Parkinson disease (PD) is a common neurodegenerative disorder that can cause a variety of motor symptoms, including resting tremor, rigidity, akinesia/bradykinesia, and postural instability and gait disturbance.1 Although these symptoms have wide-ranging effects on motor performance and completion of activities of daily living (ADL), the underlying impairment within the neuromuscular system is not fully understood. Individuals with PD often exhibit lower levels of maximal force production (muscle weakness) compared with healthy controls.2–7 Our previous investigation observed reduced torque generation at the ankle and general weakness at the hip and knee in PD compared with controls.2 These strength deficits have been shown to lead to compensatory strategies that altered the ability to perform ADL.2 Thus, reduced muscular strength has the potential to negatively influence performance of ADL.
Maximum force production in the muscles of the hip, knee, and ankle joints has been individually related to performance of ADL, including rising from a chair, navigating stairs, and forward propulsion.2 , 8 , 9 Although maximal strength appears to be important for functional mobility, most daily movements occur at submaximal force levels, ranging from 2% to 15% of maximum strength depending on the difficulty and intensity (ie, level of required muscle force) of the activity.10–13 Thus, control of submaximal force, defined as the variability in muscle force output, across the muscles of the lower extremity is also important for functional mobility. Lower extremity force control has been considered a marker of impairment during functional tasks such as walking endurance, chair rising, and stair climbing in older adults.14 Reduced force control of the ankle plantar flexors during low-intensity contractions is also highly associated with increased postural sway in elderly adults.12 Moreover, correlations between force control and falling in older adults have been reported.13 Although these studies were not performed in persons with PD, they provide a basis for investigating the force control abilities of the lower extremity in this mobility-impaired population. To date, the capacity of people with PD to exert maximal force and precisely control submaximal force within the prominent lower extremity muscles, specifically those critical for propulsion during walking, has not been fully evaluated in the extant literature. The primary aim of this study was to assess both maximal force production and force control across the primary muscles of the lower extremity responsible for propulsion and stability during walking. We hypothesized that persons with PD would exhibit reduced strength and display higher amounts of force variability across the lower extremity muscle groups compared with healthy older adults (HOAs).
Thirteen persons with PD (6 males) and 13 (7 males) healthy age controls (±2 years) were recruited for the investigation. The sample size was based on a priori power analyses utilizing force measures from pilot data and prior investigations investigating force control in both PD and older adult populations.15 , 16 Alpha was set at 0.5 and beta was set at 0.2, and the effect size of interest was set at 0.3 for sample size determination. Participants who enrolled in the study had not experienced any lower extremity orthopedic injury for at least 1 year prior to participation. All persons with PD were being treated with stable doses of antiparkinsonian medication (no change in frequency or dosage within the previous 2 months). Participants provided written informed consent before participating in the study as approved by the University of Florida Institutional Review Board. Participants with PD were evaluated and diagnosis of idiopathic PD was confirmed by a movement disorders neurologist using UK Brain bank diagnostic criteria17 and were recruited from the University's movement disorders center. Participants with PD did not exhibit fluctuations within the medication cycle and were tested in their optimally medicated state (“ON” meds). Participants were tested while “ON” because (1) this most accurately represents normal behavior throughout the waking day in most persons with PD, and (2) motor deficits can be observed in PD even after the administration of antiparkinsonian medication.18
Participants abstained from physical activity within the 24 hours prior to testing. At the beginning of the visit, participants with PD were evaluated using the Unified Parkinson Disease Rating Scale (UPDRS) while being recorded. These videos were scored by a single independent movement disorders-trained neurologist who was blinded to the purpose of the study.
Maximal force production and submaximal force control of the major muscle groups of the lower extremity were assessed via strain gauge (S-Beam Tension and Compression Load Cell, FUTEK Advanced Sensor Technology Inc, Irvine, California), with the relevant joint stabilized in a standardized position. We specifically examined performance within the hip extensors (HEs), hip flexors (HFs), hip abductors (HABs), hip adductors (HADs), and ankle plantar flexors (PFs) and dorsiflexors (DFs) utilizing a custom-built apparatus embedded with force sensors as described later. These muscles were evaluated because they are essential contributors to locomotor ability.19–23 During normal walking, the primary task of the muscles that control the hip and ankle joints are to provide support against gravity and contribute to propulsion.19 , 23 , 24 To begin, each participant was first familiarized with the assessment procedures. This familiarization period included a verbal explanation of the task and 3 practice trials at submaximal isometric efforts for each of the muscle groups to be tested. After the familiarization period, each participant performed maximum voluntary contractions (MVCs) at the hip (HE, HF, HAD, and HAB) and ankle (DF and PF) for both the right and left legs. The order of testing was randomized prior to beginning the experimental protocol.
Following the MVC testing, participants performed the force control task at 3 submaximal force levels (5%, 10%, and 20% MVC) for both the right and left legs. Again, prior to beginning the tasks participants were familiarized with the study procedures. For this task, the participants attempted to match a constant force level for 20 seconds. This approach has been previously utilized to evaluate force control ability in several previous investigations.14 , 25 , 26 The levels of intensity were selected based on prior evidence in older adults that suggested changes in force variability with age are more pronounced at low levels of MVC25 , 27 and to encompass the low end of a “normal” range of MVC that older individuals typically utilize during ADL.8 , 28 During the experiments, ratings of fatigue were assessed using the Borg Category Ratio or Borg CR-10, a numerically based, self-perceived exertion rating scale (0-10, 0 indicating rest and 10 is maximal exertion) at the beginning and end of the testing session.29 The testing order for the force levels and which leg was tested first was randomized prior to beginning the experimental protocol.
Ankle Muscle Testing
Participants were seated with the hip and knee joints positioned at 90° flexion and hip abducted approximately 10°.30 To stabilize the ankle for testing, the foot was secured in a customized device with an adjustable foot plate positioned parallel with the floor. The foot was secured by straps at the level of the metatarsals. The strap and foot positioning isolate the movement of the ankle to the sagittal plane (dorsiflexion and plantar flexion)30 (see Figure 1A).
Hip Muscle Testing
Participants stood upright in a custom frame that isolated the movement of the hip to uniplanar actions: hip flexion, hip extension, hip abduction, and adduction. The strap was positioned superior to the knee joint. Participants exerted force in the horizontal direction against a strap that was attached in series to a fixed 1-dimensional force transducer (see Figure 1B). The muscle force signals acquired with the 1-dimensional force transducer were sampled at 1 kHz with a Power 1401 A/D board (Cambridge Electronic Design, UK) and a NI-DAQ card (Model USB6251, National Instruments, Austin, Texas) and data were stored on a computer.
Maximum Voluntary Contraction
Initiation of the MVC trial began with an on-screen start command that was displayed on the monitor, and the MVC trial terminated with an on-screen stop command. Participants were instructed to increase force from baseline to maximum as quickly as possible and maintain their maximum force for approximately 3 seconds.16 , 31 Participants performed maximal trials until the maximum force of 2 trials was within 5% of each other.32 All participants could produce 2 MVC trials with 5% of each other within 3 attempts. Two trials were chosen based on pilot data that indicated no statistical difference when averaging 2 independent trials compared with the average of 3 independent trials. In addition, performing consecutive maximal effort trials increases an individual's level of fatigue. A minimum of 1 minute of rest was given between trials. An additional MVC test was performed approximately 5 minutes after completing both experimental protocols to determine whether fatigue may have influenced the results.
Submaximal Force Control
During the submaximal force control task, the target position was provided as a red line in the middle of a 32-inch monitor (SyncMaster 320MP-2, resolution: 1360 × 768 pixels, Samsung Electronics America, New Jersey), and the force produced was shown as a blue line progressing with time from left to right.30 Participants were seated during ankle muscle testing and standing during hip muscle testing, and faced a monitor located 1.25 m away at eye level.30 , 33 The position of the apparatus and the strain gauge (S-Beam Tension and Compression Load Cell, FUTEK Advanced Sensor Technology Inc, Irvine, California) was rotated 90° during hip abduction and adduction testing. Participants affirmed that they could see the screen and its display clearly, without any obstruction or limitations. The visual gain for the task was 0.05°. We selected this visual feedback to eliminate the effects of visuomotor corrections on force control.33 The protocol for the force control task was similar to previous investigations.30 , 34 The participants were instructed to gradually push/pull against the force transducer and increase their force to match the target force. When the target was reached, participants were instructed to maintain their force on the target as accurately and as consistently as possible. For each task, participants performed 3 trials and each trial lasted 20 seconds. Participants had a minimum of 30-second rest between trials and 3 minutes of rest between the tasks. A custom-written program (MATLAB, MathWorks, Inc) controlled the targeted force level and gain of visual feedback.
The maximal value of each MVC trial was quantified as the average of the 10 force values surrounding the peak force produced during a single continuous isometric contraction.32 We quantified the MVC from the average of the 2 MVC trials. This value was used for analysis and formulation of relative intensities for the submaximal force trials. This procedure produced a more conservative MVC that reflects the capacity to maintain a maximal contraction, which better reflects ADL.33
For the submaximal force trials, the first 5 seconds and final 1 second of force data were eliminated from all analyses to account for early and late force adjustments, resulting in a 14-second submaximal force signal. The 14-second submaximal force signal was filtered using a fourth-order Butterworth filter at a cutoff frequency of 20 Hz.35 For this investigation, force steadiness was defined as the coefficient of variation (CV). CV of force was computed as the standard deviation (SD) of force/mean force output × 100. Force steadiness was quantified using a detrended force signal. Detrending was performed using the detrend function in Matlab, which removes the best straight-line fit linear trend from the data.36 In addition, detrending the force signal removed any drifting of force, which could influence the quantification of force variability.
All statistical analyses were performed by using commercial software 0 (JMP Pro version 11, SAS Institute Inc, Cary, North Carolina) and the level of significance for all analyses was set at P < 0.05. Descriptive statistics are reported as mean ± SD. The normality for continuous variables in groups was confirmed by the Shapiro-Wilk test. We used the t test or the Mann-Whitney U test for comparisons for MVC. We first compared performance values between legs (most affected and least affected side and dominant and nondominant). The most affected side was determined through participant self-report and then verified from clinician scoring of the UPDRS. Since no significant differences (P > 0.05) were detected between legs, we collapsed MVC values across legs for statistical analysis. Two-way analyses of variance with repeated measures on force levels (5%, 10%, and 20% of MVC) were used to test for between- and within-group differences in force steadiness at each muscle group.
All participants successfully completed the testing protocols. MVC at the start of testing was not statistically different from MVC at the end of testing, suggesting fatigue did not influence the findings (1.8% ± 1.1%, P > 0.05). Group means for age, height, and mass did not differ between controls and persons with PD (see the Table).
Maximal Voluntary Contraction
Examination of MVC trials indicated that persons with PD generated lower isometric force across all muscle groups compared with HOAs. Although there was a distinct pattern for those with PD being weaker than HOAs, statistically significant differences were only detected for the hip flexors (P = 0.01), ankle dorsiflexors (P = 0.03), and ankle plantar flexors (P = 0.001) (see Figure 2). On average, those with PD generated 20% less hip abductor force, 14% less hip adductor force, 10% less hip extensor force, 22% less hip flexor, 35% less plantar flexor force, and 18% less dorsiflexor force.
Submaximal Force Control
For the hip flexors, there was a significant group (PD vs HOA) × force (force level) interaction [F (2, 48) = 4.612, P < 0.01], indicating that the PD group produced higher variability across all levels of intensity compared with the control group and higher CV at 5% MVC compared with 10% and 20% MVC (see Figure 3). There was a significant group × force interaction for the ankle plantar flexors [F (2, 48) = 4.3217, P < 0.01] and the ankle dorsiflexors [F (2, 48) = 5.9858, P < 0.005]. Similarly, the PD group displayed higher variability at the ankle plantar flexor and dorsiflexors across all levels of intensity compared with the control group and higher CV at 5% MVC compared with 10% and 20% MVC. In addition, participants in the PD group exhibited greater variability at the 10% MVC compared with 20% during plantar flexion. The statistical analyses failed to detect a group × time interaction for the CV of force in the hip abductors and adductors or the hip extensors. However, the statistical analyses detected a main effect of intensity for the CV of force in the hip abductors [F (2, 48) = 35.448, P < 0.001; hip adductors, F (2, 48) = 37.1, P < 0.001; and hip extensors, F (2, 48) = 22.6, P < 0.001]. Across both groups, CV at 5% MVC was higher compared with 10% and 20% MVC. Although not statistically significant, there was a trend that suggested that, across groups, the CV at 10% MVC was higher than the CV at 20% MVC.
This is the first investigation to concurrently evaluate, in persons with PD, both maximal strength and force control in the lower extremity muscles used in locomotion. The results demonstrated that participants with PD produced significantly less force and displayed higher amounts of force variability compared with HOAs. Unexpectedly, these deficits in maximal force and submaximal force control were confined to a few select muscle groups (ie, hip flexors and ankle plantar flexor and dorsiflexors). The potential mechanisms for the reduced force output and force steadiness may be related to impaired cortical activation originating from abnormal drive from the basal ganglia to the thalamus,5 , 37 which can lead to inability to sufficiently activate motoneuron pools, thereby affecting recruitment and discharge rate and thereby impede the facilitation of desired movement.38 , 39 In addition to these central origins, sarcopenia and inactivity likely co-contribute to the observed force deficits and increased difficulty performing ADL.40 , 41
Our results indicated that persons with PD produced significantly less force compared with controls, which is supported by previous literature.3 , 42–44 Likewise, the lack of statistically detectable muscle weakness across all of the joint actions observed in the current study is also supported by the literature.2 For example, individuals with PD produce smaller peak ankle plantar flexion moments, but research has failed to detect differences in moments of hip or the knee joints.2 Together, these results suggest that the muscles of the ankle joint appear to be consistently weaker in persons with PD. However, the impact of this weakness on gait deficits is unclear. While ankle plantar flexion strength has been shown to be associated with both gait velocity and stride length in persons with PD, changes in strength have not been found to be associated with changes in gait.45 Prior investigations observed that muscular deficit in PD is an independent risk factor for falls,46–48 that strength of the knee extensor and plantar flexor muscles is significantly associated with stability and recovery performance from forward falls,49 that the muscle groups around the ankle are pivotal in performance of ADL,2 and that muscle strengthening improves performance of ADL.50 While other factors such as fall history, postural control, and cognitive abilities51–53 significantly contribute to increased fall risk in PD, these findings support that persons with PD who are at risk for falling may benefit from training to increase ankle strength.
The investigation of submaximal force control found increased force variability in those with PD compared with HOAs. Consistent with the observations in muscle strength, reduced force control was evident in the hip flexors and ankle plantar flexors and dorsiflexors. Milner-Brown et al54 theorized that when individuals with PD voluntarily attempt to maintain a force, motor units inappropriately stop firing for prolonged periods or fire at abnormally low frequencies (2-3 Hz). Diminished force control interferes with and disrupts the ability to perform smooth and accurate movements and interferes with the ability to perform many ADL.25 , 27 Kouzaki and Shinohara12 reported that the increased force variability at the ankle in older adults during low-intensity lower extremity isometric contractions could accurately predict variability of center of pressure during quiet standing. Therefore, interventions that are centered around reducing force variability may have relevant clinical implications as persons with PD often exhibit impairments in gait and balance function.1
Specific to the pathology of PD, striatal dysfunction may interfere with efficient and coordinated movement. Impaired force steadiness has been linked to abnormal activation of the involved muscles, which is likely due to the structural and neural changes that occur with PD.40 , 55 , 56 Impairments in the variability, intensity, and frequency of corticospinal activation lead to irregular and intermittent discharge patterns of motor units and the recruitment of a greater number of motor units at low force thresholds in persons with PD than in controls. Yoon et al26 recently identified the putamen as one of the brain areas associated with the CV of force. The authors interpreted this as evidence that the basal ganglia play a dominant role in the control of steady contractions across a range of forces. The results from Yoon et al26 may suggest that the observed deficits in force control in the PD group from the current study are associated with the known impairments within the impaired cortico-basal ganglia-thalamic loop.26 Much of our understanding of the deficits in force steadiness or control relies on the information obtained from investigations in the upper extremity of older adults.25 , 33 , 57 However, motor control abilities are known to be different between the upper and lower extremities.58 , 59 There is clinical relevance for understanding submaximal force control across the lower extremity joints, as a more robust knowledge of the motor limitations in PD can potentially lead to a greater number of effective treatment options.
The present study is not without limitations. Our results for maximal force and submaximal force control are limited to the muscles related to actions of the hip and ankle joints. The muscles of the knee were not evaluated. The rationale for not including the knee is due to prior investigations that have suggested that the knee produces only small net mechanical work during walking, playing a primary role in absorbing energy during the stance phase and providing stable locomotion rather than being an important source of either control or propulsion.20 , 22–24 However, in future studies, evaluation of the muscles controlling the knee joint could provide additional understanding of the magnitude of deficits in force production and force control in PD. It seems likely that a comprehensive evaluation of lower extremity performance is needed to fully appreciate the role that force production, and control deficits, may have on performance of mobility-related ADL. In the current study, participants were screened using the UPDRS; the use of the MDS (Movement Disorder Society)-UPDRS, a more sensitive alternative of the UPDRS, could provide more accurate reflection of disease severity. Participants were evaluated during their self-reported optimally medicated state. There is conflicting evidence regarding the impact of antiparkinsonian medications on force steadiness and maximal force.9 , 18 , 39 Future investigations should expand on the current findings and objectively measure the effects of parkinsonian medications on submaximal and maximal force generation in the lower extremity. The relative force levels that were used for the experimental design were chosen based on prior evidence in older adults.11–13 We attempted to evaluate force steadiness at levels of MVC that older individuals typically utilize during normal ADL; however, a wider spectrum of relative intensities could provide more information on how individuals with PD perform near maximal capabilities.
The objective of this investigation was to identify reduced muscular capabilities (ie, strength and force steadiness in muscles that are primarily responsible for locomotor function in individuals with PD). These results provide evidence that reduced maximal force production was concomitant with higher force variability within joint actions critical for effective ambulation (hip flexion, ankle dorsiflexion, and plantar flexion). Together, the present data and other prior investigations suggest force production and control capabilities may contribute to impaired mobility, and perhaps fall risk, in persons with PD. We hope future investigations will expand on the results to examine the underlying relationship between deficits in strength and force control, as it has clinical importance for improving mobility and quality of life in individuals with PD.
1. Amano S, Roemmich RT, Skinner JW, Hass CJ. Ambulation and Parkinson disease
. Phys Med Rehabil Clin N Am. 2013;24(2):371–392.
2. Skinner JW, Lee HK, Roemmich RT, Amano S, Hass CJ. Execution of activities of daily living
in persons with Parkinson's disease. Med Sci Sports Exerc. 2015;47(9):1906–1912.
3. Schilling BK, Karlage RE, LeDoux MS, Pfeiffer RF, Weiss LW, Falvo MJ. Impaired leg extensor strength
in individuals with Parkinson disease
and relatedness to functional mobility. Parkinsonism Relat Disord. 2009;15(10):776–780.
4. Nocera JR, Buckley T, Waddell D, Okun MS, Hass CJ. Knee extensor strength
, dynamic stability, and functional ambulation: are they related in Parkinson's disease? Arch Phys Med Rehabil. 2010;91(4):589–595.
5. Koller W, Kase S. Muscle strength
testing in Parkinson's disease. Eur Neurol. 1986;25(2):130–133.
6. Kakinuma S, Nogaki H, Pramanik B, Morimatsu M. Muscle weakness in Parkinson's disease: isokinetic study of the lower limbs. Eur Neurol. 1998;39(4):218–222.
7. Stevens-Lapsley J, Kluger BM, Schenkman M. Quadriceps muscle weakness, activation deficits, and fatigue with Parkinson disease
. Neurorehabil Neural Repair. 2012;26(5):533–541.
8. 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. 2003;58(5):M453–M460.
9. Inkster LM, Eng JJ, MacIntyre DL, Stoessl AJ. Leg muscle strength
is reduced in Parkinson's disease and relates to the ability to rise from a chair. Mov Disord. 2003;18(2):157–162.
10. Graves AE, Kornatz KW, Enoka RM. Older adults use a unique strategy to lift inertial loads with the elbow flexor muscles. J Neurophysiol. 2000;83(4):2030–2039.
11. Tracy BL. Visuomotor contribution to force variability
in the plantarflexor and dorsiflexor muscles. Hum Mov Sci. 2007;26(6):796–807.
12. Kouzaki M, Shinohara M. Steadiness in plantar flexor muscles and its relation to postural sway in young and elderly adults. Muscle Nerve. 2010;42(1):78–87.
13. Carville SF, Perry MC, Rutherford OM, Smith IC, Newham DJ. Steadiness of quadriceps contractions in young and older adults with and without a history of falling. Eur J Appl Physiol. 2007;100(5):527–533.
14. Seynnes O, Hue OA, Garrandes F, et al Force steadiness in the lower extremities as an independent predictor of functional performance in older women. J Aging Phys Act. 2005;13(4):395–408.
15. Rose MH, Løkkegaard A, Sonne-Holm S, Jensen BR. Tremor irregularity, torque steadiness and rate of force development in Parkinson's disease. Motor Control. 2013;17(2):203–216.
16. Tracy BL. Force control is impaired in the ankle
plantarflexors of elderly adults. Eur J Appl Physiol. 2007;101(5):629–636.
17. Reichmann H. Clinical criteria for the diagnosis of Parkinson's disease. Neurodegener Dis. 2010;7(5):284–290.
18. Corcos DM, Chen CM, Quinn NP, McAuley J, Rothwell JC. Strength
in Parkinson's disease: relationship to rate of force generation and clinical status. Ann Neurol. 1996;39(1):79–88.
19. Sadeghi H, Sadeghi S, Prince F, Allard P, Labelle H, Vaughan CL. Functional roles of ankle
and hip sagittal muscle moments in able-bodied gait. Clin Biomech (Bristol Avon). 2001;16(8):688–695.
20. Sadeghi H, Prince F, Zabjek KF, Sadeghi S, Labelle H. Knee flexors/extensors in gait of elderly and young able-bodied men (II). Knee. 2002;9(1):55–63.
21. Winter DA. Overall principle of lower limb support during stance phase of gait. J Biomech. 1980;13(11):923–927.
22. Winter DA. Energy generation and absorption at the ankle
and knee during fast, natural, and slow cadences. Clin Orthop Relat Res. 1983;175:147–154.
23. Winter DA. Biomechanics of normal and pathological gait: implications for understanding human locomotor control. J Mot Behav. 1989;21(4):337–355.
24. Sadeghi H, Allard P, Barbier F, et al Main functional roles of knee flexors/extensors in able-bodied gait using principal component analysis (I). Knee. 2002;9(1):47–53.
25. Galganski ME, Fuglevand AJ, Enoka RM. Reduced control of motor output in a human hand muscle of elderly subjects during submaximal contractions. J Neurophysiol. 1993;69(6):2108–2115.
26. Yoon T, Vanden Noven ML, Nielson KA, Hunter SK. Brain areas associated with force steadiness and intensity during isometric ankle
dorsiflexion in men and women. Exp Brain Res. 2014;232(10):3133–3145.
27. Enoka RM, Christou EA, Hunter SK, et al Mechanisms that contribute to differences in motor performance between young and old adults. J Electromyogr Kinesiol. 2003;13(1):1–12.
28. John EB, Liu W, Gregory RW. Biomechanics of muscular effort: age-related changes. Med Sci Sports Exerc. 2009;41(2):418–425.
29. Hackett DA, Johnson NA, Halaki M, Chow CM. A novel scale to assess resistance-exercise effort. J Sports Sci. 2012;30(13):1405–1413.
30. Kwon M, Baweja HS, Christou EA. Ankle
variability is amplified in older adults due to lower EMG power from 30-60 Hz. Hum Mov Sci. 2012;31(6):1366–1378.
31. Chung-Hoon K, Tracy BL, Dibble LE, Marcus RL, Burgess P, LaStayo PC. The association between knee extensor force steadiness, force accuracy, and mobility in older adults who have fallen. J Geriatr Phys Ther. 2016;39(1):1–7.
32. 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. 2001;56(12):B524–B532.
33. Moon H, Kim C, Kwon M, et al Force control is related to low-frequency oscillations in force and surface EMG. PLoS One. 2014;9(11):e109202.
34. Moon H, Kim C, Kwon M, Chen YT, Fox E, Christou EA. High-gain visual feedback exacerbates ankle
movement variability in children. Exp Brain Res. 2015;233(5):1597–1606.
35. Lodha N, Misra G, Coombes SA, Christou EA, Cauraugh JH. Increased force variability
in chronic stroke: contributions of force modulation below 1 Hz. PLoS One. 2013;8(12):e83468.
36. Park SH, Casamento-Moran A, Yacoubi B, Christou EA. Voluntary reduction of force variability
via modulation of low-frequency oscillations. Exp Brain Res. 2017;235(9):2717–2727.
37. Albin RL, Young AB, Penney JB. The functional anatomy of disorders of the basal ganglia. Trends Neurosci. 1995;18(2):63–64.
38. Marchand WR, Lee JN, Suchy Y, et al Age-related changes of the functional architecture of the cortico-basal ganglia circuitry during motor task execution. Neuroimage. 2011;55(1):194–203.
39. Foreman KB, Singer ML, Addison O, Marcus RL, Lastayo PC, Dibble LE. Effects of dopamine replacement therapy on lower extremity kinetics and kinematics during a rapid force production task in persons with Parkinson disease
. Gait Posture. 2014;39(1):638–640.
40. Glendinning DS, Enoka RM. Motor unit behavior in Parkinson's disease. Phys Ther. 1994;74(1):61–70.
41. Dengler R, Konstanzer A, Gillespie J, Argenta M, Wolf W, Struppler A. Behavior of motor units in parkinsonism. Adv Neurol. 1990;53:167–173.
42. Pääsuke M, Ereline J, Gapeyeva H, Joost K, Mõttus K, Taba P. Leg-extension strength
and chair-rise performance in elderly women with Parkinson's disease. J Aging Phys Act. 2004;12(4):511–524.
43. Kelly NA, Ford MP, Standaert DG, et al Novel, high-intensity exercise prescription improves muscle mass, mitochondrial function, and physical capacity in individuals with Parkinson's disease. J Appl Physiol (1985). 2014;116(5):582–592.
44. Stelmach GE, Teasdale N, Phillips J, Worringham CJ. Force production characteristics in Parkinson's disease. Exp Brain Res. 1989;76(1):165–172.
45. Rafferty MR, Prodoehl J, Robichaud JA, et al Effects of 2 years of exercise on gait impairment in people with Parkinson disease
: the PRET-PD randomized trial. J Neurol Phys Ther. 2017;41(1):21–30.
46. Allen NE, Sherrington C, Canning CG, Fung VS. Reduced muscle power is associated with slower walking velocity and falls in people with Parkinson's disease. Parkinsonism Relat Disord. 2010;16(4):261–264.
47. Kerr GK, Worringham CJ, Cole MH, Lacherez PF, Wood JM, Silburn PA. Predictors of future falls in Parkinson disease
. Neurology. 2010;75(2):116–124.
48. Robinson K, Dennison A, Roalf D, et al Falling risk factors in Parkinson's disease. NeuroRehabilitation. 2005;20(3):169–182.
49. Moreno Catalá M, Woitalla D, Arampatzis A. Recovery performance and factors that classify young fallers and non-fallers in Parkinson's disease. Hum Mov Sci. 2015;41:136–146.
50. Hass CJ, Buckley TA, Pitsikoulis C, Barthelemy EJ. Progressive resistance training improves gait initiation in individuals with Parkinson's disease. Gait Posture. 2012;35(4):669–673.
51. Pickering RM, Grimbergen YA, Rigney U, et al A meta-analysis of six prospective studies of falling in Parkinson's disease. Mov Disord. 2007;22(13):1892–1900.
52. Canning CG, Paul SS, Nieuwboer A. Prevention of falls in Parkinson's disease: a review of fall risk factors and the role of physical interventions. Neurodegener Dis Manag. 2014;4(3):203–221.
53. Paul SS, Sherrington C, Canning CG, Fung VS, Close JC, Lord SR. The relative contribution of physical and cognitive fall risk factors in people with Parkinson's disease: a large prospective cohort study. Neurorehabil Neural Repair. 2014;28(3):282–290.
54. Milner-Brown HS, Fisher MA, Weiner WJ. Electrical properties of motor units in Parkinsonism and a possible relationship with bradykinesia. J Neurol Neurosurg Psychiatry. 1979;42(1):35–41.
55. Robichaud JA, Pfann KD, Vaillancourt DE, Comella CL, Corcos DM. Force control and disease severity in Parkinson's disease. Mov Disord. 2005;20(4):441–450.
56. Berardelli A, Rothwell JC, Thompson PD, Hallett M. Pathophysiology of bradykinesia in Parkinson's disease. Brain. 2001;124(pt 11):2131–2146.
57. Kornatz KW, Christou EA, Enoka RM. Practice reduces motor unit discharge variability in a hand muscle and improves manual dexterity in old adults. J Appl Physiol (1985). 2005;98(6):2072–2080.
58. Christou EA, Zelent M, Carlton LG. Force control is greater in the upper compared with the lower extremity. J Mot Behav. 2003;35(4):322–324.
59. Prodoehl J, Vaillancourt DE. Effects of visual gain on force control at the elbow and ankle
. Exp Brain Res. 2010;200(1):67–79.