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Gait characterization for patients with orthostatic tremor
Parkinsonism and Related Disorders 71 (2020) 23–27
Contents lists available at ScienceDirect
Parkinsonism and Related Disorders journal homepage: www.elsevier.com/locate/parkreldis
Short communication
Gait characterization for patients with orthostatic tremor b
a
a
a
T c
Enrico Opri , Wei Hu , Zakia Jabarkheel , Christopher W. Hess , Abigail C. Schmitt , Aysegul Gunduzb, Chris J. Hassc, Michael S. Okuna, Aparna Wagle Shuklaa,∗ a b c
Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA Department of Biomedical engineering, University of Florida, College of Engineering, Gainesville, FL, USA Department of Applied Physiology and Kinesiology, University of Florida, College of Health and Human Performance, Gainesville, FL, USA
A R T I C LE I N FO
A B S T R A C T
Keywords: Orthostatic tremor Gait Instrumented walkway Physiology Tremor
Introduction: Orthostatic tremor (OT) patients frequently report gait unsteadiness with the advancement of disease; however, there is little understanding of its physiology. We sought to examine in OT, the spatial and temporal characteristics of gait, and the relationship with tremor physiology. Methods: Gait parameters for OT (n = 16) were recorded with an instrumented Zeno walkway system. All participants complained of gait unsteadiness, especially during slow walking. In a subset of OT, recordings were synchronized with a wireless EMG system for tremor assessment and feet pressure recording. Gait assessments were performed at self-selected habitual, fast, and slow speeds. Results: Compared to data available for an age- and sex-matched healthy controls, OT patients had a significantly reduced step length, increased step width, and increased gait variability (p < 0.0001). Tremor discharges related to OT were consistently recorded across three different speeds of walking. These discharges persisted through all phases of the gait cycle, including the swing phase when the limb was not weight-bearing. The highest tremor amplitude was recorded in the single support phase, followed by double support, and least during the swing phase. Conclusion: OT patients have distinct gait abnormalities similar to cerebellar disorders. Tremor discharges from the non-weight bearing leg in the swing phase suggests that muscle contractions, even when occurring without resistance, contribute to OT generation.
1. Introduction Orthostatic Tremor (OT) is a rare progressive tremor disorder characterized by a high frequency of 13–18 Hz leg tremor that characteristically appears upon standing [1]. The most frequent clinical symptom is a sensation of unsteadiness, which results in standing becoming an intolerable task. The clinical features of OT are unique as the symptoms related to standing are reported to resolve with sitting, walking or leaning against a surface. However, as the disease severity increases, many patients may report the sensation of unsteadiness to persist during walking [2]. Although previous studies have assessed postural balance in OT [2,3], and many previous studies have proposed oscillatory disturbance to arise from the cerebellum, there is minimal literature on gait characterization in OT. Furthermore, whether the gait characteristics in OT suggest an underlying cerebellar disorder has not been examined. In a recent study, more than half of the participants (27/34) could not walk in a straight line, and 17 subjects complained of subjective unsteadiness ∗
when performing the walking task [2]. These findings indicate that the nature of gait abnormalities in OT warrants further examination and characterization. We aimed to examine the spatial and temporal characteristics of gait in OT and determine whether tremor persists during walking and has a relationship with specific phases of the gait cycle. 2. Methods We prospectively enrolled OT patients in an IRB approved study that consecutively presented between 2017 and 2019 to our center at the University of Florida. Diagnosis of OT was confirmed with clinical criteria and surface electromyography (EMG) assessment, following recommendations of the Movement Disorders Society [4]. We enrolled patients who complained of gait unsteadiness yet were able to perform gait tasks comfortably on an instrumented walkway system. The exclusion criteria were: 1) requiring wheelchair for ambulation, 2) substantial active arthritis, and 3) diagnosis of secondary OT such as the presence of significant neuropathy. 4) Significant visual difficulties.
Corresponding author. Norman Fixel Institute for Neurological Diseases, #3009 Williston Road, Gainesville, FL, 32608, USA. E-mail addresses: enrico.opri@ufl.edu (E. Opri), [email protected]fl.edu (A. Wagle Shukla).
https://doi.org/10.1016/j.parkreldis.2020.01.007 Received 27 September 2019; Received in revised form 12 January 2020; Accepted 13 January 2020 1353-8020/ © 2020 Published by Elsevier Ltd.
Parkinsonism and Related Disorders 71 (2020) 23–27
E. Opri, et al.
rectus femoris, bilateral biceps femoris and bilateral gastrocnemius muscles (lateral head). The location for sensor placement was guided by muscle palpation during active flexion and extension of knee and ankle joints and was further confirmed with inspection of EMG output recorded with Delsys, EMG works software. Force transducers were applied to each foot (one on the heel, and three distributed on the sole border) for pressure recordings.
2.1. Study protocol Informed consent was obtained, participants underwent a detailed clinical history and a complete physical examination by the movement disorders specialist was performed. Data were collected while patients withheld OT medications for at least 12 h duration (five participants reported gabapentin intake, three reported clonazepam, two reported propranolol and the remaining six had discontinued all OT medications). Each subject was asked to sit with both feet placed on the ground on a chair that was 42 cm high and was placed at the end of a gait mat. The subject stood up in response to an auditory cue, and walked twice on a 26′x 2′ long gait mat or the Zeno walkway system (Zenometrics LLC, USA). The gait was characterized for velocity, step width, step length, % of time spent during swing phase, stance phase, single support phase and double support phase and the gait variability index (GVI) to quantify the variability in spatiotemporal variables; a score ≥ 100 indicating values similar to healthy controls, whereas lower scores denoting increased gait variability. Subjects walked on the gait mat back and forth without breaks unless symptoms of unsteadiness precluded completion of the task. Gait was recorded at three different speeds: self-selected habitual, fast, and slow. Four passes were recorded at each speed. (Fig. 1).
4. Data analysis The EMG data at the sensor was sampled at 1926 Hz, amplified, digitized and filtered at 20–450 Hz. The raw accelerometer signal was sampled at 148 Hz, digitized and filtered (0–50 Hz). The Zeno walkway data was sampled at 120 Hz. In a subset of participants, gait assessment was synchronized with EMG recording and feet pressure through a time-stamped TTL pulse, which was recorded on a shared digital channel that logged the beginning of the gait task. The Zeno walkway, pressure, and acceleration data were upsampled to the EMG sampling rate. Data was exported into MATLAB software (MathWorks, Inc., Natick, MA) for further analysis using methods described in previous literature [5]. Each speed was analyzed separately for each subject. Data collected during four passes of gait trials were subjected to a combined analysis. Initial inspection for the raw EMG signal obtained from all homologous muscle pairs was performed. The acceleration data was used for visual validation of pressure profiles such as absence or presence of movement. For analysis of tremor amplitude, EMG activation profile was determined based on the absolute value of the Hilbert transform of the band passed signal (20–450 Hz) [5]. For each leg gait phase (single support, double support, swing phase), spectral analyses
3. Setup and recordings We employed the Trigno™ Wireless EMG system (Delsys, Inc., Boston, Massachusetts) which include EMG sensors, triaxial accelerometers, and force transducers. Sensors were mounted over bilateral
Fig. 1. A reveals the gait cycle, which is the period or sequence of movements during locomotion in which one-foot contacts the ground to when that same foot again contacts the ground. Single support followed by double support followed by the single support phase is illustrated. B reveals step length, stride length and stride width. Step length is the distance between corresponding successive heels of opposite feet, measured parallel to the direction of the progression for the ipsilateral stride (cm). Stride length is the distance between two consecutive heel contacts, averaged for the left and right side. Stride width is the perpendicular distance between the line connecting the two ipsilateral foot heel contacts (stride) with the contralateral heel contact between those events (cm). C reveals surface EMG tremor recording synchronized with gait cycle recording for a sample OT subject (Subject 9). The subject was evaluated at self-selected habitual, self-selected fast and self-selected slow speed. Gait speeds recorded by the Zeno walkway system are depicted in the figure. Surface EMG signals recorded with sensors mounted over bilateral rectus femoris muscles are shown. Top panel reveals gait cycle for the left leg, the middle panel reveals for the right leg, and the bottom panel reveals recordings from the averaged pressure from sensors distributed under the feet (for each foot, one was mounted over the heel, and three distributed on the sole border). Tracings for the left leg are marked orange, and tracings for the right leg are marked blue. Arrows point to tremor discharges recorded from the non-weight bearing leg during the swing phase of the gait cycle (corresponding pressure tracings noted to be zero). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.) 24
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of the gait cycle for the right (p = 0.000056) and the left legs (p = 0.000078) (Supplementary Fig. 3). The post hoc analysis found single support > double support (right, p = 0.0061; left, p = 0.000055), single support > swing phase (right, p = 0.0063; left, p = 0.000051), double support > swing phase (right, p = 0.11; left, p = 0.06) difference. There was no correlation between tremor amplitude and disease duration; however there was significant correlation (right, r = 0.9 ± 0.059 and left, r = 0.89 ± 0.042; p < 0.00001) of amplitude and EMG activation (tonic EMG envelope peak) for the agonists and antagonists.
were calculated using maximum entropy spectral estimation, with a 200–order autoregressive model with 380 ms window length and a 50% overlap for the data. We used the highest amplitude recorded for all the spectral estimates through the entire recording (all four passes) as a normalization reference. OT gait was compared with a cohort of age- and sex-matched healthy controls (data available from Protokinetics Inc.) with a nonparametric Mann Whitney test. Sample size determination was based on effect size deemed as moderate, power estimation 80% and type I error at 0.05. Tremor amplitude across different phases of the gait cycle for each leg (single support vs. double support vs. swing phase) was determined with a power spectrum analysis and subjected to ANOVA followed by a Tukey's post hoc testing. Spearman correlation analysis between tremor amplitude and disease duration and EMG activation profile was performed. We set the threshold for significance at pvalue < 0.05.
6. Discussion Previous studies in OT have examined the postural balance [2,3]; however, there is sparse data on the spatial and temporal characterization of gait [6]. Our select cohort of OT patients with symptomatic gait unsteadiness revealed a spectrum of abnormalities comprising shorter steps, wider base and increased gait variability. OT participants spent more time in the double support phase compared to the single support phase of the gait cycle. These patterns of gait abnormalities were similar to those seen in patients with cerebellar disorders [7] and likely developed in OT as a compensatory response to offset the unsteadiness symptoms. Although slow walking was observed to worsen the unsteadiness symptoms, many OT participants walked slower on the walkway system compared to the controls. These observations are paradoxical and suggest that some aspects of gait abnormalities may indeed reflect a disease progression. Finally, OT discharges were consistently observed in our patients during walking and across three different speeds. More interestingly, tremor discharges continued through all phases of the gait cycle including the swing phase even though the limb that was off the ground was non-weight bearing. The pathogenic source for OT is believed to be a single central oscillator residing in the posterior fossa, more precisely in the cerebellum as shown by many previous studies [8,9]. A cerebellar dysfunction in OT is the likely source of the spectrum of gait abnormalities seen in our cohort [8]. A similar support for gait disturbances arising from cerebellar dysfunction has also been reported in essential tremor [10]; a tremor disorder overlapping in some respects with OT disorder. The unique nature OT manifestation during standing posture can be explained by the weight-bearing theory (muscle contraction against resistance, also isometric in part) that is probably the final key factor for the generation of tremor [11]. Furthermore, OT is seen to resolve when lying supine, sitting, and in one study upright posture but with no weight-bearing (patients were suspended in a harness) [12], these observations lend support to the theory of muscle contraction against resistance. On the other hand, a tremor discharge during the swing phase contradicts the weight-bearing hypothesis. We speculate that there may be a subliminal muscle contraction in some muscle groups, probably isometric by nature even when the leg is off the ground [13], or alternately with the advancement of the disease there are additional factors that contribute to OT pathogenesis. While our study findings imply theories of weight-bearing proposed by earlier studies may not be an absolute necessity for the genesis of tremor discharge, we found the tremor amplitude in the weight-bearing leg increased as the pressure applied to the foot increased. Indeed, the tremor amplitude was maximal during the single support phase followed by the double support phase and was least during the swing phase. In our opinion, similar to essential tremor and Parkinson's disease tremor [14], OT likely has a distinct central pacemaker circuit for control of tremor frequency and a separate propagation circuit for control of tremor amplitude that depends predominantly on muscle contraction especially when contracting against resistance. Whether there is decoupling of these two circuits with the progression of the disease will need further examination. We acknowledge, our sample was relatively small, was recruited from a single-center, we did not include a control group of early-stage
5. Results Sixteen OT patients (4 males, 12 females) with complaints of gait unsteadiness met the inclusion and exclusion criteria and were enrolled for the recordings (Supplementary Fig. 1). Slow walking was reported difficult by all participants (supplementary video for two sample patients illustrates the walking task at fast and slow speeds). Considering that participants could tolerate standing for only about 1–2 min, suggested a moderately advanced disease severity (Supplementary Table 1). The mean ( ± SD) age was 71.5 ( ± 8.6) years, the age of onset was 57.6 ( ± 11.6) years, disease duration was 13.8 ( ± 10.5) years, and the OT frequency was 15.3 ( ± 0.9) Hz with a 13–16 Hz range. The mean onset time for OT symptoms was 98.8 ± 47.1 s (range 60–180 s) although the latency time for tremor in the EMG recording was 210.7 ± 157.2 ms (range 50–500 ms). Only one subject reported a history of fall attributable to OT related unsteadiness. Patients were assessed while off medications for at least 8 h (overnight), and in one patient who reported a history of ventralis intermedius nucleus DBS, the stimulator was turned off 1 h before the gait assessment. Supplementary video related to this article can be found at https:// doi.org/10.1016/j.parkreldis.2020.01.007 The most frequent abnormalities at an individual level were reduced step length in 12/16 subjects; increased step width in 8/16 subjects and reduced gait velocity in 9/16 subjects. Then the following comprised the less frequent abnormalities: reduced GVI scores in 6/16 subjects (reduced scores consistent with increased gait variability), reduced swing phase % time in 7/16 subjects, increased swing phase (1/16 subjects), reduced single support % time and increased double support % time in 6/16 subjects and reduced double support % time in 1/16 subjects (Supplementary Table 1). Group comparisons of OT vs healthy controls (Fig. 2) revealed significantly reduced step length (p = 0.0001), increased step width (p = 0.0001), and reduced GVI (p = 0.0001). However, abnormalities in the other gait variables such as gait velocity (reduced; p = 0.09), swing % (reduced; p = 0.06), single support % (reduced; p = 0.12), double support % (increased; p = 0.06), stance % (increased; p = 0.08) were not significant. Additionally, there was no significant change in step time and cadence (p > 0.05). In the simultaneous recording of tremor and gait, we found distinct high-frequency OT discharges during the swing phase from muscles of the non-weight bearing leg (corresponded with pressure sensor readings as zero). The high frequency discharges noted when the gait speed was slow and matched with those recorded during the stance phase (Fig. 1 and Supplementary Fig. 2). The power spectrum analysis of the swing phase discharges revealed a frequency similar to the one recorded during the single support phase and double support phase; however, the tremor amplitude in the swing phase was the lowest. The normalized power estimates were significantly different across phases 25
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Fig. 2. Group data analysis for OT versus healthy controls. Significance threshold p < 0.05 is depicted by asterisk between the bars for step length, stride width and gait variability index (GVI).
Abigail Schmitt: Employment University of Florida. Chris Hass: employment- University of Florida. Christopher Hess: employment- University of Florida. Michael S. Okun – Serves as consultant for the National Parkinson's Foundation, and has received research grants from the National Institutes of Health, National Parkinson's Foundation, Michael J. Fox Foundation, Parkinson Alliance, Smallwood Foundation, BachmannStrauss Foundation, Tourette Syndrome Association, and UF Foundation. Dr. Okun has previously received honoraria, but in the past > 60 months has received no support from industry. Dr. Okun has received royalties for publications with Demos, Manson, Amazon, Smashwords, Books4Patients, and Cambridge (movement disorders books). Dr. Okun is an associate editor for New England Journal of Medicine Journal Watch Neurology. Dr. Okun has participated in CME and educational activities on movement disorders (in the last 36 months) sponsored by PeerView, Prime, Quantia, Henry Stewart, and the Vanderbilt University. The institution and not Dr. Okun receives grants from Medtronic, Abbvie, and /St. Jude, and Dr. Okun has no financial interest in these grants. Dr. Okun has participated as a site PI and/or co-I for several NIH, foundation, and industry sponsored trials over the years but has not received honoraria. Aparna Wagle Shukla – Reports grants from the NIH and has received grant support from Benign Essential Blepharospasm Research foundation, Dystonia coalition, Dystonia Medical Research foundation, National Organization for Rare Disorders and grant support from NIH (KL2 and K23 NS092957-01A1).
OT for comparisons, and gait speeds were self-selected. The EMG sensors, pressure sensors and walkway systems have inherent noise and artifact that can affect data collection and analysis. As such, for the purpose of this study, all acquisition sources were inspected and validated throughout the recording (e.g. for good EMG contact) by trained staff at our study site. Nevertheless, our study findings are novel as they characterize the spatial and temporal characteristics of gait in a select cohort of OT patients, and demonstrate that there is a persistence of tremor discharge through all phases of the gait cycle including the swing phase. The OT gait abnormalities were found to be similar to cerebellar disorders, supporting the hypothesis that the main pathophysiology of OT resides in the cerebellum. We also speculate that with the advancement of the disease, the central oscillator relays continuous rhythmic OT discharges to the leg muscles during all phases of the gait cycle but the tremor amplitude fluctuates in tandem with the change in pressure applied to the feet. Persistence of OT discharge in all gait phases possibly explains the unsteadiness symptoms perceived during walking and considering that the longer stance phase evokes the largest number of OT discharges, it explains the worsened severity of symptoms during slow walking. Future studies involving larger cohorts should examine the gait changes longitudinally for better characterization and further examine the exact relationship between isometric muscle contraction and OT discharge for an improved understanding. Author roles Enrico Opri was involved in data analysis, execution, review and critique of manuscript; Wei Hu was involved in collection of data and critique of manuscript; Zakia Jabarkheel was involved in execution and collection of data; Abigail Schmitt was involved in collection of data and critique of manuscript; Aysegul Gunduz was involved in review and critique of manuscript. Chris Hass was involved in collection of data and critique of manuscript. Christopher Hess was involved in collection of data and critique of manuscript. Michael S Okun was involved in review and critique of manuscript. Aparna Wagle Shukla was involved in conception, organization and execution of research project, execution and critique of statistical analysis, review and critique of manuscript;
Acknowledgment We would like to acknowledge Tyler's Hope Foundation for dystonia cure. Written informed consent was obtained from the patients to the publication of their images and videotapes, in both the print and online modalities. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.parkreldis.2020.01.007. References
Financial disclosures [1] A. Lenka, P.K. Pal, D.E. Bhatti, E.D. Louis, Pathogenesis of primary orthostatic tremor: current concepts and controversies, Tremor and other hyperkinetic movements (New York, N.Y.) 7 (2017) 513. [2] D. Bhatti, R. Thompson, Y. Xia, A. Hellman, L. Schmaderer, K. Suing, J. McKune, C. Penke, R. Iske, B.J. Roeder, K.C. Siu, J.M. Bertoni, D. Torres-Russotto, Comprehensive, blinded assessment of balance in orthostatic tremor, Park. Relat.
Enrico Opri: Employment University of Florida. Wei Hu: Employment University of Florida. Zakia Jabarkheel: Employment University of Florida. Aysegul Gunduz: Employment University of Florida. 26
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Disord. 47 (2018) 22–25. [3] K. Feil, N. Bottcher, F. Guri, S. Krafczyk, F. Schoberl, A. Zwergal, M. Strupp, Longterm course of orthostatic tremor in serial posturographic measurement, Park. Relat. Disord. 21 (8) (2015) 905–910. [4] K.P. Bhatia, P. Bain, N. Bajaj, R.J. Elble, M. Hallett, E.D. Louis, J. Raethjen, M. Stamelou, C.M. Testa, G. Deuschl, Consensus statement on the classification of tremors. From the task force on tremor of the international Parkinson and movement disorder society, movement disorders, official journal of the Movement Disorder Society 33 (1) (2018) 75–87. [5] I. Basu, D. Graupe, D. Tuninetti, P. Shukla, K.V. Slavin, L.V. Metman, D.M. Corcos, Pathological tremor prediction using surface electromyogram and acceleration: potential use in 'ON-OFF' demand driven deep brain stimulator design, J. Neural Eng. 10 (3) (2013) 036019. [6] M. Wuehr, C. Schlick, K. Mohwald, R. Schniepp, Walking in orthostatic tremor modulates tremor features and is characterized by impaired gait stability, Sci. Rep. 8 (1) (2018) 14152. [7] E. Croarkin, J. Maring, L. Pfalzer, M. Harris-Love, K. Siegel, N. DiProspero, Characterizing gait, locomotor status, and disease severity in children and adolescents with Friedreich ataxia, J. Neurol. Phys. Ther. : J. Neurol. Phys. Ther. 33 (3) (2009) 144–149. [8] C. Gallea, T. Popa, D. Garcia-Lorenzo, R. Valabregue, A.P. Legrand, E. Apartis, L. Marais, B. Degos, C. Hubsch, S. Fernandez-Vidal, E. Bardinet, E. Roze,
[9]
[10] [11]
[12]
[13]
[14]
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S. Lehericy, S. Meunier, M. Vidailhet, Orthostatic tremor: a cerebellar pathology? Brain : J. Neurol. 139 (Pt 8) (2016) 2182–2197. J. Benito-Leon, J.P. Romero, E.D. Louis, A. Sanchez-Ferro, M. Matarazzo, J.A. Molina-Arjona, V. Mato-Abad, Diffusion tensor imaging in orthostatic tremor: a tract-based spatial statistics study, Annals of clinical and translational neurology 6 (11) (2019) 2212–2222. J. Benito-Leon, A. Labiano-Fontcuberta, Linking essential tremor to the cerebellum: clinical evidence, Cerebellum 15 (3) (2016) 253–262. A. Hassan, J.A. van Gerpen, Orthostatic tremor and orthostatic myoclonus: weightbearing hyperkinetic disorders: a systematic review, New insights, and unresolved questions, tremor and other hyperkinetic movements (New York, N. Y. 6 (2016) 417. B. Boroojerdi, A. Ferbert, H. Foltys, C.M. Kosinski, J. Noth, M. Schwarz, Evidence for a non-orthostatic origin of orthostatic tremor, J. Neurol. Neurosurg. Psychiatry 66 (3) (1999) 284–288. B. Koster, M. Lauk, J. Timmer, M. Poersch, B. Guschlbauer, G. Deuschl, C.H. Lucking, Involvement of cranial muscles and high intermuscular coherence in orthostatic tremor, Ann. Neurol. 45 (3) (1999) 384–388. R.C. Helmich, M. Hallett, G. Deuschl, I. Toni, B.R. Bloem, Cerebral causes and consequences of parkinsonian resting tremor: a tale of two circuits? Brain : J. Neurol. 135 (Pt 11) (2012) 3206–3226.
Contents lists available at ScienceDirect
Parkinsonism and Related Disorders journal homepage: www.elsevier.com/locate/parkreldis
Short communication
Gait characterization for patients with orthostatic tremor b
a
a
a
T c
Enrico Opri , Wei Hu , Zakia Jabarkheel , Christopher W. Hess , Abigail C. Schmitt , Aysegul Gunduzb, Chris J. Hassc, Michael S. Okuna, Aparna Wagle Shuklaa,∗ a b c
Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA Department of Biomedical engineering, University of Florida, College of Engineering, Gainesville, FL, USA Department of Applied Physiology and Kinesiology, University of Florida, College of Health and Human Performance, Gainesville, FL, USA
A R T I C LE I N FO
A B S T R A C T
Keywords: Orthostatic tremor Gait Instrumented walkway Physiology Tremor
Introduction: Orthostatic tremor (OT) patients frequently report gait unsteadiness with the advancement of disease; however, there is little understanding of its physiology. We sought to examine in OT, the spatial and temporal characteristics of gait, and the relationship with tremor physiology. Methods: Gait parameters for OT (n = 16) were recorded with an instrumented Zeno walkway system. All participants complained of gait unsteadiness, especially during slow walking. In a subset of OT, recordings were synchronized with a wireless EMG system for tremor assessment and feet pressure recording. Gait assessments were performed at self-selected habitual, fast, and slow speeds. Results: Compared to data available for an age- and sex-matched healthy controls, OT patients had a significantly reduced step length, increased step width, and increased gait variability (p < 0.0001). Tremor discharges related to OT were consistently recorded across three different speeds of walking. These discharges persisted through all phases of the gait cycle, including the swing phase when the limb was not weight-bearing. The highest tremor amplitude was recorded in the single support phase, followed by double support, and least during the swing phase. Conclusion: OT patients have distinct gait abnormalities similar to cerebellar disorders. Tremor discharges from the non-weight bearing leg in the swing phase suggests that muscle contractions, even when occurring without resistance, contribute to OT generation.
1. Introduction Orthostatic Tremor (OT) is a rare progressive tremor disorder characterized by a high frequency of 13–18 Hz leg tremor that characteristically appears upon standing [1]. The most frequent clinical symptom is a sensation of unsteadiness, which results in standing becoming an intolerable task. The clinical features of OT are unique as the symptoms related to standing are reported to resolve with sitting, walking or leaning against a surface. However, as the disease severity increases, many patients may report the sensation of unsteadiness to persist during walking [2]. Although previous studies have assessed postural balance in OT [2,3], and many previous studies have proposed oscillatory disturbance to arise from the cerebellum, there is minimal literature on gait characterization in OT. Furthermore, whether the gait characteristics in OT suggest an underlying cerebellar disorder has not been examined. In a recent study, more than half of the participants (27/34) could not walk in a straight line, and 17 subjects complained of subjective unsteadiness ∗
when performing the walking task [2]. These findings indicate that the nature of gait abnormalities in OT warrants further examination and characterization. We aimed to examine the spatial and temporal characteristics of gait in OT and determine whether tremor persists during walking and has a relationship with specific phases of the gait cycle. 2. Methods We prospectively enrolled OT patients in an IRB approved study that consecutively presented between 2017 and 2019 to our center at the University of Florida. Diagnosis of OT was confirmed with clinical criteria and surface electromyography (EMG) assessment, following recommendations of the Movement Disorders Society [4]. We enrolled patients who complained of gait unsteadiness yet were able to perform gait tasks comfortably on an instrumented walkway system. The exclusion criteria were: 1) requiring wheelchair for ambulation, 2) substantial active arthritis, and 3) diagnosis of secondary OT such as the presence of significant neuropathy. 4) Significant visual difficulties.
Corresponding author. Norman Fixel Institute for Neurological Diseases, #3009 Williston Road, Gainesville, FL, 32608, USA. E-mail addresses: enrico.opri@ufl.edu (E. Opri), [email protected]fl.edu (A. Wagle Shukla).
https://doi.org/10.1016/j.parkreldis.2020.01.007 Received 27 September 2019; Received in revised form 12 January 2020; Accepted 13 January 2020 1353-8020/ © 2020 Published by Elsevier Ltd.
Parkinsonism and Related Disorders 71 (2020) 23–27
E. Opri, et al.
rectus femoris, bilateral biceps femoris and bilateral gastrocnemius muscles (lateral head). The location for sensor placement was guided by muscle palpation during active flexion and extension of knee and ankle joints and was further confirmed with inspection of EMG output recorded with Delsys, EMG works software. Force transducers were applied to each foot (one on the heel, and three distributed on the sole border) for pressure recordings.
2.1. Study protocol Informed consent was obtained, participants underwent a detailed clinical history and a complete physical examination by the movement disorders specialist was performed. Data were collected while patients withheld OT medications for at least 12 h duration (five participants reported gabapentin intake, three reported clonazepam, two reported propranolol and the remaining six had discontinued all OT medications). Each subject was asked to sit with both feet placed on the ground on a chair that was 42 cm high and was placed at the end of a gait mat. The subject stood up in response to an auditory cue, and walked twice on a 26′x 2′ long gait mat or the Zeno walkway system (Zenometrics LLC, USA). The gait was characterized for velocity, step width, step length, % of time spent during swing phase, stance phase, single support phase and double support phase and the gait variability index (GVI) to quantify the variability in spatiotemporal variables; a score ≥ 100 indicating values similar to healthy controls, whereas lower scores denoting increased gait variability. Subjects walked on the gait mat back and forth without breaks unless symptoms of unsteadiness precluded completion of the task. Gait was recorded at three different speeds: self-selected habitual, fast, and slow. Four passes were recorded at each speed. (Fig. 1).
4. Data analysis The EMG data at the sensor was sampled at 1926 Hz, amplified, digitized and filtered at 20–450 Hz. The raw accelerometer signal was sampled at 148 Hz, digitized and filtered (0–50 Hz). The Zeno walkway data was sampled at 120 Hz. In a subset of participants, gait assessment was synchronized with EMG recording and feet pressure through a time-stamped TTL pulse, which was recorded on a shared digital channel that logged the beginning of the gait task. The Zeno walkway, pressure, and acceleration data were upsampled to the EMG sampling rate. Data was exported into MATLAB software (MathWorks, Inc., Natick, MA) for further analysis using methods described in previous literature [5]. Each speed was analyzed separately for each subject. Data collected during four passes of gait trials were subjected to a combined analysis. Initial inspection for the raw EMG signal obtained from all homologous muscle pairs was performed. The acceleration data was used for visual validation of pressure profiles such as absence or presence of movement. For analysis of tremor amplitude, EMG activation profile was determined based on the absolute value of the Hilbert transform of the band passed signal (20–450 Hz) [5]. For each leg gait phase (single support, double support, swing phase), spectral analyses
3. Setup and recordings We employed the Trigno™ Wireless EMG system (Delsys, Inc., Boston, Massachusetts) which include EMG sensors, triaxial accelerometers, and force transducers. Sensors were mounted over bilateral
Fig. 1. A reveals the gait cycle, which is the period or sequence of movements during locomotion in which one-foot contacts the ground to when that same foot again contacts the ground. Single support followed by double support followed by the single support phase is illustrated. B reveals step length, stride length and stride width. Step length is the distance between corresponding successive heels of opposite feet, measured parallel to the direction of the progression for the ipsilateral stride (cm). Stride length is the distance between two consecutive heel contacts, averaged for the left and right side. Stride width is the perpendicular distance between the line connecting the two ipsilateral foot heel contacts (stride) with the contralateral heel contact between those events (cm). C reveals surface EMG tremor recording synchronized with gait cycle recording for a sample OT subject (Subject 9). The subject was evaluated at self-selected habitual, self-selected fast and self-selected slow speed. Gait speeds recorded by the Zeno walkway system are depicted in the figure. Surface EMG signals recorded with sensors mounted over bilateral rectus femoris muscles are shown. Top panel reveals gait cycle for the left leg, the middle panel reveals for the right leg, and the bottom panel reveals recordings from the averaged pressure from sensors distributed under the feet (for each foot, one was mounted over the heel, and three distributed on the sole border). Tracings for the left leg are marked orange, and tracings for the right leg are marked blue. Arrows point to tremor discharges recorded from the non-weight bearing leg during the swing phase of the gait cycle (corresponding pressure tracings noted to be zero). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.) 24
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of the gait cycle for the right (p = 0.000056) and the left legs (p = 0.000078) (Supplementary Fig. 3). The post hoc analysis found single support > double support (right, p = 0.0061; left, p = 0.000055), single support > swing phase (right, p = 0.0063; left, p = 0.000051), double support > swing phase (right, p = 0.11; left, p = 0.06) difference. There was no correlation between tremor amplitude and disease duration; however there was significant correlation (right, r = 0.9 ± 0.059 and left, r = 0.89 ± 0.042; p < 0.00001) of amplitude and EMG activation (tonic EMG envelope peak) for the agonists and antagonists.
were calculated using maximum entropy spectral estimation, with a 200–order autoregressive model with 380 ms window length and a 50% overlap for the data. We used the highest amplitude recorded for all the spectral estimates through the entire recording (all four passes) as a normalization reference. OT gait was compared with a cohort of age- and sex-matched healthy controls (data available from Protokinetics Inc.) with a nonparametric Mann Whitney test. Sample size determination was based on effect size deemed as moderate, power estimation 80% and type I error at 0.05. Tremor amplitude across different phases of the gait cycle for each leg (single support vs. double support vs. swing phase) was determined with a power spectrum analysis and subjected to ANOVA followed by a Tukey's post hoc testing. Spearman correlation analysis between tremor amplitude and disease duration and EMG activation profile was performed. We set the threshold for significance at pvalue < 0.05.
6. Discussion Previous studies in OT have examined the postural balance [2,3]; however, there is sparse data on the spatial and temporal characterization of gait [6]. Our select cohort of OT patients with symptomatic gait unsteadiness revealed a spectrum of abnormalities comprising shorter steps, wider base and increased gait variability. OT participants spent more time in the double support phase compared to the single support phase of the gait cycle. These patterns of gait abnormalities were similar to those seen in patients with cerebellar disorders [7] and likely developed in OT as a compensatory response to offset the unsteadiness symptoms. Although slow walking was observed to worsen the unsteadiness symptoms, many OT participants walked slower on the walkway system compared to the controls. These observations are paradoxical and suggest that some aspects of gait abnormalities may indeed reflect a disease progression. Finally, OT discharges were consistently observed in our patients during walking and across three different speeds. More interestingly, tremor discharges continued through all phases of the gait cycle including the swing phase even though the limb that was off the ground was non-weight bearing. The pathogenic source for OT is believed to be a single central oscillator residing in the posterior fossa, more precisely in the cerebellum as shown by many previous studies [8,9]. A cerebellar dysfunction in OT is the likely source of the spectrum of gait abnormalities seen in our cohort [8]. A similar support for gait disturbances arising from cerebellar dysfunction has also been reported in essential tremor [10]; a tremor disorder overlapping in some respects with OT disorder. The unique nature OT manifestation during standing posture can be explained by the weight-bearing theory (muscle contraction against resistance, also isometric in part) that is probably the final key factor for the generation of tremor [11]. Furthermore, OT is seen to resolve when lying supine, sitting, and in one study upright posture but with no weight-bearing (patients were suspended in a harness) [12], these observations lend support to the theory of muscle contraction against resistance. On the other hand, a tremor discharge during the swing phase contradicts the weight-bearing hypothesis. We speculate that there may be a subliminal muscle contraction in some muscle groups, probably isometric by nature even when the leg is off the ground [13], or alternately with the advancement of the disease there are additional factors that contribute to OT pathogenesis. While our study findings imply theories of weight-bearing proposed by earlier studies may not be an absolute necessity for the genesis of tremor discharge, we found the tremor amplitude in the weight-bearing leg increased as the pressure applied to the foot increased. Indeed, the tremor amplitude was maximal during the single support phase followed by the double support phase and was least during the swing phase. In our opinion, similar to essential tremor and Parkinson's disease tremor [14], OT likely has a distinct central pacemaker circuit for control of tremor frequency and a separate propagation circuit for control of tremor amplitude that depends predominantly on muscle contraction especially when contracting against resistance. Whether there is decoupling of these two circuits with the progression of the disease will need further examination. We acknowledge, our sample was relatively small, was recruited from a single-center, we did not include a control group of early-stage
5. Results Sixteen OT patients (4 males, 12 females) with complaints of gait unsteadiness met the inclusion and exclusion criteria and were enrolled for the recordings (Supplementary Fig. 1). Slow walking was reported difficult by all participants (supplementary video for two sample patients illustrates the walking task at fast and slow speeds). Considering that participants could tolerate standing for only about 1–2 min, suggested a moderately advanced disease severity (Supplementary Table 1). The mean ( ± SD) age was 71.5 ( ± 8.6) years, the age of onset was 57.6 ( ± 11.6) years, disease duration was 13.8 ( ± 10.5) years, and the OT frequency was 15.3 ( ± 0.9) Hz with a 13–16 Hz range. The mean onset time for OT symptoms was 98.8 ± 47.1 s (range 60–180 s) although the latency time for tremor in the EMG recording was 210.7 ± 157.2 ms (range 50–500 ms). Only one subject reported a history of fall attributable to OT related unsteadiness. Patients were assessed while off medications for at least 8 h (overnight), and in one patient who reported a history of ventralis intermedius nucleus DBS, the stimulator was turned off 1 h before the gait assessment. Supplementary video related to this article can be found at https:// doi.org/10.1016/j.parkreldis.2020.01.007 The most frequent abnormalities at an individual level were reduced step length in 12/16 subjects; increased step width in 8/16 subjects and reduced gait velocity in 9/16 subjects. Then the following comprised the less frequent abnormalities: reduced GVI scores in 6/16 subjects (reduced scores consistent with increased gait variability), reduced swing phase % time in 7/16 subjects, increased swing phase (1/16 subjects), reduced single support % time and increased double support % time in 6/16 subjects and reduced double support % time in 1/16 subjects (Supplementary Table 1). Group comparisons of OT vs healthy controls (Fig. 2) revealed significantly reduced step length (p = 0.0001), increased step width (p = 0.0001), and reduced GVI (p = 0.0001). However, abnormalities in the other gait variables such as gait velocity (reduced; p = 0.09), swing % (reduced; p = 0.06), single support % (reduced; p = 0.12), double support % (increased; p = 0.06), stance % (increased; p = 0.08) were not significant. Additionally, there was no significant change in step time and cadence (p > 0.05). In the simultaneous recording of tremor and gait, we found distinct high-frequency OT discharges during the swing phase from muscles of the non-weight bearing leg (corresponded with pressure sensor readings as zero). The high frequency discharges noted when the gait speed was slow and matched with those recorded during the stance phase (Fig. 1 and Supplementary Fig. 2). The power spectrum analysis of the swing phase discharges revealed a frequency similar to the one recorded during the single support phase and double support phase; however, the tremor amplitude in the swing phase was the lowest. The normalized power estimates were significantly different across phases 25
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Fig. 2. Group data analysis for OT versus healthy controls. Significance threshold p < 0.05 is depicted by asterisk between the bars for step length, stride width and gait variability index (GVI).
Abigail Schmitt: Employment University of Florida. Chris Hass: employment- University of Florida. Christopher Hess: employment- University of Florida. Michael S. Okun – Serves as consultant for the National Parkinson's Foundation, and has received research grants from the National Institutes of Health, National Parkinson's Foundation, Michael J. Fox Foundation, Parkinson Alliance, Smallwood Foundation, BachmannStrauss Foundation, Tourette Syndrome Association, and UF Foundation. Dr. Okun has previously received honoraria, but in the past > 60 months has received no support from industry. Dr. Okun has received royalties for publications with Demos, Manson, Amazon, Smashwords, Books4Patients, and Cambridge (movement disorders books). Dr. Okun is an associate editor for New England Journal of Medicine Journal Watch Neurology. Dr. Okun has participated in CME and educational activities on movement disorders (in the last 36 months) sponsored by PeerView, Prime, Quantia, Henry Stewart, and the Vanderbilt University. The institution and not Dr. Okun receives grants from Medtronic, Abbvie, and /St. Jude, and Dr. Okun has no financial interest in these grants. Dr. Okun has participated as a site PI and/or co-I for several NIH, foundation, and industry sponsored trials over the years but has not received honoraria. Aparna Wagle Shukla – Reports grants from the NIH and has received grant support from Benign Essential Blepharospasm Research foundation, Dystonia coalition, Dystonia Medical Research foundation, National Organization for Rare Disorders and grant support from NIH (KL2 and K23 NS092957-01A1).
OT for comparisons, and gait speeds were self-selected. The EMG sensors, pressure sensors and walkway systems have inherent noise and artifact that can affect data collection and analysis. As such, for the purpose of this study, all acquisition sources were inspected and validated throughout the recording (e.g. for good EMG contact) by trained staff at our study site. Nevertheless, our study findings are novel as they characterize the spatial and temporal characteristics of gait in a select cohort of OT patients, and demonstrate that there is a persistence of tremor discharge through all phases of the gait cycle including the swing phase. The OT gait abnormalities were found to be similar to cerebellar disorders, supporting the hypothesis that the main pathophysiology of OT resides in the cerebellum. We also speculate that with the advancement of the disease, the central oscillator relays continuous rhythmic OT discharges to the leg muscles during all phases of the gait cycle but the tremor amplitude fluctuates in tandem with the change in pressure applied to the feet. Persistence of OT discharge in all gait phases possibly explains the unsteadiness symptoms perceived during walking and considering that the longer stance phase evokes the largest number of OT discharges, it explains the worsened severity of symptoms during slow walking. Future studies involving larger cohorts should examine the gait changes longitudinally for better characterization and further examine the exact relationship between isometric muscle contraction and OT discharge for an improved understanding. Author roles Enrico Opri was involved in data analysis, execution, review and critique of manuscript; Wei Hu was involved in collection of data and critique of manuscript; Zakia Jabarkheel was involved in execution and collection of data; Abigail Schmitt was involved in collection of data and critique of manuscript; Aysegul Gunduz was involved in review and critique of manuscript. Chris Hass was involved in collection of data and critique of manuscript. Christopher Hess was involved in collection of data and critique of manuscript. Michael S Okun was involved in review and critique of manuscript. Aparna Wagle Shukla was involved in conception, organization and execution of research project, execution and critique of statistical analysis, review and critique of manuscript;
Acknowledgment We would like to acknowledge Tyler's Hope Foundation for dystonia cure. Written informed consent was obtained from the patients to the publication of their images and videotapes, in both the print and online modalities. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.parkreldis.2020.01.007. References
Financial disclosures [1] A. Lenka, P.K. Pal, D.E. Bhatti, E.D. Louis, Pathogenesis of primary orthostatic tremor: current concepts and controversies, Tremor and other hyperkinetic movements (New York, N.Y.) 7 (2017) 513. [2] D. Bhatti, R. Thompson, Y. Xia, A. Hellman, L. Schmaderer, K. Suing, J. McKune, C. Penke, R. Iske, B.J. Roeder, K.C. Siu, J.M. Bertoni, D. Torres-Russotto, Comprehensive, blinded assessment of balance in orthostatic tremor, Park. Relat.
Enrico Opri: Employment University of Florida. Wei Hu: Employment University of Florida. Zakia Jabarkheel: Employment University of Florida. Aysegul Gunduz: Employment University of Florida. 26
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Disord. 47 (2018) 22–25. [3] K. Feil, N. Bottcher, F. Guri, S. Krafczyk, F. Schoberl, A. Zwergal, M. Strupp, Longterm course of orthostatic tremor in serial posturographic measurement, Park. Relat. Disord. 21 (8) (2015) 905–910. [4] K.P. Bhatia, P. Bain, N. Bajaj, R.J. Elble, M. Hallett, E.D. Louis, J. Raethjen, M. Stamelou, C.M. Testa, G. Deuschl, Consensus statement on the classification of tremors. From the task force on tremor of the international Parkinson and movement disorder society, movement disorders, official journal of the Movement Disorder Society 33 (1) (2018) 75–87. [5] I. Basu, D. Graupe, D. Tuninetti, P. Shukla, K.V. Slavin, L.V. Metman, D.M. Corcos, Pathological tremor prediction using surface electromyogram and acceleration: potential use in 'ON-OFF' demand driven deep brain stimulator design, J. Neural Eng. 10 (3) (2013) 036019. [6] M. Wuehr, C. Schlick, K. Mohwald, R. Schniepp, Walking in orthostatic tremor modulates tremor features and is characterized by impaired gait stability, Sci. Rep. 8 (1) (2018) 14152. [7] E. Croarkin, J. Maring, L. Pfalzer, M. Harris-Love, K. Siegel, N. DiProspero, Characterizing gait, locomotor status, and disease severity in children and adolescents with Friedreich ataxia, J. Neurol. Phys. Ther. : J. Neurol. Phys. Ther. 33 (3) (2009) 144–149. [8] C. Gallea, T. Popa, D. Garcia-Lorenzo, R. Valabregue, A.P. Legrand, E. Apartis, L. Marais, B. Degos, C. Hubsch, S. Fernandez-Vidal, E. Bardinet, E. Roze,
[9]
[10] [11]
[12]
[13]
[14]
27
S. Lehericy, S. Meunier, M. Vidailhet, Orthostatic tremor: a cerebellar pathology? Brain : J. Neurol. 139 (Pt 8) (2016) 2182–2197. J. Benito-Leon, J.P. Romero, E.D. Louis, A. Sanchez-Ferro, M. Matarazzo, J.A. Molina-Arjona, V. Mato-Abad, Diffusion tensor imaging in orthostatic tremor: a tract-based spatial statistics study, Annals of clinical and translational neurology 6 (11) (2019) 2212–2222. J. Benito-Leon, A. Labiano-Fontcuberta, Linking essential tremor to the cerebellum: clinical evidence, Cerebellum 15 (3) (2016) 253–262. A. Hassan, J.A. van Gerpen, Orthostatic tremor and orthostatic myoclonus: weightbearing hyperkinetic disorders: a systematic review, New insights, and unresolved questions, tremor and other hyperkinetic movements (New York, N. Y. 6 (2016) 417. B. Boroojerdi, A. Ferbert, H. Foltys, C.M. Kosinski, J. Noth, M. Schwarz, Evidence for a non-orthostatic origin of orthostatic tremor, J. Neurol. Neurosurg. Psychiatry 66 (3) (1999) 284–288. B. Koster, M. Lauk, J. Timmer, M. Poersch, B. Guschlbauer, G. Deuschl, C.H. Lucking, Involvement of cranial muscles and high intermuscular coherence in orthostatic tremor, Ann. Neurol. 45 (3) (1999) 384–388. R.C. Helmich, M. Hallett, G. Deuschl, I. Toni, B.R. Bloem, Cerebral causes and consequences of parkinsonian resting tremor: a tale of two circuits? Brain : J. Neurol. 135 (Pt 11) (2012) 3206–3226.