Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2014 Sep 15.
Published in final edited form as: Mov Disord. 2013 Sep 15;28(11):10.1002/mds.25672. doi: 10.1002/mds.25672

Classification of gait disturbances: distinguishing between continuous and episodic changes

Nir Giladi 1,2,3, Fay B Horak 4, Jeffrey M Hausdorff 1,3,5,6
PMCID: PMC3859887  NIHMSID: NIHMS517896  PMID: 24132835

Abstract

The increased awareness of the importance of gait and postural control to quality of life and functional independence has led many research groups to study the patho-physiology, epidemiology, clinical, and therapeutic aspects of these motor functions. In recognition of the increased awareness of the significance of this topic, the Movement Disorders Journal is devoting this entire issue to gait and postural control. Leading research groups provide critical reviews of the current knowledge and propose future directions for this evolving field. The results of a large randomized controlled trial designed to reduce falls and improve mobility in people with Parkinson’s disease is also included in this issue.

The intensive work in this area throughout the world has created an urgent need for a unified language. Because gait and postural disturbances are so common, the clinical classification should be clear, straightforward and simple to use. As an introduction to this special issue, we propose a new clinically based classification scheme that is organized according to the dominant observed disturbance, while taking into an account the results of a basic neurological exam. The proposed classification differentiates between continuous and episodic gait disturbances since this subdivision has important ramifications from the functional, prognostic and mechanistic perspectives.

We anticipate that research into gait and postural control will continue to flourish over the next decade as the search for new ways of promoting mobility and independence aims to keep up with the exponentially growing population of aging older adults. Hopefully, this new classification scheme and the papers focusing on gait and postural control in this special issue of the Movement Disorders Journal will help to facilitate future investigations in this exciting and rapidly growing area.

Keywords: balance, gait, classification, falls, Parkinson’s disease

INTRODUCTION

The ability to walk safely, effectively and efficiently is essential for an independent and productive life. Gait and postural control predict quality of life, morbidity and mortality1-11. The fear of losing the ability to walk or even to stand or sit in an upright position is frequently the first and most significant concern that is raised when a person is diagnosed with stroke, Parkinson’s disease, ataxia or other movement disorders. It is not surprising that people make great efforts to maintain independent walking. Many studies have shown the significant role of mobility and safe walking in the quality of life of patients and older adults12-16. Recently, a large systematic review reported that walking safely is the most significant motor symptom in the quality of life among patients with Parkinson’s disease17.

The increased awareness of the importance of gait and postural control in quality of life and functional independence has led many research groups around the globe to focus their research programs on the pathophysiology, epidemiology, clinical, and therapeutic aspects of walking and balance18. As part of the increased awareness of the significance of this topic, the Movement Disorders Journal is devoting this entire issue to gait and postural control. Here, leading research groups provide critical reviews of the current knowledge on specific aspects of gait and posture and propose future directions for translating this evolving research field into clinical implementation.

OVERVIEW OF THE SPECIAL ISSUE

Recent work has shown that the locomotion and posture control networks use very large parts of the central and peripheral nervous systems19-24. Similarly, gait and balance are no longer perceived as purely motor tasks or reflexes but are viewed as complex, sensorimotor behaviors, heavily affected by cognitive and affective aspects3;8;22;25-32. This may partially explain the sensitivity to subtle neuronal dysfunction, and why abnormal gait or postural control can predict the development of dementia or parkinsonism years before they are diagnosed clinically2;4;33-36. These ideas will be highlighted throughout this special issue of the Movement Disorders Journal. These fundamental concepts will also be discussed with respect to emerging therapeutic approaches that combine physical, technological and cognitive interventions, along with traditional physical and occupational therapy for improving gait and mobility37-41.

Another recent development in gait and posture research is the ability to quantify and characterize the overall locomotor pattern, individual steps, and postural sway during stance in the gait lab or at home using body-fixed sensors, i.e., small lightweight devices that can be worn by the subject42-47. The combination of very detailed assessment of discrete steps or postural responses with a less detailed, but longer monitoring of mobility and stability in real-life, has the potential to significantly enhance our understanding of mobility behavior and episodic gait disturbances31;48-50. Objective measures of balance and gait promise to lead to the development of a personalized approach to the evaluation and treatment of each subject’s gait or posture disturbances. Home-based monitoring and online, real-time notification of episodic events, such as falls, is at the forefront of gait research, along with new modes of intervention modalities that will hopefully make their way into the clinic in the near future. The significant progress in gait and posture assessment and long-term monitoring has started to influence the entire field and the current understanding and potential interventions discussed in this special issue of the Movement Disorders Journal reflect this general progress.

A NEW CLINICAL CLASSIFICATION SCHEME

The intensive work in gait and posture research throughout the world has created an urgent need for a unified language. Over the past 20 years, several groups have proposed classifications of gait and posture disturbances, focusing on the neurological systems, the anatomical source of dysfunction, or the clinical features18;51-56. Because gait and postural disturbances are so common and their assessment is part of the basic physical and neurological exam, the clinical classification should be clear, straightforward and simple to use. As an introduction to this exciting special issue of the Movement Disorders Journal on gait and posture, we propose a new clinical classification scheme which is clinically based according to the dominant observed disturbance, while taking into an account the results of a basic neurological exam.

The proposed classification differentiates between continuous and episodic gait disturbances because we believe that this subdivision has important ramifications from the functional, prognostic and mechanistic perspectives. Continuous gait disturbances may be the result of chronic neuronal or peripheral dysfunction. Typically, the patient will adapt to abnormal, but predictable, impairments and will learn to adjust and compensate with changes in motor behavior. Evaluation of gait and balance in patients with continuous disturbances reflects the underlying pathology as well as any compensatory mechanisms. Walking aids are one obvious form of compensation that may help to improve continuous gait disturbances. However, cognitive resources may also be called in to play, either consciously or sub-consciously, to ameliorate the underlying pathology. The role of all compensatory factors should be assessed.

In the past, episodic gait disturbances have received less attention. In contrast to the continuous gait disturbances, episodic disturbances are, by definition, unpredictable. The patient is not able to adapt to these transient changes and as a result, these gait disturbances are often the primary cause of falls, anxiety, fear, and avoidance behavior57-60. Treatment may focus on the underlying pathology, decreasing the provocative factors, and strategies to avoid or overcome the event. However, optimal therapies are still not available for most episodic gait disturbances.

Gait classification is relatively straightforward when the peripheral nervous system or the musculo-skeletal changes play a major role in the clinical picture. When abnormal gait is the result of isolated spinal cord, cortico-spinal tract, cerebellum or extra-pyramidal system dysfunction, it is still relatively easy to characterize. These could be referred to as “pure” disturbances. Characterization of gait problems becomes a real challenge when only subtle changes in multiple neural systems are the underlying pathophysiology; sometimes this could be referred to as a form of mixed or multi-factorial disturbance. The task becomes extremely difficult when cognitive and affective changes exacerbate the complex picture. In those instances, one cannot refer to specific neuronal system and the gait features are highly variable and do not follow a specific pattern. Previous classifications61, including ours62, have referred to these bizarre gaits as “High Level Gait Disorders”, “Frontal Gait Disorders” or “Subcortical Gait Disturbances” (See Nutt for further discussion on this issue63). In these patients, one can easily diagnose an abnormal gait but it is usually impossible to distinguish between the specific contributions of different sensory, motor or mental modalities. Increased fear, imbalance, muscle weakness, loss of basic locomotion rhythmicity and cognitive disturbances in the form of dys-executive syndrome all may contribute to the clinical picture5;64;65. Abnormal motor planning and execution, disturbed negotiation with obstacles or the environment in general, increased gait and postural disturbances while dual-tasking or misjudgment of hazard risks or personal abilities can further increase the diagnostic challenge. In contrast to the more simple pure and mixed types, perhaps it may be helpful to consider that these gait disturbances involve problems of integration among multiple systems.

Before concluding, it is important to take note of a caveat when distinguishing between the continuous and episodic gait disturbances. Freezing of gait is a prime example of an episodic gait disturbance. Freezing is unpredictable, transient, and does not take place continuously. At the same time, however, patients with Parkinson’s disease who suffer from freezing may also suffer from more exaggerated continuous gait disturbances, compared to those patients who are less likely to have freezing66-69. In some sense, episodic gait disturbances like freezing of gait may be the unsafe combination of a transient event operating on the background of continuous changes that, unfortunately, help to set the stage for these episodic disturbances. In other words, the underlying risk that an episodic gait disturbance might occur may be related to continuous and transient changes that may also be occurring simultaneously in a given patient. A simple dichotomy between the continuous and episodic gait disturbances may sometimes belie a more complex and nuanced picture. Similar to the way that the continuous gait alterations can be isolated or several can take place simultaneously in a more mixed state (e.g., spasticity and bradykinesia; spasticity and weakness), so too the same patient may suffer from both episodic and continuous gait disturbances. Since many of the gait disturbances may co-exist, determination of a multidimensional profile may help to inform the clinical diagnosis.

To conclude, we suggest that differentiating gait disturbances based on the proposed classification will improve future communication when clinically characterizing a patient’s gait for teaching or research purposes. We anticipate that research into gait and postural control will continue to flourish over the next decade as the search for new ways of promoting the maintenance of mobility and independence try to keep up with the exponentially growing population of older adults who are prone to gait disturbances. Hopefully, this new classification scheme and the papers focusing on gait and postural control in this special issue of Movement Disorders will help to facilitate future investigations in this exciting and rapidly growing area.

Table 1.

Classification of gait disturbances by clinical presentation*

Continuous – Occurs consistently with locomotion (can vary in severity)
  Ataxic – disequilibrium and hypermetria of stance and gait
     Somatosensory
     Vestibular
     Cerebellar
  Spastic – associated with increased postural tone
     Hemiparetic
     Paraparetic / Tetraparetic
  Bradykinetic / hypokinetic – slow or small steps and/or slow or small postural
  responses
  Dyskinetic/Choreic/Dystonic – involuntary movements
  Paretic – associated with muscle weakness or paralysis
  Trunkal – static, axial postural deformities
  Antalgic – secondary to musculo-skeletal or central pain
    Higher Level (Frontal)
     “Apractic”
     Anxious, fear of falling, cautious
     Bizarre
     Severely depressed
     Psychogenic
  Undetermined – sometimes it may be difficult to classify the continuous nature of
  the gait disturbance.
Episodic – occurs intermittently during locomotion (may vary in severity and frequency)
  Freezing – transient inability to create effective stepping
  Festination – unintentional increase in speed, usually with small steps
  Disequilibrium – transient loss of balance
Mixed types - where a person suffers from more than one continuous disturbance, or continuous
and episodic disturbances, for example, are possible.
*

classification should be performed after completion of a general and neurological exam.

Acknowledgments

Funding sources for the study: Support from the National Institutes on Aging, the National Center of Medical Rehabilitation Research, the European Commission, and the Kinetics Foundation, and OHSU.

REFERENCES

  • 1.Studenski S, Perera S, Patel K, et al. Gait speed and survival in older adults. JAMA. 2011;305:50–58. doi: 10.1001/jama.2010.1923. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Verghese J, Lipton RB, Hall CB, Kuslansky G, Katz MJ, Buschke H. Abnormality of gait as a predictor of non-Alzheimer’s dementia. N Engl J Med. 2002;347:1761–1768. doi: 10.1056/NEJMoa020441. [DOI] [PubMed] [Google Scholar]
  • 3.Montero-Odasso M, Verghese J, Beauchet O, Hausdorff JM. Gait and cognition: a complementary approach to understanding brain function and the risk of falling. J Am Geriatr Soc. 2012;60:2127–2136. doi: 10.1111/j.1532-5415.2012.04209.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Verghese J, Holtzer R, Lipton RB, Wang C. Mobility stress test approach to predicting frailty, disability, and mortality in high-functioning older adults. J Am Geriatr Soc. 2012;60:1901–1905. doi: 10.1111/j.1532-5415.2012.04145.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Beauchet O, Annweiler C, Dubost V, et al. Stops walking when talking: a predictor of falls in older adults? Eur J Neurol. 2009;16:786–795. doi: 10.1111/j.1468-1331.2009.02612.x. [DOI] [PubMed] [Google Scholar]
  • 6.Elbers RG, van Wegen EE, Verhoef J, Kwakkel G. Is gait speed a valid measure to predict community ambulation in patients with Parkinson’s disease? J Rehabil Med. 2013;45:370–375. doi: 10.2340/16501977-1123. [DOI] [PubMed] [Google Scholar]
  • 7.Greene BR, Doheny EP, Walsh C, Cunningham C, Crosby L, Kenny RA. Evaluation of falls risk in community-dwelling older adults using body-worn sensors. Gerontology. 2012;58:472–480. doi: 10.1159/000337259. [DOI] [PubMed] [Google Scholar]
  • 8.Lundin-Olsson L, Nyberg L, Gustafson Y. “Stops walking when talking” as a predictor of falls in elderly people. Lancet. 1997;349:617. doi: 10.1016/S0140-6736(97)24009-2. [DOI] [PubMed] [Google Scholar]
  • 9.Mancini M, Carlson-Kuhta P, Zampieri C, Nutt JG, Chiari L, Horak FB. Postural sway as a marker of progression in Parkinson’s disease: a pilot longitudinal study. Gait Posture. 2012;36:471–476. doi: 10.1016/j.gaitpost.2012.04.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Hirsch CH, Buzkova P, Robbins JA, Patel KV, Newman AB. Predicting late-life disability and death by the rate of decline in physical performance measures. Age Ageing. 2012;41:155–161. doi: 10.1093/ageing/afr151. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Upatising B, Hanson GJ, Kim YL, Cha SS, Yih Y, Takahashi PY. Effects of home telemonitoring on transitions between frailty states and death for older adults: a randomized controlled trial. Int J Gen Med. 2013;6:145–151. doi: 10.2147/IJGM.S40576. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Ellis T, Cavanaugh JT, Earhart GM, Ford MP, Foreman KB, Dibble LE. Which measures of physical function and motor impairment best predict quality of life in Parkinson’s disease? Parkinsonism Relat Disord. 2011;17:693–697. doi: 10.1016/j.parkreldis.2011.07.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Gomez-Esteban JC, Zarranz JJ, Lezcano E, et al. Influence of motor symptoms upon the quality of life of patients with Parkinson’s disease. Eur Neurol. 2007;57:161–165. doi: 10.1159/000098468. [DOI] [PubMed] [Google Scholar]
  • 14.Horder H, Skoog I, Frandin K. Health-related quality of life in relation to walking habits and fitness: a population-based study of 75-year-olds. Qual Life Res. 2012 doi: 10.1007/s11136-012-0267-7. [DOI] [PubMed] [Google Scholar]
  • 15.Marras C, McDermott MP, Rochon PA, Tanner CM, Naglie G, Lang AE. Predictors of deterioration in health-related quality of life in Parkinson’s disease: results from the DATATOP trial. Mov Disord. 2008;23:653–659. doi: 10.1002/mds.21853. [DOI] [PubMed] [Google Scholar]
  • 16.Muslimovic D, Post B, Speelman JD, Schmand B, de Haan RJ. Determinants of disability and quality of life in mild to moderate Parkinson disease. Neurology. 2008;70:2241–2247. doi: 10.1212/01.wnl.0000313835.33830.80. [DOI] [PubMed] [Google Scholar]
  • 17.Soh SE, Morris ME, McGinley JL. Determinants of health-related quality of life in Parkinson’s disease: a systematic review. Parkinsonism Relat Disord. 2011;17:1–9. doi: 10.1016/j.parkreldis.2010.08.012. [DOI] [PubMed] [Google Scholar]
  • 18.Nutt JG, Horak FB, Bloem BR. Milestones in gait, balance, and falling. Mov Disord. 2011;26:1166–1174. doi: 10.1002/mds.23588. [DOI] [PubMed] [Google Scholar]
  • 19.Taga G. A model of the neuro-musculo-skeletal system for human locomotion. Biological cybernetics. 1995;73:97–111. doi: 10.1007/BF00204048. [DOI] [PubMed] [Google Scholar]
  • 20.Dietz V. Spinal cord pattern generators for locomotion. Clin Neurophysiol. 2003;114:1379–1389. doi: 10.1016/s1388-2457(03)00120-2. [DOI] [PubMed] [Google Scholar]
  • 21.Patla AE. The neural control of locomotion. In: B. S., Spivack BS, editors. Evaluation and management of gait disorders. Marcel Dekker, Inc.; New York: 1995. pp. 53–77. [Google Scholar]
  • 22.Amboni M, Barone P, Hausdorff JM. Cognitive contributions to gait and falls: evidence and implications. Mov Disord. 2013 doi: 10.1002/mds.25674. in press. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Bohnen N, Jahn K. Imaging: what can it tell us about parkinsonian gait? Mov Disord. 2013 doi: 10.1002/mds.25534. in press. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Takakusaki K. Neurophysiology of gait: From the CPG to the frontal lobe. Mov Disord. 2013 doi: 10.1002/mds.25669. in press. [DOI] [PubMed] [Google Scholar]
  • 25.Mirelman A, Herman T, Brozgol M, et al. Executive function and falls in older adults: new findings from a five-year prospective study link fall risk to cognition. PLoS One. 2012;7:e40297. doi: 10.1371/journal.pone.0040297. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Herman T, Mirelman A, Giladi N, Schweiger A, Hausdorff JM. Executive control deficits as a prodrome to falls in healthy older adults: a prospective study linking thinking, walking, and falling. J Gerontol A Biol Sci Med Sci. 2010;65:1086–1092. doi: 10.1093/gerona/glq077. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Yogev-Seligmann G, Rotem-Galili Y, Mirelman A, Dickstein R, Giladi N, Hausdorff JM. How does explicit prioritization alter walking during dual-task performance? Effects of age and sex on gait speed and variability. Phys Ther. 2010;90:177–186. doi: 10.2522/ptj.20090043. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Sheridan PL, Solomont J, Kowall N, Hausdorff JM. Influence of executive function on locomotor function: divided attention increases gait variability in Alzheimer’s disease. J Am Geriatr Soc. 2003;51:1633–1637. doi: 10.1046/j.1532-5415.2003.51516.x. [DOI] [PubMed] [Google Scholar]
  • 29.Sheridan PL, Hausdorff JM. The role of higher-level cognitive function in gait: executive dysfunction contributes to fall risk in Alzheimer’s disease. Dement Geriatr Cogn Disord. 2007;24:125–137. doi: 10.1159/000105126. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Woollacott M, Shumway-Cook A. Attention and the control of posture and gait: a review of an emerging area of research. Gait Posture. 2002;16:1–14. doi: 10.1016/s0966-6362(01)00156-4. [DOI] [PubMed] [Google Scholar]
  • 31.Lord S, Galna B, Rochester L. Moving forward on gait measurement: towards a more refined approach. Mov Disord. 2013 doi: 10.1002/mds.25545. in press. [DOI] [PubMed] [Google Scholar]
  • 32.Rosso AL, Studenski SA, Chen WG, et al. Aging, the central nervous system, and mobility. J Gerontol A Biol Sci Med Sci. 2013 doi: 10.1093/gerona/glt089. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Camicioli R, Majumdar SR. Relationship between mild cognitive impairment and falls in older people with and without Parkinson’s disease: 1-Year Prospective Cohort Study. Gait Posture. 2010;32:87–91. doi: 10.1016/j.gaitpost.2010.03.013. [DOI] [PubMed] [Google Scholar]
  • 34.Baltadjieva R, Giladi N, Gruendlinger L, Peretz C, Hausdorff JM. Marked alterations in the gait timing and rhythmicity of patients with de novo Parkinson’s disease. Eur J Neurosci. 2006;24:1815–1820. doi: 10.1111/j.1460-9568.2006.05033.x. [DOI] [PubMed] [Google Scholar]
  • 35.Buracchio T, Dodge HH, Howieson D, Wasserman D, Kaye J. The trajectory of gait speed preceding mild cognitive impairment. Arch Neurol. 2010;67:980–986. doi: 10.1001/archneurol.2010.159. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Mielke MM, Roberts RO, Savica R, et al. Assessing the temporal relationship between cognition and gait: slow gait predicts cognitive decline in the mayo clinic study of aging. J Gerontol A Biol Sci Med Sci. 2013;68:929–937. doi: 10.1093/gerona/gls256. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Maetzler W, Nieuwhof F, Hasmann S, Bloem BR. Emerging therapies for gait disability and balance impairment: promises and pitfalls. Mov Disord. 2013 doi: 10.1002/mds.25682. in press. [DOI] [PubMed] [Google Scholar]
  • 38.Mirelman A, Maidan I, Deustsch J. Virtual reality and motor imagery: promising tools for assesment and thearpy in patients with neurodegenerative disease. Mov Disord. 2013 doi: 10.1002/mds.25670. in press. [DOI] [PubMed] [Google Scholar]
  • 39.Potter-Nerger M, Volkmann J. Deep brain stimulation for gait, posture and other axialsymptoms. Mov Disord. 2013 doi: 10.1002/mds.25677. in press. [DOI] [PubMed] [Google Scholar]
  • 40.van der Kolk N, King L. Effects of exercise on mobility in people with Parkinson’s disease. Mov Disord. 2013 doi: 10.1002/mds.25658. in press. [DOI] [PubMed] [Google Scholar]
  • 41.Morris M, Menz HB, McGinley JL, et al. Randomized controlled trial to reduce falls and improve mobility in people with Parkinson’s disease. Mov Disord. 2013 in press. [Google Scholar]
  • 42.Weiss A, Mirelman A, Buchman AS, Bennett DA, Hausdorff JM. Using a body-fixed sensor to identify subclinical gait difficulties in older adults with IADL disability: maximizing the output of the Timed Up and Go. PLoS One. 2013;8:e68885. doi: 10.1371/journal.pone.0068885. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Mancini M, Salarian A, Carlson-Kuhta P, et al. ISway: a sensitive, valid and reliable measure of postural control. J Neuroeng Rehabil. 2012;9:59. doi: 10.1186/1743-0003-9-59. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Menz HB, Lord SR, Fitzpatrick RC. Acceleration patterns of the head and pelvis when walking are associated with risk of falling in community-dwelling older people. J Gerontol A Biol Sci Med Sci. 2003;58:M446–M452. doi: 10.1093/gerona/58.5.m446. [DOI] [PubMed] [Google Scholar]
  • 45.Weiss A, Shimkin I, Giladi N, Hausdorff JM. Automated detection of near falls: algorithm development and preliminary results. BMC Res Notes. 2010;3:62. doi: 10.1186/1756-0500-3-62. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Weiss A, Sharifi S, Plotnik M, van Vugt JP, Giladi N, Hausdorff JM. Toward automated, at-home assessment of mobility among patients with Parkinson disease, using a body-worn accelerometer. Neurorehabil Neural Repair. 2011;25:810–818. doi: 10.1177/1545968311424869. [DOI] [PubMed] [Google Scholar]
  • 47.Weiss A, Brozgol M, Dorfman M, et al. Does the Evaluation of Gait Quality during Daily Life Provide Insight Into Fall Risk? A Novel Approach Using 3-Day Accelerometer Recordings. Neurorehabil Neural Repair. 2013 doi: 10.1177/1545968313491004. ePub ahead of print. [DOI] [PubMed] [Google Scholar]
  • 48.Earhart G. Dynamic control of posture across locomotor tasks. Mov Disord. 2013 doi: 10.1002/mds.25592. in press. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Mancini M, Horak FB. Objective biomarkers of balance and gait for Parkinson’s disease using body-worn sensors. Mov Disord. 2013 doi: 10.1002/mds.25684. in press. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Nieuwboer A, Giladi N. Characterising freezing of gait in Parkinson’s disease: models of an episodic phenomenon. Mov Disord. 2013 doi: 10.1002/mds.25683. in press. [DOI] [PubMed] [Google Scholar]
  • 51.Hoehn MM, Yahr MD. Parkinsonism: onset, progression and mortality. Neurology. 1967;17:427–442. doi: 10.1212/wnl.17.5.427. [DOI] [PubMed] [Google Scholar]
  • 52.Holden MK, Gill KM, Magliozzi MR, Nathan J, Piehl-Baker L. Clinical gait assessment in the neurologically impaired. Reliability and meaningfulness. Phys Ther. 1984;64:35–40. doi: 10.1093/ptj/64.1.35. [DOI] [PubMed] [Google Scholar]
  • 53.Jankovic J, Nutt JG, Sudarsky L. Classification, diagnosis, and etiology of gait disorders. Adv Neurol. 2001;87:119–133. [PubMed] [Google Scholar]
  • 54.Mancini M, Horak FB. The relevance of clinical balance assessment tools to differentiate balance deficits. Eur J Phys Rehabil Med. 2010;46:239–248. [PMC free article] [PubMed] [Google Scholar]
  • 55.Snijders AH, van de Warrenburg BP, Giladi N, Bloem BR. Neurological gait disorders in elderly people: clinical approach and classification. Lancet Neurol. 2007;6:63–74. doi: 10.1016/S1474-4422(06)70678-0. [DOI] [PubMed] [Google Scholar]
  • 56.Tinetti ME, Williams TF, Mayewski R. Fall risk index for elderly patients based on number of chronic disabilities. Am J Med. 1986;80:429–434. doi: 10.1016/0002-9343(86)90717-5. [DOI] [PubMed] [Google Scholar]
  • 57.Plotnik M, Giladi N, Dagan Y, Hausdorff JM. Postural instability and fall risk in Parkinson’s disease: impaired dual tasking, pacing, and bilateral coordination of gait during the “ON” medication state. Exp Brain Res. 2011;210:529–538. doi: 10.1007/s00221-011-2551-0. [DOI] [PubMed] [Google Scholar]
  • 58.Plotnik M, Dagan Y, Gurevich T, Giladi N, Hausdorff JM. Effects of cognitive function on gait and dual tasking abilities in patients with Parkinson’s disease suffering from motor response fluctuations. Exp Brain Res. 2011;208:169–179. doi: 10.1007/s00221-010-2469-y. [DOI] [PubMed] [Google Scholar]
  • 59.Kerr GK, Worringham CJ, Cole MH, Lacherez PF, Wood JM, Silburn PA. Predictors of future falls in Parkinson disease. Neurology. 2010;75:116–124. doi: 10.1212/WNL.0b013e3181e7b688. [DOI] [PubMed] [Google Scholar]
  • 60.Thomas AA, Rogers JM, Amick MM, Friedman JH. Falls and the falls efficacy scale in Parkinson’s disease. J Neurol. 2010;257:1124–1128. doi: 10.1007/s00415-010-5475-x. [DOI] [PubMed] [Google Scholar]
  • 61.Nutt JG, Marsden CD, Thompson PD. Human walking and higher-level gait disorders, particularly in the elderly. Neurology. 1993;43:268–279. doi: 10.1212/wnl.43.2.268. [DOI] [PubMed] [Google Scholar]
  • 62.Herman T, Giladi N, Gurevich T, Hausdorff JM. Gait instability and fractal dynamics of older adults with a “cautious” gait: why do certain older adults walk fearfully? Gait Posture. 2005;21:178–185. doi: 10.1016/j.gaitpost.2004.01.014. [DOI] [PubMed] [Google Scholar]
  • 63.Nutt J. Higher level gait disorders: an open frontier. Mov Disord. 2013 doi: 10.1002/mds.25673. in press. [DOI] [PubMed] [Google Scholar]
  • 64.Allali G, Kressig RW, Assal F, Herrmann FR, Dubost V, Beauchet O. Changes in gait while backward counting in demented older adults with frontal lobe dysfunction. Gait Posture. 2007;26:572–576. doi: 10.1016/j.gaitpost.2006.12.011. [DOI] [PubMed] [Google Scholar]
  • 65.Allali G, Assal F, Kressig RW, Dubost V, Herrmann FR, Beauchet O. Impact of impaired executive function on gait stability. Dement Geriatr Cogn Disord. 2008;26:364–369. doi: 10.1159/000162358. [DOI] [PubMed] [Google Scholar]
  • 66.Peterson DS, Plotnik M, Hausdorff JM, Earhart GM. Evidence for a relationship between bilateral coordination during complex gait tasks and freezing of gait in Parkinson’s disease. Parkinsonism Relat Disord. 2012;18:1022–1026. doi: 10.1016/j.parkreldis.2012.05.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Plotnik M, Giladi N, Hausdorff JM. Bilateral coordination of walking and freezing of gait in Parkinson’s disease. Eur J Neurosci. 2008;27:1999–2006. doi: 10.1111/j.1460-9568.2008.06167.x. [DOI] [PubMed] [Google Scholar]
  • 68.Plotnik M, Giladi N, Hausdorff JM. Is freezing of gait in Parkinson’s disease a result of multiple gait impairments? Implications for treatment. Parkinsons Dis. 2012;2012:459321. doi: 10.1155/2012/459321. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Plotnik M, Giladi N, Balash Y, Peretz C, Hausdorff JM. Is freezing of gait in Parkinson’s disease related to asymmetric motor function? Ann Neurol. 2005;57:656–663. doi: 10.1002/ana.20452. [DOI] [PubMed] [Google Scholar]

RESOURCES