Post on 19-Jul-2018
transcript
Does cycling cadence affect interlimb symmetry in pedaling power in individuals with 1
Parkinson’s disease? 2
3
Student Name, Harsh H. Buddhadev, Jun G. San Juan, David N. Suprak 4
Department of Health and Human Development, Western Washington University, Bellingham, 5
Washington, United States of America 6
7
Conflict of Interest Disclosure: None 8
9
Correspondence Address: 10
Harsh H. Buddhadev, PhD 11
Department of Health and Human Development 12
201H Carver Academic Facility, MS 9067, 13
516 High Street, Bellingham, WA 98225 14
Telephone: +1 (360) 650-4115 15
Fax: +1 (360) 650-7447 16
Email: harsh.buddhadev@wwu.edu 17
18
19
Running Title: Parkinson’s disease and asymmetry during cycling 20
21
22
23
Abstract 24
Cycling at higher pedaling rates leads to symptomatic improvement in patients with Parkinson’s 25
disease (PD). However, these patients show inter-limb asymmetry in pedaling power when 26
cycling at their slow self-selected cadence. The effects of higher pedaling cadence on symmetry 27
of effort between limbs is unknown. We compared the effect of pedaling cadence on symmetry 28
of crank power output in individuals with PD versus healthy controls. Fifteen participants with 29
PD and 15 healthy controls performed 2-minute bouts of stationary cycling at three cadences (50, 30
65, 80 rpm) at 60W and self-selected workload. Power output contribution of each limb towards 31
total crank power output was computed over 60 crank cycles from the effective component of 32
pedal force, which was perpendicular to the crank arm. 33
34
35
36
37
38
Keywords: Ergometer, neurorehabilitation, UPDRS 39
40
Word Count: 41
Introduction 42
Parkinson’s disease (PD) is a common progressive neuromuscular condition affecting 43
more than 10 million individuals worldwide 1-3 and costs the healthcare system in the United 44
States 14 billion dollars annually 4. In patients with PD, degeneration of the dopaminergic 45
neurons within the substantia nigra leads to substantial reduction in dopamine production 5-6 46
resulting in symptoms such as resting tremors, bradykinesia or akinesia, rigidity, and postural 47
imbalance 7-11. These symptoms adversely affect the ability of these patients to perform activities 48
of daily living such as maintaining balance and walking. In addition, these clinical features in 49
patients with PD are generally more pronounced on side compared to the other, thereby leading 50
to asymmetry in performing motor tasks such was walking and cycling 12-13. 51
Cycling at is a commonly prescribed mode of neurorehabilitation for patients with PD 9, 52
13-14. Generally, patients with PD are prescribed stationary cycling at high cadences (i.e. 80-90 53
rpm) three times per week with sessions ranging from 30-60 minutes 9, 15-16. Post-cycling 54
sessions, patients experience immediate and long terms improvements such as decrease in resting 55
tremor, bradykinesia, and rigidity 9, 17-18, and enhancement in executive function 19. Cycling 56
cadence is a very critical variable for effectiveness of pedaling as an intervention for patients 57
with PD. Several studies have shown that symptomatic improvement is only observed at higher 58
and not lower preferred cadences of patients with PD 9, 14, 17, 20. Researcher have speculated that 59
cycling at higher cadences alleviates symptoms of PD by promoting changes in neural drive by 60
increasing both motor output and sensory input 14, 16. 61
Penko et al.13 found that individuals with PD are asymmetrical when pedaling at their 62
self-selected cadences. Specifically, these individuals exerted lesser power with their more 63
affected leg and compensate by exerting greater power with their less affected side. Generally, 64
self-selected cadence of patients with PD were low (59 ± 13 rpm) 9, 14, 16-17, 21, whereas 65
symptomatic improvements were observed at higher pedaling cadences (80-90 rpm) 9, 14, 16-17, 21. 66
Previous research in healthy subjects has shown that pedaling at higher cadences reduces 67
asymmetry in power output. However, no previous research has investigated whether asymmetry 68
of power output between lower limbs in cycling changes when pedaling at higher compared to 69
lower cadences in patients with PD. Similar to healthy subjects, pedaling at higher cadences 70
could also reduce interlimb asymmetry in power output for patients with PD. However, this 71
hypothesis has not yet been tested. Interlimb asymmetry in effort would place asymmetrical 72
stresses on the lower extremity joints on each side 22, 23. By reducing interlimb asymmetry in 73
cycling, effectiveness of pedaling could potentially be improved for rehabilitation of patients 74
with PD. 75
The purpose of this study is to examine the effects of pedaling cadence on interlimb 76
asymmetry in crank power output in patients with PD compared to healthy control. We 77
hypothesize that: 1) interlimb asymmetry in power output will be greater for patients with PD 78
compared to healthy controls, and; 2) interlimb asymmetry in power output will decrease at 79
higher cadences. 80
Methods 81
Study design: In this cross-sectional, case-controlled study differences in interlimb 82
asymmetry in crank power outputs at different cadences were assessed during low-intensity 83
stationary cycling between patients with PD and age-and-sex matched control subjects. All 84
experimental data were collected in single data collection session. 85
Participants: Sixteen individuals with idiopathic PD and twenty age-and-sex matched 86
healthy controls were recruited from the surrounding community. Sample size was calculated 87
using GPower 3.1 software based on index of asymmetry data reported by Penko et al.13. A total 88
sample size of 16 participants (8 per group) was needed to achieve a statistical power of 0.8 to 89
detect a large effect size (Cohen’s f=0.53) 24 for group main at an alpha level of 0.05. 90
A local neurologist screened the individuals with PD. Only individuals with Hoehn and 91
Yahr stage II-III when “off” anti-parkinsonian medication were eligible to participate 13. These 92
individuals were also assessed by the neurologist on the day of their testing using the Movement 93
Disorders Society’s revision of Unified Parkinson’s Disease Rating Scale (UPDRS) while “off” 94
anti-parkinsonian medication for at least twelve hours prior to examination 13. UPDRS is a 95
reliable and valid test to assess the severity of Parkinson’s disease 25-26. This scale was used to 96
determine which lower extremity was more affected based on UPDRS motor examination of 97
tremor, rigidity, and leg agility score on each side. These tests were scored on a scale from 0-4. 98
A score of 0 indicates a normal, unaffected individual, where a score of 4 indicates a high 99
severity of PD 15. These data were used to identify the limb that was more affected by PD. 100
All of the participants completed a health history and physical health questionnaire to 101
screen for exclusion criteria and obtain information about their current physical activity status 102
and cycling experience. Exclusion criteria included any muscular, orthopedic, neurologic, and/or 103
cardiovascular disorders that limited an individual’s ability to pedal on an ergometer at low to 104
moderate intensities. The Western Washington University Institutional Review Board approved 105
the study, and all participants gave written informed consent before participating. 106
Data Collection: In a single test session, participants completed 8 three-minutes pedaling 107
trials at cadence of 50, 65, 80 rpm at an experimentally controlled power output (i.e. 60 W) 13 108
and self-selected power output 9, 14, 16 in a random order. These chosen cadences fell within the 109
range of self-selected cadences (i.e. 50-70 rpm) 9, 14, 16 and therapeutically prescribed cadences 110
(i.e. 75-90 rpm) 9, 14, 16, 21 of individuals with PD. 111
All pedaling trials were conducted on an electronically braked Velotron Dynafit 112
ergometer cycle ergometer (Racer-Mate Inc., Seattle, WA) which is shown to be accurate and 113
reliable for measuring power output during cycling 27, 28. Power output of each leg was 114
determined using an instructed force pedal system (Sensix, Poitiers, France) which 115
synchronously measures pedal forces in all planes of motion via strain gauges and pedal and 116
crank orientation via optical encoders. Prior to arrival of participants, the calibration of the 117
Velotron ergometer was verified by performing the Accuwatt calibration check test (Racer-Mate 118
Inc., Seattle, WA) and instrumented force pedals were initialized to ensure they were calibrated 119
accurately with respect to manufacturer settings. 120
Subjects were then asked to change into spandex clothing and shoes provided by the 121
researchers. The subject’s weight and height were measured in pounds and inches, respectively, 122
using a standard balance beam scale with stadiometer. Subjects then completed a five-minute 123
warm-up at 20 W resistance and a self-selected cadence on the Velotron cycle ergometer 13, 15. 124
Three to five minutes of rest followed the warm-up where participants sat on the cycle 125
ergometer. Following this warm-up, participants completed three-minute trials under each of the 126
three randomly ordered workload-cadence conditions (60 W 50 rpm, 60 W 65 rpm, 60 W 80 127
rpm). Following the fixed power output pedaling conditions, participants repeated the three 3-128
minute trials of the same cadences in random order at self-selected power output. A rest interval 129
of three to five minutes separated each condition. 130
During these six cycling conditions, data were synchronously captured for bilateral pedal 131
forces and orientation, and crank position using instrumented force pedals at a sampling 132
frequency of 240 Hz during the last two minutes of each three-minute experimental condition. 133
Verbal encouragement was provided along with a visual screen that participations could look at 134
to maintain their assigned cadence. Participants finished with a five-minute cool-down at 20 W 135
resistance and a self-selected cadence 13, 15. 136
Data analysis: The crank position, pedal orientation, and pedal force data were low pass 137
filtered at 4 Hz using a fourth order recursive Butterworth filter. The pedal forces were 138
transposed to the crank coordinate system using pedal force and orientation, and crank position 139
data using the Sensix I-Crankset software (Poitiers, France). The anterior-posterior and normal 140
components of pedal forces were then used to compute resultant sagittal pedal forces. Effective 141
component of force is the only component of force that creates the angular impulse to rotate the 142
crank. The effective force was computed as the component of the resultant force perpendicular to 143
the crank arm using trigonometric methods described in previous studies 29, 30. Effective crank 144
torque on each side for a complete crank cycle was computed as a product of the component of 145
the effective pedal force and length of crank arm (0.1725 m). The crank power on each side was 146
computed as a product of effective crank torque and crank angular velocity. The data for crank 147
power on each side were then averaged over 60 crank cycles. 148
Based on the average crank power output measured for each limb, the Symmetry Index 149
(SI) was calculated for each 360-degree crank cycle. The equation to compute symmetry index is 150
based on previous research 13, 31 and it is as follows: 151
𝑆𝑦𝑚𝑚𝑒𝑡𝑟𝑦 𝐼𝑛𝑑𝑒𝑥 (𝑆𝐼) = (𝑈𝑛𝑎𝑓𝑓𝑒𝑐𝑡𝑒𝑑 𝑙𝑖𝑚𝑏 − 𝐴𝑓𝑓𝑒𝑐𝑡𝑒𝑑 𝑙𝑖𝑚𝑏
(𝑈𝑛𝑎𝑓𝑓𝑒𝑐𝑡𝑒𝑑 𝑙𝑖𝑚𝑏 + 𝐴𝑓𝑓𝑒𝑐𝑡𝑒𝑑 𝑙𝑖𝑚𝑏)/2) 152
Values from this equation can be used to quantify the magnitude of contribution from each limb. 153
A positive value indicates a greater contribution from the unaffected limb, while a negative value 154
indicates a greater contribution from the affected limb 13. This equation can be modified to 155
evaluate the contribution of left versus right lower extremity contribution, or dominant versus 156
non-dominant leg power. For the control group, leg dominance was determined by asking which 157
leg they preferred to kick a ball 32, 33. 158
𝑆𝑦𝑚𝑚𝑒𝑡𝑟𝑦 𝐼𝑛𝑑𝑒𝑥 (𝑆𝐼) = (𝐷𝑜𝑚𝑖𝑛𝑎𝑛𝑡 − 𝑁𝑜𝑛𝑑𝑜𝑚𝑖𝑛𝑎𝑛𝑡 𝑙𝑖𝑚𝑏
(𝐷𝑜𝑚𝑖𝑛𝑎𝑛𝑡 𝑙𝑖𝑚𝑏 + 𝑁𝑜𝑛𝑑𝑜𝑚𝑖𝑛𝑎𝑛𝑡 𝑙𝑖𝑚𝑏)/2) 159
Statistical analysis: Two-factor mixed model analysis of variance (ANOVAs) (limb 160
condition (4) x cadence (4)) with repeated measures on cadence were used to test the effects of 161
limb condition on index of asymmetry and total, average, and relative crank power output. For 162
between group contrasts, limb condition for the Parkinson’s disease group (i.e. more affected and 163
less affected leg) was not equivalent to the limb condition for healthy controls (dominant and 164
non-dominant leg). Therefore, limb condition variable with four levels (PD-more affected, PD-165
less affected, control dominant, and control non-dominant) was used for the between group 166
contrast. The statistical design used in the current study is identical to the one used by Hunt et 167
al.10, contrasting interlimb asymmetry in ACL-deficient individuals and healthy controls. Alpha 168
was set at .05. Significant main effects and interactions were further analyzed using univariate 169
ANOVAs and t-test, respectively. Effect sizes (Cohen’s f) are reported for primary dependent 170
variables. Small, medium, and large effect sizes correspond to Cohen’s f-values of 0.1, 0.25, and 171
0.40, respectively 24. All statistical procedures were performed using SPSS (Version 21). 172
173
Review of literature
Cycling at higher pedaling rates leads to symptomatic improvement in patients with
Parkinson’s disease (PD). However, these patients show inter-limb asymmetry in pedaling power
when cycling at their slow self-selected cadence. The effects of higher pedaling cadence on
symmetry of effort between limbs is unknown. This chapter will introduce the reader to relevant
information about PD, neurorehabilitation via cycling, assessment of symmetry in cycling, and
cycling cadence (a mechanical variable that affects both symptoms and symmetry in cycling).
This pertinent review of literature provides evidence to support the testing protocol and
procedures used in the current study.
Overview of Parkinson’s disease
Etiology
Parkinson’s disease (PD) is the second most common, progressive neuromuscular
condition, after Alzheimer’s disease, affecting more than 10 million individuals worldwide 1-3, 34.
Both the prevalence and the incidence of the disease increases with age. For individuals age 60
years or higher, the incidence of PD is 1-2% 34-35. Though the prevalence rates compared
between sexes has shown to be insignificant, more males have been reported to have the disease
34, with incidence showing significance in the age range of 60-69 and 70-79 36. The exact cause
for the disease is unknown, but studies have shown that both genetic and environmental factors
play a role in the development of PD 34-35, 37-38.
Neurophysiology
Parkinson’s disease is characterized by changes in the brain, more specifically the basal
ganglia. The basal ganglia are a group of subcortical nuclei that are highly connected with many
areas of the brain including the cortex, thalamus, and brain stem. These nuclei are associated
with many functions of life including voluntary movement, cognition, and emotion. Synaptic
pathways between the basal ganglia and the cortical systems are affected by dopaminergic status,
and dysfunction in these connections may lead to Parkinson’s disease symptomology 5, 38.
Within the basal ganglia is a structure known as the substantia nigra, which plays a role
in movement and reward. Degeneration of the dopaminergic neurons within the substantia nigra
pars compacta leads to as much as a 90% reduction in dopamine in the striatum, depriving the
basal ganglia of the dopamine that it requires to initiate and facilitate movement and postural
control required of daily living. Thus, leading to many of the motor and non-motor signs and
symptoms observed in PD 3, 6, 34, 37. de Lau et al. 1 speculated that dysfunction at the muscular
level, such as mitochondrial dysfunction, oxidative stress, and protein mishandlings, may play a
role in the pathogenesis of PD.
Symptomology
PD is characterized by motor and non-motor symptoms. As the disease progresses, it
becomes an increasing social and economic burden on those affected. Four cardinal motor
symptoms associated with PD are resting tremors, bradykinesia or akinesia, rigidity, and postural
imbalances. Resting tremors are an involuntary oscillatory movement produced when a limb is
fully supported against gravity and the muscles involved are not active 7. Bradykinesia or
akinesia are defined as a slowness or absence in movement initiation and execution. There is also
an observed reduction in its amplitude of movement up until complete cessation of the
movement 8. Diminished levels of dopamine and associated reduced motor control output in
patients with PD, is suggested to influence bradykinetic movements and impaired sensory
integration 9. Rigidity refers to an increase in resistance when passively stretching a muscle 10.
As PD progresses, patients begin to exhibit abnormal body posture, including an increase in
flexion of the head and cervical spine, an increase in thoracic kyphosis, and other postural
imbalances that greatly affect daily life 1, 11. Even though these symptoms are very common in
patients with PD, some of these symptoms are not always observed. The current criteria for the
diagnosis of PD includes the presence of at least two of these motor symptoms 1. The non-motor
symptoms include sensory deficits, insomnia, and emotional problems such as depression, lack
of facial expression, a slowing of gastrointestinal function, and reduction in the sense of smelling
39-40.
Diagnosis and Classification
Unified Parkinson’s Disease Rating Scale
Though there lacks a reliable and valid tool for these assessments, the Unified
Parkinson’s Disease Rating Scale (UPDRS) has been widely used to assess many factors of PD
including activities of daily living (ADLs), motor symptoms, mentation, and treatment
complications in these patients 25-26. Ramaker et al. 25 reports high internal consistency, inter-
rater reliability, and a moderate construct validity. The UPDRS has specific use in PD, covers
many arrays of the widespread scope of PD in differing severities, as well as clinimetric
properties, especially in ADLs, and motor examination. In 2009, the release of the Movement
Disorder Society-UPDRS (MDS-UPDRS) improved the older version of the test to cover
multiple groups at differing levels of severity 41. The MDS-UPDRS consists of four parts: I: non-
motor experiences of daily living; II: Motor experiences of daily living; III: Motor examination;
IV: Motor complications. Patient and caregiver or administrator complete questions in each
section on a rating scale of zero to four, with zero being normal, one being slight, two being
mild, three being moderate, and four being severe 42. The MDS-UPDRS rates sixty-five items,
taking the patient and caregiver approximately thirty minutes to complete 42.
Hoehn and Yahr scale
The Hoehn and Yahr scale has been widely accepted and utilized in the research of PD 18,
43-44. In a research setting, the Hoehn and Yahr scale is primarily used to define
inclusion/exclusion criteria 43. The scale consists of five stages, with each stage increasing in the
severity of the disease.
The modified Hoehn and Yahr scale is as follows: 41
Stage 0: No signs of disease
Stage 1.0: Symptoms are very mild; unilateral involvement only
Stage 1.5: Unilateral and axial involvement
Stage 2: Bilateral involvement without impairment of balance
Stage 2.5: Mild bilateral disease with recovery on pull test
Stage 3: Mild to moderate bilateral disease; some postural instability; physically independent
Stage 4: Severe disability; still able to walk or stand unassisted
Stage 5: Wheelchair bound or bedridden unless aided
Pharmacological management with Levodopa
Since PD remains a progressive and thus far, a non-curable disease, rehabilitation has
focused on decreasing the rate of progression as well as aiding in alleviating the side-effects that
are common from the debilitation disease. For nearly the past half century, the use of the drug
Levadopa (L-dopa) has been used to help alleviate the symptoms of PD. Further research found
that administration of L-dopa in lab animals led to an excretion of dopamine in the urine,
suggesting that dopamine levels were elevated 9, 45-46. As the disease progresses though,
complications arise from Levodopa including either inadequate dopaminergic tone, where the
drug wears-off or there are dose failures, or excessive dopaminergic tone that can cause
levodopa-induced dyskinesia 46. Though alternative medication can be used once L-dopa begins
to have negative side-effects, alternative medications are used when tolerance increases 46.
Neurorehabilitation for PD
PD is identified as a dysfunction in sensorimotor integration, leading to common
symptoms such as bradykinesia and other atypical movement. Alternative rehabilitation methods
have been researched and how they can positively elicit changes in the symptoms seen in PD 2-3,
8-9, 14. Neurorehabilitation programs are an increasingly favorable method for the rehabilitation of
PD 47. Huang et al. 47 also stated since the mechanism for the symptoms of PD, including
weakness and fatigue, are unknown and often subjective, challenges arise when constructing
neurorehabilitation programs. Though exercise has shown to combat other side-effects such as
sleep deprivation and depression, finding a regimen that can improve kinesthetic deficits as well
can be difficult 17. Many studies have shown an increased attention to interventions that promote
changes in neural drive 9, 13. These studies have shown that an increase in not just motor output,
but sensory input may play a role in these motor improvements, and since drugs like levodopa do
not improve these kinesthetic deficits, neurorehabilitation interventions like these are greatly
needed 14. High intensity exercise has been highly suggested as a method to increase neural drive
and promote neural plasticity as well as neuroprotection against dopaminergic cell loss 14.
Though the exact method is still undetermined, non-invasive trans-magnetic stimulation has been
used to show a decrease in the dysfunction of corticomotor excitability in people with PD 48.
These changes in corticomotor excitability could be at the base of symptomatic improvements.
Neurorehabilitation through cycling
An increasing interest in cycling specifically has occurred in researches studying the
effects of neurorehabilitation interventions for PD 16. Penko et al.13 stated that pedaling is a
bidpedal motor task, similar to walking, that requires the same principles of lower extremity
coordination, so quantifying pedaling kinetics can give a more precise measurement of lower
extremity function. The exact protocol for cycling has been studied largely by researchers hoping
to find a protocol that improves kinesthetic deficits the most 9, 13-14, 16. Alberts et al.16 stated that
in order for the patients to gain a benefit from exercise, the rate of the exercise must be increased
to trigger a release of neurotrophic factors and possibly dopamine.
Mode of cycling
A wide array of protocols has been looked at regarding cycling, and can be classified into
three distinct categories; Active, active-assisted, and passive. Active, also known as voluntary
cycling, is performed by the patient alone, usually at a self-selected pace 49. Though individuals
do see some improvements in symptomology from an active protocol, the other modes of
exercise have been shown to elicit greater improvements 9, 13-14, 16, 49. Active-assisted cycling
involves the individual biking with the assistance of an able-bodied assistant on a tandem
bicycle. The exact mechanism for a greater response in this mode is unknown, but it is
hypothesized that patients in this mode cycle at a cadence higher than their preferred speed, and
this intervention promotes an increase in afferent input to the central nervous system 50. Ridgel et
al. 14 found that patients in an active-assisted group showed a 13% greater increase in UPDRS
scores than compared to a voluntary group. In a practical sense, active-assisted cycling may not
be the best mode in terms of resources as well as at-home protocols. Not every individual will be
able to have an able-bodied assistant help them during at-home sessions. Passive cycling, or
forced exercise (FE), has been researched to work around these limitations. During FE, the
individual is assisted through a motorized bike that is set at a specific cadence. Patients are told
to cycle with the cadence of the motorized bike, so it is not passive in the sense that the patient
isn’t cycling, but they do not need to exert the force need to increase the cadence past their
comfortable range 14, 16. It has been proposed that FE promotes angiogenesis and synaptogenesis
which begin to degenerate in Parkinson’s disease. Acute aerobic exercise, in this case through a
forced-cycling regimen, has been shown to release neurotrophins such as brain-derived
neurotrophic fact (BDNF) and glial-derived neurotrophic factor (GDNF) as well as dopamine,
which aids in supporting neuroplasticity as well as protect against cell loss in the basal ganglia.
The key to this difference between FE and VE is the increase in intrinsic feedback, given by the
higher pedaling rate 16.
Mechanical variables critical for cycling performance assessment
Cadence
The specific modality of the cycling training program has been extensively studied as to
which modality is the most beneficial, and there has been an increasing interest in speed-based
training. Uygur et al. 18 examined the effects of an acute cadence-derived protocol primarily on
the symptoms of bradykinesia in Parkinson’s disease patients. Three groups were looked at; no
exercise, voluntary cycling, and high cadence-low resistance (HC:LR) cycling. For the HC:LR
group, the cycled at a self-selected pace, similar to the voluntary group, but during the first 15-
seconds of minutes 5-24, they pedaled at a self-selected fast cadence. They found that subjects in
the HC:LR group had significant improvement during a 4-square step test and 10-minute walk
test, primarily in walking velocity. It is suggested that this exercise facilitates locomotor central
pattern generators, which are generally impaired in the Parkinson’s disease population.
Power output
Power output as well as lower extremity function can be quantified using pedaling
kinetics. Power output can be a direct measurement of lower extremity asymmetries by
examining crank torque produced on the pedals 13. Penko et al.13 studied the effects that power
output has on common asymmetries seen in PD subjects. They tested their subjects by having
them cycle on a cycle ergometer beginning at 20W for three minutes at a self-selected pace.
They then increased the power by 20W every two minutes until the fourth stage (eighth minute),
when 40W increases were made until exhaustion. A symmetry Index was calculated to determine
whether the affected limb was contributing more or less as power increased. They witnessed a
decrease in the symmetry index as workload increased, indicating that symmetry was increasing.
The results of their study helped support a claim for a therapeutic intervention that provides
higher quality and quantity afferent information through the use of augmented pedaling motion,
as seen in forced exercise.
Measurement of cycling and its importance in rehabilitation
Asymmetry
As PD progresses, individuals experience a decrease in gait function, postural stability,
and coordination of voluntary movements. Every human exhibits some degree of asymmetry that
mostly goes unnoticed throughout the gait cycle 51, but individuals with PD exhibit a greater
degree of asymmetry that affects their activities of daily living. Asymmetry can be directly
quantified by measuring the crank torque of a modified cycle 13. Identifying asymmetry in
Parkinson’s disease patients would therefore provide a baseline to be later used to measure the
effectiveness of an intervention 13. Primary goals of exercise regimens for PD individuals should
be in reducing asymmetry, thus improving normal daily activity.
Index of asymmetry
Researchers have used the Symmetry Index as a method of evaluating the lower
extremity kinematics and degree of asymmetry in cyclers. Penko et al. 13 calculated the
symmetry index using the equation below:
𝑺𝒚𝒎𝒎𝒆𝒕𝒓𝒚 𝑰𝒏𝒅𝒆𝒙 (𝑺𝑰) = Unaffected limb − Affected limb
(Unaffected limb + affected limb)/2
Using this equation, the researchers could evaluate the degree of contribution from each limb,
with a positive value indicating a greater contribution by the unaffected limb, and a negative
number indicating a greater contribution from the affected limb 13. These variables could be
modified to evaluate left versus right leg contribution. Penko and colleagues 13 found that as the
power increased during a maximal cycle ergometry test, the symmetry index decreased,
indicating an increase in symmetry.
References
1. de Lau LM, Breteler MM. Epidemiology of Parkinson’s disease. Lancet Neurol.
2006;5(6):525–535. doi: 10.1016/S1474-4422(06)70471-9
2. Massano J, Bhatia KP. Clinical approach to Parkinson’s disease: Features, diagnosis, and
principles of management. Cold Spring Harb Perspect Med. 2012;2(6):1-17. doi:
10.1101/cshperspect.a008870
3. Alshehri AM. Parkinson’s disease: An overview of diagnosis and ongoing management.
Int. J. Pharm. Res. AlliedSci. 2017;6(2):163-70.
4. Kowal SL, Dall TM, Chakrabarti R, Storm MV, Jain A. The current and projected
economic burden of Parkinson’s disease in the United States. Mov Disord.
2013;28(3):311-318. doi: 10.1002/mds.25292
5. Ahn S, Zauber SE, Worth RM, Witt T, Rubchinsky LL. Interaction of synchronized
dynamics in cortex and basal ganglia in Parkinson’s disease. Eur. J. Neurosci.
2015;42(5):2164-2171. doi:10.1111/ejn.12980
6. Duce JA, Wong BX, Durham H, Devedjian J-C, Smith DP, Devos D. Post translational
changes to α-synuclein control iron and dopamine trafficking; a concept for neuron
vulnerability in Parkinson’s disease. Mol Neurodegen. 2017;12(1):1-12.
doi:10.1186/s13024-017-0186-8
7. Anouti A, Koller WC. Tremor disorders. Diagnosis and management. West J Med.
1995;162(6):510-513.
8. Bonassi G, Pelosin E, Ogliastro C, Cerulli C, Abbruzzese G, Avanzino L. Mirror visual
feedback to improve bradykinesia in Parkinson’s disease. Neural Plast. 2016;2016:1-11.
doi:10.1155/2016/8764238
9. Ridgel AL, Vitek JL, Alberts JL. Forced, not voluntary, exercise improves motor
function in Parkinson’s disease patients. Neurorehabil Neural Repair. 2009;23(6):600-
608. doi:10.1177/1545968308328726
10. Berardelli A, Sabra AF, Hallett M. Physiological mechanisms of rigidity in Parkinson’s
disease. J Neurol Neurosurg Psychiatry. 1983;46(1):45–53.
11. Wilczyński J, Pedrycz A, Mucha D, Ambroży T, Mucha D. Body posture, postural
stability, and metabolic age in patients with Parkinson’s disease. Biomed Res Int.
2017;2017:1-9. doi: 10.1155/2017/3975417
12. Boonstra TA, van Vugt JPP, van der Kooij H, Bloem BR. Balance asymmetry in
Parkinson’s disease and its contribution to freezing of gait. PLoS ONE. 2014;9(7):1-15.
doi: 10.1371/journal.pone.0102493
13. Penko AL, Hirsch JR, Voelcker-Rehage C, Martin PE, Blackburn G, Alberts JL.
Asymmetrical pedaling patterns in Parkinson’s disease patients. Clin Biomech.
2014;29(10):1089-1094. doi: 10.1016/j.clinbiomech.2014.10.006
14. Ridgel AL, Phillips RS, Walter BL, Discenzo FM, Loparo KA. Dynamic high-cadence
cycling improves motor symptoms in Parkinson’s disease. Front Neurol. 2015;6:1-9.
doi:10.3389/fneur.2015.00194
15. Fickes EJ. Effects of interval active-assisted cycling on balance in individuals with
Parkinson’s disease. [master’s thesis]. Kent, OH: Kent State University; 2012.
16. Alberts JL, Linder SM, Penko AL, Lowe MJ, Phillips M. It is not about the bike, it is
about the pedaling: Forced exercise and Parkinson’s disease. Exerc Sport Sci Rev.
2011;39(4):177–186. doi: 10.1097/JES.obo13e31822cc71a
17. Ridgel AL, Peacock CA, Fickes EJ, Kim CH. Active-assisted cycling improves tremor
and bradykinesia in Parkinson’s disease. Arch Phys Med Rehabil. 2012;93(11):2049-
2054. doi: 10.1016/j.apmr.2012.05.015
18. Uygur M, Bellumori M, LeNoir K, Poole K, Pretzer-Aboff I, Knight CA. Immediate
effects of high-speed cycling intervals on bradykinesia in Parkinson’s disease. Physiother
Theory Pract. 2015;31(2):77-82. doi: 10.3109/09593985.2014.972530
19. Ridgel AL, Muller Md, Kim CH, Fickes EJ, Mera TO. Acute effects of passive leg
cycling on upper extremity tremor and bradykinesia in Parkinson’s disease. Phys
Sportsmed. 2011;39(3):83-93. doi: 10.3810/psm.2011.09.1924
20. Alberts JL, Phillips M, Lowe MJ, et al. Cortical and motor responses to acute forced
exercise in Parkinson’s disease. Parkinsonism Relat Disord. 2016;24:56-62. doi:
10.1016/j.parkreldis.2016.01.015
21. Ridgel AL, Fickes EJ, Wilson KA. Effects of active-assisted cycling on motor function
and balance in Parkinson’s disease. J Neurol Sci. 2013;333:e91
22. Hunt MA, Sanderson DJ, Moffet H, Inglis T. Biomechanical changes elicited by an
anterior cruciate ligament deficiency during steady rate cycling. Clin Biomech.
2003;18(5):393-400.
23. Hunt MA, Sanderson DJ, Moffet H, Inglis JT. Interlimb asymmetry in persons with and
without an anterior cruciate ligament deficiency during stationary cycling. Arch Phys
Med Rehabil. 2004;85(9):1475-1478.
24. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd ed. Hillsdale, New
Jersey: Lawrence Erlbaum Associates; 1988.
25. Ramaker C, Marinus J, Stiggelbout AM, van Hilten BJ. Systematic evaluation of rating
scales for impairment and disability in Parkinson’s disease. Mov Disord. 2002;17(5):867-
876. doi:10.1002/mds.10248
26. Jankovic J. Parkinson’s disease: Clinical features and diagnosis. J Neurol Neurosurg
Psychiatry. 2008;79(4):368-376. doi:10.1136/jnnp.2007.131045
27. Abbis CR, Quod MJ, Levin G, Martin DT, Laursen PB. Accuracy of the Velotron
ergometer and SRM power meter. Int J Sports Med. 2009;30(2):107-112. doi: 10.1055/s-
0028-1103285
28. Astorino TA, Cottrell T, Lozano AT, Aburto-Pratt K, Duhon J. Increases in cycling
performance in response to caffeine ingestion are repeatable. Nutr Res. 2012;32(2):78-84.
doi: 10.1016/j.nutres.2011.12.001
29. Davis RR, Hull ML. Measurement of pedal loading in bicycling: II. Analysis and results.
J Biomech. 1981;14(12):857-61,863-872. doi: 10.1016/0021-9290(81)90013-0
30. Dorel S, Couturier A, Lacour JR, Vandewalle H, Hautier C, Hug F. Force-velocity
relationship in cycling revisted: benefit of two-dimensional pedal forces analysis. Med
Sci Sports Exerc. 2010;42(6):1174-1183. doi: 10.1249/MSS.0b013e3181c91f35
31. Carpes FP, Mota CB, Faria IE. On the bilateral asymmetry during running and cycling –
A review considering leg preference. Phys Ther Sport. 2010;11(4):136-142.
doi:10.1016/j.ptsp.2010.06.005
32. Smak W, Neptune RR, Hull ML. The influence of pedaling rate on bilateral asymmetry
in cycling. J biomech. 1999;32(9):899–906.
33. Carpes FP, Rossato M, Faria IE, Bolli Mota C. Bilateral pedaling asymmetry during a
simulated 40-km cycling time-trial. J Sports Med Phys Fitness. 2007;47(1):51-57
34. Mariani E, Frabetti F, Tarozzi A, Pelleri MC, Pizzetti F, Casadei R. Meta-analysis of
Parkinson’s disease transcriptome data using TRAM software: Whole substantia nigra
tissue and single dopamine neuron differential gene expression. PLoS ONE.
2016;11(9):1-21. doi:10.1371/journal.pone.0161567
35. Pringsheim T, Jette N, Frolkis A, Steeves TDL. The prevalence of Parkinson’s disease: A
systematic review and meta-analysis: PD PREVALENCE. Mov Disord.
2014;29(13):1583-1590. doi:10.1002/mds.25945
36. Hirsch L, Jette N, Frolkis A, Steeves T, Pringsheim T. The incidence of Parkinson’s
disease: A systematic review and meta-analysis. Neuroepidemiology. 2016;46(4):292-
300. doi: 10.1159/000445751
37. Vernier P, Moret F, Callier S, Snapyan M, Wersinger C, Sidhu A. The degeneration of
dopamine neurons in Parkinson’s disease: Insights from embryology and evolution of the
mesostriatocortical system. Ann N Y Acad Sci. 2004;1035:231-249
38. Sharott A, Magill PJ, Bolam JP, Brown P. Directional analysis of coherent oscillatory
field potentials in the cerebral cortex and basal ganglia of the rat: Directional analysis of
activity in cortico-basal ganglia circuits. Journal Physiol. 2005;562(3):951-963.
doi:10.1113/jphysiol.2004.073189
39. Huertas I, Jesús S, García-Gómez FJ, et al. Genetic factors influencing frontostriatal
dysfunction and the development of dementia in Parkinson’s disease. PLoS ONE.
2017;12(4):1-11. doi:10.1371/journal.pone.0175560
40. Goetz CG. The history of Parkinson’s disease: Early clinical descriptions and
neurological therapies. Cold Spring Harb Perspect Med. 2011;1(1):1-16.
doi:10.1101/cshperspect.a008862
41. Goetz CG, Stebbins GT, Tilley BC. Calibration of unified Parkinson’s disease rating
scale scores to Movement Disorder Society-unified Parkinson’s disease rating scale
scores. Mov Disord. 2012;27(10):1239-1242. doi: 10.1002/mds.25122
42. Goetz CG, Tilley BC, Shaftman SR, et al. Movement Disorder Society-sponsored
revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS): Scale
presentation and clinimetric testing results. Mov Disord. 2008;23(15):2129-2170. doi:
10.1002/mds.22340
43. Goetz CG, Poewe W, Rascol O, et al. Movement Disorder Society Task Force report on
the Hoehn and Yahr staging scale: Status and recommendations. Mov Disord.
2004;19(9):1020-1028. doi: 10.1002/mds.20213
44. Soh SE, Morris ME, McGinley JL. Determinants of health-related quality of life in
Parkinson’s disease: A systematic review. Parkinsonism Relat Disord. 2011;17(1):1-9.
doi: 10.1016;j.parkreldis.2010.08.012
45. Guin D, Mishra MK, Talwar P, Rawat C, Kushwaha SS, Kukreti S, Kukreti R. A
systematic review and integrative approach to decode the common molecular link
between levodopa response and Parkinson’s disease. BMC Med Genomics.
2017;10(56):1-21. doi: 10.1186/s12920-017-0291-0
46. Jongkyu P, Younsoo K, Jinyoung Y, et al. Levodopa dose maintenance or reduction in
patients with Parkinson’s disease transitioning to levodopa/carbidopa/entacapone. Neurol
India. 2017;65(4):746-751. doi:10.4103/neuroindia.NI_597_16
47. Huang Y, Chang F, Liu W, Chuang Y, Chuang L, Chang Y. Fatigue and muscle strength
involving walking speed in Parkinson’s disease: Insights for developing rehabilitation
strategy for PD. Neural Plast. 2017;2017:1-9. doi: 10.1155/2017/1941980
48. Fisher BE, Wu AD, Salem GJ, et al. The effect of exercise training in improving motor
performance and corticomotor excitability in people with early Parkinson’s disease. Arch
Phys Med Rehabil. 2008;89(7):1221-9. doi: 10.1016/j.apmr.2008.01.013
49. Rosenfeldt AB, Rasanow M, Penko AL, Beall EB, Alberts JL. The cyclical lower
extremity exercise for Parkinson’s trial (CYCLE): Methodology for a randomized
controlled trial. BMC Neurol. 2015;15(63):1-9. doi: 10.1186/s12883-015-0313-5
50. Corbett DB, Peer KS, Ridgel AL. Biomechanical muscle stimulation and active-assisted
cycling improves active range of motion in individuals with Parkinson’s disease.
Neurorehabil. 2013;33(2):313-322. doi: 10.3233/NRE-130961
51. Handzic I, Reed KB. Perception of gait patterns that deviate from normal and symmetric
biped locomotion. Front Psychol. 2015;6:1-14. doi: 10.3389/fpsyg.2015.00199