- Research article
- Open Access
- Open Peer Review
This article has Open Peer Review reports available.
Upper limb position control in fibromyalgia
© Bardal et al.; licensee BioMed Central Ltd. 2012
Received: 13 December 2011
Accepted: 20 September 2012
Published: 24 September 2012
Motor problems are reported by patients with fibromyalgia (FM). However, the mechanisms leading to alterations in motor performance are not well understood. In this study, upper limb position control during sustained isometric contractions was investigated in patients with FM and in healthy controls (HCs).
Fifteen female FM patients and 13 HCs were asked to keep a constant upper limb position during sustained elbow flexion and shoulder abduction, respectively. Subjects received real-time visual feedback on limb position and both tasks were performed unloaded and while supporting loads (1, 2, and 3 kg). Accelerations of the dominant upper limb were recorded, with variance (SD of mean position) and power spectrum analysis used to characterize limb position control. Normalized power of the acceleration signal was extracted for three frequency bands: 1–3 Hz, 4–7 Hz, and 8–12 Hz.
Variance increased with load in both tasks (P < 0.001) but did not differ significantly between patients and HCs (P > 0.17). Power spectrum analysis showed that the FM patients had a higher proportion of normalized power in the 1–3 Hz band, and a lower proportion of normalized power in the 8–12 Hz band compared to HCs (P < 0.05). The results were consistent for all load conditions and for both elbow flexion and shoulder abduction.
FM patients exhibit an altered neuromuscular strategy for upper limb position control compared to HCs. The predominance of low-frequency limb oscillations among FM patients may indicate a sensory deficit.
Fibromyalgia (FM) is a chronic pain syndrome with complex etiology, characterized by widespread muscle pain and undue muscle fatigue. Several studies indicate that FM symptoms are associated with alterations in central processing of sensory feedback[1–4].
FM patients commonly report motor problems such as poor balance and coordination, clumsiness, tremors, and slowness of movements. However, motor problems are mainly self-reported, and few studies have investigated the characteristics of motor performance in FM patients. Studies of motor control in FM patients have shown a lower rate of change in the electromyographic mean spectral frequency of biceps brachii during sustained elbow flexion and an altered activation pattern of different regions within the trapezius muscle during sustained shoulder elevation. Gerdle and co-workers have also found that differences between FM patients and healthy controls (HCs) in firing rate, muscle fiber conduction velocity and differential activation of the trapezius muscle are load dependent. However, neither of the abovementioned studies investigated whether the altered muscle activation patterns were accompanied by alterations in upper limb motor performance.
To optimize upper limb motor performance during fine motor tasks, the intrinsic tendency of the human motor system to oscillate (tremor) must be minimized. The amplitude of these oscillations can be used as an index of stability. Limb oscillations or rhythmic muscle contractions and relaxations occur as a result of the synaptic input to the motor neuron pool. Alterations in sensory information will therefore have the potential to influence the common drive and, thereby, the spectral power distribution of the limb oscillations. In addition to the neural processes causing the synchronization of motor unit firing, the amplitude and frequency content of the oscillations is dependent on mechanical properties of the limbs[12–14]. Low frequency oscillations (<7 Hz) are assumed to be influenced by voluntary, mechanical, and reflexive factors, whereas the most common range of physiological tremor (8–12 Hz) is likely to be centrally mediated[12, 13, 15–18]. Although the physiological correlates to the different oscillatory frequencies are not fully understood the power distribution between different frequencies may still provide important information about the underlying neural processes that might induce alterations in neuromuscular control in chronic pain syndromes.
The purpose of this study was to investigate upper limb position control in patients with FM and HCs during sustained isometric contractions. Related to the motor problems commonly reported by FM patients we hypothesize that the patient group will show higher amplitude oscillations than HCs. Limb position control was tested in the elbow and shoulder joint to evaluate consistency between upper limb joints with four different load levels to reveal any dependency on mechanical load or muscle strength. Limb oscillations were recorded with accelerometers and the signal was analysed in the time domain by variance and in the frequency domain by power spectrum analysis.
Subject characteristics of fibromyalgia (FM) patients and healthy controls (HCs)
FM patients (n = 15)
HCs (n = 13)
Body mass (kg)
Upper arm girth (cm)
Epicondylar humerus width (cm)
Neck/shoulder pain before testing (VAS)
Neck/shoulder pain after testing (VAS)
No. of tender points
Years since diagnosed
Intensity of neck/shoulder pain was assessed using the Visual Analogue Scale (VAS) before and after testing. Epicondylar humerus width and relaxed upper arm girth were recorded as described by MacDougall and co-workers. In brief, the humerus width was measured as the distance between the lateral and medial epicondyles of the humerus, and the upper arm girth was measured at the mid-acromiale-radiale distance. Dominant arm was assessed using Edinburgh handedness inventory. In addition, FM patients answered the Fibromyalgia Impact Questionnaire (FIQ).
The study protocol was approved by the Regional Committee for Ethics in medical research (project no. 4.2008.2115) and all participants signed an informed consent before enrolment. The study was carried out according to the Declaration of Helsinki.
Experimental setup and procedure
The acceleration signal is determined by two components; the gravitational force and changes in the velocity of the accelerometer. The effect of the gravitational force is dependent on the orientation of the accelerometer in space, which forms a robust signal which we have calibrated to arm position (degrees). Since we used an isometric task, the main component of the acceleration signal was determined by arm position and was therefore used for feedback. The small variations around this main gravitational component are caused by the actual acceleration of the limb.
Force output during isometric maximal voluntary contractions (MVCs) was recorded with two force transducers (Interface Inc. Scottsdale, Arizona). The subjects wore a forearm orthosis where the force transducers were attached with non-elastic polyester bands at a standardized distance from the elbow joint rotation centre. The same sites were used for load attachments (Figure1b). The force transducers were attached to adjustable rails at the side of the chair, ensuring that all subjects pulled vertically in the transducers.
The subjects performed three MVCs with 3–5 s duration, separated by 1 min rest. As in the position tasks the elbow flexion task was performed unilaterally and the shoulder abduction task was performed bilaterally. The subjects were verbally encouraged to apply maximal effort during the MVCs. Maximal force level was defined by the highest achieved force level in the dominant arm across the MVCs. Isometric MVC was recorded after the position task to avoid post-activation potentiating.
Data analysis was performed in the time domain, investigating the amount of position variability, and the frequency domain, investigating the oscillatory structure of the variability. All analysis was computed in Matlab (version 7.8.0., Mathworks, Nattick, USA).
Both the acceleration and the force signal were sampled at 1000 Hz. The first 10 s and the last 5 s of the limb stability trials were removed from the data set. The vertical component of the accelerometer signal is used in all analysis. Because of the orientation of the accelerometer on the segment, this component represents acceleration perpendicular to the longitudinal axis of the segment. The acceleration signal was filtered with an orthogonal wavelet filter. The force signal was filtered with a 10 Hz 8th order Butterworth low pass filter.
In the time domain, standard deviation (SD) of the acceleration signal was calculated to indicate variance in limb position. In the frequency domain, the power spectrum was calculated using Welch’s averaged, modified periodogram method. The Goertzel algorithm was used to divide the data into bins of 1 Hz, ranging from 1–25 Hz. The power within each bin was normalized to percent of total power. Normalized power were extracted from three frequency bands, i.e., a low frequency band (1–3 Hz), a middle frequency band (4–7 Hz), and a high frequency band (8–12 Hz). These frequency bands covered approximately 90% of the energy of the 1–25 Hz power spectrum. The main outcome variables from the frequency domain analysis were normalized power within the three frequency bands.
Descriptive statistics including mean, standard deviation (SD), and 95% confidence interval (95% CI) were calculated for the main outcome variables. A mixed design repeated measures ANOVA (2x4) was used to investigate the effect of group (two levels; HCs and FM patients) and load (four levels; 0, 1, 2, and 3 kg) on SD of mean limb position and normalized power within the three frequency bands. Group by load interactions were also tested. When the assumption of sphericity was violated, significance was adjusted using the Greenhouse-Geisser method. Independent samples tests were used to investigate between-group differences within the different load levels. The independent samples t-test was used to test differences between groups for normally distributed data while the Mann–Whitney U test was used to test group differences for non-normally distributed data (3 of 46 parameters were not normally distributed). Spearman’s ρ was used to assess correlations between anthropometric variables and normalized power within the three frequency bands. All tests were performed two-tailed and statistical significance was accepted at P < 0.05 for all comparisons.
The FM patients had similar age, but were heavier than the HCs, had a larger upper arm girth, and higher self-reported neck/shoulder pain (Table1). All subjects performed the required tasks without difficulties, and the FM patients did not report any significant change in shoulder/neck pain from before to after the testing (P = 0.15).
Group wise comparisons within each load level showed that the FM patients had a significantly higher normalized power located in the low frequency band, and a significantly lower normalized power in the high frequency band compared with the HCs (Figure5). This result was consistent for all load levels and for both elbow flexion and shoulder abduction. No significant group differences were found in the middle frequency band (P > 0.17 for all comparisons).
Normalized power in the three frequency bands was independent of age, neck/shoulder pain (i.e., before and after testing), years since FM diagnosis, FIQ score, number of tender points, epicondylar humerus width, and force output during MVC. Arm girth was significantly and negatively correlated with normalized power in the high frequency band and positively correlated with the low frequency band (15 of 32 correlations signinficant). The significant correlations were evenly distributed among groups, load levels, and joints. (range: FM Spearman’s ρ = 0.50 to 0.69, P = 0.04 to 0.004, HCs Spearman’s ρ = 0.54 to 0.64, P = 0.049 to 0.016).
Maximal voluntary contraction (MVC)
The FM patients had significantly lower force output during MVC of shoulder abductors compared to HCs (FM, 13.1 kg, SD 3.6 vs HCs, 19.1 kg, SD 5.9, P = 0.003), but not during MVC of elbow flexors (FM, 17.3 kg, SD 3.7 vs HCs, 19.2 kg, SD 3.0, P = 0.16). As a consequence, the FM patients used a higher percentage of maximal voluntary force during the loaded shoulder abduction task compared to the HCs (P = 0.001 for all load conditions).
The main finding of this study was a large and consistent difference in the distribution of normalized power of upper limb oscillations between FM patients and HCs in sustained position tasks of the elbow and shoulder joint. Upper limb oscillations in the FM patients showed a strong dependency towards lower frequencies during both elbow flexion and shoulder abduction. Moreover, this difference was consistent across different loading conditions. Even though there were no overall significant differences between FM patients and HCs in variance of limb stability (time domain), neither during sustained elbow flexion nor shoulder abduction, the FM patients had a significantly higher variance in the shoulder abduction task when supporting 2 and 3 kg than HCs. Based on these results we can neither confirm nor reject the hypothesis that FM patients have higher amplitude oscillations compared with HCs.
The non-significant difference in steadiness between FM patients and HCs is in line with results of limb stability found in other chronic pain conditions, such as subacromial impingement syndrome, and knee osteoarthritis. In contrast, a significant decrease in head steadiness during a 10 s isometric cervical flexion task has been found in patients with chronic neck pain. However, the adjustment period at the start of this task was not removed prior to analysis and initial gross adjustments may have influenced the result. It should be noted that the abovementioned studies investigated force control while the current study investigated position control. Force control differs from position control in several important parameters such as muscle coactivation, reflex responsiveness to afferent feedback, recruitment pattern of the motor unit pool, and joint stiffness. Hence, the results of force control studies cannot directly be compared with our results, but are rather used as an indication of system stability in chronic pain conditions. It should also be noted that various chronic pain conditions may differ in terms of the possible effects on motor control characteristics, making generalization of findings across conditions difficult. Nevertheless, both our and the previous studies referred to above indicate that isometric limb stability is only mildly influenced by FM or other chronic musculoskeletal pain conditions.
Compared to HCs, FM patients showed a preponderance of normalized power in the low frequency band. Tremor is most often measured with an accelerometer, but is initially a displacement. Even though the power of an acceleration signal is elevated in high frequencies, the displacement amplitude represents a small share of the total displacement signal[33, 34]. A recent study of index finger oscillations showed that removal of frequencies corresponding to our low frequency band (i.e., 1–3 Hz) resulted in a 56% reduction of the original amplitude, which emphasize the importance of including low frequency oscillations when studying limb position control. Although the origin of the frequencies between 1–3 Hz are not completely understood they seem to be influenced by voluntary control, the processing and integration of visual feedback[16, 35, 36], and stress hormone level.
The task in the present study was to match a given limb position using real-time visual feedback. The use of visual feedback during limb stability tasks seems to increase the amplitude of low frequency oscillations[15, 38, 39]. It has also been demonstrated that motor disorders, low level of fine motor skills, age, and inability to voluntarily modulate tremor cause an additional increase in the amplitude of low frequency limb oscillations when using visual feedback to reduce limb oscillations[15, 16, 39, 40]. Our finding of increased normalized power in the low frequency band among FM patients may therefore relate to the motor problems commonly reported by these patients[5, 6, 41].
It has been suggested that subjects with low motor skills are more dependent on sensory feedback such as vision and proprioception to update their movement plan/strategy. Vaillancourt et al. (2001) on the other hand propose that increased low frequency oscillations during force control in Parkinson patients are associated with hyperactive feedback loops. Increased low frequency oscillations are often accompanied by an increase in overall time-domain variance. In the current study there was a mild and non-significant difference in motor performance between FM patients and HCs indicated by time-domain variance. Our study, however, indicates that maintenance of a stable limb position is achieved by different control strategies in FM patients and HCs. The enhanced power in the low frequency band among FM patients may indicate a larger dependency upon visual feedback to reduce low frequency oscillations. To examine the effect of visual feedback in the FM group, further studies should examine the frequency distribution when visual feedback is not available.
Alternatively, the enhanced low frequency power among FM patients may relate to a deficit in the sensory feedback system. Several indications of sensory deficits are observed in FM, including amplification of sensory input[1, 2, 4], disruption of somatosensory processing, mismatch between sensory feedback and motor output, and impaired visual and vestibular control. These sensory alterations are suggested to be related to acceleration of age-related changes in the grey substance of the brain, especially in pain related areas, but also in motor areas.
Alteration in sensory information might lead to higher reliance on muscle coactivation to maintain joint stiffness. While coactivation leads to high metabolic energy consumption, the use of sensory feedback is more energy efficient[47, 48]. The coactivation strategy seems to reduce the ability to perform high-acceleration movements and is often observed in elderly. Although we observed reduced high frequency acceleration in FM patients we cannot determine if this is due to enhanced coactivation. Altered muscle synergies are shown in FM patients, but future studies need to examine if they have a higher rate of coactivation in stability tasks and whether this can help to explain undue muscle fatigue commonly reported by FM patients.
There were no significant differences in normalized power in the middle frequency band (4–7 Hz) between FM patients and HCs. This component is proposed to be limb specific, of mechanical and reflexive origin, and is sensitive to load[12, 13, 17, 18]. We found that arm girth, as an indication of limb mass, was positively associated with low frequency oscillations. Although the greater arm girth among patients may explain the FM patients’ shift towards lower frequencies in the unloaded condition, the additional loading did not lead to a consistent shift towards lower frequencies. Thus, the difference in arm volume does not explain the group difference in the power spectrum distribution.
The FM patients were significantly weaker than HCs in the shoulder abductors, but not in the elbow flexors. Our results add to the inconclusive literature concerning upper body muscle strength in FM[7, 51–53]. FM patients generally have more pain in shoulder and neck muscles compared with arm muscles. Pain or fear of pain may therefore explain the present findings of reduced MVC in shoulder abduction
The observed difference in power distribution between FM patients and HCs in the limb stability tasks were independent of load, indicating that the results are not due to reduced muscle strength. The use of absolute load instead of load relative to MVC will therefore be of little importance to our results. It has earlier been shown that reduced force steadiness in patients with chronic neck pain was not due to reduced strength.
We have shown that limb stability during both loaded and unloaded elbow flexion and shoulder abduction position tasks is not significantly altered in FM patients. However, upper limb oscillations in FM patients showed a strong preponderance of normalized low frequency power compared to HCs. This difference does not seem to arise from instability or lower muscle strength in FM patients. We conclude that FM patients have a different motor control strategy to maintain limb stability in upper limb position tasks compared to HCs.
The authors thank Øystein Vetting for assistance with data collection, Xcianchun Tan for technical assistance, and Espen Alexander Fürst Ihlen for assistance with data analysis. Ellen Marie Bardal was supported with a grant from the Faculty of Social Sciences and Technology Management, Norwegian University of Science and Technology, Norway.
- Desmeules JA, Cedraschi C, Rapiti E, Baumgartner E, Finckh A, Cohen P, Dayer P, Vischer TL: Neurophysiologic evidence for a central sensitization in patients with fibromyalgia. Arthritis Rheum. 2003, 48: 1420-1429. 10.1002/art.10893.View ArticlePubMedGoogle Scholar
- Staud R: Evidence of involvement of central neural mechanisms in generating fibromyalgia pain. Curr Rheumatol Rep. 2002, 4: 299-305. 10.1007/s11926-002-0038-5.View ArticlePubMedGoogle Scholar
- Smith HS, Harris R, Clauw D: Fibromyalgia: an afferent processing disorder leading to a complex pain generalized syndrome. Pain Physician. 2011, 14: E217-E245.PubMedGoogle Scholar
- Geisser ME, Glass JM, Ralcevska LD, Clauw DJ, Williams DA, Kileny PR, Gracely RH: A psychophysical study of auditory and pressure sensitivity in patients with fibromyalgia and healthy controls. J Pain. 2008, 9: 417-422. 10.1016/j.jpain.2007.12.006.View ArticlePubMedGoogle Scholar
- Watson NF, Buchwald D, Goldberg J, Noonan C, Ellenbogen RG: Neurologic signs and symptoms in fibromyalgia. Arthritis Rheum. 2009, 60: 2839-2844. 10.1002/art.24772.View ArticlePubMedPubMed CentralGoogle Scholar
- McCabe CS, Cohen H, Hall J, Lewis J, Rodham K, Harris N: Somatosensory conflicts in complex regional pain syndrome type 1 and fibromyalgia syndrome. Curr Rheumatol Rep. 2009, 11: 461-465. 10.1007/s11926-009-0067-4.View ArticlePubMedGoogle Scholar
- Casale R, Sarzi-Puttini P, Atzeni F, Gazzoni M, Buskila D, Rainoldi A: Central motor control failure in fibromyalgia: a surface electromyography study. BMC Musculoskelet Disord. 2009, 10: 78-10.1186/1471-2474-10-78.View ArticlePubMedPubMed CentralGoogle Scholar
- Gerdle B, Gronlund C, Karlsson SJ, Holtermann A, Roeleveld K: Altered neuromuscular control mechanisms of the trapezius muscle in fibromyalgia. BMC Musculoskelet Disord. 2010, 11: 42-10.1186/1471-2474-11-42.View ArticlePubMedPubMed CentralGoogle Scholar
- Gerdle B, Ostlund N, Gronlund C, Roeleveld K, Karlsson JS: Firing rate and conduction velocity of single motor units in the trapezius muscle in fibromyalgia patients and healthy controls. J Electromyogr Kinesiol. 2008, 18: 707-716. 10.1016/j.jelekin.2007.02.016.View ArticlePubMedGoogle Scholar
- Enoka RM: Neuromechanics of human movement. 2002, Champaign, IL: Human Kinetics, 3Google Scholar
- Tracy BL: Visuomotor contribution to force variability in the plantarflexor and dorsiflexor muscles. Hum Mov Sci. 2007, 26: 796-807. 10.1016/j.humov.2007.07.001.View ArticlePubMedPubMed CentralGoogle Scholar
- McAuley JH, Marsden CD: Physiological and pathological tremors and rhythmic central motor control. Brain. 2000, 123: 1545-1567. 10.1093/brain/123.8.1545.View ArticlePubMedGoogle Scholar
- Takanokura M, Sakamoto K: Physiological tremor of the upper limb segments. Eur J Appl Physiol. 2001, 85: 214-225. 10.1007/s004210100476.View ArticlePubMedGoogle Scholar
- Morrison S, Newell KM: Postural and resting tremor in the upper limb. Clin Neurophysiol. 2000, 111: 651-663. 10.1016/S1388-2457(99)00302-8.View ArticlePubMedGoogle Scholar
- Vaillancourt DE, Slifkin AB, Newell KM: Intermittency in the visual control of force in Parkinson's disease. Exp Brain Res. 2001, 138: 118-127. 10.1007/s002210100699.View ArticlePubMedGoogle Scholar
- Carignan B, Daneault JF, Duval C: The amplitude of physiological tremor can be voluntarily modulated. Exp Brain Res. 2009, 194: 309-316. 10.1007/s00221-008-1694-0.View ArticlePubMedGoogle Scholar
- Halliday DM, Conway BA, Farmer SF, Rosenberg JR: Load-independent contributions from motor-unit synchronization to human physiological tremor. J Neurophysiol. 1999, 82: 664-675.PubMedGoogle Scholar
- Raethjen J, Pawlas F, Lindemann M, Wenzelburger R, Deuschl G: Determinants of physiologic tremor in a large normal population. Clin Neurophysiol. 2000, 111: 1825-1837. 10.1016/S1388-2457(00)00384-9.View ArticlePubMedGoogle Scholar
- Hwang IS, Chen YC, Wu PS: Differential load impact upon arm tremor dynamics and coordinative strategy between postural holding and position tracking. Eur J Appl Physiol. 2009, 105: 945-957. 10.1007/s00421-009-0981-1.View ArticlePubMedGoogle Scholar
- Wolfe F, Smythe HA, Yunus MB, Bennett RM, Bombardier C, Goldenberg DL, Tugwell P, Campbell SM, Abeles M, Clark P: The american-college-of-rheumatology 1990 criteria for the classification of fibromyalgia- report of the multicenter criteria committee. Arthritis Rheum. 1990, 33: 160-172. 10.1002/art.1780330203.View ArticlePubMedGoogle Scholar
- MacDougall JD, Wenger HA, Green HJ: Physiological testing of the high-performance athlete. 1991, Champaign, Illinois: Human kinetics, 2Google Scholar
- Oldfield RC: Assessment and analysis of handedness - Edinburgh inventory. Neuropsychologia. 1971, 9: 97-10.1016/0028-3932(71)90067-4.View ArticlePubMedGoogle Scholar
- Burckhardt CS, Clark SR, Bennett RM: The fibromyalgia impact questionnaire: development and validation. J Rheumatol. 1991, 18: 728-733.PubMedGoogle Scholar
- Knight CA, Marmon AR, Poojari DH: Postcontraction errors in isometric force control. Motor Control. 2008, 12: 267-278.PubMedGoogle Scholar
- Welch PD: Use of fast fourier transform for estimastion of power spectra - A method based on time averaging over short modified periodograms. Ieee Transactions on Audio and Electroacoustics. 1967, AU15: 70-View ArticleGoogle Scholar
- Bandholm T, Rasmussen L, Aagaard P, Jensen BR, Diederichsen L: Force steadiness, muscle activity, and maximal muscle strength in subjects with subacromial impingement syndrome. Muscle Nerve. 2006, 34: 631-639. 10.1002/mus.20636.View ArticlePubMedGoogle Scholar
- Hortobagyi T, Garry J, Holbert D, Devita P: Aberrations in the control of quadriceps muscle force in patients with knee osteoarthritis. Arthritis Rheum-Arthritis Care Res. 2004, 51: 562-569. 10.1002/art.20545.View ArticleGoogle Scholar
- Muceli S, Farina D, Kirkesola G, Katch F, Falla D: Reduced force steadiness in women with neck pain and the effect of short term vibration. J Electromyogr Kinesiol. 2011, 21: 283-290. 10.1016/j.jelekin.2010.11.011.View ArticlePubMedGoogle Scholar
- Buchanan TS, Lloyd DG: Muscle-activity is different for humans performing static tasks which require force control and position control. Neurosci Lett. 1995, 194: 61-64. 10.1016/0304-3940(95)11727-E.View ArticlePubMedGoogle Scholar
- Maluf KS, Barry BK, Riley ZA, Enoka RM: Reflex responsiveness of a human hand muscle when controlling isometric force and joint position. Clin Neurophysiol. 2007, 118: 2063-2071. 10.1016/j.clinph.2007.06.009.View ArticlePubMedPubMed CentralGoogle Scholar
- Mottram CJ, Christou EA, Meyer FG, Enoka RM: Frequency modulation of motor unit discharge has task-dependent effects on fluctuations in motor output. J Neurophysiol. 2005, 94: 2878-2887. 10.1152/jn.00390.2005.View ArticlePubMedGoogle Scholar
- Franklin DW, Milner TE: Adaptive control of stiffness to stabilize hand position with large loads. Exp Brain Res. 2003, 152: 211-220. 10.1007/s00221-003-1540-3.View ArticlePubMedGoogle Scholar
- Duval C, Jones J: Assessment of the amplitude of oscillations associated with high-frequency components of physiological tremor: impact of loading and signal differentiation. Exp Brain Res. 2005, 163: 261-266. 10.1007/s00221-005-2233-x.View ArticlePubMedGoogle Scholar
- Carignan B, Daneault JF, Duval C: Quantifying the importance of high frequency components on the amplitude of physiological tremor. Exp Brain Res. 2010, 202: 299-306. 10.1007/s00221-009-2132-7.View ArticlePubMedGoogle Scholar
- Slifkin AB, Vaillancourt DE, Newell KM: Intermittency in the control of continuous force production. J Neurophysiol. 2000, 84: 1708-1718.PubMedGoogle Scholar
- Vaillancourt DE, Newell KM: Aging and the time and frequency structure of force output variability. J Appl Physiol. 2003, 94: 903-912.View ArticlePubMedGoogle Scholar
- Christou EA, Jakobi JM, Critchlow A, Fleshner M, Enoka RM: The 1-to 2-Hz oscillations in muscle force are exacerbated by stress, especially in older adults. J Appl Physiol. 2004, 97: 225-235. 10.1152/japplphysiol.00066.2004.View ArticlePubMedGoogle Scholar
- Vallbo AB, Wessberg J: Organization of motor output in slow finger movements in man. J Physiol-London. 1993, 469: 673-691.View ArticlePubMedPubMed CentralGoogle Scholar
- Bye RT, Neilson PD: The BUMP model of response planning: Intermittent predictive control accounts for 10 Hz physiological tremor. Hum Mov Sci. 2010, 29: 713-736. 10.1016/j.humov.2010.01.006.View ArticlePubMedGoogle Scholar
- Seidler-Dobrin RD, Stelmach GE: Persistence in visual feedback control by the elderly. Exp Brain Res. 1998, 119: 467-474. 10.1007/s002210050362.View ArticlePubMedGoogle Scholar
- Stehlik R, Arvidsson L, Ulfberg J: Restless legs syndrome is common among female patients with fibromyalgia. Eur Neurol. 2009, 61: 107-111. 10.1159/000180313.View ArticlePubMedGoogle Scholar
- McCabe CS, Cohen H, Blake AR: Somaesthetic disturbances in fibromyalgia are exaggerated by sensory-motor conflict: implications for chronicity of the disease?. Rheumatology. 2007, 46: 1587-1592. 10.1093/rheumatology/kem204.View ArticlePubMedGoogle Scholar
- Jones KD, King LA, Mist SD, Bennett RM, Horak FB: Postural control deficits in people with fibromyalgia: a pilot study. Arthritis Res Ther. 2011, 13: R127-10.1186/ar3432.View ArticlePubMedPubMed CentralGoogle Scholar
- Kuchinad A, Schweinhardt P, Seminowicz DA, Wood PB, Chizh BA, Bushnell MC: Accelerated brain gray matter loss in fibromyalgia patients: premature aging of the brain?. J Neurosci. 2007, 27: 4004-4007. 10.1523/JNEUROSCI.0098-07.2007.View ArticlePubMedGoogle Scholar
- Robinson ME, Craggs JG, Price DD, Perlstein WM, Staud R: Gray matter volumes of pain-related brain areas are decreased in fibromyalgia syndrome. J Pain. 2011, 12: 436-443. 10.1016/j.jpain.2010.10.003.View ArticlePubMedGoogle Scholar
- Puri BK, Agour M, Gunatilake KD, Fernando KA, Gurusinghe AI, Treasaden IH: Reduction in left supplementary motor area grey matter in adult female fibromyalgia sufferers with marked fatigue and without affective disorder: a pilot controlled 3-T magnetic resonance imaging voxel-based morphometry study. J Int Med Res. 2010, 38: 1468-1472.View ArticlePubMedGoogle Scholar
- Schuurmans J, van der Helm FCT, Schouten AC: Relating reflex gain modulation in posture control to underlying neural network properties using a neuromusculoskeletal model. J Comput Neurosci. 2011, 30: 555-565. 10.1007/s10827-010-0278-8.View ArticlePubMedGoogle Scholar
- Forbes PA, Happee R, van der Helm FCT, Schouten AC: EMG feedback tasks reduce reflexive stiffness during force and position perturbations. Exp Brain Res. 2011, 213: 49-61. 10.1007/s00221-011-2776-y.View ArticlePubMedPubMed CentralGoogle Scholar
- Pierrynowski MR, Tiidus PM, Galea V: Women with fibromyalgia walk with an altered muscle synergy. Gait Posture. 2005, 22: 210-218. 10.1016/j.gaitpost.2004.09.007.View ArticlePubMedGoogle Scholar
- Fox JR, Randall JE: Relationship between forearm tremor and biceps electromyogram. J Appl Physiol. 1970, 29: 103-PubMedGoogle Scholar
- Dombernowsky T, Dreyer L, BArtels EM, Danneskiold-Samsoe B: Muscular strength in patients with fibromyalgia. A literature review. Ugeskr Laeger. 2008, 170: 217-224.PubMedGoogle Scholar
- Miller TA, Allen GM, Gandevia SC: Muscle force, perceived effort, and voluntary activation of the elbow flexors assessed with sensitive twitch interpolation in fibromyalgia. J Rheumatol. 1996, 23: 1621-1627.PubMedGoogle Scholar
- Nørregaard J, Bulow PM, Lykkegaard JJ, Mehlsen J, DanneskioldSamsoe B: Muscle strength, working capacity and effort in patients with fibromyalgia. Scand J Rehabil Med. 1997, 29: 97-102.PubMedGoogle Scholar
- Maquet D, Croisier JL, Demoulin C, Crielaard JM: Pressure pain thresholds of tender point sites in patients with fibromyalgia and in healthy controls. Eur J Pain. 2004, 8: 111-117. 10.1016/S1090-3801(03)00082-X.View ArticlePubMedGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2474/13/186/prepub
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/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.