elbow flexion and extension tasks than the older subjects, but the difference between the two groups increased as a function of effort level (a 2.5-N difference at effort level 1 to a 15.6-N difference at effort level 9). In addition, the interaction effect between age and task across all effort levels (F1,28 = 3.18, P = 0.085) and the interaction effect between age, task, and effort level (F5,24 = 1.03, P = 0.42) were not significant.
Relative (% MVC) torque.
There was a significant main effect of age on relative (% MVC) elbow joint torque values (F1,28 = 24.83, P < 0.0001). For both elbow flexion and extension tasks, the younger subjects produced significantly greater relative joint torques than the older subjects across all effort levels except for effort level 1. During elbow flexion tasks, the relative joint torques ranged from 13.8% ± 5.5% to 79.6% ± 11.3% MVC and from 11.2% ± 5.4% to 56.8% ± 16.1% MVC (mean ± SD) for the younger and the older subjects, respectively, as the effort level increased from 1 to 9 (see Fig. 3A). During elbow extension tasks, the joint torques ranged from 13.7% ± 5.0% to 76.6% ± 14.9% MVC and from 11.0% ± 6.1% to 56.6% ± 15.0% MVC for the younger and the older subjects, respectively, as the effort level increased from 1 to 9 (see Fig. 3B). The main effect of effort level was also significant (F5,24 = 674.87, P < 0.0001). For each increase in effort level, both the younger and the older subjects produced significantly greater relative joint torques during both elbow flexion and extension tasks. In addition, the main effect of task was not significant (F1,28 = 0.40, P = 0.53). For both the younger and the older subjects, there were no differences between the relative joint torques produced during elbow flexion versus extension tasks across all effort levels.
There was one significant interaction effect across the main effects of age, task, and effort level. Across both elbow flexion and extension tasks, the interaction effect between age and effort level was significant (F4,25 = 4.45, P < 0.01). Not only did the younger subjects produce greater relative joint torques during both elbow flexion and extension tasks than the older subjects except for effort level 1, but the difference between the two groups increased as a function of effort level (a 2.6% MVC difference at effort level 1 to a 21.4% MVC difference at effort level 9). The interaction between task and effort level across both age groups was not significant (F4,25 = 0.40, P = 0.81); the subjects normalized joint torques were virtually identical during both elbow flexion and extension tasks at all effort levels. In addition, the interaction effect between age and task across effort levels (F1,28 = 0.10, P = 0.76) and the interaction effect between age, task, and effort level (F5,24 = 0.80, P = 0.55) were not significant.
Muscular effort scaling error.
A priori, it was reasonable to expect that relative (% MVC) joint torque values during both elbow flexion and extension tasks would be 10%, 30%, 50%, 70%, and 90% MVC for the effort levels of 1, 3, 5, 7, and 9, respectively. However, significant differences were observed between the expected and experimentally measured relative joint torques (mean ± SD) during both elbow flexion and extension tasks for both the younger and the older subjects across effort levels 1-9. This difference between the expected and the measured elbow joint torques was classified as "muscular effort scaling error" (see Fig. 4). Paired t-tests revealed significantly greater than expected joint torque values during both flexion (P < 0.05) and extension (P < 0.05) tasks for effort level 1, whereas significantly lower than expected joint torque values were found for flexion (P < 0.0005, P < 0.0001, P < 0.0001, and P < 0.0001 for effort levels of 3, 5, 7, and 9, respectively) and extension (P < 0.0001, P < 0.0001, P < 0.0001, and P < 0.0001 for effort levels of 3, 5, 7, and 9, respectively) tasks for effort levels 3, 5, 7, and 9 across all subjects. For each increase in effort level, there was significantly greater (F5,24 = 35.66, P < 0.0001) joint torque production error for both the younger and the older subjects during both elbow flexion (Fig. 4A) and extension (Fig. 4B) tasks. In addition, there was significantly greater (F1,28 = 19.67, P < 0.0001) joint torque production error by the older subjects as compared with the younger subjects during both elbow flexion (Fig. 4A) and extension (Fig. 4B) tasks.
There was a significant main effect of age on muscle cocontraction values (F1,28 = 4.24, P < 0.05). For both elbow flexion and extension tasks, the older subjects demonstrated significantly greater muscle cocontraction than the younger subjects across all effort levels. Across both tasks and all effort levels, the older subjects had a mean muscle cocontraction value of 26.8% ± 7.50% whereas the younger subjects had a mean value of 21.2% ± 7.50%. During elbow flexion tasks, the muscle cocontraction values ranged between 16.9% ± 6.1% and 22.4% ± 13.8% and between 20.9% ± 7.8% and 26.0% ± 11.0% for the younger and the older subjects, respectively (see Table 2). During elbow extension tasks, the muscle cocontraction values ranged between 22.2% ± 12.7% and 25.1% ± 15.3% and between 24.2% ± 12.6% and 39.0% ± 19.3% for the younger and the older subjects, respectively. The main effect of task was also significant (F1,28 = 6.27, P < 0.05). Both the younger and the older subjects demonstrated significantly greater muscle cocontraction values during elbow extension than flexion tasks across all effort levels. In addition, the main effect for effort level was significant (F5,24 = 14.45, P < 0.0001). For both the younger and the older subjects, there was significantly less muscle cocontraction for the highest effort level (effort level 9) than that found in the lower effort levels (effort levels 1-7); there were no differences in muscle cocontraction found between effort levels 1 and 7.
This study demonstrated that muscular effort is significantly elevated by aging during isometric elbow flexion and extension torque production tasks. The results showed that across all effort levels (except for effort level 1, very light effort), the older subjects produced lower joint torques as compared with the younger subjects for the same tasks. This implies that when older adults are asked to perform willful motor tasks, they will perceive equivalent levels of physical activity as more effortful than younger adults. It is important to note that the interpretation of our data is not confounded by age-related differences in absolute joint torque production between younger and older adults. It has been shown in previous studies that when torque is normalized to an individual's maximum capacities, it precludes the effects of absolute muscle strength differences that may be due to aging and gender (1,19,32).
Our findings on aging and muscular effort are in agreement with the results of studies by Allman and Rice (1), which examined the effects of aging on ratings of perceived exertion, and Hortobágyi et al. (19), which examined effects of aging on ADL performance. Allman and Rice (1) found age-related elevation of perceived exertion when young and older subjects performed intermittent isometric elbow flexion motor tasks to exertion at 60% MVC. Similarly, Hortobágyi et al. (19) demonstrated that older adults performed ADL tasks at levels significantly closer to their maximal capacities as compared with younger adults. However, our findings contradict the results of Taylor et al. (39). Taylor et al. (39) found no age-related differences in perceived exertion between younger and older men for sustained handgrip contractions at 30% MVC held to fatigue. The discrepancy between our findings and that of Taylor et al. (39) may be due to differences in the exercise protocols and the muscle groups used in both studies. The current study examined age-related differences during nonfatiguing isometric elbow flexion and extension tasks, whereas Taylor et al. (39) examined perceived effort ratings during isometric handgrip contractions held to exhaustion. Furthermore, a major difference between the current study and the previous studies by Allman and Rice (1) and Taylor et al. (39) is that subjects were instructed to perform nonfatiguing tasks at predetermined levels of effort rather than being asked to rate their effort after performance of fatiguing mucle contractions.
The exact mechanism responsible for age-related elevation of muscular effort has not yet been established. However, based on findings from previous aging and perceived effort studies, it appears that age-related physiological and psychophysical changes in the central nervous system are the most likely reasons for the age-related increase in muscular effort found in this study (1,23,29,36). Several studies have suggested that sense of effort is brought about by centrally generated efferent signals within descending motor commands to muscles and is proportional to the magnitude of achieved muscle force (5,13,14,24,30). It therefore appears that older adults need increased levels of descending efferent signals to working muscles to match equivalent muscular effort exerted by younger subjects, hence the observed muscular effort elevation in older adults (1,23). This hypothesis is supported by recent fMRI studies, which show that older adults recruited extracortical and subcortical areas that were not recruited by younger adults during performance of simple physical tasks (29,36,41). These possible mechanisms mediating muscular effort elevation in aging require further investigation.
This study also demonstrated that older adults have significantly lower absolute muscle force generation capacity compared with younger adults at all effort levels greater than very light effort. The difference in absolute joint torques produced by the younger and the older subjects across effort levels was to be expected because muscular strength decreases as we age. These results support previous studies that have demonstrated loss of muscular capacities with aging (9,19,25,26). Altered processing of the physiological cues for muscular effort due to age-related changes in the brain such as synaptic restructuring or loss of cortical neurons may have lead to the smaller absolute joint torques produced by the older subjects as a function of effort (1,10,15,27).
Another important finding of this study showed that a muscular effort scaling error exists within the motor system, which increases with the intensity of motor task performance. Both the younger and the older subjects demonstrated significant deviations (underscaling of effort) from theoretically expected levels of torque production as the effort level increased from 3 to 9. Our results further showed that muscular effort scaling error was elevated in the older adults. An implication of this finding suggests that when compared with younger adults, older adults will not only perceive motor tasks of higher intensity as more effortful but will also make more severe errors in their judgment of the amount of effort needed to accomplish similar motor tasks. This may significantly impact the ability of older adults to perform ADL as well as increase the risks of falls in the elderly. It is plausible that muscular effort scaling error may have contributed to the observation by Hortobágyi et al. (19) that older adults perform ADL closer to their maximal capacities as compared with younger adults.
Our finding on age-related muscular effort scaling error is in agreement with previous studies (6,7). For instance, Christou and Carlton (6) examined the ability of young and elderly individuals to control submaximum levels of force (5-90%) during continuous and rapid discrete isometric contractions of the quadriceps femoris. They found that there was more variability (error) in the older subjects during rapid discrete isometric contractions but not during continuous isometric contractions. Similarly, Christou et al. (7) reported that during the performance of 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−1), the older subjects were found to be three times less accurate than the younger subjects. In addition, the greater muscular effort scaling error in the older subjects may be due to increased muscle cocontraction as a result of elevated antagonist muscle group coactivation. This finding has been demonstrated previously in several training studies (16,17,28). Also, we found a significant main effect of age on muscle cocontraction values. Across both tasks and all effort levels, the older subjects had a mean muscle cocontraction value of 26.8% ± 7.50% whereas the younger subjects had a mean value of 21.2% ±7.50%. Therefore, the increased muscle cocontraction in the older subjects may have led to a decrease in relative joint torque production for a given effort level (i.e., an increase in muscular effort scaling error) as compared with the younger subjects.
The mechanisms responsible for muscular effort scaling error are not yet understood. However, the Task Optimization in the Presence of Signal-Dependent Noise (TOPS) model of motor control proposed by Harris and Wolpert (18) offers some insights that may help to explain the muscular effort scaling error phenomenon. The TOPS model suggests that during voluntary motor task performance, descending motor command signals to the muscles include physiological noise derived from neuronal and synaptic action potential discharges, which leads to fluctuations and variability in muscle force production. Studies of the TOPS model have shown that neuronal noise increases with the magnitude of the motor command (i.e., the intensity of a motor task) and the increases made worse with age (8,18,21). The maximal muscle torque in the current study was the average value of the last 3 s during the MVC trials. The nervous system, however, might truncate most of the fluctuations in the motor command or the force production signals so that the perceived muscle torque was lower than the measured one. This lower signal was then probably used in scaling the muscle torque at the other effort levels. A future study that examines the direct relationship of the TOPS model to the biomechanical effects of muscular effort due to aging, across varying levels of intensity, and its impact on muscular effort scaling errors is necessary.
The purpose of this study was to assess the age-related effects of the perception of muscular effort during static, single-joint torque production tasks. Findings from this study showed a significant age-related increase of muscular effort in older adults as compared with younger adults. Although the mechanisms mediating the observed age-related elevation of effort are not fully understood, there are important implications for older adults and their performance of ADL and other dynamic physical tasks. Furthermore, the results also indicate that a muscular effort scaling error exists in the motor system that increases with the intensity of effort and increases with aging. This error in scaling muscular effort needs to be further examined in future studies.
This investigation was supported by the University of Kansas General Research Fund allocations nos. 2301069 and 2301572. The results of the present study do not constitute endorsement by ACSM.
1. Allman BL, Rice CL. Perceived exertion is elevated in old age during an isometric fatigue task. Eur J Appl Physiol
2. Aminoff T, Smolander J, Korhonen O, Louhevaara V. Cardiorespiratory and subjective responses to prolonged arm and leg exercise in healthy young and older men. Eur J Appl Physiol
3. Andrews JG. Biomechanical measures of muscular effort. Med Sci Sports Exerc
4. Borg G. Borg's Perceived Exertion and Pain Scales
. Champaign (IL): Human Kinetics; 1998. p. 53-91.
5. Burgess P, Jones L. Perceptions of effort and heaviness during fatigue and during the size-weight illusion. Somatosens Mot Res
6. Christou EA, Carlton LG. Old adults exhibit greater motor output variability than young adults only during rapid discrete isometric contractions. J Gerontol A Biol Sci Med Sci
7. Christou EA, Shinohara M, Enoka RM. Fluctuations in acceleration during voluntary contractions lead to greater impairment of movement accuracy in old adults. J Appl Physiol
8. Christou EA, Tracy BL. Aging and variability in motor output. In: Movement System Variability
. Davids K, Bennett S, Newell K, editors. Champaign (IL): Human Kinetics; 2006, p. 199-295.
9. Chung SG, Van Rey EM, Bai Z, Rogers MW, Roth EJ, Zhang L-Q. Aging-related neuromuscular changes characterized by tendon reflex system properties. Arch Phys Med Rehabil
10. Earles D, Vardaxis V, Koceja D. Regulation of motor output between young and elderly subjects. Clin Neurophysiol
11. Flash T, Hogan N. The coordination of arm movements: an experimentally confirmed mathematical model. J Neurosci
12. Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for clinician. J Psychiatr Res
13. Gandevia SC. The perception of motor commands or effort during muscular paralysis. Brain
14. Gandevia SC, McCloskey DI. Interpretation of perceived motor commands by reference to afferent signals. J Physiol
15. Guttmann C, Jolesz F, Kikinis R, et al. White matter changes with normal aging. Neurology
16. Häkkinen K, Alen M, Kallinen M, Newton RU, Kraemer WJ. Neuromuscular adaptation during prolonged strength training, detraining and re-strength-training in middle-aged and elderly people. Eur J Appl Physiol
17. Hakkinen K, Kallinen M, Izquierdo M, et al. Changes in agonist-antagonist EMG, muscle CSA, and force during strength training in middle-aged and older people. J Appl Physiol
18. Harris CM, Wolpert DM. Signal-dependent noise determines motor planning. Nature
19. Hortobagyi T, Mizelle C, Beam S, DeVita P. Old adults perform activities of daily living near their maximal capabilities. J Gerontol A Biol Sci Med Sci
20. Jasperse JL, Seals DR, Callister R. Active forearm blood flow adjustments to handgrip exercise in young and older healthy men. J Physiol (Lond)
21. Jones KE, Hamilton AC, Wolpert DM. Sources of signal-dependent noise during isometric force production. J Neurophysiol
22. Jones NL, Killian KJ. Exercise limitation in health and disease. N Engl J Med
23. Kamen G, Sison SV, Du CC, Patten C. Motor unit discharge behavior in older adults during maximal-effort contractions. J Appl Physiol
24. Lafargue G, Paillard J, Lamarre Y, Sirigu A. Production and perception of grip force without proprioception: is there a sense of effort in deafferented subjects? Eur J Neurosci
25. Lanza IR, Towse TF, Caldwell GE, Wigmore DM, Kent-Braun JA. Effects of age on human muscle torque, velocity, and power in two muscle groups. J Appl Physiol
26. Lexell J. Human aging, muscle mass, and fiber type composition. J Gerontol A Biol Sci Med Sci
. 1995;50 Spec No:11-16.
27. Lexell J. Evidence for nervous system degeneration with advancing age. J Nutr
28. Macaluso A, Nimmo MA, Foster JE, Cockburn M, McMillan NC, De Vito G. Contractile muscle volume and agonist-antagonist coactivation account for differences in torque between young and older women. Muscle Nerve
29. Mattay VS, Fera F, Tessitore A, et al. Neurophysiological correlates of age-related changes in human motor function. Neurology
30. McCloskey DI, Ebeling P, Goodwin GM. Estimation of weights and tensions and apparent involvement of a "sense of effort". Exp Neurol
31. Noble BJ, Robertson RJ. Perceived Exertion
. Champaign (IL): Human Kinetics; 1996. p. 59-92.
32. Pincivero DM, Campy RM, Coelho AJ. Knee flexor torque and perceived exertion: a gender and reliability analysis. Med Sci Sports Exerc
33. Rosenbaum D, Gregory R. Development of a method for measuring movement-related effort. Exp Brain Res
34. Rosenbaum DA, van Heugten CM, Caldwell GE. From cognition to biomechanics and back: the end-state comfort effect and the middle-is-faster effect. Acta Psychol (Amst)
35. Rudolph KS, Axe MJ, Buchanan TJ, Scholz JP, Snyder-Mackler L. Dynamic stability in the anterior cruciate ligament deficient knee. Knee Surg Sport Traumatol Arthrosc
36. Sailer A, Dichgans J, Gerloff C. The influence of normal aging on the cortical processing of a simple motor task. Neurology
37. Smolander J, Aminoff T, Korhonen I, et al. Heart rate and blood pressure responses to isometric exercise in young and older men. Eur J Appl Physiol
38. Soechting JF, Buneo CA, Herrmann U, Flanders M. Moving effortlessly in three dimensions: does Donders' law apply to arm movement? J Neurosci
39. Taylor JA, Hand GA, Johnson DG, Seals DR. Sympathoadrenal-circulatory regulation during sustained isometric exercise in young and older men. Am J Physiol Regul Integr Comp Physiol
40. Uno Y, Kawato M, Suzuki R. Formation and control of optimal trajectories in human multijoint arm movements: minimum torque-change model. Biol Cybern
41. Ward NS, Frackowiak RSJ. Age-related changes in the neural correlates of motor performance. Brain