J Neurol DOI 10.1007/s00415-015-7686-7
NEUROLOGICAL UPDATE
Neurological update: emerging issues in gait disorders Simon J. G. Lewis
Received: 13 February 2015 / Accepted: 17 February 2015 Ó Springer-Verlag Berlin Heidelberg 2015
Abstract Gait disorders represent a common and diverse challenge in Neurological practice. The literature on this field is expanding and is seeking to address mainstream clinical issues as well as a greater understanding of pathophysiological mechanisms. This update will introduce a range of these concepts. Keywords Gait Parkinson’s Mild cognitive impairment Dementia Neuroimaging Neurophysiology
Introduction The term ‘‘gait disorder’’ is a challenging one in Neurological practice. It will be instantly associated with a range of common and rarer diseases where disturbances of gait characterise the condition, such as in Parkinson’s disease and the other parkinsonian disorders. In addition, there is a growing appreciation that a disorder of gait whilst being clinically subtle may represent a significant component of the underlying disease process, as can be seen in mild cognitive impairment and dementia. Furthermore, the term gait disorder is also used as the descriptor for phenomenological events, which may occur consistently like step-to-step variability or episodically as with problems of gait initiation failure and freezing of gait. Much of this confusion in nomenclature has arisen from the evolution of our specialty. Whereas, there was an initial emphasis on clinical observation, diagnosis and prognostication our greater understanding of pathophysiology and S. J. G. Lewis (&) University of Sydney and Royal Prince Alfred Hospital, Sydney, Australia e-mail: [email protected]
the neurobiology of gait disorders has challenged us to become more cognisant about our approach to the problem. An expansion of available research modalities including optical motion capture systems, wireless motion sensor devices, accelerometry, transcranial magnetic stimulation (TMS) and neuroimaging, coupled with detailed clinical phenotyping with an emphasis on non-motor symptoms has resulted in a more comprehensive appreciation of the neural correlates underlying gait disorders. A full review of these advances is clearly beyond the scope of this article but this topic holds significance for all of us given recent data highlighting the startling statistic that simple gait speed is a predictor of survival in older adults [1]! Therefore this update will aim to focus on selected areas that will hopefully be of interest to those who may not have been able to ‘‘keep pace with this moving field’’. Gait disorder in dementia The presence of gait disorders in dementia has been recognised for over 30 years. Original work in Alzheimer’s disease (AD) described these patients as having significantly shorter step length, slower gait speed, lower stepping frequency, greater step-to-step variability, greater double support ratio and greater sway path than age matched controls [2]. A gait disorder is evident even in mild AD (e.g. mini mental state examination [20/30) and may be a more sensitive functional marker than cognitive decline [3]. Despite the initial reports of gait disorder in association with AD, it has become increasingly accepted that the prevalence and severity of gait disturbance is significantly higher in the non-AD dementias. Perhaps not surprisingly given their neuropathological underpinnings, both Lewy Body and particularly, vascular dementia have higher rates of gait disorder than AD [4]. Indeed the appearance of
123
J Neurol
early gait disturbance in patients with dementia has been taken as a more supportive feature of non-AD dementia [5]. Given that the processes underlying gait disturbance are closely linked with cognition, a number of studies have attempted to use the emergence of a gait disorder as a preclinical biomarker in the prediction of dementia. Early studies relied on approaches such as the identification of neurologically classified baseline gait disturbances [6] and simple timed walking tasks [7] to gather prospective data in non-demented older population samples. These rudimentary approaches successfully identified higher rates of incident dementia amongst those older participants who showed gait slowing and other features. The advent of technology that permits the objective recording of quantitative gait parameters using techniques such as a computerised walkway with embedded pressure sensors has permitted an increased understanding of the relationships between motor control and cognition. For example, a prospective cohort study of 399 dementia-free, community-based older adults over 5 years of follow-up (median 2 years) identified 33 subjects who developed dementia [8]. However, by reducing eight baseline quantitative gait parameters to three independent factors representing pace, rhythm and variability the investigators were able to perform a factor analysis that identified differential relationships between gait and cognition. Just a one point increase on the rhythm factor was associated with memory decline, whereas the pace factor was associated with decline on executive function. In Cox models adjusted for age, sex and education, a one point increase on baseline rhythm and variability factor scores was associated with increased risk of dementia. Furthermore, the pace factor specifically predicted the risk of developing vascular dementia. An appreciation of these relationships has led some researchers to perform cognitive risk assessments that incorporate motoric signs. The newly proposed motoric cognitive risk (MCR) syndrome is defined as the presence of cognitive complaints and slow gait (one standard deviation below age- and sex-specific gait speed means) in non-demented individuals [9]. Over the age of 70 years, 7 % of the population fulfil diagnostic criteria for MCR and have a significant risk of developing dementia [9]. These findings highlight that objective gait markers of preclinical dementia may lead to new insights into early disease stages, improve diagnostic assessments, allow for disease monitoring and identify new preventive strategies. Gait disorder in Parkinson’s disease The parkinsonian gait of Parkinson’s disease (PD) and related Parkinson plus syndromes has been well described elsewhere (for review see [10]) but there are a number of newly emerging concepts that are of particular relevance in
123
the field. In keeping with the work relating the emergence of gait disorder as a red flag for the development of dementia, there has been a concentrated effort in identifying the pre-motor syndrome of PD. Whilst a number of non-motor features including constipation, anosmia and mood disturbance have been identified as risk factors for PD (for review see [11] ), probably the most likely symptom to be useful in routine clinical practice is the emergence of idiopathic rapid eye movement sleep behaviour disorder (iRBD) where otherwise healthy individuals begin acting out their dreams. Significantly, two recent prospective studies following patients for over 14 year have identified that the transition of patients with iRBD to an alpha-synucleinopathy (i.e. PD, dementia with Lewy bodies and multiple system atrophy) is over 80 % [12, 13]. Studies exploring the relationship between RBD and gait disorder in established PD have reported conflicting results [14, 15]. However, there would appear to be obvious neuroanatomical connections between sleep regulating nuclei and regions controlling gait and posture especially within the pontine tegmentum, pedunculopontine nucleus and medial medulla. Thus given the relationship between iRBD and neurodegeneration the identification of any characteristic gait disorder in these patients may prove highly relevant. For example, it is possible that severity and/or any pattern of gait dysfunction in iRBD may potentially be helpful in predicting how soon a patient will transition to an alpha-synucleinopathy and even for predicting their specific pre-morbid diagnosis before the appearance of more clinically diagnostic features. Recent work evaluating gait parameters in iRBD has identified decreased velocity and cadence, as well as significantly increased double limb support variability and greater stride/swing time variability compared to age matched controls [16]. As yet, prospective follow-up data are not available to determine the clinical utility of these observations regarding transition to an alpha-synucleinopathy. The presence of subclinical gait and postural dysfunction in early and incident PD is also an area of growing interest. Patients with early PD often do not complain of any subjective gait disturbance and it may only be when they are challenged by the addition of a cognitive load when walking (known as dual tasking) that deficits emerge. Whilst maintaining gait velocity during dual tasking, changes can be observed on other objective measures such as, increased stride width, number of cadences and a reduction in swing/cycle time [17]. However, a study of dual tasking in incident PD who were assessed within just 4 months of their diagnosis did not show these more general deficits [18]. In fact these patients only differed from controls in their inability to modulate step width variability suggesting a greater risk to postural stability when they were engaged in more complex tasks. Additionally, home
J Neurol
activity monitoring devices have revealed that incident PD patients are significantly less active than controls, with an inability to sustain levels of walking, which highlights the fact that interventional strategies should be implemented at the time of diagnosis [19]. Many inconsistencies reported in studies of gait in PD may in fact be related to the significant heterogeneity and possible sub-groups that exist within the condition [20]. Although potentially artificial, the division of cases into tremor dominant and patients with postural instability and gait difficulty (PIGD) on the basis of predominant motor phenotype is commonly undertaken. Neuroimaging studies have highlighted that whilst these motor sub-groups do not seem to be differentiated by the presence of white matter lesions [21], those patients with PIGD have demonstrated selective grey matter atrophy predominantly across motor, cognitive and limbic associative areas with their symptom severity correlating with volume loss in pre-supplementary motor and motor cortices [22]. However, recent work objectively evaluating tremor dominant and PIGD patients has demonstrated that significant overlap occurs between many parameters of gait and balance casting serious doubt on the clinical utility of this simplistic classification scheme [23]. Understanding the neurobiology of gait disorders A range of other novel approaches has been extensively utilised in the research setting to enhance our understanding of gait disorders. The expansion of structural and functional neuroimaging techniques, cerebrospinal fluid markers, TMS and a range of neurophysiological approaches have yet to find any place in routine clinical practice but they do offer potential for improving our management across a range of diseases. The use of magnetic resonance imaging (MRI) and positron emission tomography (PET) in the dementia field has largely explored the neurobiology underlying specific cognitive deficits, disease progression and response to therapy with far less work being focused on the imaging correlates of the associated gait disorders. However, in view of the pre-morbid association between motor and cognitive decline discussed above, some neuroimaging work has recently been undertaken in patients identified as having mild cognitive impairment (MCI). The syndrome of MCI is characterised by cognitive decline that is greater than that expected for an individual’s age and education level, whilst not significantly interfering with activities of daily life [24]. Patients with MCI constitute an ‘at-risk’ population for dementia with an approximate conversion rate of 50 % within 5 years [24]. One recent MRI study using combined volumetric and spectroscopic analysis has studied MCI patients who had undergone quantitative gait analysis [25]. Both the volume
of the primary motor cortex as well as higher levels of choline/creatine, a measure of cellular turnover that is elevated in inflammatory processes and ischaemic lesions of the brain, predicted slower gait velocity in MCI patients. The authors hypothesised that selective regional atrophy in the motor cortex would impact on the cognitive control network of locomotion and that chronic ischaemic demyelination related to cerebrovascular disease may further contribute to gait slowing. Furthermore, the N-acetyl aspartate/creatine ratio, a marker of neuronal health and function was correlated with higher (i.e. worse) stride time variability when dual tasking, suggesting that the regularity of gait is associated with neural function, even at the molecular level during the evolution of dementia. Given the contributory role of cerebral small vessel disease on gait disorders and cognitive decline, work has also been conducted in this field with structural MRI. Significantly, pathological studies have demonstrated abnormalities in white matter that may appear normal on brain imaging and as such techniques like diffusion tensor imaging (DTI) have been utilised to offer additional insights in vivo. One such study evaluated 429 healthy individuals (50–85 year) who had undergone quantitative gait assessment. Results revealed a loss of white matter integrity particularly in the genu of the corpus callosum, as indicated by a lower fractional anisotropy and higher mean diffusivity [26]. This finding emphasises the importance of the interconnections between the right and left hemispheric cortical regions, especially in the prefrontal cortex that are involved in the cognitive control of motor performance. The role of atrophy and disrupted networks has also been investigated in higher-level gait disorders (HLGD) which is a term used for patients with locomotor and balance difficulties that cannot be readily explained by specific lesions throughout the different components of the nervous system. Whilst a variety of neurodegenerative and other pathologies can produce HLGD, the most common cause appears to be microvascular disease causing white matter lesions that disrupt the balance and locomotor circuits [27]. Recent neuroimaging work in such patients has identified that gait and balance deficits appear to arise from lesions or dysfunctions in a network linking the primary motor cortex and the mesencephalic locomotor region (MLR). In contrast, more cognitive and ‘appendicular’ hypokinetic-rigid features are associated with deep white matter lesions possibly through their impact on corticostriatal networks [28]. Much of early work evaluating gait disorders in PD focused on the role of the failing dopaminergic nigrostriatal tract and the motor loop of the basal ganglia. However, the incomplete amelioration offered by current treatments, even in mild disease, has made it increasingly obvious that other pathways must be playing a critical role.
123
J Neurol
One clue towards a potential substrate for the gait disorder seen in PD is the pattern of cognitive impairment observed. It has long been known that many cognitive deficits in PD are often worsened by anti-cholinergic medications, whereas some benefits may be derived from the cholinesterase inhibitors [29]. In keeping with these clinical observations, recent PET research that has revealed cortical cholinergic deficits rather than dopaminergic losses are correlated with gait speed in PD [30]. Further evidence for a causative role of cholinergic disruption in the gait disorders of PD comes from neurophysiological results utilising short-latency afferent inhibition (SAI) in PD. The non-invasive SAI technique conditions the motor cortex via peripheral stimulation of the median nerve before delivering transcranial magnetic stimulation with a short inter-stimulus delay. This approach assesses an inhibitory circuit in the sensorimotor cortex, which is believed to depend on intact cortical and subcortical cholinergic systems. Work in early PD has confirmed that cholinergic loss determined by SAI is an independent predictor of slower gait speed [31]. In addition to its role in more general gait dysfunction, cholinergic PET has been used to explore freezing of gait (FOG) in PD. Compared to non-freezers, patients with FOG showed lower levels of neocortical cholinergic innervation and striatal dopamine but did not have significantly different thalamic cholinergic denervation [32]. The pathophysiology underlying FOG is not well understood and a number of models have recently been proposed [33]. Interestingly, a number of research groups have attempted to map out regional grey matter atrophy in association with FOG with conflicting results, perhaps suggesting that there is likely to be a more functional rather than structural pathology driving this phenomenon [34– 39]. Two recent functional MRI (fMRI) studies exploring the freezing phenomenon have both demonstrated similar abnormalities across corticostriatal networks [40, 41]. One of these fMRI studies utilised a Virtual Reality (VR) approach, which has been able to correlate actual episodes of FOG to performance in the VR environment [42]. The investigators reported that VR freezing was associated with a decreased blood oxygen level-dependent response bilaterally in the sensorimotor regions, head of caudate nucleus, the thalamus and the globus pallidus internus and MLR, whereas increased activation was seen within frontoparietal cortical regions [40]. Furthermore, these signal changes were correlated with the severity of clinical FOG. A subsequent VR fMRI has revealed that during freezing there is a functional decoupling between the basal ganglia network and the cognitive control network in each hemisphere suggesting that FOG is related to paroxysmal breakdowns between communicating neural networks [43].
123
The observation that FOG is associated with a pattern of cortical changes on fMRI has led researchers to explore the role of electroencephalography (EEG) in detecting the phenomenon. When compared to walking, episodes of FOG were associated with a significant increase in theta band power within the central and frontal leads [44]. Significantly, in relation to possible future management strategies, such EEG changes could be detected a few seconds before gait arrest [45]. Therefore, FOG is associated with abnormal oscillatory activity and taken together, these neuroimaging and neurophysiological results support the hypothesis that freezing in PD arises from impaired communication between complimentary yet competing neural networks in association with paroxysmal increases in inhibitory basal ganglia outflow [46].
Conclusion Unfortunately, the translation of our increased understanding of gait disorders into more effective clinical management has not yet occurred. However, it should be clear that being aware about the relationships between gait disorder and a variety of neurological conditions, as well as the ability to account for the neurobiology underpinning them will present many such opportunities in the future. It is anticipated that the use of novel pharmacological and non-pharmacological strategies will offer more directed approaches to symptom relief. This will be assisted by identifying the role of neurotransmitters and targeting the restoration of disrupted circuits. Furthermore, emerging technologies such as closed loop deep brain stimulation may allow for the treatment of paroxysmal symptoms. Whilst remaining an enigma, the clinical challenge of gait disorders represents one of the most exciting prospects for our specialty moving forwards! Conflicts of interest
None.
References 1. Studenski S, Perera S, Patel K et al (2011) Gait speed and survival in older adults. JAMA 305(1):50–58 2. Visser H (1983) Gait and balance in senile dementia of Alzheimer’s type. Age Ageing 12(4):296–301 3. Cedervall Y, Halvorsen K, Aberg AC (2014) A longitudinal study of gait function and characteristics of gait disturbance in individuals with Alzheimer’s disease. Gait Posture 39(4):1022–1027 4. Allan LM, Ballard CG, Burn DJ, Kenny RA (2005) Prevalence and severity of gait disorders in Alzheimer’s and non-Alzheimer’s dementias. J Am Geriatr Soc 53(10):1681–1687 5. Ala TA, Frey WH 2nd (1995) Validation of the NINCDSADRDA criteria regarding gait in the clinical diagnosis of Alzheimer disease. A clinicopathologic study. Alzheimer Dis Assoc Disord 9(3):152–159
J Neurol 6. Verghese J, Lipton RB, Hall CB, Kuslansky G, Katz MJ, Buschke H (2002) Abnormality of gait as a predictor of non-Alzheimer’s dementia. N Engl J Med 347(22):1761–1768 7. Waite LM, Grayson DA, Piguet O, Creasey H, Bennett HP, Broe GA (2005) Gait slowing as a predictor of incident dementia: 6-year longitudinal data from the Sydney Older Persons Study. J Neurol Sci 229–230:89–93 8. Verghese J, Wang C, Lipton RB, Holtzer R, Xue X (2007) Quantitative gait dysfunction and risk of cognitive decline and dementia. J Neurol Neurosurg Psychiatry 78(9):929–935 9. Verghese J, Wang C, Lipton RB, Holtzer R (2013) Motoric cognitive risk syndrome and the risk of dementia. J Gerontol A Biol Sci Med Sci 68(4):412–418 10. Ebersbach G, Moreau C, Gandor F, Defebvre L, Devos D (2013) Clinical syndromes: Parkinsonian gait. Mov Disord 28(11): 1552–1559 11. Postuma RB, Aarsland D, Barone P et al (2012) Identifying prodromal Parkinson’s disease: pre-motor disorders in Parkinson’s disease. Mov Disord 27(5):617–626 12. Iranzo A, Tolosa E, Gelpi E et al (2013) Neurodegenerative disease status and post-mortem pathology in idiopathic rapid-eyemovement sleep behaviour disorder: an observational cohort study. Lancet Neurol 12(5):443–453 13. Schenck CH, Boeve BF, Mahowald MW (2013) Delayed emergence of a parkinsonian disorder or dementia in 81 % of older men initially diagnosed with idiopathic rapid eye movement sleep behavior disorder: a 16-year update on a previously reported series. Sleep Med 14(8):744–748 14. Benninger DH, Michel J, Waldvogel D et al (2010) REM sleep behavior disorder is not linked to postural instability and gait dysfunction in Parkinson. Mov Disord 25(11):1597–1604 15. Bugalho P, Viana-Baptista M (2013) REM sleep behavior disorder and motor dysfunction in Parkinson’s disease—a longitudinal study. Parkinsonism Relat Disord 19(12):1084–1087 16. McDade EM, Boot BP, Christianson TJ et al (2013) Subtle gait changes in patients with REM sleep behavior disorder. Mov Disord 28(13):1847–1853 17. Panyakaew P, Bhidayasiri R (2013) The spectrum of preclinical gait disorders in early Parkinson’s disease: subclinical gait abnormalities and compensatory mechanisms revealed with dual tasking. J Neural Transm (Vienna, Austria: 1996) 120(12):1665– 1672 18. Rochester L, Galna B, Lord S, Burn D (2014) The nature of dualtask interference during gait in incident Parkinson’s disease. Neuroscience 265:83–94 19. Lord S, Godfrey A, Galna B, Mhiripiri D, Burn D, Rochester L (2013) Ambulatory activity in incident Parkinson’s: more than meets the eye? J Neurol 260(12):2964–2972 20. Lewis SJG, Foltynie T, Blackwell AD, Robbins TW, Owen AM, Barker RA (2005) Heterogeneity of Parkinson’s disease in the early clinical stages using a data driven approach. J Neurol Neurosurg Psychiatry 76:343–348 21. Herman T, Rosenberg-Katz K, Jacob Y et al (2013) White matter hyperintensities in Parkinson’s disease: do they explain the disparity between the postural instability gait difficulty and tremor dominant subtypes? PLoS One 8(1):e55193 22. Rosenberg-Katz K, Herman T, Jacob Y, Giladi N, Hendler T, Hausdorff JM (2013) Gray matter atrophy distinguishes between Parkinson disease motor subtypes. Neurology 80(16):1476–1484 23. Herman T, Weiss A, Brozgol M, Giladi N, Hausdorff JM (2014) Gait and balance in Parkinson’s disease subtypes: objective measures and classification considerations. J Neurol 261(12): 2401–2410. doi:10.1007/s00415-014-7513-6 24. Gauthier S, Reisberg B, Zaudig M et al (2006) Mild cognitive impairment. Lancet 367(9518):1262–1270
25. Annweiler C, Beauchet O, Bartha R et al (2013) Motor cortex and gait in mild cognitive impairment: a magnetic resonance spectroscopy and volumetric imaging study. Brain 136(Pt 3):859–871 26. de Laat KF, Tuladhar AM, van Norden AG, Norris DG, Zwiers MP, de Leeuw FE (2011) Loss of white matter integrity is associated with gait disorders in cerebral small vessel disease. Brain 134(Pt 1):73–83 27. Nutt JG (2013) Higher-level gait disorders: an open frontier. Mov Disord 28(11):1560–1565 28. Demain A, Westby GW, Fernandez-Vidal S et al (2014) Highlevel gait and balance disorders in the elderly: a midbrain disease? J Neurol 261(1):196–206 29. Williams-Gray CH, Foltynie T, Lewis SJG, Barker RA (2006) Cognitive deficits and psychosis in Parkinson’s disease: a review of pathophysiology and therapeutic options. CNS Drugs 20(6):477–505 30. Bohnen NI, Frey KA, Studenski S et al (2013) Gait speed in Parkinson disease correlates with cholinergic degeneration. Neurology 81(18):1611–1616 31. Rochester L, Yarnall AJ, Baker MR et al (2012) Cholinergic dysfunction contributes to gait disturbance in early Parkinson’s disease. Brain 135(Pt 9):2779–2788 32. Bohnen NI, Frey KA, Studenski S et al (2014) Extra-nigral pathological conditions are common in Parkinson’s disease with freezing of gait: an in vivo positron emission tomography study. Mov Disord 29(9):1118–1124 33. Nieuwboer A, Giladi N (2013) Characterizing freezing of gait in Parkinson’s disease: models of an episodic phenomenon. Mov Disord 28(11):1509–1519 34. Kostic VS, Agosta F, Pievani M et al (2012) Pattern of brain tissue loss associated with freezing of gait in Parkinson disease. Neurology 78(6):409–416 35. Tessitore A, Amboni M, Cirillo G et al (2012) Regional gray matter atrophy in patients with Parkinson disease and freezing of gait. AJNR Am J Neuroradiol 33(9):1804–1809 36. Herman T, Rosenberg-Katz K, Jacob Y, Giladi N, Hausdorff JM (2014) Gray matter atrophy and freezing of gait in Parkinson’s disease: is the evidence black-on-white? Mov Disord 29(1): 134–139 37. Rubino A, Assogna F, Piras F, Di Battista ME, Imperiale F, Chiapponi C, Spalletta G, Meco G (2014) Does a volume reduction of the parietal lobe contribute to freezing of gait in Parkinson’s disease? Parkinsonism Relat Disord 20(10): 1101–1103. doi:10.1016/j.parkreldis.2014.07.002 38. Youn J, Cho JW, Lee WY, Kim GM, Kim ST, Kim HT (2012) Diffusion tensor imaging of freezing of gait in patients with white matter changes. Mov Disord 27(6):760–764 39. Fling BW, Cohen RG, Mancini M, Nutt JG, Fair DA, Horak FB (2013) Asymmetric pedunculopontine network connectivity in parkinsonian patients with freezing of gait. Brain 136(Pt 8):2405–2418 40. Shine JM, Matar E, Ward PB et al (2013) Exploring the cortical and subcortical functional magnetic resonance imaging changes associated with freezing in Parkinson’s disease. Brain 136(Pt 4):1204–1215 41. Vercruysse S, Spildooren J, Heremans E, Wenderoth N, Swinnen SP, Vandenberghe W, Nieuwboer A (2014) The neural correlates of upper limb motor blocks in Parkinson’s disease and their relation to freezing of gait. Cereb Cortex 24(12):3154–3166. doi:10.1093/cercor/bht170 42. Shine JM, Matar E, Bolitho SJ et al (2013) Modeling freezing of gait in Parkinson’s disease with a virtual reality paradigm. Gait Posture 38(1):104–108 43. Shine JM, Matar E, Ward PB et al (2013) Freezing of gait in Parkinson’s disease is associated with functional decoupling
123
J Neurol between the cognitive control network and the basal ganglia. Brain 136(Pt 12):3671–3681 44. Shine JM, Handojoseno AM, Nguyen TN, Tran Y, Naismith SL, Nguyen H, Lewis SJ (2014) Abnormal patterns of theta frequency oscillations during the temporal evolution of freezing of gait in Parkinson’s disease. Clin Neurophysiol 125(3):569–576. doi:10. 1016/j.clinph.2013.09.006
123
45. Handojoseno AM, Shine JM, Nguyen TN, Tran Y, Lewis SJ, Nguyen HT (2012) The detection of Freezing of Gait in Parkinson’s disease patients using EEG signals based on Wavelet decomposition. Conf Proc 2012:69–72 46. Lewis SJG, Barker RA (2009) A pathophysiological model of freezing of gait in Parkinson’s disease. Parkinsonism Relat Disord 15(5):333–338
NEUROLOGICAL UPDATE
Neurological update: emerging issues in gait disorders Simon J. G. Lewis
Received: 13 February 2015 / Accepted: 17 February 2015 Ó Springer-Verlag Berlin Heidelberg 2015
Abstract Gait disorders represent a common and diverse challenge in Neurological practice. The literature on this field is expanding and is seeking to address mainstream clinical issues as well as a greater understanding of pathophysiological mechanisms. This update will introduce a range of these concepts. Keywords Gait Parkinson’s Mild cognitive impairment Dementia Neuroimaging Neurophysiology
Introduction The term ‘‘gait disorder’’ is a challenging one in Neurological practice. It will be instantly associated with a range of common and rarer diseases where disturbances of gait characterise the condition, such as in Parkinson’s disease and the other parkinsonian disorders. In addition, there is a growing appreciation that a disorder of gait whilst being clinically subtle may represent a significant component of the underlying disease process, as can be seen in mild cognitive impairment and dementia. Furthermore, the term gait disorder is also used as the descriptor for phenomenological events, which may occur consistently like step-to-step variability or episodically as with problems of gait initiation failure and freezing of gait. Much of this confusion in nomenclature has arisen from the evolution of our specialty. Whereas, there was an initial emphasis on clinical observation, diagnosis and prognostication our greater understanding of pathophysiology and S. J. G. Lewis (&) University of Sydney and Royal Prince Alfred Hospital, Sydney, Australia e-mail: [email protected]
the neurobiology of gait disorders has challenged us to become more cognisant about our approach to the problem. An expansion of available research modalities including optical motion capture systems, wireless motion sensor devices, accelerometry, transcranial magnetic stimulation (TMS) and neuroimaging, coupled with detailed clinical phenotyping with an emphasis on non-motor symptoms has resulted in a more comprehensive appreciation of the neural correlates underlying gait disorders. A full review of these advances is clearly beyond the scope of this article but this topic holds significance for all of us given recent data highlighting the startling statistic that simple gait speed is a predictor of survival in older adults [1]! Therefore this update will aim to focus on selected areas that will hopefully be of interest to those who may not have been able to ‘‘keep pace with this moving field’’. Gait disorder in dementia The presence of gait disorders in dementia has been recognised for over 30 years. Original work in Alzheimer’s disease (AD) described these patients as having significantly shorter step length, slower gait speed, lower stepping frequency, greater step-to-step variability, greater double support ratio and greater sway path than age matched controls [2]. A gait disorder is evident even in mild AD (e.g. mini mental state examination [20/30) and may be a more sensitive functional marker than cognitive decline [3]. Despite the initial reports of gait disorder in association with AD, it has become increasingly accepted that the prevalence and severity of gait disturbance is significantly higher in the non-AD dementias. Perhaps not surprisingly given their neuropathological underpinnings, both Lewy Body and particularly, vascular dementia have higher rates of gait disorder than AD [4]. Indeed the appearance of
123
J Neurol
early gait disturbance in patients with dementia has been taken as a more supportive feature of non-AD dementia [5]. Given that the processes underlying gait disturbance are closely linked with cognition, a number of studies have attempted to use the emergence of a gait disorder as a preclinical biomarker in the prediction of dementia. Early studies relied on approaches such as the identification of neurologically classified baseline gait disturbances [6] and simple timed walking tasks [7] to gather prospective data in non-demented older population samples. These rudimentary approaches successfully identified higher rates of incident dementia amongst those older participants who showed gait slowing and other features. The advent of technology that permits the objective recording of quantitative gait parameters using techniques such as a computerised walkway with embedded pressure sensors has permitted an increased understanding of the relationships between motor control and cognition. For example, a prospective cohort study of 399 dementia-free, community-based older adults over 5 years of follow-up (median 2 years) identified 33 subjects who developed dementia [8]. However, by reducing eight baseline quantitative gait parameters to three independent factors representing pace, rhythm and variability the investigators were able to perform a factor analysis that identified differential relationships between gait and cognition. Just a one point increase on the rhythm factor was associated with memory decline, whereas the pace factor was associated with decline on executive function. In Cox models adjusted for age, sex and education, a one point increase on baseline rhythm and variability factor scores was associated with increased risk of dementia. Furthermore, the pace factor specifically predicted the risk of developing vascular dementia. An appreciation of these relationships has led some researchers to perform cognitive risk assessments that incorporate motoric signs. The newly proposed motoric cognitive risk (MCR) syndrome is defined as the presence of cognitive complaints and slow gait (one standard deviation below age- and sex-specific gait speed means) in non-demented individuals [9]. Over the age of 70 years, 7 % of the population fulfil diagnostic criteria for MCR and have a significant risk of developing dementia [9]. These findings highlight that objective gait markers of preclinical dementia may lead to new insights into early disease stages, improve diagnostic assessments, allow for disease monitoring and identify new preventive strategies. Gait disorder in Parkinson’s disease The parkinsonian gait of Parkinson’s disease (PD) and related Parkinson plus syndromes has been well described elsewhere (for review see [10]) but there are a number of newly emerging concepts that are of particular relevance in
123
the field. In keeping with the work relating the emergence of gait disorder as a red flag for the development of dementia, there has been a concentrated effort in identifying the pre-motor syndrome of PD. Whilst a number of non-motor features including constipation, anosmia and mood disturbance have been identified as risk factors for PD (for review see [11] ), probably the most likely symptom to be useful in routine clinical practice is the emergence of idiopathic rapid eye movement sleep behaviour disorder (iRBD) where otherwise healthy individuals begin acting out their dreams. Significantly, two recent prospective studies following patients for over 14 year have identified that the transition of patients with iRBD to an alpha-synucleinopathy (i.e. PD, dementia with Lewy bodies and multiple system atrophy) is over 80 % [12, 13]. Studies exploring the relationship between RBD and gait disorder in established PD have reported conflicting results [14, 15]. However, there would appear to be obvious neuroanatomical connections between sleep regulating nuclei and regions controlling gait and posture especially within the pontine tegmentum, pedunculopontine nucleus and medial medulla. Thus given the relationship between iRBD and neurodegeneration the identification of any characteristic gait disorder in these patients may prove highly relevant. For example, it is possible that severity and/or any pattern of gait dysfunction in iRBD may potentially be helpful in predicting how soon a patient will transition to an alpha-synucleinopathy and even for predicting their specific pre-morbid diagnosis before the appearance of more clinically diagnostic features. Recent work evaluating gait parameters in iRBD has identified decreased velocity and cadence, as well as significantly increased double limb support variability and greater stride/swing time variability compared to age matched controls [16]. As yet, prospective follow-up data are not available to determine the clinical utility of these observations regarding transition to an alpha-synucleinopathy. The presence of subclinical gait and postural dysfunction in early and incident PD is also an area of growing interest. Patients with early PD often do not complain of any subjective gait disturbance and it may only be when they are challenged by the addition of a cognitive load when walking (known as dual tasking) that deficits emerge. Whilst maintaining gait velocity during dual tasking, changes can be observed on other objective measures such as, increased stride width, number of cadences and a reduction in swing/cycle time [17]. However, a study of dual tasking in incident PD who were assessed within just 4 months of their diagnosis did not show these more general deficits [18]. In fact these patients only differed from controls in their inability to modulate step width variability suggesting a greater risk to postural stability when they were engaged in more complex tasks. Additionally, home
J Neurol
activity monitoring devices have revealed that incident PD patients are significantly less active than controls, with an inability to sustain levels of walking, which highlights the fact that interventional strategies should be implemented at the time of diagnosis [19]. Many inconsistencies reported in studies of gait in PD may in fact be related to the significant heterogeneity and possible sub-groups that exist within the condition [20]. Although potentially artificial, the division of cases into tremor dominant and patients with postural instability and gait difficulty (PIGD) on the basis of predominant motor phenotype is commonly undertaken. Neuroimaging studies have highlighted that whilst these motor sub-groups do not seem to be differentiated by the presence of white matter lesions [21], those patients with PIGD have demonstrated selective grey matter atrophy predominantly across motor, cognitive and limbic associative areas with their symptom severity correlating with volume loss in pre-supplementary motor and motor cortices [22]. However, recent work objectively evaluating tremor dominant and PIGD patients has demonstrated that significant overlap occurs between many parameters of gait and balance casting serious doubt on the clinical utility of this simplistic classification scheme [23]. Understanding the neurobiology of gait disorders A range of other novel approaches has been extensively utilised in the research setting to enhance our understanding of gait disorders. The expansion of structural and functional neuroimaging techniques, cerebrospinal fluid markers, TMS and a range of neurophysiological approaches have yet to find any place in routine clinical practice but they do offer potential for improving our management across a range of diseases. The use of magnetic resonance imaging (MRI) and positron emission tomography (PET) in the dementia field has largely explored the neurobiology underlying specific cognitive deficits, disease progression and response to therapy with far less work being focused on the imaging correlates of the associated gait disorders. However, in view of the pre-morbid association between motor and cognitive decline discussed above, some neuroimaging work has recently been undertaken in patients identified as having mild cognitive impairment (MCI). The syndrome of MCI is characterised by cognitive decline that is greater than that expected for an individual’s age and education level, whilst not significantly interfering with activities of daily life [24]. Patients with MCI constitute an ‘at-risk’ population for dementia with an approximate conversion rate of 50 % within 5 years [24]. One recent MRI study using combined volumetric and spectroscopic analysis has studied MCI patients who had undergone quantitative gait analysis [25]. Both the volume
of the primary motor cortex as well as higher levels of choline/creatine, a measure of cellular turnover that is elevated in inflammatory processes and ischaemic lesions of the brain, predicted slower gait velocity in MCI patients. The authors hypothesised that selective regional atrophy in the motor cortex would impact on the cognitive control network of locomotion and that chronic ischaemic demyelination related to cerebrovascular disease may further contribute to gait slowing. Furthermore, the N-acetyl aspartate/creatine ratio, a marker of neuronal health and function was correlated with higher (i.e. worse) stride time variability when dual tasking, suggesting that the regularity of gait is associated with neural function, even at the molecular level during the evolution of dementia. Given the contributory role of cerebral small vessel disease on gait disorders and cognitive decline, work has also been conducted in this field with structural MRI. Significantly, pathological studies have demonstrated abnormalities in white matter that may appear normal on brain imaging and as such techniques like diffusion tensor imaging (DTI) have been utilised to offer additional insights in vivo. One such study evaluated 429 healthy individuals (50–85 year) who had undergone quantitative gait assessment. Results revealed a loss of white matter integrity particularly in the genu of the corpus callosum, as indicated by a lower fractional anisotropy and higher mean diffusivity [26]. This finding emphasises the importance of the interconnections between the right and left hemispheric cortical regions, especially in the prefrontal cortex that are involved in the cognitive control of motor performance. The role of atrophy and disrupted networks has also been investigated in higher-level gait disorders (HLGD) which is a term used for patients with locomotor and balance difficulties that cannot be readily explained by specific lesions throughout the different components of the nervous system. Whilst a variety of neurodegenerative and other pathologies can produce HLGD, the most common cause appears to be microvascular disease causing white matter lesions that disrupt the balance and locomotor circuits [27]. Recent neuroimaging work in such patients has identified that gait and balance deficits appear to arise from lesions or dysfunctions in a network linking the primary motor cortex and the mesencephalic locomotor region (MLR). In contrast, more cognitive and ‘appendicular’ hypokinetic-rigid features are associated with deep white matter lesions possibly through their impact on corticostriatal networks [28]. Much of early work evaluating gait disorders in PD focused on the role of the failing dopaminergic nigrostriatal tract and the motor loop of the basal ganglia. However, the incomplete amelioration offered by current treatments, even in mild disease, has made it increasingly obvious that other pathways must be playing a critical role.
123
J Neurol
One clue towards a potential substrate for the gait disorder seen in PD is the pattern of cognitive impairment observed. It has long been known that many cognitive deficits in PD are often worsened by anti-cholinergic medications, whereas some benefits may be derived from the cholinesterase inhibitors [29]. In keeping with these clinical observations, recent PET research that has revealed cortical cholinergic deficits rather than dopaminergic losses are correlated with gait speed in PD [30]. Further evidence for a causative role of cholinergic disruption in the gait disorders of PD comes from neurophysiological results utilising short-latency afferent inhibition (SAI) in PD. The non-invasive SAI technique conditions the motor cortex via peripheral stimulation of the median nerve before delivering transcranial magnetic stimulation with a short inter-stimulus delay. This approach assesses an inhibitory circuit in the sensorimotor cortex, which is believed to depend on intact cortical and subcortical cholinergic systems. Work in early PD has confirmed that cholinergic loss determined by SAI is an independent predictor of slower gait speed [31]. In addition to its role in more general gait dysfunction, cholinergic PET has been used to explore freezing of gait (FOG) in PD. Compared to non-freezers, patients with FOG showed lower levels of neocortical cholinergic innervation and striatal dopamine but did not have significantly different thalamic cholinergic denervation [32]. The pathophysiology underlying FOG is not well understood and a number of models have recently been proposed [33]. Interestingly, a number of research groups have attempted to map out regional grey matter atrophy in association with FOG with conflicting results, perhaps suggesting that there is likely to be a more functional rather than structural pathology driving this phenomenon [34– 39]. Two recent functional MRI (fMRI) studies exploring the freezing phenomenon have both demonstrated similar abnormalities across corticostriatal networks [40, 41]. One of these fMRI studies utilised a Virtual Reality (VR) approach, which has been able to correlate actual episodes of FOG to performance in the VR environment [42]. The investigators reported that VR freezing was associated with a decreased blood oxygen level-dependent response bilaterally in the sensorimotor regions, head of caudate nucleus, the thalamus and the globus pallidus internus and MLR, whereas increased activation was seen within frontoparietal cortical regions [40]. Furthermore, these signal changes were correlated with the severity of clinical FOG. A subsequent VR fMRI has revealed that during freezing there is a functional decoupling between the basal ganglia network and the cognitive control network in each hemisphere suggesting that FOG is related to paroxysmal breakdowns between communicating neural networks [43].
123
The observation that FOG is associated with a pattern of cortical changes on fMRI has led researchers to explore the role of electroencephalography (EEG) in detecting the phenomenon. When compared to walking, episodes of FOG were associated with a significant increase in theta band power within the central and frontal leads [44]. Significantly, in relation to possible future management strategies, such EEG changes could be detected a few seconds before gait arrest [45]. Therefore, FOG is associated with abnormal oscillatory activity and taken together, these neuroimaging and neurophysiological results support the hypothesis that freezing in PD arises from impaired communication between complimentary yet competing neural networks in association with paroxysmal increases in inhibitory basal ganglia outflow [46].
Conclusion Unfortunately, the translation of our increased understanding of gait disorders into more effective clinical management has not yet occurred. However, it should be clear that being aware about the relationships between gait disorder and a variety of neurological conditions, as well as the ability to account for the neurobiology underpinning them will present many such opportunities in the future. It is anticipated that the use of novel pharmacological and non-pharmacological strategies will offer more directed approaches to symptom relief. This will be assisted by identifying the role of neurotransmitters and targeting the restoration of disrupted circuits. Furthermore, emerging technologies such as closed loop deep brain stimulation may allow for the treatment of paroxysmal symptoms. Whilst remaining an enigma, the clinical challenge of gait disorders represents one of the most exciting prospects for our specialty moving forwards! Conflicts of interest
None.
References 1. Studenski S, Perera S, Patel K et al (2011) Gait speed and survival in older adults. JAMA 305(1):50–58 2. Visser H (1983) Gait and balance in senile dementia of Alzheimer’s type. Age Ageing 12(4):296–301 3. Cedervall Y, Halvorsen K, Aberg AC (2014) A longitudinal study of gait function and characteristics of gait disturbance in individuals with Alzheimer’s disease. Gait Posture 39(4):1022–1027 4. Allan LM, Ballard CG, Burn DJ, Kenny RA (2005) Prevalence and severity of gait disorders in Alzheimer’s and non-Alzheimer’s dementias. J Am Geriatr Soc 53(10):1681–1687 5. Ala TA, Frey WH 2nd (1995) Validation of the NINCDSADRDA criteria regarding gait in the clinical diagnosis of Alzheimer disease. A clinicopathologic study. Alzheimer Dis Assoc Disord 9(3):152–159
J Neurol 6. Verghese J, Lipton RB, Hall CB, Kuslansky G, Katz MJ, Buschke H (2002) Abnormality of gait as a predictor of non-Alzheimer’s dementia. N Engl J Med 347(22):1761–1768 7. Waite LM, Grayson DA, Piguet O, Creasey H, Bennett HP, Broe GA (2005) Gait slowing as a predictor of incident dementia: 6-year longitudinal data from the Sydney Older Persons Study. J Neurol Sci 229–230:89–93 8. Verghese J, Wang C, Lipton RB, Holtzer R, Xue X (2007) Quantitative gait dysfunction and risk of cognitive decline and dementia. J Neurol Neurosurg Psychiatry 78(9):929–935 9. Verghese J, Wang C, Lipton RB, Holtzer R (2013) Motoric cognitive risk syndrome and the risk of dementia. J Gerontol A Biol Sci Med Sci 68(4):412–418 10. Ebersbach G, Moreau C, Gandor F, Defebvre L, Devos D (2013) Clinical syndromes: Parkinsonian gait. Mov Disord 28(11): 1552–1559 11. Postuma RB, Aarsland D, Barone P et al (2012) Identifying prodromal Parkinson’s disease: pre-motor disorders in Parkinson’s disease. Mov Disord 27(5):617–626 12. Iranzo A, Tolosa E, Gelpi E et al (2013) Neurodegenerative disease status and post-mortem pathology in idiopathic rapid-eyemovement sleep behaviour disorder: an observational cohort study. Lancet Neurol 12(5):443–453 13. Schenck CH, Boeve BF, Mahowald MW (2013) Delayed emergence of a parkinsonian disorder or dementia in 81 % of older men initially diagnosed with idiopathic rapid eye movement sleep behavior disorder: a 16-year update on a previously reported series. Sleep Med 14(8):744–748 14. Benninger DH, Michel J, Waldvogel D et al (2010) REM sleep behavior disorder is not linked to postural instability and gait dysfunction in Parkinson. Mov Disord 25(11):1597–1604 15. Bugalho P, Viana-Baptista M (2013) REM sleep behavior disorder and motor dysfunction in Parkinson’s disease—a longitudinal study. Parkinsonism Relat Disord 19(12):1084–1087 16. McDade EM, Boot BP, Christianson TJ et al (2013) Subtle gait changes in patients with REM sleep behavior disorder. Mov Disord 28(13):1847–1853 17. Panyakaew P, Bhidayasiri R (2013) The spectrum of preclinical gait disorders in early Parkinson’s disease: subclinical gait abnormalities and compensatory mechanisms revealed with dual tasking. J Neural Transm (Vienna, Austria: 1996) 120(12):1665– 1672 18. Rochester L, Galna B, Lord S, Burn D (2014) The nature of dualtask interference during gait in incident Parkinson’s disease. Neuroscience 265:83–94 19. Lord S, Godfrey A, Galna B, Mhiripiri D, Burn D, Rochester L (2013) Ambulatory activity in incident Parkinson’s: more than meets the eye? J Neurol 260(12):2964–2972 20. Lewis SJG, Foltynie T, Blackwell AD, Robbins TW, Owen AM, Barker RA (2005) Heterogeneity of Parkinson’s disease in the early clinical stages using a data driven approach. J Neurol Neurosurg Psychiatry 76:343–348 21. Herman T, Rosenberg-Katz K, Jacob Y et al (2013) White matter hyperintensities in Parkinson’s disease: do they explain the disparity between the postural instability gait difficulty and tremor dominant subtypes? PLoS One 8(1):e55193 22. Rosenberg-Katz K, Herman T, Jacob Y, Giladi N, Hendler T, Hausdorff JM (2013) Gray matter atrophy distinguishes between Parkinson disease motor subtypes. Neurology 80(16):1476–1484 23. Herman T, Weiss A, Brozgol M, Giladi N, Hausdorff JM (2014) Gait and balance in Parkinson’s disease subtypes: objective measures and classification considerations. J Neurol 261(12): 2401–2410. doi:10.1007/s00415-014-7513-6 24. Gauthier S, Reisberg B, Zaudig M et al (2006) Mild cognitive impairment. Lancet 367(9518):1262–1270
25. Annweiler C, Beauchet O, Bartha R et al (2013) Motor cortex and gait in mild cognitive impairment: a magnetic resonance spectroscopy and volumetric imaging study. Brain 136(Pt 3):859–871 26. de Laat KF, Tuladhar AM, van Norden AG, Norris DG, Zwiers MP, de Leeuw FE (2011) Loss of white matter integrity is associated with gait disorders in cerebral small vessel disease. Brain 134(Pt 1):73–83 27. Nutt JG (2013) Higher-level gait disorders: an open frontier. Mov Disord 28(11):1560–1565 28. Demain A, Westby GW, Fernandez-Vidal S et al (2014) Highlevel gait and balance disorders in the elderly: a midbrain disease? J Neurol 261(1):196–206 29. Williams-Gray CH, Foltynie T, Lewis SJG, Barker RA (2006) Cognitive deficits and psychosis in Parkinson’s disease: a review of pathophysiology and therapeutic options. CNS Drugs 20(6):477–505 30. Bohnen NI, Frey KA, Studenski S et al (2013) Gait speed in Parkinson disease correlates with cholinergic degeneration. Neurology 81(18):1611–1616 31. Rochester L, Yarnall AJ, Baker MR et al (2012) Cholinergic dysfunction contributes to gait disturbance in early Parkinson’s disease. Brain 135(Pt 9):2779–2788 32. Bohnen NI, Frey KA, Studenski S et al (2014) Extra-nigral pathological conditions are common in Parkinson’s disease with freezing of gait: an in vivo positron emission tomography study. Mov Disord 29(9):1118–1124 33. Nieuwboer A, Giladi N (2013) Characterizing freezing of gait in Parkinson’s disease: models of an episodic phenomenon. Mov Disord 28(11):1509–1519 34. Kostic VS, Agosta F, Pievani M et al (2012) Pattern of brain tissue loss associated with freezing of gait in Parkinson disease. Neurology 78(6):409–416 35. Tessitore A, Amboni M, Cirillo G et al (2012) Regional gray matter atrophy in patients with Parkinson disease and freezing of gait. AJNR Am J Neuroradiol 33(9):1804–1809 36. Herman T, Rosenberg-Katz K, Jacob Y, Giladi N, Hausdorff JM (2014) Gray matter atrophy and freezing of gait in Parkinson’s disease: is the evidence black-on-white? Mov Disord 29(1): 134–139 37. Rubino A, Assogna F, Piras F, Di Battista ME, Imperiale F, Chiapponi C, Spalletta G, Meco G (2014) Does a volume reduction of the parietal lobe contribute to freezing of gait in Parkinson’s disease? Parkinsonism Relat Disord 20(10): 1101–1103. doi:10.1016/j.parkreldis.2014.07.002 38. Youn J, Cho JW, Lee WY, Kim GM, Kim ST, Kim HT (2012) Diffusion tensor imaging of freezing of gait in patients with white matter changes. Mov Disord 27(6):760–764 39. Fling BW, Cohen RG, Mancini M, Nutt JG, Fair DA, Horak FB (2013) Asymmetric pedunculopontine network connectivity in parkinsonian patients with freezing of gait. Brain 136(Pt 8):2405–2418 40. Shine JM, Matar E, Ward PB et al (2013) Exploring the cortical and subcortical functional magnetic resonance imaging changes associated with freezing in Parkinson’s disease. Brain 136(Pt 4):1204–1215 41. Vercruysse S, Spildooren J, Heremans E, Wenderoth N, Swinnen SP, Vandenberghe W, Nieuwboer A (2014) The neural correlates of upper limb motor blocks in Parkinson’s disease and their relation to freezing of gait. Cereb Cortex 24(12):3154–3166. doi:10.1093/cercor/bht170 42. Shine JM, Matar E, Bolitho SJ et al (2013) Modeling freezing of gait in Parkinson’s disease with a virtual reality paradigm. Gait Posture 38(1):104–108 43. Shine JM, Matar E, Ward PB et al (2013) Freezing of gait in Parkinson’s disease is associated with functional decoupling
123
J Neurol between the cognitive control network and the basal ganglia. Brain 136(Pt 12):3671–3681 44. Shine JM, Handojoseno AM, Nguyen TN, Tran Y, Naismith SL, Nguyen H, Lewis SJ (2014) Abnormal patterns of theta frequency oscillations during the temporal evolution of freezing of gait in Parkinson’s disease. Clin Neurophysiol 125(3):569–576. doi:10. 1016/j.clinph.2013.09.006
123
45. Handojoseno AM, Shine JM, Nguyen TN, Tran Y, Lewis SJ, Nguyen HT (2012) The detection of Freezing of Gait in Parkinson’s disease patients using EEG signals based on Wavelet decomposition. Conf Proc 2012:69–72 46. Lewis SJG, Barker RA (2009) A pathophysiological model of freezing of gait in Parkinson’s disease. Parkinsonism Relat Disord 15(5):333–338
