Rest tremor in patients with essential tremor: prevalence, clinical correlates, and electrophysiologic characteristics

Differential influences of rest tremor on brain fiber architecture in essential tremor and Parkinson's disease

BACKGROUND

Rest tremor is a movement disorder commonly found in diseases like Parkinson's disease (PD) and essential tremor (ET). Rest tremor typically shows slower progression in PD, but more severe progression in ET. However, the underlying white matter organization of rest tremor behind PD and ET remains unclear.

METHODS

This study included 57 ET patients (40 without rest tremor (ETWR), 17 with rest tremor (ETRT)), 68 PD patients (34 without rest tremor (PDWR), 34 with rest tremor (PDRT)), and 62 normal controls (NC). Fixel-based analysis was used to evaluate the structural changes of white matter in rest tremor in these different diseases.

RESULTS

The fiber-bundle cross-section (FC) of the right non-decussating dentato-rubro-thalamic tract and several fibers outside the dentato-rubro-thalamic pathway in ETWR were significantly higher than that in NC. The fiber density and cross-section of the left nigro-pallidal in PDWR is significantly lower than that in NC, while the FC of bilateral nigro-pallidal in PDRT is significantly lower than that in NC.

CONCLUSION

ET patients with pure action tremor showed over-activation of fiber tracts. However, when superimposed with rest tremor, ET patients no longer exhibited over-activation of fiber tracts, but rather showed a trend of fiber tract damage. Except for the nigro-pallidal degeneration in all PD, PDRT will not experience further deterioration in fiber organization. These results provide important insights into the unique effects of rest tremor on brain fiber architecture in ET and PD.

Clinical and kinematic characterization of parkinsonian soft signs in essential tremor

BACKGROUND

Subtle parkinsonian signs, i.e., rest tremor and bradykinesia, are considered soft signs for defining essential tremor (ET) plus.

OBJECTIVES

Our study aimed to further characterize subtle parkinsonian signs in a relatively large sample of ET patients from a clinical and neurophysiological perspective.

METHODS

We employed clinical scales and kinematic techniques to assess a sample of 82 ET patients. Eighty healthy controls matched for gender and age were also included. The primary focus of our study was to conduct a comparative analysis of ET patients (without any soft signs) and ET-plus patients with rest tremor and/or bradykinesia. Additionally, we investigated the asymmetry and side concordance of these soft signs.

RESULTS

In ET-plus patients with parkinsonian soft signs (56.10% of the sample), rest tremor was clinically observed in 41.30% of cases, bradykinesia in 30.43%, and rest tremor plus bradykinesia in 28.26%. Patients with rest tremor had more severe and widespread action tremor than other patients. Furthermore, we observed a positive correlation between the amplitude of action and rest tremor. Most ET-plus patients had an asymmetry of rest tremor and bradykinesia. There was no side concordance between these soft signs, as confirmed through both clinical examination and kinematic evaluation.

CONCLUSIONS

Rest tremor and bradykinesia are frequently observed in ET and are often asymmetric but not concordant. Our findings provide a better insight into the phenomenology of ET and suggest that the parkinsonian soft signs (rest tremor and bradykinesia) in ET-plus may originate from distinct pathophysiological mechanisms.

Bedside clinical assessment of patients with common upper limb tremor and algorithmic approach

The diagnostic approach for patients with tremor is challenging due to the complex and overlapping phenotypes among tremor syndromes. The first step in the evaluation of tremor is to identify the tremulous movement and exclude the tremor mimics. The second step is to classify the tremor syndrome based on the characteristics of tremor from historical clues and focused examination (Axis 1). Comprehensive tremor examinations involve the assessment of tremor in different conditions (rest, action or mixed, position or task-specific), distribution of tremor (upper limb, lower limb, head, jaw), positive signs for functional tremor (FT) if suspected (distractibility, entrainment, co-contraction), and associated neurological signs including parkinsonism, dystonic posture, cerebellar/brainstem signs, neuropathy, and cognitive impairment. A pivotal feature in this step is to determine any distinct feature of a specific isolated or combined tremor syndrome. In this review, we propose an algorithm to assess upper limb tremors. Ancillary testing should be performed if clinical evaluation is unclear. The choice of investigation depends on the types of tremors considered to narrow down the spectrum of etiology (Axis 2). Laboratory blood tests are considered for acute onset and acute worsening of tremors, while structural neuroimaging is indicated in unilateral tremors with acute onset, nonclassical presentations, and a combination of neurological symptoms. Neurophysiological study is an important tool that aids in distinguishing between tremor and myoclonus, etiology of tremor and document specific signs of FT. Treatment is mainly symptomatic based depending on the etiology of the tremor and the patient's disabilities.

Combined cortical thickness and blink reflex recovery cycle to differentiate essential tremor with and without resting tremor

Objective

To investigate the performance of structural MRI cortical and subcortical morphometric data combined with blink-reflex recovery cycle (BRrc) values using machine learning (ML) models in distinguishing between essential tremor (ET) with resting tremor (rET) and classic ET.

Methods

We enrolled 47 ET, 43 rET patients and 45 healthy controls (HC). All participants underwent brain 3 T-MRI and BRrc examination at different interstimulus intervals (ISIs, 100-300 msec). MRI data (cortical thickness, volumes, surface area, roughness, mean curvature and subcortical volumes) were extracted using Freesurfer on T1-weighted images. We employed two decision tree-based ML classification algorithms (eXtreme Gradient Boosting [XGBoost] and Random Forest) combining MRI data and BRrc values to differentiate between rET and ET patients.

Results

ML models based exclusively on MRI features reached acceptable performance (AUC: 0.85-0.86) in differentiating rET from ET patients and from HC. Similar performances were obtained by ML models based on BRrc data (AUC: 0.81-0.82 in rET vs. ET and AUC: 0.88-0.89 in rET vs. HC). ML models combining imaging data (cortical thickness, surface, roughness, and mean curvature) together with BRrc values showed the highest classification performance in distinguishing between rET and ET patients, reaching AUC of 0.94 ± 0.05. The improvement in classification performances when BRrc data were added to imaging features was confirmed by both ML algorithms.

Conclusion

This study highlights the usefulness of adding a simple electrophysiological assessment such as BRrc to MRI cortical morphometric features for accurately distinguishing rET from ET patients, paving the way for a better classification of these ET syndromes.

Upper limb intention tremor assessment: opportunities and challenges in wearable technology

BACKGROUND

Tremors are involuntary rhythmic movements commonly present in neurological diseases such as Parkinson's disease, essential tremor, and multiple sclerosis. Intention tremor is a subtype associated with lesions in the cerebellum and its connected pathways, and it is a common symptom in diseases associated with cerebellar pathology. While clinicians traditionally use tests to identify tremor type and severity, recent advancements in wearable technology have provided quantifiable ways to measure movement and tremor using motion capture systems, app-based tasks and tools, and physiology-based measurements. However, quantifying intention tremor remains challenging due to its changing nature.

METHODOLOGY & RESULTS

This review examines the current state of upper limb tremor assessment technology and discusses potential directions to further develop new and existing algorithms and sensors to better quantify tremor, specifically intention tremor. A comprehensive search using PubMed and Scopus was performed using keywords related to technologies for tremor assessment. Afterward, screened results were filtered for relevance and eligibility and further classified into technology type. A total of 243 publications were selected for this review and classified according to their type: body function level: movement-based, activity level: task and tool-based, and physiology-based. Furthermore, each publication's methods, purpose, and technology are summarized in the appendix table.

CONCLUSIONS

Our survey suggests a need for more targeted tasks to evaluate intention tremors, including digitized tasks related to intentional movements, neurological and physiological measurements targeting the cerebellum and its pathways, and signal processing techniques that differentiate voluntary from involuntary movement in motion capture systems.

Artificial-intelligence-based MRI brain volumetry in patients with essential tremor and tremor-dominant Parkinson's disease

Essential tremor and Parkinson's disease patients may present with various tremor types. Overlapping tremor features can be challenging to diagnosis and misdiagnosis is common. Although underlying neurodegenerative mechanisms are suggested, neuroimaging studies arrived at controversial results and often the different tremor types were not considered. We investigated whether different tremor types displayed distinct structural brain features. Structural MRI of 61 patients with essential tremor and 29 with tremor-dominant Parkinson's disease was analysed using a fully automated artificial-intelligence-based brain volumetry to compare volumes of several cortical and subcortical regions. Furthermore, essential tremor subgroups with and without rest tremor or more pronounced postural and kinetic tremor were investigated. Deviations from an internal reference collective of age- and sex-adjusted healthy controls and volumetric differences between groups were examined; regression analysis was used to determine the contribution of disease-related factors on volumetric measurements. Compared with healthy controls, essential tremor and tremor-dominant Parkinson's disease patients displayed deviations in the occipital lobes, hippocampus, putamen, pallidum and mesencephalon while essential tremor patients exhibited decreased volumes within the nucleus caudatus and thalamus. Analysis of covariance revealed similar volumetric patterns in both diseases. Essential tremor patients without rest tremor showed a significant atrophy within the thalamus compared to tremor-dominant Parkinson's disease and atrophy of the mesencephalon and putamen were found in both subgroups compared to essential tremor with rest tremor. Disease-related factors contribute to volumes of occipital lobes in both diseases and to volumes of temporal lobes in essential tremor and the putamen in Parkinson's disease. Fully automated artificial-intelligence-based volumetry provides a fast and rater-independent method to investigate brain volumes in different neurological disorders and allows comparisons with an internal reference collective. Our results indicate that essential tremor and tremor-dominant Parkinson's disease share structural changes, indicative of neurodegenerative mechanisms, particularly of the basal-ganglia-thalamocortical circuitry. A discriminating, possibly disease-specific involvement of the thalamus was found in essential tremor patients without rest tremor and the mesencephalon and putamen in tremor-dominant Parkinson's disease and essential tremor without rest tremor.

A Wearable Multi-Segment Upper Limb Tremor Assessment System for Differential Diagnosis of Parkinson's Disease Versus Essential Tremor

Upper limb tremor is a prominent symptom of both Parkinson's disease and essential tremor. Its kinematic parameters overlap substantially for these two pathological conditions, thus leading to high rate of misdiagnosis, especially for community doctors. Several groups have proposed various methods for improving differential diagnosis. These prior studies have attempted to identify better kinematic parameters, however they have mainly focused on single limb features including tremor intensity, tremor frequency, and tremor variability. In this paper, we propose a wearable system for multi-segment assessment of upper limb tremor and differential diagnosis of Parkinson's disease versus essential tremor. The proposed system collected tremor data from both wrist and fingers simultaneously. From this data, we extracted multi-segment features in the form of phase relationships between limb segments. Using support vector machine classifiers, we then performed differential diagnosis from the extracted features. We evaluated the performance of the proposed system on 19 Parkinson's disease patients and 12 essential tremor patients. Moreover, we also assessed the performance cost associated with reducing task load and sensor array size. The proposed system reached perfect accuracy in leave-one-out cross validation. Task reduction and sensor array reduction were associated with penalties of 2% and 9-10% respectively. The results demonstrated that the proposed system could be simplified for clinical applications, and successfully applied to the differential diagnosis of Parkinson's disease versus essential tremor in real-world setting.

Erythrocytic alpha-synuclein as potential biomarker for the differentiation between essential tremor and Parkinson's disease

Introduction

The differentiation between essential tremor (ET) and Parkinson's disease (PD) can be difficult because of the symptom overlaps. Erythrocytes are the major source of peripheral α-synuclein (α-syn), which is the most studied pathological molecular of PD. We have reported that erythrocytic α-syn levels in PD patients are significantly increased compared to those in healthy controls (HCs). However, little is known about the levels of erythrocytic α-syn species in ET patients.

Methods

This study includes 15 patients with ET, 64 patients with PD, and 49 age and sex matched HCs. A well-established electrochemiluminescence assay was used to measure the erythrocytic total and aggregated α-syn levels. The receiver operating characteristic (ROC) curve analysis was applied to evaluate the diagnostic values of erythrocytic α-syn for ET diagnosis and differentiation. The correlations of erythrocytic α-syn levels with disease durations were tested using Spearman's Rank Correlation analysis.

Results

We found that both erythrocytic total and aggregated α-syn concentrations are significantly increased in PD and ET patients compared to those in HCs. Erythrocytic total α-syn levels are significantly higher in ET patients than those in PD group. Furthermore, the ratios of erythrocytic aggregated to total α-syn levels in ET patients are significantly decreased than those in PD and HC subjects. We also found a significant association of erythrocytic aggregated α-syn levels with the disease duration of ET patients.

Conclusion

Our findings suggest new insight into the changes of erythrocytic total and aggregated α-syn levels as potential biomarkers for ET patients.

Clinical Heterogeneity of Essential Tremor: Understanding Neural Substrates of Action Tremor Subtypes

Essential tremor (ET) is a common movement disorder affecting millions of people. Studies of ET patients and perturbations in animal models have provided a foundation for the neural networks involved in its pathophysiology. However, ET encompasses a wide variability of phenotypic expression, and this may be the consequence of dysfunction in distinct subcircuits in the brain. The cerebello-thalamo-cortical circuit is a common substrate for the multiple subtypes of action tremor. Within the cerebellum, three sets of cerebellar cortex-deep cerebellar nuclei connections are important for tremor. The lateral hemispheres and dentate nuclei may be involved in intention, postural and isometric tremor. The intermediate zone and interposed nuclei could be involved in intention tremor. The vermis and fastigial nuclei could be involved in head and proximal upper extremity tremor. Studying distinct cerebellar circuitry will provide important framework for understanding the clinical heterogeneity of ET.

Essential tremor

Essential tremor (ET) is a chronic and progressive neurologic disease. Its central and defining clinical feature is a 4-12Hz kinetic tremor, that is, tremor that occurs during voluntary movements such as drinking from a cup or writing. Patients may also exhibit a range of other tremors-postural, rest, intention, additional motor features (e.g., mild gait ataxia, mild dystonia), as well as nonmotor features. The disease itself seems to be a risk factor for other degenerative diseases such as Alzheimer's disease and Parkinson's disease. Both genetic and toxic environmental factors have been explored as etiologic factors. In addition to a growing appreciation of the presence of clinical, etiologic, and pathologic heterogeneity, there is some support for the notion that ET itself may not be a single disease, but may be a family of diseases whose central defining feature is kinetic tremor of the arms, and which might more accurately be referred to as "the essential tremors." Recent research has increasingly placed the seat of the disease in the cerebellum and cerebellar system and identified a host of neurodegenerative changes within the cerebellum, indicating that this progressive disorder is likely degenerative.

Essential tremor plus rest tremor: current concepts and controversies

Since the initial description of Essential Tremor (ET), the entity of ET with rest tremor has proven to be a controversial concept. Some authors argued it could be a late manifestation of ET, others suggested it could be a variant of ET, yet others suggested it could represent a transitional state between ET and Parkinson's disease. The novel tremor classification has proposed the construct of ET-plus to differentiate patients with rest tremor from pure ET. However, there is no clarity of what ET-plus rest tremor represents. With the aim of shedding light on this controversial entity, we have, therefore, systematically reviewed all clinical, electrophysiological, imaging and anatomopathological studies indexed in the Medline database published both before and after the new tremor classification and involving patients with ET-plus rest tremor. Forty-four studies involving 4028 patients were included in this review and analyzed in detail by means of descriptive statistics. The results of the current review suggest that ET-plus rest tremor is a heterogenous group of conditions: thus, rest tremor might represent a late feature of ET, might reflect a different disorder with higher age at onset and lower dependance on genetic susceptibility than ET, might suggest the development of Parkinson's disease or might indicate a misdiagnosis of ET. The reviewed lines of evidence refuse recent claims arguing against the construct of ET-plus, which should be viewed as a syndrome with different possible underpinnings, and highlights methodological issues to be solved in future research.

Wearable sensors during drawing tasks to measure the severity of essential tremor

Commonly used methods to assess the severity of essential tremor (ET) are based on clinical observation and lack objectivity. This study proposes the use of wearable accelerometer sensors for the quantitative assessment of ET. Acceleration data was recorded by inertial measurement unit (IMU) sensors during sketching of Archimedes spirals in 17 ET participants and 18 healthy controls. IMUs were placed at three points (dorsum of hand, posterior forearm, posterior upper arm) of each participant's dominant arm. Movement disorder neurologists who were blinded to clinical information scored ET patients on the Fahn-Tolosa-Marin rating scale (FTM) and conducted phenotyping according to the recent Consensus Statement on the Classification of Tremors. The ratio of power spectral density of acceleration data in 4-12 Hz to 0.5-4 Hz bands and the total duration of the action were inputs to a support vector machine that was trained to classify the ET subtype. Regression analysis was performed to determine the relationship of acceleration and temporal data with the FTM scores. The results show that the sensor located on the forearm had the best classification and regression results, with accuracy of 85.71% for binary classification of ET versus control. There was a moderate to good correlation (r² = 0.561) between FTM and a combination of power spectral density ratio and task time. However, the system could not accurately differentiate ET phenotypes according to the Consensus classification scheme. Potential applications of machine-based assessment of ET using wearable sensors include clinical trials and remote monitoring of patients.

Is essential tremor a family of diseases or a syndrome? A family of diseases

It is now well-established that essential tremor (ET) can manifest with different clinical presentations and progressions (i.e., upper limb tremor, head tremor, voice tremor, lower limb tremor, task- or position-specific tremor, or a combination of those). Common traits and overlaps are identifiable across these different subtypes of ET, including a slow rate of progression, a response to alcohol and a positive family history. At the same time, each of these manifestations are associated with specific demographic, clinical and treatment-response characteristics suggesting a family of diseases rather than a spectrum of a syndrome. Here we summarize the most important clinical, demographic, neuropathological and imagingfeatures of ET and of its subtypes to support ET as a family of identifiable conditions. This classification has relevance for counseling of patients with regard to disease progression and treatment response, as well as for the design of therapeutic clinical trials.

Is inferior olive central to the pathophysiology of essential tremor? No

Essential tremor (ET) represents one of the commonest movement disorder worldwide and is the most common tremor disorder. ET manifests with various combinations of motor and nonmotor symptoms. The clinical hallmark is a kinetic tremor of upper limbs. Historically, the pathogenesis of ET has been based on the hypothesis of an overactivity of the inferior olive (inferior olive hypothesis: IOH) where the inferior olive would act as the central pace-maker of ET, resulting in impaired electrophysiological discharges of the olivo-cerebellar tract. The absence of structural alterations in post-mortem studies of the inferior olive is a striking argument against the IOH. Furthermore, neuroimaging studies point towards the implication of the cerebello-thalamo-cerebral pathway rather than the IO, and the harmaline model which has been considered as an animal model of ET presents important weaknesses. By contrast, a series of experiments by Louis et al. have provided convincing evidence of impaired wiring of the Purkinje cell microcircuitry and progressive neurodegeneration of the cerebellar cortex. The Purkinje neuron appears as the primary culprit (Purkinjopathy). The cerebellar cortex hypothesis (CCH) has solid neuropathological signatures, unlike the purely physiological IOH. Rather than a dysregulatory electrophysiological disorder suggested by IOH, ET is a clinical-pathological entity similar to late onset neurodegenerative disorders such as Parkinson's disease or Alzheimer's disease. The CCH emphasizes the need to develop novel therapeutic strategies in order to maintain or promote the cerebellar reserve. The modern reconceptualization of ET in a genuine cerebellar disorder is cleaning the IOH to the light of histopathological studies. ET falls in the large basket of the neurodegenerative diseases and we have entered into a novel formulation of the disease pathogenesis with direct impacts on future therapies.

Identification and Classification of Parkinsonian and Essential Tremors for Diagnosis Using Machine Learning Algorithms

Due to overlapping tremor features, the medical diagnosis of Parkinson’s disease (PD) and essential tremor (ET) mainly relies on the clinical experience of doctors, which often leads to misdiagnosis. Seven predictive models using machine learning algorithms including random forest (RF), eXtreme Gradient Boosting (XGBoost), support vector machine (SVM), logistic regression (LR), ridge classification (Ridge), backpropagation neural network (BP), and convolutional neural network (CNN) were evaluated and compared aiming to better differentiate between PD and ET by using accessible demographics and tremor information of the upper limbs. The tremor information including tremor acceleration and surface electromyogram (sEMG) signals were collected from 398 patients (PD = 257, ET = 141) and then were used to train the established models to separate PD and ET. The performance of the models was evaluated by indices of accuracy and area under the curve (AUC), which indicated the ensemble learning models including RF and XGBoost showed the best overall predictive ability with accuracy above 0.84 and AUC above 0.90. Furthermore, the relative importance of sex, age, four postures, and five tremor features was analyzed and ranked showing that the dominant frequency of sEMG of flexors, the average amplitude of sEMG of flexors, resting posture, and winging posture had a greater impact on the diagnosis of PD, whereas sex and age were less important. These results provide a reference for the intelligent diagnosis of PD and show promise for use in wearable tremor suppression devices.

Computerised analysis of writing and drawing by essential tremor phenotype

We investigated whether computerised analysis of writing and drawing could discriminate essential tremor (ET) phenotypes according to the 2018 Consensus Statement on the Classification of Tremors. The Consensus scheme emphasises soft additional findings, mainly motor, that do not suffice to diagnose another tremor syndrome. Ten men and nine women were classified by blinded assessors according to Consensus Axis 1 definitions of ET and ET plus. Blinded scoring of tremor severity and alternating limb movement was also conducted. Twenty healthy participants acted as controls. Four writing and three drawing tasks were performed on a Wacom Intuos Pro Large digital tablet with a pressure-sensor mounted ink pen. Sixty-seven computerised measurements were obtained, comprising static (dimensional and temporal), kinematic and pen pressure features. The mean age of ET participants was 67.2±13.0 years and mean tremor duration was 21.7±19.0 years. Six were classified as ET, five had one plus feature and eight had two plus features. The computerised analysis could predict the presence and number of ET plus features. Measures of acceleration and variation of pen pressure performed strongly to separate ET phenotypes (p<0.05). Plus features were associated with higher scores on the Fahn-Tolosa-Marin Tremor Rating Scale (p=0.001) and it appeared that ET groups were mainly being separated according to severity of tremor and by compensatory manoeuvres used by participants with more severe tremor. There were, in addition, a small number of negative kinematic correlations suggesting some slowness with ET plus. Abnormal repetitive limb movement was also correlated with tremor severity (R=0.57) by clinical grading. Critics of the Consensus Statement have drawn attention to weaknesses of the ET plus concept in relation to duration and severity of ET. This classification of ET may be too biased towards tremor severity to assist in distinguishing underlying biological differences by clinical measurement.

Is essential tremor a degenerative disorder or an electric disorder? Degenerative disorder

Essential tremor (ET) is a highly prevalent neurologic disease and is the most common of the many tremor disorders. ET is a progressive condition with marked clinical heterogeneity, associated with a spectrum of both motor and non-motor features. However, its disease mechanisms remain poorly understood. Much debate has centered on whether ET should be considered a degenerative disorder, with underlying pathological changes in brain causing progressive disease manifestations, or an electric disorder, with overactivity of intrinsically oscillatory motor networks that occur without underlying structural brain abnormalities. Converging data from clinical, neuroimaging and pathological studies in ET now provide considerable evidence for the neurodegenerative hypothesis. A major turning point in this debate is that rigorous tissue-based studies have recently identified a series of structural changes in the ET cerebellum. Most of these pathological changes are centered on the Purkinje cell and connected neuronal populations, which can result in partial loss of Purkinje cells and circuitry reorganizations that would disturb cerebellar function. There is significant overlap in clinical and pathological features of ET with other disorders of cerebellar degeneration, and an increased risk of developing other degenerative diseases in ET. The combined implication of these studies is that ET could be degenerative. The evidence in support of the degenerative hypothesis is presented.

Differentiation of Parkinson’s disease tremor and essential tremor based on a novel hand posture

Background

Tremor is one of the most common movement disorders but the correct diagnosis of tremor disorders, especially the differentiation between Parkinson’s disease tremor (PT) and essential tremor (ET) remains a challenge for clinicians.

Method

We examined a novel hand position to distinguish PT from ET. We prospectively collected accelerometric tremor data in 14 ET patients and 14 PT patients with arms and hands fully stretched against arms stretched and hands relaxed, i. e. hanging down. The total acceleration from the three pairwise-perpendicular accelerometric axes during the 1-minute blocks of the two hand positions were computed and high-passed filtered at 2 Hz. The power spectral density during each hand position was calculated and summed up over the frequency domain.

Results

Our results showed a significantly higher occurrence of tremor in the hands hanging down position in PT patients compared to ET patients (p = 0.0262). Moreover, in PT patients the tremor intensity significantly increased when transitioning from the stretched hand position to the hanging-down position (83 % of cohort) and vice versa in ET patients (75 % of cohort).

Conclusion

In conclusion, the new hand posture can differentiate between PT and ET with high accuracy (sensitivity 83 %, specificity 75 % for PT) and may be a helpful tool in the clinical assessment of tremor.

Morphological and morphometric changes in the Purkinje cells of patients with essential tremor

Essential tremor (ET) is a progressive neurological syndrome characterised by involuntary tremors of the hands or arms, head, jaw and voice. The pathophysiology of ET is not clearly understood yet. However, previous studies have reported several changes in the brain of patients with ET. One of the brain areas extensively investigated is the cerebellum. In the present study, a morphometric analysis of Purkinje cells in patients with ET and ET-plus was performed, and subsequently compared with normal controls using the Golgi silver staining method and 3D neuronal reconstruction. Substantial morphological changes were uncovered in the Purkinje cells of patients with ET compared with normal controls, including a decreased dendritic length and field density, an overall loss of terminal branches and a decreased density of dendritic spines.

Discrimination between parkinsonian tremor and essential tremor using artificial neural network with hybrid features

BACKGROUND

Essential tremor (ET) and the tremor in Parkinson's disease (PD) are the two most common pathological tremors with a certain overlap in the clinical presentation.

OBJECTIVE

The main purpose of this work is to use an artificial neural network to select the best features and to discriminate between the two types of tremors. The features used are of hybrid type obtained from two different algorithms: the statistical signal characterization (SSC) of the signal describing its morphology, and the soft-decision wavelet-decomposition (SDWD) features extracted from the accelerometer and surface EMG signals.

METHODS

The SSC method is used to obtain morphology-based features of the spectrum of the accelerometer and two surface EMG signals. The SDWD technique is used in this work to obtain the approximate spectral representation of both accelerometer and the two surface EMG signals. Two sets of data (training and test) are used in this paper. The training set consists of 21 ET subjects and 19 PD subjects, while the test set consists of 20 ET and 20 PD subjects. A neural network of the type feed forward back propagation has been used to combine best SSC features and best SDWD features of the accelerometer and EMG signals.

RESULTS

Efficiency result of 92.5% was obtained using best hybrid features.

CONCLUSIONS

The artificial neural network has been used successfully to combine two types of features in an automatic discrimination system between PD and ET.

Parkinsonism and tremor syndromes

Tremor, the most common movement disorder, may occur in isolation or may co-exist with a variety of other neurologic and movement disorders including parkinsonism, dystonia, and ataxia. When associated with Parkinson's disease, tremor may be present at rest or as an action tremor overlapping in phenomenology with essential tremor. Essential tremor may be associated not only with parkinsonism but other neurological disorders, suggesting the possibility of essential tremor subtypes. Besides Parkinson's disease, tremor can be an important feature of other parkinsonian disorders, such as atypical parkinsonism and drug-induced parkinsonism. In addition, tremor can be a prominent feature in patients with other movement disorders such as fragile X-associated tremor/ataxia syndrome, and Wilson's disease in which parkinsonian features may be present. This article is part of the Special Issue "Parkinsonism across the spectrum of movement disorders and beyond" edited by Joseph Jankovic, Daniel D. Truong and Matteo Bologna.

Tremor-Suppression Orthoses for the Upper Limb: Current Developments and Future Challenges

Introduction: Pathological tremor is the most common motor disorder in adults and characterized by involuntary, rhythmic muscular contraction leading to shaking movements in one or more parts of the body. Functional Electrical Stimulation (FES) and biomechanical loading using wearable orthoses have emerged as effective and non-invasive methods for tremor suppression. A variety of upper-limb orthoses for tremor suppression have been introduced; however, a systematic review of the mechanical design, algorithms for tremor extraction, and the experimental design is still missing.

Methods: To address this gap, we applied a standard systematic review methodology to conduct a literature search in the PubMed and PMC databases. Inclusion criteria and full-text access eligibility were used to filter the studies from the search results. Subsequently, we extracted relevant information, such as suppression mechanism, system weights, degrees of freedom (DOF), algorithms for tremor estimation, experimental settings, and the efficacy.

Results: The results show that the majority of tremor-suppression orthoses are active with 47% prevalence. Active orthoses are also the heaviest with an average weight of 561 ± 467 g, followed by semi-active 486 ± 395 g, and passive orthoses 191 ± 137 g. Most of the orthoses only support one DOF (54.5%). Two-DOF and three-DOF orthoses account for 33 and 18%, respectively. The average efficacy of tremor suppression using wearable orthoses is 83 ± 13%. Active orthoses are the most efficient with an average efficacy of 83 ± 8%, following by the semi-active 77 ± 19%, and passive orthoses 75 ± 12%. Among different experimental setups, bench testing shows the highest efficacy at 95 ± 5%, this value dropped to 86 ± 8% when evaluating with tremor-affected subjects. The majority of the orthoses (92%) measured voluntary and/or tremorous motions using biomechanical sensors (e.g., IMU, force sensor). Only one system was found to utilize EMG for tremor extraction.

Conclusions: Our review showed an improvement in efficacy of using robotic orthoses in tremor suppression. However, significant challenges for the translations of these systems into clinical or home use remain unsolved. Future challenges include improving the wearability of the orthoses (e.g., lightweight, aesthetic, and soft structure), and user control interfaces (i.e., neural machine interface). We also suggest addressing non-technical challenges (e.g., regulatory compliance, insurance reimbursement) to make the technology more accessible.

A Study on the Essential and Parkinson’s Arm Tremor Classification

In this article, the challenge of discriminating between essential and Parkinson’s tremor is addressed. Although a variety of methods have been proposed for diagnosing the severity of these highly occurring tremor types, their rapid and effective identification, especially in their early stages, proves particularly difficult and complicated due to their wide range of causes and similarity of symptoms. To this goal, a clinical analysis was performed, where a number of volunteers including essential and Parkinson’s tremor-diagnosed patients underwent a series of pre-defined motion patterns, during which a wearable sensing setup was used to measure their lower arm tremor characteristics from multiple selected points. Extracted features from the acquired accelerometer signals were used to train classification algorithms, including decision trees, discriminant analysis, support vector machine (SVM), K-nearest neighbor (KNN) and ensemble learning algorithms, for providing a comparative study and evaluating the potential of utilizing machine learning to accurately discriminate among different tremor types. Overall, SVM related classifiers proved to be the most successful in terms of classifying between Parkinson’s, essential and no tremor diagnosed with percentages reaching up to 100% for a single accelerometer measurement at the metacarpal area. In general and in motion while holding an object position, Coarse Gaussian SVM classifier reached 82.62% accuracy.

Valproate-induced rest tremor and parkinsonism

Tremor and parkinsonism are recognized side effects of valproate; however, the relationship between rest tremor and other signs of parkinsonism has not been addressed in patients taking valproate. We studied a cohort of 125 consecutive patients treated with valproate due to epilepsy or migraine, evaluated with the Fahn-Tolosa-Marin Tremor Rating Scale (FTM-TRS). A total of 14 (11.2%) patients had rest tremor (bilateral n = 10, unilateral n = 4). Patients with rest tremor had significant higher scores in the FTM-TRS (P < 0.001), but only one was diagnosed with parkinsonism. Patients may have valproate-induced parkinsonism or exacerbated motor features of Parkinson's disease by valproate. The frequency of parkinsonism was 1.6% in this cohort and of 3% in the pooled data of 717 patients from previous reports. Rest tremor is observed in 11.2% of patients treated with valproate and is related to the burden of valproate-induced tremor, rather than the presence of parkinsonism.

The Essential Tremors: Evolving Concepts of a Family of Diseases

The past 10 years has seen a remarkable advance in our understanding of the disease traditionally referred to as “essential tremor” (ET). First, the clinical phenotype of ET has been expanded from that of a bland, unidimensional, and monosymptomatic entity to one with a host of heterogeneous features. These features include a broader and more nuanced collection of tremors, non-tremor motor features (e.g., gait abnormalities) and a range of non-motor features, including cognitive, psychiatric, sleep, and other abnormalities. The natural history of these features, as well as their relationships with one another and with disease duration and severity, are better appreciated than they were previously. Studies of disease etiology have identified a number of candidate genes as well as explored several environmental determinants of disease. In addition, the decade has seen the beginnings and expansion of rigorous postmortem studies that have identified and described the postmortem changes in the brains of patients with ET. This emerging science has given rise to a new notion that the disease, in many cases, is one of cerebellar system degeneration. Across all of these studies (clinical, etiological, and pathophysiological) is the observation that there is heterogeneity across patients and that “essential tremor” is likely not a single disease but, rather, a family of diseases. The time has come to use the more appropriate terminology, “the essential tremors,” to fully describe and encapsulate what is now apparent. In this paper, the author will review the clinical, etiological, and pathophysiological findings, referred to above, and make the argument that the terminology should evolve to reflect advances in science and that “the essential tremors” is a more scientifically appropriate term.

A Phase 2 Proof-of-Concept, Randomized, Placebo-Controlled Trial of CX-8998 in Essential Tremor

Background

Available essential tremor (ET) therapies have limitations.

Objectives

The objective of this study was to evaluate CX‐8998, a selective T‐type calcium channel modulator, in essential tremor.

Methods

Patients 18–75 years old with moderate to severe essential tremor were randomized 1:1 to receive CX‐8998 (titrated to 10 mg twice daily) or placebo. The primary end point was change from baseline to day 28 in The Essential Tremor Rating Assessment Scale performance subscale scored by independent blinded video raters. Secondary outcomes included in‐person blinded investigator rating of The Essential Tremor Rating Assessment Scale performance subscale, The Essential Tremor Rating Assessment Scale activities of daily living subscale, and Kinesia ONE accelerometry.

Results

The video‐rated The Essential Tremor Rating Assessment Scale performance subscale was not different for CX‐8998 (n = 39) versus placebo (n = 44; P = 0.696). CX‐8998 improved investigator‐rated The Essential Tremor Rating Assessment Scale performance subscale (P = 0.017) and The Essential Tremor Rating Assessment Scale activities of daily living (P = 0.049) but not Kinesia ONE (P = 0.421). Adverse events with CX‐8998 included dizziness (21%), headache (8%), euphoric mood (6%), and insomnia (6%).

Conclusions

The primary efficacy end point was not met; however, CX‐8998 improved some assessments of essential tremor, supporting further clinical investigation. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Patterns of intrinsic brain activity in essential tremor with resting tremor and tremor-dominant Parkinson's disease

The clinical pictures of essential tremor (ET) with resting tremor (rET) and tremor-dominant Parkinson's disease (tPD) are often quite mimic at the early stage, current approaches to the diagnosis and treatment therefore remain challenging. The regional homogeneity (ReHo) method under resting-state functional magnetic resonance imaging (rs-fMRI) would help exhibit the patterns in neural activity, which further contribute to differentiate these disorders and explore the relationship between symptoms and regional functional abnormalities. Sixty-eight Chinese participants were recruited, including 19 rET patients, 24 tPD patients and 25 age- and gender-matched healthy controls (HCs). All participants underwent clinical assessment and rs-fMRI with a ReHo method to investigate the alterations of neural activity, and the correlation between them. Differences were compared by two-sample t-test (corrected with AlphaSim, p < 0.05). Compared with HCs, patients' groups both displayed decreased ReHo in the default mode network (DMN), bilateral putamen and bilateral cerebellum. While tPD patients specifically exihibited decreased ReHo in the bilateral supplementary motor area (SMA) and precentral gyrus (M1). The correlation analysis revealed that ReHo in the bilateral putamen, right SMA and left cerebellum_crus I were negatively correlated with the UPDRS-III score, respectively, in tPD group. Our results indicated the rET patients may share part of the pathophysiological mechanism of tPD patients. In addition, we found disorder-specific involvement of the SMA and M1 in tPD. Such a distinction may lend itself to use as a potential biomarker for differentiating between these two diseases.

A Voxel-Wise Meta-Analysis on the Cerebellum in Essential Tremor

Background and Objectives: Essential tremor is a chronic progressive neurological condition. The clinical presentation of essential tremor is heterogeneous and includes involuntary tremor on hands or arms and progressively on head, jaw, and voice. More extensive and complex symptoms may also be noticed in several patients. Many studies have been carried out to identify biomarkers to help the diagnosis, however, all the efforts have not shown any substantial results yet. Materials and Methods: Here, we aimed to perform a voxel-based meta-analysis using a dedicated cerebellar mask to clarify whether the results from the previous studies are robust and have any clinical significance. We included studies with a total of 377 essential tremor patients and 338 healthy control individuals. Results: A significant regional decrease in the volume of the gray matter was detected in the right cerebellar hemispheric lobule IV/V, and in the cerebellar vermic lobule IV/V. Conclusions: This is the first study focused on the cerebellum and using a specific cerebellar mask, which increases the sensitivity. It showed regional statistically significant changes that could not be seen in the whole-brain analysis.

Non-motor symptoms in essential tremor, akinetic rigid and tremor-dominant subtypes of Parkinson's disease

Objectives

To compare non-motor symptoms (NMSs) among patients with essential tremor (ET), Parkinson’s disease (PD) subtypes (akinetic-rigid type (ART) and tremor-dominant type (TDT)), and healthy controls.

Patients and methods

This retrospective study included 129 participants, 72 PD (33 PD-ART, 33 PD-TDT, and 6 Mixed), 29 ET patients, and 28 controls. PD patients were assessed by the unified Parkinson’s disease rating scale (UPDRS), Hoehn, and Yahr scale (H&Y), while ET patients were evaluated by the Fahn Tolosa Marin Tremor Rating Scale. All subjects were evaluated by non-motor symptoms scale (NMSS) for NMSs and Beck depression inventory (BDI) for depression.

Results

PD subtypes groups, ET, and controls were age and gender-matched. Compared to controls, all PD, PD subtypes, and ET showed significantly worse most of NMSs (p<0.001) and depression. Compared to ET, all PD and PD-ART had significantly worse gastrointestinal (p = 0.002), urinary symptoms (p = 0.001, p = 0.003) and depression (p = 0.002) and PD-TDT worse depression, while ET patients showed worse memory/attention than PD subtypes. Total NMSS of ET is highly correlated to depression and moderately to tremor severity and age of onset, while total of NMSS is highly correlated to depression, disease severity, and disability.

Conclusion

The current study demonstrated several comparable domains of NMSs of PD subtypes and ET, except worse gastrointestinal and urinary symptoms among PD-ART. Identifying different NMSs profiles is important for predicting, better assessing, and tailoring management of ET and PD subtypes.

Clinical Characteristics and Electrophysiological Biomarkers of Parkinson's Disease Developed From Essential Tremor

Background and Objective: Parkinson's disease developed from essential tremor (ET-PD) is a distinct clinical syndrome that is different from essential tremor (ET) and Parkinson's disease (PD). There is currently a lack of research on ET-PD. Tremor characteristics (amplitude and frequency) are primary quantitative indexes for diagnosing and monitoring of tremors. In this study, we aimed to explore specific clinical and electrophysiological biomarkers for the identification of ET-PD. Methods: The study included patients with ET-PD (n = 22), ET (n = 42), and tremor-dominant PD (t-PD, n = 47). We collected demographic data, clinical characteristics (including motor and non-motor symptoms), and tremor analysis. The frequency, amplitude, contracting patterns of resting tremor and postural tremor were collected. The analysis of ET-PD and ET/t-PD was compared. The receiver operating characteristic (ROC) curve was used to analyze the electrophysiological features in distinguishing ET-PD from ET or t-PD. Results: Compared with ET, hyposmia, bradykinesia, rigidity, postural abnormality, and resting tremor were more common in the ET-PD group (P = 0.01, 0.003, 0.001, 0.001, 0.019, respectively). The postural tremor frequencies of the head, upper limbs, and lower limbs were significantly lower in the ET-PD than in the ET (P = 0.007, 0.003, 0.035, respectively), which were the most appropriate variables for distinguishing ET-PD from ET (AUC: 0.775, 0.727, and 0.701, respectively). Compared with t-PD, bradykinesia, rigidity, postural abnormality (both P < 0.001), and resting tremor (P = 0.024) were less common in the ET-PD. The postural tremor amplitudes of the head and upper limbs were significantly higher in the ET-PD than in the t-PD (P = 0.022, 0.001, respectively), which were the most appropriate variables for distinguishing ET-PD from t-PD (AUC: 0.793 and 0.716). Conclusions: Hyposmia and electrophysiological biomarkers (postural tremor frequencies and amplitudes) help early recognition of ET-PD.

Multi-Dimensional, Short-Timescale Quantification of Parkinson's Disease and Essential Tremor Motor Dysfunction

Introduction: Parkinson's disease (PD) is a progressive movement disorder characterized by heterogenous motor dysfunction with fluctuations in severity. Objective, short-timescale characterization of this dysfunction is necessary as therapies become increasingly adaptive.

Objectives: This study aims to characterize a novel, naturalistic, and goal-directed tablet-based task and complementary analysis protocol designed to characterize the motor features of PD.

Methods: A total of 26 patients with PD and without deep brain stimulation (DBS), 20 control subjects, and eight patients with PD and with DBS completed the task. Eight metrics, each designed to capture an aspect of motor dysfunction in PD, were calculated from 1-second, non-overlapping epochs of the raw positional and pressure data captured during task completion. These metrics were used to generate a classifier using a support vector machine (SVM) model to produce a unifying, scalar “motor error score” (MES). The data generated from these patients with PD were compared to same-day standard clinical assessments. Additionally, these data were compared to analogous data generated from a separate group of 12 patients with essential tremor (ET) to assess the task's specificity for different movement disorders. Finally, an SVM model was generated for each of the eight patients with PD and with DBS to differentiate between their motor dysfunction in the “DBS On” and “DBS Off” stimulation states.

Results: The eight metrics calculated from the raw positional and force data captured during task completion were non-redundant. MES generated by the SVM analysis protocol showed a strong correlation with MDS-UPDRS-III scores assigned by movement disorder specialists. Analysis of the relative contributions of each of the eight metrics showed a significant difference between the motor dysfunction of PD and ET. Much of this difference was attributable to the homogenous, tremor-dominant phenotype of ET motor dysfunction. Finally, in individual patients with PD with DBS, task performance and subsequent SVM classification effectively differentiated between the “DBS On” and “DBS Off” stimulation states.

Conclusion: This tablet-based task and analysis protocol correlated strongly with expert clinical assessments of PD motor dysfunction. Additionally, the task showed specificity for PD when compared to ET, another common movement disorder. This specificity was driven by the relative heterogeneity of motor dysfunction of PD compared to ET. Finally, the task was able to distinguish between the “DBS On” and “DBS Off” states within single patients with PD. This task provides temporally-precise and specific information about motor dysfunction in at least two movement disorders that could feasibly correlate to neural activity.

Discrimination of physiological tremor from pathological tremor using accelerometer and surface EMG signals

BACKGROUND AND OBJECTIVE: Although careful clinical examination and medical history are the most important steps towards a diagnostic separation between different tremors, the electro-physiological analysis of the tremor using accelerometry and electromyography (EMG) of the affected limbs are promising tools. METHODS: A soft-decision wavelet-based decomposition technique is applied with 8 decomposition stages to estimate the power spectral density of accelerometer and surface EMG signals (sEMG) sampled at 800 Hz. A discrimination factor between physiological tremor (PH) and pathological tremor, namely, essential tremor (ET) and the tremor caused by Parkinson’s disease (PD), is obtained by summing the power entropy in band 6 (B6: 7.8125–9.375 Hz) and band 11 (B11: 15.625–17.1875 Hz). RESULTS: A discrimination accuracy of 93.87% is obtained between the PH group and the ET & PD group using a voting between three results obtained from the accelerometer signal and two sEMG signals. CONCLUSION: Biomedical signal processing techniques based on high resolution wavelet spectral analysis of accelerometer and sEMG signals are implemented to efficiently perform classification between physiological tremor and pathological tremor.

Prodromal Markers of Parkinson's Disease in Patients With Essential Tremor

Background: Essential tremor (ET) is manifested as an isolated syndrome of bilateral upper limb action tremor. Parkinson's disease (PD) is the second most common neurodegenerative disease, with typical motor symptoms of bradykinesia, rigidity, and resting tremor. ET-PD describes the new-onset of PD in ET patients. Recently, numerous studies on epidemiology, genetics, pathology, clinical features, and neuroimaging studies are challenging the idea that ET is an isolated disease, suggesting that patients with ET have the tendency to develop PD. Methods: In this review article, we collected recent findings that reveal prodromal markers of PD in patients with ET. Results: Substantia nigra hyperechogenicity serves as a prodromal marker for predicting the development of PD in patients with ET and provides a reference for therapeutic strategies. Additional potential markers include other neuroimaging, clinical features, heart rate, and genetics, whereas others lack sufficient evidence. Conclusion: In consideration of the limited research of PD in patients with ET, we are still far from revealing the prodromal markers. However, from the existing follow-up studies on ET patients, Substantia nigra hyperechogenicity may enable further exploration of the relationship between ET and PD and the search for pathogenesis-based therapies.

Tremor analysis with wearable sensors correlates with outcome after thalamic deep brain stimulation

INTRODUCTION

Thalamic deep brain stimulation (DBS) provides excellent tremor control in most patients with essential tremor (ET). However, not all tremor patients show clinically significant improvement after DBS surgery. Currently, there is no reliable clinical or instrument-based measure to predict how patients respond to DBS. Therefore, we set out to provide a method for tremor outcome prediction prior to surgery.

METHODS

We retrospectively analysed quantitative tremor data collected with inertial measurement units (IMU) in 13 patients who underwent DBS surgery in the ventral intermediate nucleus of the thalamus (VIM). All patients were diagnosed with either ET or ET-plus according to current diagnostic criteria of the movement disorder society. We used linear and logistic regression models to evaluate the influence of different tremor characteristics on tremor outcome.

RESULTS

We found that the ratio between the amplitude of the first overtone and the amplitude of the fundamental frequency, denoted as the Harmonic Index, has a significant influence on tremor reduction after DBS surgery. This measure shows a strong correlation with the post-operative improvement of tremor outcome based on the Whiget Tremor Rating Scale.

CONCLUSION

Based on these findings, we propose a novel approach to predict tremor outcome after DBS surgery. Quantitative tremor assessment adds to the preoperative prediction of DBS response and might therefore have a relevant clinical impact in the management of patients suffering from pharmacoresistant tremor.

Systematic clinical approach for diagnosing upper limb tremor

Tremor is the most common movement disorder worldwide, but diagnosis is challenging. In 2018, the task force on tremor of the International Parkinson and Movement Disorder Society published a consensus statement that proposes a tremor classification along two independent axes: a clinical tremor syndrome and its underlying aetiology. In line with this statement, we here propose a stepwise diagnostic approach that leads to the correct clinical and aetiological classification of upper limb tremor. We also describe the typical clinical signs of each clinical tremor syndrome. A key feature of our algorithm is the distinction between isolated and combined tremor syndromes, in which tremor is accompanied by bradykinesia, cerebellar signs, dystonia, peripheral neuropathy or brainstem signs. This distinction subsequently informs the selection of appropriate diagnostic tests, such as neurophysiology, laboratory testing, structural and dopaminergic imaging and genetic testing. We highlight treatable metabolic causes of tremor, as well as drugs and toxins that can provoke tremor. The stepwise approach facilitates appropriate diagnostic testing and avoids unnecessary investigations. We expect that the approach offered in this article will reduce diagnostic uncertainty and increase the diagnostic yield in patients with tremor.

Altered spontaneous brain activity in essential tremor with and without resting tremor: a resting-state fMRI study

OBJECTIVES

Essential tremor with resting tremor (rET) often exhibits severer clinical features and more extensive functional impairment than essential tremor without resting tremor (ETwr). However, the pathophysiology of rET is still unclear. This study aims to use resting-state functional magnetic resonance imaging (rs-fMRI) to explore the alterations of brain activity between the drug-naïve patients of rET and ETwr.

METHODS

We recruited 19 patients with rET, 31 patients with ETwr and 25 healthy controls (HCs) to undergo a 3.0-T rs-fMRI examination. The differences of regional brain spontaneous activity between the rET, ETwr and HCs, as well as between total ET (rET + ETwr) and HCs were measured by amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). The relationships between the altered brain measurements and the clinical scores were analyzed.

RESULTS

Compared with HCs, both ET subgroups showed significantly decreased ALFF or fALFF values in the basal ganglia, inferior orbitofrontal gyrus and insula. The rET group specifically showed decreased ALFF values in the hippocampus and motor cortices, while the ETwr group specifically evidenced increased ALFF and fALFF values in the cerebellum.

DISCUSSION

Regional spontaneous activity in rET and ETwr share common changes and have differences, which may suggest that the functional activities in the limbic system and cerebellum are different between the two subtypes. Improved insights into rET and ETwr subtypes and the different brain spontaneous activity will be valuable for improving our understanding of the pathophysiology of the disease.

Rest tremor in dystonia: epidemiology, differential diagnosis, and pathophysiology

BACKGROUND

The most common type of tremor reported in dystonia patients is postural and kinetic. There is uncertainty regarding the prevalence of rest tremor in dystonia.

OBJECTIVE

This review focuses on the clinical and neurophysiological features of rest tremor in dystonia, its differential diagnosis, and methods to distinguish it from other rest tremor syndromes.

METHODS

A PubMed search was done, and the available literature identified. Bibliography of the available literature was reviewed for relevant references.

RESULTS

Rest tremor in dystonia has been reported with a variable frequency of 1.81-12.05%. The most common body distribution is arm, and it tends to be asymmetric. Most of the affected patients have multifocal and segmental dystonia. Rest tremor is a late-onset phenomenon associated with severe and spreading dystonia. Clinically, it is difficult to distinguish rest tremor in dystonia from other rest tremor syndromes based on tremor characteristics; however, other neurological signs can provide clues to differentiate these syndromes. Surface electromyography and other neurophysiological tests can help differentiate the various rest tremor syndromes.

CONCLUSION

Rest tremor in dystonia can be differentiated from other rest tremor syndromes based on neurophysiological techniques. There is some evidence to suggest that SWEDDs could be a form of dystonic tremor, but further studies are required to clarify this diagnostic dilemma. Data regarding the treatment of rest tremor in dystonia are virtually nonexistent, and there is an urgent need for prospective studies focusing its medical management and to know the surgical targets.

Essential tremor: New advances

Background

Essential Tremor (ET) is one of the most common movement disorders but many controversies still exist in regards to its definition and pathophysiology. In view of the recent published criteria by the Tremor Task Force of the International Parkinson's and Movement Disorders Society (IPMDS), we intended to analyze if this has changed our view of ET and if new developments have arisen since.

Methods

A Medline search for English-written articles was done on June 15, 2019 using the keyword "Essential Tremor". Publications from November 2017 (publication date of the new tremor classification) were taken into account. Reviews, letters and original studies relevant to the subject were selected and reviewed according to the following themes: clinical characteristics, epidemiology, genetics, pathology, biomarkers and treatment.

Results

Out of 132 publications the most relevant articles were selected and reviewed (total of 65 articles). The great majority of these studies focused on surgical treatments (new targets, new technologies) while relatively few articles addressed epidemiology, pathology and pathophysiology.

Conclusions

The use of the new classification is not commonly used still, excepting more recent studies on therapeutics. This is in keeping with diverse opinions and criticisms reported by the IPMDS task force members themselves. One important change has been validating ET as a heterogeneous condition and defining the ET-plus category. We propose a further sub-group classification derived from the new definition of ET-plus.

Revisiting the Clinical Phenomenology of "Cerebellar Tremor": Beyond the Intention Tremor

Tremor is an involuntary, rhythmic, oscillatory movement of a body part. It is a central feature of a range of diseases resulting from pathological changes in the cerebellum. Interestingly, in modern times, the terms "cerebellar tremor" and "intention tremor" are often used synonymously and interchangeably. However, "cerebellar tremor" (i.e., tremors of cerebellar origin) do not always present exclusively as intention tremor. In this article, we comprehensively revisit the clinical phenomenology of tremors observed in various diseases that are based in the cerebellum. By this, we mean diseases for which the cerebellum and its various connections are often seen as playing a central and defining role. These include spinocerebellar ataxias, essential tremor, orthostatic tremor, dystonia, acute cerebellitis, cerebellar tumors, paraneoplastic cerebellar degeneration, and cerebellar strokes. The theme of this article is to highlight, through published data available in the current literature, that the clinical phenomenology of tremor of cerebellar origin is heterogeneous, and it extends beyond that of intention tremor to include postural tremors, kinetic tremor, rest tremor, and orthostatic tremor. This heterogeneity is consistent with the seminal work of Gordon Holmes, in which he described a variety of tremors aside from intention tremor in the setting of cerebellar lesions. In the end, it would seem that the notion that intention tremor is the sole signature of cerebellar lesions is an over-simplification and is not correct. Future studies are warranted to identify and further characterize the heterogeneity of tremors arising from the various cerebellar etiologies.

Effects of ventral intermediate nucleus deep brain stimulation across multiple effectors in essential tremor

OBJECTIVE

Essential tremor (ET) prominently affects the upper-limbs during voluntary movements, but can also affect the lower-limbs, head, and chin. Although deep brain stimulation (DBS) of the ventral intermediate nucleus (VIM) of thalamus improves both clinical ratings and quantitative measures of tremor, no study has quantified effects of DBS on tremor across multiple body parts. Our objective was to quantify therapeutic effects of DBS across multiple body parts in ET.

METHODS

We performed quantitative assessment of tremor in ET patients who had DBS for at least one year. We assessed tremor on and off VIM-stimulation using triaxial accelerometers on the upper-limbs, lower-limbs, head and chin during seated and standing tasks.

RESULTS

VIM-DBS significantly reduced tremor, but there was no statistical difference in degree of tremor reduction across the measured effectors. Compared to healthy controls, ET patients treated with DBS showed significantly greater tremor power (4-8 Hz) across all effectors during seated and standing tasks.

CONCLUSIONS

VIM-DBS reduced tremor in ET patients. There was no significant difference in the degree of tremor reduction across the measured effectors.

SIGNIFICANCE

This study provides new quantitative evidence that VIM-DBS is effective at reducing tremor across multiple parts of the body.

A Power Spectral Density-Based Method to Detect Tremor and Tremor Intermittency in Movement Disorders

There is no objective gold standard to detect tremors. This concerns not only the choice of the algorithm and sensors, but methods are often designed to detect tremors in one specific group of patients during the performance of a specific task. Therefore, the aim of this study is twofold. First, an objective quantitative method to detect tremor windows (TWs) in accelerometer and electromyography recordings is introduced. Second, the tremor stability index (TSI) is determined to indicate the advantage of detecting TWs prior to analysis. Ten Parkinson’s disease (PD) patients, ten essential tremor (ET) patients, and ten healthy controls (HC) performed a resting, postural and movement task. Data was split into 3-s windows, and the power spectral density was calculated for each window. The relative power around the peak frequency with respect to the power in the tremor band was used to classify the windows as either tremor or non-tremor. The method yielded a specificity of 96.45%, sensitivity of 84.84%, and accuracy of 90.80% of tremor detection. During tremors, significant differences were found between groups in all three parameters. The results suggest that the introduced method could be used to determine under which conditions and to which extent undiagnosed patients exhibit tremors.

Population-scale hand tremor analysis via anonymized mouse cursor signals

Tremors are a common movement disorder with a spectrum of benign and pathological causes, including neurodegenerative disease, alcohol withdrawal, and physical overexertion. Studies of tremors in clinical practice are limited in size and scope and depend on explicit tracking of tremor characteristics by clinicians. Data drawn from small numbers of patients observed in short-duration sessions pose challenges for understanding the nature and distribution of tremors over a large population. Methods are presented to estimate hand tremors based on anonymized computer mouse cursor movement data collected from millions of users of a web search engine. To determine the feasibility of using this signal for the estimation of the prevalence of tremors over a large population, the characteristics of tremor-like movements are computed and compared against user data that can be interpreted as self-reports, the findings of published clinical studies, and a target selection study where participants self-report hand tremors and known causes. The results demonstrate significant alignment between estimated tremors and both self-reports and clinical findings. Those with cursor tremor events are more likely to report tremor-related search interests. Variations in cursor tremor quantity and cursor tremor frequency with demographics mirror those from clinical studies. Distributions of cursor tremor frequencies vary as expected for different medical conditions. Overall, the study finds evidence for the validity of harnessing anonymized mouse cursor motion as a population-scale tremor sensor for epidemiologic studies. Feasible future applications include opt-in services for screening and for monitoring the progression of illness.

Need for mechanically and ergonomically enhanced tremor-suppression orthoses for the upper limb: a systematic review

INTRODUCTION

Tremor is the most common movement disorder, affecting 5.6% of the population with Parkinson's disease or essential tremor over the age of 65. Conventionally, tremor diseases like Parkinson's are treated with medication. An alternative non-invasive symptom treatment is the mechanical suppression of the oscillation movement. The purpose of this review is to identify the weaknesses of past wearable tremor-suppression orthoses for the upper limb and identify the need for further research and developments.

METHOD

A systematic literature search was conducted by performing a keyword combination search of the title, abstract and keyword sections in the four databases Web of Science, MedLine, Scopus, and ProQuest. Initially, the retrieved articles were selected by title and abstract using selection criteria. The same criteria were then applied to the full publication text. After the selection process, relevant information on the retrieved orthoses was isolated, sorted and analysed systematically.

RESULTS

Forty-six papers, representing 21 orthoses, were identified and analysed according to the mechanical and ergonomic properties. The identified orthoses can be divided into 5 concepts and 16 functional prototypes, then subdivided further based upon their use of passive, semi-active, or active suppression mechanisms. Most of the orthoses concentrate on the wrist and elbow flexion and extension. They mainly rely on rigid structures and actuators while having tremor-suppression efficacies for tremorous subjects from 30 to 98% using power spectral density or other methods.

CONCLUSION

The comparison of tremor-suppression orthoses considered and mapped their various mechanical and ergonomic properties, including the degrees of freedom, weight, suppression characteristics, and efficacies. This review shows that most of the orthoses are bulky and heavy, with a non-adapted human-machine interface which can cause rejection by the user. The main challenge of the design of an effective, minimally intrusive and portable tremor-suppressing orthosis is the integration of compact, powerful, lightweight, and non-cumbersome suppression mechanisms. None of the existing prototypes combine all the desired characteristics. Future research should focus on novel suppression orthoses and mechanisms with compact dimensions and light weight in order to be less cumbersome while giving a good tremor-suppression performance.

Essential tremor: a nuanced approach to the clinical features

Click here to listen to the Podcast Essential tremor is the most common form of tremor in humans. Given neurologists' high exposure to this condition, and its seemingly straightforward phenotype, it might seem easy to diagnose. However, 30%-50 % of patients labelled as having 'essential tremor' have other diagnoses, mostly Parkinson's disease and dystonia. The tremor of essential tremor is neither non-descript nor featureless but is multifaceted and highly patterned. This review focuses on its clinical features, beginning with a discussion of tremors and then briefly discussing its additional motor features, and presents several aids to help distinguish essential tremor from Parkinson's disease and dystonia. Careful attention to certain clinical nuances will aid the diagnosis and care of patients with essential tremor.

A Phase 2, Randomized, Double-Blind, Placebo-Controlled Trial of CX-8998, a Selective Modulator of the T-Type Calcium Channel in Inadequately Treated Moderate to Severe Essential Tremor: T-CALM Study Design and Methodology for Efficacy Endpoint and Digital Biomarker Selection

Background: Essential tremor (ET) is a common, progressive neurological syndrome with bilateral upper-limb dysfunction of at least 3-year duration, with or without tremor in other body locations. This disorder has a negative impact on daily function and quality of life. A single oral therapy has been approved by FDA for ET. Off-label pharmacotherapies have inadequate efficacy and poor tolerability with high rates of patient dissatisfaction and discontinuation. Safe and efficacious pharmacotherapies are urgently needed to decrease tremor and improve daily living. T-CALM (Tremor-CAv3 modulation) protocol is designed to assess safety and efficacy of CX-8998, a selective modulator of the T-type calcium channel, for ET therapy.

Methods/Design: T-CALM is a phase 2, proof of concept, randomized, double-blind, placebo-controlled trial. Titrated doses of CX-8998 to 10 mg BID or placebo will be administered for 28 days to moderate to severe ET patients who are inadequately treated with existing therapies. The primary endpoint will be change from baseline to day 28 of The Essential Tremor Rating Assessment Performance Subscale (TETRAS-PS). Secondary efficacy endpoints for clinician and patient perception of daily function will include TETRAS Activity of Daily Living (ADL), Quality of Life in Essential Tremor Questionnaire (QUEST), Clinical Global Impression-Improvement (CGI-I), Patient Global Impression of Change (PGIC), and Goal Attainment Scale (GAS). Kinesia One, Kinesia 360, and iMotor will biometrically evaluate motor function and tremor amplitude. Safety will be assessed by adverse events, physical and neurological exams and laboratory tests. Sample size of 43 patients per group is estimated to have 90% power to detect a 5.5-point difference between CX-8998 and placebo for TETRAS-PS. Efficacy analyses will be performed with covariance (ANCOVA) and 2-sided test at 0.05 significance level.

Discussion: T-CALM has a unique design with physician rating scales, patient-focused questionnaires and scales and objective motor measurements to assess clinically meaningful and congruent efficacy. Patient perception of ET debilitation and therapy with CX-8998 will be key findings. Overall goal of T-CALM is generation of safety and efficacy data to support a go, no-go decision to further develop CX-8998 for ET. Design of T-CALM may guide future clinical studies of ET pharmacotherapies.

Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT03101241

Neuroimaging and neuropathological findings in essential tremor

Essential tremor is a chronic neurological syndrome of heterogenous clinical phenotypes and multiple etiologies. Numerous studies have been done in order to investigate the pathological, neuroimaging, physiological, and clinical features of essential tremor; however, a clear pathophysiological mechanism has not been identified. One of the brain structures has been extensively investigated at the macroscopic and the microscopic level in the cerebellum. In the present study, we aim to discuss the main neuroimaging and neuropathological changes of the cerebellum in essential tremor.