- Research article
- Open Access
- Open Peer Review
This article has Open Peer Review reports available.
Different ankle muscle coordination patterns and co-activation during quiet stance between young adults and seniors do not change after a bout of high intensity training
© Donath et al.; licensee BioMed Central. 2015
Received: 9 December 2014
Accepted: 17 February 2015
Published: 4 March 2015
Available evidence suggests that young adults and seniors use different strategies to adjust for increasing body sway during quiet standing. Altered antagonist muscle co-activation and different ankle muscle coordination patterns may account for this finding. Consequently, we aimed at addressing whether aging leads to changes in neuromuscular coordination patterns as well as co-activation during quiet stance. We additionally investigated whether a bout of high intensity interval training additionally alters these patterns.
Twenty healthy seniors (age: 70 ± 4 y) and twenty young adults (age: 27 ± 3 y) were enrolled in the present study. In between the testing procedures, four consecutive high-intensity intervals of 4 min duration at a target exercise intensity of 90 to 95% HRmax were completed on a treadmill. The total center of pressure (COP) path length displacement served as standing balance performance outcome. In order to assess ankle muscle coordination patterns, amplitude ratios (AR) were calculated for each muscle (e.g. tibialis anterior (TA) [%] = (TA × 100)/(gastrocnemius medialis (GM) + soleus (SOL) + peroneus longus (PL) + TA). The co-activation was calculated for the SOL and TA muscles computing the co-activation index (CAI = 2 × TA/TA + SOL).
Seniors showed an inverted ankle muscle coordination pattern during single limb stance with eyes open (SLEO), compared to young adults (rest: GM, S: 15 ± 8% vs Y: 24 ± 9%; p = 0.03; SOL, S: 27 ± 14% vs Y: 37 ± 18%; p = 0.009; TA, S: 31 ± 13% vs Y: 13 ± 7%; p = 0.003). These patterns did not change after a high-intensity training session. A moderate correlation between amplitude ratios of the TA-contribution and postural sway was observed for seniors during SLEO (r = 0.61). Ankle co-activation was twofold elevated in seniors compared to young adults during SLEO (p < 0.001). These findings were also not affected by high intensity training.
Increased ankle co-activation in the anterior-posterior plane and inverted ankle muscle coordination pattern merely occurred during single-leg stance. Seniors with decreased postural control showed higher TA contributions during SLEO. These neuromuscular changes are not affected by acute intermittent high intensity aerobic exercise.
Beside numerous external fall risk factors (e.g. lack of handrail, uneven terrain, twilight, obstacles), a body of evidence also emphasized that personal or intrinsic risk factors (e.g. visual impairment, medication intake, strength deficits of the lower limb, increased spatio-temporal gait variability and impaired balance performance) cause an elevated risk of falling in older people [1-3]. An aging-induced loss of vestibular, visual, somatosensory and neuromuscular function has been reported to result in deteriorated postural control with an increased postural sway during standing balance tasks in the elderly . For example, diminished peripheral perception, delayed spinal reflex-loop recruitment, higher muscle activity levels with increased muscular co-activation and decreased spinal reflex transmission are considered to mainly account for deteriorated standing balance performance in seniors [5,6].
Postural sway serves as an appropriate outcome measure to examine postural control under static balance conditions. Thereby, single and double limb standing have been frequently applied . The base of support and different sensory conditions can be modified in order to provide adequate progression . Many studies indicated that the process of aging leads to declines in static postural control under various conditions .
Although muscle activity, postural control strategies (e.g. hip vs. ankle) and neuromuscular adaptations to balance training were previously examined in seniors , age-related differences of ankle muscle coordination and ankle-co-activation patterns have not yet been cross-sectionally examined during resting states and following an intense bout of aerobic exercise training. Several studies indicated that aerobic exercise training can lead to transient impairments of postural control [11-13]. It is, however, not clear to date whether underlying changes of muscle coordination account for these increases of postural sway. Although it seems well known that increased antagonist muscle co-activation in the elderly provides mechanical stability via stiffening joints and reducing degrees of freedom during balance tasks during several standing and walking tasks [10,14], these indices were not yet addressed after intense exercise. These altered age-related neuromuscular adaptations of ankle muscles to dynamic constraints are not necessarily present during static balance tasks or after an acute bout of intense exercise. Thus, the acute impact of intense exercise training on ankle muscle co-activation and ankle muscle coordination patterns during mono- and bipedal stance needs to be more clearly disentangled.
Against the aforementioned background, the present study aimed at investigating the relative contribution of ankle muscles to uni- and bipedal standing balance tasks in young and old adults during rest and after one bout of a single session of high-intensity interval training (HIIT). Due to previously reported age-specific postural strategies to maintain standing balance , we assume that seniors may also reveal different patterns of ankle muscle activity during rest compared to young adults. Since maximal exercise deteriorate postural control , we further presume that these ankle muscle coordination patterns in seniors are becoming more distinctive after exhaustive exercise and putative muscle-coordination pattern changes could be linked to acute exercise-induced elevations of postural sway.
We additionally intended to elucidate in which way intense exercise and aging affect ankle muscle co-activation. The present study may contribute to a better understanding of aging- and exercise-induced changes of ankle muscle coordination and co-activation. Thus, balance training approaches in seniors should be tailored to the specifities of aging-specific of ankle muscle coordination.
Study design and participants
Twenty healthy and physically active seniors older than 65 years (female/male: 12/8, age: 70 ± 4 y; body mass index: 25.0 (3.6) kg/m2 (mean (SD)); Body fat: 27.0 (9.1) %; physical activity: 10.9 (5.8) h/week) and twenty young and active adults (female/male: 9/11, age: 27 ± 3 y; body mass index: 22.4 (2.2) kg/m2; body fat: 17.9 (5.9) %; physical activity: 8.7 (4.1) h/week) were enrolled in the present study. All participants did not report any medication intake and health impairments that may affect balance and muscle activity testing. Seniors with diabetes, untreated hypertension (>180/110 mmHG), glaucoma, endoprosthesis, stroke, eczema and beta-blocker users were not included in the study. Static balance and muscle activity data were collected on two days one week apart. The first day served as familiarisation day for balance testing and to perform maximal exercise testing in order to derive maximum heart rate (HRmax). The second testing day (one week later) was conducted to perform HIIT. Balance and muscle activity data were collected immediately before and after HIIT. The study was approved by the local ethics committee (Ethikkommission beider Basel (EKBB), approval number 257/12) and fulfilled the criteria of the declaration of Helsinki. All participants signed an informed written consent prior to the start of the study.
Testings and analyses
Standing balance was tested during double limb stance with eyes closed (DLEC) and single limb stance with eyes open (SLEO) on a piezoelectric force-plate (Kistler, Type 9286, Winterthur, Switzerland). The task order was randomly assigned. Three attempts for each standing condition were achieved. The average of the performed trials was included into further analyses. Participants were standardizely instructed to perform without shoes, with feet placed shoulder width apart, hands attached at the hip and slightly bent knees. Additionally, they were controlled to keep the trunk in an upright position. Data were collected for 10 s at 40 Hz and analysed off-line using a low pass cut-off frequency of 10 Hz . The total center of pressure (COP) path length displacement served as outcome measure.
Ankle muscle surface electromyography (mm. soleus, SOL; medial head of gastrocnemius, GM; tibialis anterior, TA; peroneus longus, PL) was measured according to the European recommendations for surface electromyography (SENIAM). To provide a skin conductance level of <5kΩ, the skin of the dominant leg, determined by means of the lateral preference inventory  was gently prepared (shavers and fine sandpaper). Raw electromyographic data were processed off-line using custom-made algorithms in MATLAB (The Mathworks, Natick, USA). After correcting possible offsets, removing 50 Hz and odd-numbered harmonics of the signals, a 20 Hz high-pass and a 400 Hz low-pass filter were applied, respectively (Kurz et al. ). Muscle activity was calculated with a moving root mean square (RMS) window of 0.2 s resulting in a total of 99 RMS values representing the envelope. Mean activity of the envelope was considered for further analysis, separately for each muscle, condition and trial. The average of the related EMG-signals of the three trials for each standing condition was included into analyses. In order to assess ankle muscle coordination patterns, the amplitude ratios (AR) were calculated  for each muscle (e.g. TA [%] = (TA × 100)/(GM + SOL + PL + TA)) . The co-activation was calculated for the soleus (SOL) and tibialis anterior (TA) muscles computing the co-activation index (CAI = 2 × TA/TA + SOL). This equation assumes that TA is acting as an antagonist. Through this CAI a relative measure (arbitrary units, 0 indicating no co-activation) of TA contribution to total activation of both ankle muscles during the standing is provided.
Four consecutive high-intensity intervals of 4 min duration at a target exercise intensity of 90 to 95% HRmax were completed on a treadmill. Outcome variables were computed before and after the acute exercise intervention, The respective interval bouts were interspersed with active rest periods of 3 min at 70% HRmax . In order to stay in between the required range of heart rate, treadmill inclination and velocity were adjusted if necessary. Seniors walked briskly with inclination to avoid locomotor or coordinative limitations. The young adults were allowed to run. Heart rate and gas exchange data were continuously measured.
Two separate 2 (age: seniors vs. young adults) × 2 (condition: pre vs. post) × 4 (muscle: GM, SOL, PL, TA) repeated measures analyses of variance (rANOVA) were computed for the COP as well as AR variables during SLEO and DLEC. Similarly, 2 (age: seniors vs. young adults) × 2 (condition: pre vs. post) rANOVA were calculated for the CAI during both stance conditions (SLEO, DLEC). To estimate practical relevance, partial eta squared (ηp2) were calculated for the rANOVA of the respective interaction effects. Thereby, ηp2 ≥ 0.01 indicates a small, ≥ 0.06 a medium and ≥ 0.14 a large effect . In case of statistically significant interaction terms, Tukey HSD post hoc tests were calculated. Cohen’s d (standardized mean difference) was calculated for the between-group effect size for each muscle (trivial: d < 0.2, small: 0.2 ≤ d < 0.5, moderate: 0.5 ≤ d < 0.8, large: d ≥ 0.8). Correlations between total COP path lengths and activation ratios were examined using Pearson’s product–moment correlation. Data are reported as means with standard deviations. Gender, body mass index and physical activity were additionally considered as covariates and did not affected the results.
We did not find differences of COP path length displacements between groups from pre to post after conducting the acute HIIT intervention for DLEC (0.30 < p < 0.80, ηp2 < 0.04) and SLEO (0.38 < p < 0.98, ηp2 < 0.03).
Regarding DLEC, neither interaction effects including the factor “condition” (0.41 < p < 0.49; 0.02 < ηp2 < 0.03) nor muscle × age interactions were found (p = 0.14, ηp2 = 0.05) (Figure 1C, D).
The present study revealed for the first time that seniors showed an inverted ankle muscle coordination patterns during static single-limb standing compared to young adults. The occurrence and magnitude of the age-specific ankle muscle coordination patterns during SLEO and DLEC did not change after a single HIIT session in both groups. Whereas young adults seem to maintain single limb standing with a higher percentage contribution of posterior ankle muscles (soleus and gastrocnemius muscles), seniors ankle muscle coordination pattern rely on the anteriorly located tibialis muscle. Interestingly, COP path lengths did not changed after HIIT in both groups. Elevated postural sway during SLEO led to higher relative contribution of the tibialis muscle in the elderly. These patterns were, however, not present during double limb stance with closed eyes and did not alter after an intense bout of highly intense aerobic interval exercise. Similar findings were observed for the co-activation indices: Higher tibialis/soleus muscle co-activations during single limb standing balance which were not present during double limb standing and not affected by HIIT.
Regarding ankle muscle coordination patterns, amplitude ratios for the back-sided ankle muscles (GM + SOL) decreased for about 20% at rest and 30% after HIIT during SLEO in seniors compared to young adults. Merely considering percentage contribution does not clarify the origin of activity changes. Thus, tibialis AR increases might be a result of increased TA activity or, in turn, decreases of plantar flexor activity. In turn, the percentage contribution of the TA muscle increased for about 20% at rest and 18% after HIIT during SLEO. This inverted ankle muscle coordination pattern might reflect (a) the frequently used hip-strategy in seniors which is possibly accompanied with deteriorated postural control and/or (b) a higher TA/SOL muscle co-activation that has been reported to be associated with postural sway . It seems plausible that a larger body sway modulated by the hip can provoke a backward shift of the lower extremity resulting in a greater activity of the TA. Similar shifts to a more TA-related coordination pattern have been observed in a clinical population with considerably deteriorated static balance performance during easy double-limb stance conditions with open eyes . Corroboratively, a posterior shift of the COP has been proposed to account for this finding in the study of Kurz and coworkers . However, we did not measure hip or ankle movements by kinematic analyses to address this issue with certainty. The positive linear relationship between postural sway and percentage TA contribution to SLEO stance underpins the importance of TA activation to adjust for increased body sway. One may indirectly conclude that decreased postural control with larger body sway cause higher TA/SOL co-activation and may induce the hip-strategy to maintain balance with a higher percentage contribution of the tibialis muscle. In turn, younger subjects might be more capable to adjust postural destabilizations by using the ankle strategy due to a potentially more efficient sensori-motor integration . The hip-strategy, however, seems to allow a faster response to adjust COP displacements for the elderly. In contrast, independent from age, double leg standing with suppressed visual feedback on a stable base of support does not change ankle muscle activation patterns. It seems likely that the difficulty of tasks leading to increased sway path may result in changes in muscle activity patterns due to changes in the adjustment strategy (ankle vs. hip).
Taking the results after the acute HIIT intervention into account, the inverted ankle muscle coordination pattern did not change as a result of exhaustive endurance exercise, neither in young nor in healthy elderly persons. Although several studies revealed increased postural sway after moderate cycling  and exhaustive walking  in seniors, an indirect link between exercise-induced increases of postural sway and changes of ankle muscle coordination patterns should be handled with caution. It seems more likely that age-induced changes of postural strategies account for changes of relative muscle activity contribution of the ankle, independent from the mode of exercise. Thus, it would be reasonable to assume that muscle fatigue after endurance exercise lead to depressed proprioception (decreased spindle afferent fibre discharge) with decreased γ-motoneurone activity consistently in all muscles that are involved during upright stance [23,24]. To date, however, no studies investigated the influence of acute and chronic exercise on muscle coordination pattern. These studies are mandatorily required to better understand the interrelation between aging, balance training and postural control strategies and muscle coordination. Therefore, dynamic, kinematic and electromyographic methods should be integratively employed in future studies.
Increasing co-activation has been frequently reported in the elderly . Elevated co-activation is considered to increase joint stiffness and a stiffer joint, in turn, shows reduced degrees of freedom that need to be integratively organized by the sensori-motor system . As a consequence, higher joint stability during dynamic tasks has been assumed. There is no conclusive evidence available on the interrelation between co-activation, acute exercise effects and postural sway under static balance condition [10,26,27]. It is still unclear whether exercise affects co-activation and elevated co-activation leads to higher postural sway or, in turn, decreased postural control lead to higher co-activation, also after exercise. Although Collins et al. as well as Laughton and coworkers emphasized early, that increased muscle co-activation may account for increases of short-term postural sway [10,28], only few randomized controlled trials examined the interdependency between improvements of balance performance and changes of ankle co-activation in the elderly . Interestingly, the latter study revealed that training-induced balance improvements lead to decreased co-activation under dynamic balance conditions (e.g. functional reach). It appears likely that elevated co-activation during balance tasks are more a compensatory strategy to counteract aging-related muscle weakness or detraining . This seems to be particularly true for the tibialis anterior muscle. The neuromuscular properties (e.g. firing rate twitch contraction duration) of the TA muscle are tremendously changing with aging and are additionally regarded as major contributors to fall incidences [29,30]. Although ageing is accompanied with muscle atrophy, force generation of plantar flexors seems to be unaffected . However, due to basically lower muscle volume of TA compared with triceps surae muscle group  even a high CAI does not necessarily reflect a balanced mechanical state . Increased co-activation of the TA and SOL has been reported to facilitate muscle spindle proprioceptive function by increasing fibre recruitment and firing rates of primary afferents . Since muscle fatigue seems to diminish muscle spindle function, we expected higher co-activation after exercise . However, an acute bout of intense exercise does not seem to adversely affect proprioceptive function. Thus, increases of postural sway after intense exercise does not necessarily affect the co-activation interplay between the tibialis and soleus muscles.
However, some limitations need to be addressed. The included subjects were highly active and did not reflect a very fall-prone population. The generalizability and transferability to older and frail subjects might be limited. It is reasonable to assume that frail and less active older adults might show inverted activity patterns during double limb stance. This finding is particularly important since muscle activity data provide large baseline variability. Small effects cannot be detected sufficiently. Although shorter data collection periods (<20 seconds) can yield a transient time signal shift that may affect COP assessment , we refrained from collecting longer time frames since a majority of seniors are unable to stand longer than 10 seconds . However, the acute effects during SLEO were large and not affected by this statistical power issue. Moreover, kinematic measures were not included. Also EMG applications of the trunk muscles were not employed. Thus, we can only speculate on potential underlying postural strategies. Further cross-sectional and longitudinal studies need to be conducted in order to address changes of trunk muscle activity and kinematics in more frail subjects before and after balance training interventions.
Ankle joint muscle coordination and TA/SOL co-activation during single leg standing with open eyes seems to be affected by age but not inevitably by intense aerobic exercise. Although several studies revealed increases of postural sway after submaximal cycling or exhaustive walking in seniors, an increased exercise-induced body sway is neither linked to modulated ankle muscle coordination pattern nor co-activation. Although this finding might be of relevance for balance training programs in seniors, training recommendations from young adults are not necessarily applicable to seniors and vice versa. It might be hypothesized that a progressive training approach for seniors should start with different forms of supported single leg stance with open eyes in order to overcome the altered activity of ankle muscles and ensure a more stable situation for advanced postural tasks. Adequately developed future balance training regimes could then improve postural strategies in the elderly to better adapt to external perturbations and balance study implications for balance training to improve fall-risk factors in seniors.
The present study was not financially supported. No conflict of interest has to be declared. We appreciate the engagement of the participants and thank Tobias van Baarsen and Claudia Egli for their helpful research assistance.
- de Menezes RL, Bachion MM. Study of intrinsic risk factors for falls in institutionalized elderly people. Cien Saude Colet. 2008;13(4):1209–18.View ArticlePubMedGoogle Scholar
- Granacher U, Muehlbauer T, Gollhofer A, Kressig RW, Zahner L. An intergenerational approach in the promotion of balance and strength for fall prevention - a mini-review. Gerontology. 2011;57(4):304–15.View ArticlePubMedGoogle Scholar
- Granacher U, Gruber M, Gollhofer A. Force production capacity and functional reflex activity in young and elderly men. Aging Clin Exp Res. 2010;22(5–6):374–82.View ArticlePubMedGoogle Scholar
- Manchester D, Woollacott M, Zederbauer-Hylton N, Marin O. Visual, vestibular and somatosensory contributions to balance control in the older adult. J Gerontol. 1989;44(4):M118–27.View ArticlePubMedGoogle Scholar
- Barry BK, Carson RG. The consequences of resistance training for movement control in older adults. J Gerontol A Biol Sci Med Sci. 2004;59(7):730–54.View ArticlePubMedGoogle Scholar
- Baudry S, Duchateau J. Age-related influence of vision and proprioception on Ia presynaptic inhibition in soleus muscle during upright stance. J Physiol. 2012;590(Pt 21):5541–54.View ArticlePubMedPubMed CentralGoogle Scholar
- Donath L, Roth R, Zahner L, Faude O. Testing single and double limb standing balance performance: comparison of COP path length evaluation between two devices. Gait Posture. 2012;36(3):439–43.View ArticlePubMedGoogle Scholar
- Muehlbauer T, Roth R, Bopp M, Granacher U. An exercise sequence for progression in balance training. J Strength Cond Res. 2012;26(2):568–74.View ArticlePubMedGoogle Scholar
- Muehlbauer T, Besemer C, Wehrle A, Gollhofer A, Granacher U. Relationship between strength, power and balance performance in seniors. Gerontology. 2012;58(6):504–12.View ArticlePubMedGoogle Scholar
- Laughton CA, Slavin M, Katdare K, Nolan L, Bean JF, Kerrigan DC, et al. Aging, muscle activity, and balance control: physiologic changes associated with balance impairment. Gait Posture. 2003;18(2):101–8.View ArticlePubMedGoogle Scholar
- Donath L, Zahner L, Roth R, Fricker L, Cordes M, Hanssen H, et al. Balance and gait performance after maximal and submaximal endurance exercise in seniors: is there a higher fall-risk? Eur J Appl Physiol. 2013;113(3):661–9.View ArticlePubMedGoogle Scholar
- Donath L, Kurz E, Roth R, Hanssen H, Schmidt-Trucksass A, Zahner L. Does a single session of high-intensity interval training provoke a transient elevated risk of falling in seniors and adults? Gerontology. 2015;61(1):15–23.View ArticlePubMedGoogle Scholar
- Stemplewski R, Maciaszek J, Salamon A, Tomczak M, Osinski W. Effect of moderate physical exercise on postural control among 65–74 years old men. Arch Gerontol Geriatr. 2012;54(3):e279–83.View ArticlePubMedGoogle Scholar
- Tucker MG, Kavanagh JJ, Barrett RS, Morrison S. Age-related differences in postural reaction time and coordination during voluntary sway movements. Hum Mov Sci. 2008;27(5):728–37.View ArticlePubMedGoogle Scholar
- Liaw MY, Chen CL, Pei YC, Leong CP, Lau YC. Comparison of the static and dynamic balance performance in young, middle-aged, and elderly healthy people. Chang Gung Med J. 2009;32(3):297–304.PubMedGoogle Scholar
- Coren S. The lateral preference inventory for measurement of handedness, footedness, eyedness, and earedness: norms for young adults. Bull Psych Soc. 1993;31(1):1–3.View ArticleGoogle Scholar
- Kurz E, Anders C, Herbsleb M, Puta C, Czepa D, Hilberg T. Ankle muscle activation in people with haemophilia. Haemophilia. 2012;18(6):948–54.View ArticlePubMedGoogle Scholar
- Edgerton VR, Wolf SL, Levendowski DJ, Roy RR. Theoretical basis for patterning EMG amplitudes to assess muscle dysfunction. Med Sci Sports Exerc. 1996;28(6):744–51.View ArticlePubMedGoogle Scholar
- Helgerud J, Hoydal K, Wang E, Karlsen T, Berg P, Bjerkaas M, et al. Aerobic high-intensity intervals improve VO2max more than moderate training. Med Sci Sports Exerc. 2007;39(4):665–71.View ArticlePubMedGoogle Scholar
- Cohen J. Statistical power analysis for the behavior sciences. 2nd ed. New Jersey: Lawrence Erlbaum Associates; 1988.Google Scholar
- Freitas SM, Duarte M. Joint coordination in young and older adults during quiet stance: effect of visual feedback of the center of pressure. Gait Posture. 2012;35(1):83–7.View ArticlePubMedGoogle Scholar
- Horak FB, Shupert CL, Mirka A. Components of postural dyscontrol in the elderly: a review. Neurobiol Aging. 1989;10(6):727–38.View ArticlePubMedGoogle Scholar
- Hagbarth KE, Macefield VG. The fusimotor system. Its role in fatigue. Adv Exp Med Biol. 1995;384:259–70.View ArticlePubMedGoogle Scholar
- Nardone A, Tarantola J, Giordano A, Schieppati M. Fatigue effects on body balance. Electroencephalogr Clin Neurophysiol. 1997;105(4):309–20.View ArticlePubMedGoogle Scholar
- 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. 2002;25(6):858–63.View ArticlePubMedGoogle Scholar
- Nagai K, Yamada M, Tanaka B, Uemura K, Mori S, Aoyama T, et al. Effects of balance training on muscle coactivation during postural control in older adults: a randomized controlled trial. J Gerontol A Biol Sci Med Sci. 2012;67(8):882–9.View ArticlePubMedGoogle Scholar
- Nagai K, Yamada M, Uemura K, Yamada Y, Ichihashi N, Tsuboyama T. Differences in muscle coactivation during postural control between healthy older and young adults. Arch Gerontol Geriatr. 2011;53(3):338–43.View ArticlePubMedGoogle Scholar
- Collins JJ, De Luca CJ, Burrows A, Lipsitz LA. Age-related changes in open-loop and closed-loop postural control mechanisms. Exp Brain Res. 1995;104(3):480–92.View ArticlePubMedGoogle Scholar
- Connelly DM, Rice CL, Roos MR, Vandervoort AA. Motor unit firing rates and contractile properties in tibialis anterior of young and old men. J Appl Physiol (1985). 1999;87(2):843–52.Google Scholar
- McNeil CJ, Doherty TJ, Stashuk DW, Rice CL. Motor unit number estimates in the tibialis anterior muscle of young, old, and very old men. Muscle Nerve. 2005;31(4):461–7.View ArticlePubMedGoogle Scholar
- Kubo K, Ishida Y, Komuro T, Tsunoda N, Kanehisa H, Fukunaga T. Age-related differences in the force generation capabilities and tendon extensibilities of knee extensors and plantar flexors in men. J Gerontol A Biol Sci Med Sci. 2007;62(11):1252–8.View ArticlePubMedGoogle Scholar
- Fukunaga T, Roy RR, Shellock FG, Hodgson JA, Edgerton VR. Specific tension of human plantar flexors and dorsiflexors. J Appl Physiol (1985). 1996;80(1):158–65.Google Scholar
- Billot M, Simoneau E, Van Hoecke J, Martin A. Coactivation at the ankle joint is not sufficient to estimate agonist and antagonist mechanical contribution. Muscle Nerve. 2010;41(4):511–8.View ArticlePubMedGoogle Scholar
- Cordo P, Inglis JT, Verschueren S, Collins JJ, Merfeld DM, Rosenblum S, et al. Noise in human muscle spindles. Nature. 1996;383(6603):769–70.View ArticlePubMedGoogle Scholar
- Carpenter MG, Frank JS, Winter DA, Peysar GW. Sampling duration effects on centre of pressure summary measures. Gait Posture. 2001;13(1):35–40.View ArticlePubMedGoogle Scholar
- Macrae PG, Lacourse M, Moldavon R. Physical performance measures that predict faller status in community-dwelling older adults. J Orthop Sports Phys Ther. 1992;16(3):123–8.View ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.