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Essential tremor (ET) is a major cause of disability and is not effectively managed in half of the patients. We investigated whether mechanical vibration could reduce tremor in ET by selectively recruiting afferent pathways. We used piezoelectric actuators to deliver vibratory stimuli to the hand and forearm during long trials (4 min), while we monitored the tremor using inertial sensors. We analyzed the effect of four stimulation strategies, including different constant and variable vibration frequencies, in 18 ET patients. Although there was not a clear homogeneous response to vibration across patients and strategies, in most cases (50-72%) mechanical vibration was associated with an increase in the amplitude of their tremor. In contrast, the tremor was reduced in 5-22% of the patients, depending on the strategy. However, these results are hard to interpret given the intrinsic variability of the tremor: during equally long trials without vibration, the tremor changed significantly in 67% of the patients (increased in 45%; decreased in 22%). We conclude that mechanical vibration of the limb does not have a systematic effect on tremor in ET. Moreover, the observed intrinsic variability of the tremor should be taken into account when designing future experiments to assess tremor in ET and how it responds to any intervention.

Essential tremor (ET) is a neurological disease with both motor and nonmotor manifestations; however, little is known about its underlying brain basis. Furthermore, the overall organization of the brain network in ET remains largely unexplored. We investigated the topological properties of brain functional network, derived from resting-state functional magnetic resonance imaging (MRI) data, in 23 ET patients versus 23 healthy controls. Graph theory analysis was used to assess the functional network organization. At the global level, the functional network of ET patients was characterized by lower small-worldness values than healthy controls-less clustered functionality of the brain. At the regional level, compared with the healthy controls, ET patients showed significantly higher values of global efficiency, cost and degree, and a shorter average path length in the left inferior frontal gyrus (pars opercularis), right inferior temporal gyrus (posterior division and temporo-occipital part), right inferior lateral occipital cortex, left paracingulate, bilateral precuneus bilaterally, left lingual gyrus, right hippocampus, left amygdala, nucleus accumbens bilaterally, and left middle temporal gyrus (posterior part). In addition, ET patients showed significant higher local efficiency and clustering coefficient values in frontal medial cortex bilaterally, subcallosal cortex, posterior cingulate cortex, parahippocampal gyri bilaterally (posterior division), right lingual gyrus, right cerebellar flocculus, right postcentral gyrus, right inferior semilunar lobule of cerebellum and culmen of vermis. Finally, the right intracalcarine cortex and the left orbitofrontal cortex showed a shorter average path length in ET patients, while the left frontal operculum and the right planum polare showed a higher betweenness centrality in ET patients. In conclusion, the efficiency of the overall brain functional network in ET is disrupted. Further, our results support the concept that ET is a disorder that disrupts widespread brain regions, including those outside of the brain regions responsible for tremor., (© 2019 Wiley Periodicals, Inc.)

Objective: Although the cerebello-thalamo-cortical network has often been suggested to be of importance in the pathogenesis of essential tremor (ET), the origins of tremorgenic activity in this disease are not fully understood. We used a combination of cortical thickness imaging and neurophysiological studies to analyze whether the severity of tremor was associated with anatomical changes in the brain in ET patients ., Methods: Magnetic resonance imaging (MRI) and a neurophysiological assessment were performed in 13 nondemented ET patients. High field structural brain MRI images acquired in a 3T scanner and analyses of cortical thickness and surface were carried out. Cortical reconstruction and volumetric segmentation was performed with the FreeSurfer image analysis software. We used high-density surface electromyography (hdEMG) and inertial measurement units (IMUs) to quantify the tremor severity in upper extrimities of patients. In particular, advanced computer tool was used to reliably identify discharge patterns of individual motor units from surface hdEMG and quantify motor unit synchronization., Results: We found significant association between increased motor unit synchronization (i.e., more severe tremor) and cortical changes (i.e., atrophy) in widespread cerebral cortical areas, including the left medial orbitofrontal cortex, left isthmus of the cingulate gyrus, right paracentral lobule, right lingual gyrus, as well as reduced left supramarginal gyrus (inferior parietal cortex), right isthmus of the cingulate gyrus, left thalamus, and left amygdala volumes., Interpretation: Given that most of these brain areas are involved in controlling movement sequencing, ET tremor could be the result of an involuntary activation of a program of motor behavior used in the genesis of voluntary repetitive movements.

Background: The use of wearable technology is an emerging field of research in movement disorders. This paper introduces a clinical study to evaluate the feasibility, clinical correlation and reliability of using a system based in smartwatches to quantify tremor in essential tremor (ET) patients and check its acceptance as clinical monitoring tool., New Method: The system is based on a commercial smartwatch and an Android smartphone. An investigational Android application controls the process of recording raw data from the smartwatch three-dimensional gyroscopes. Thirty-four ET patients were consecutively enrolled in the experiments and assessed along one year. Arm tremor was videofilmed and scored using the Fahn-Tolosa-Marin Tremor Rating Scale (FTM-TRS). Tremor intensity was quantified with the root mean square of angular velocity measured in the patients' wrists., Results: Eighty-two assessments with smartwatches were performed. Spearman's correlation coefficients (ρ) between clinical tremor (FTM-TRS) scores and smartwatch measures for tremor intensity were 0.590 at rest; ρ = 0.738 in steady posture; ρ = 0.189 in finger-to-nose maneuvers; and ρ = 0.652 in pouring water task. Smartwatch reliability was checked by intraclass realiability coefficients: 0.85, 0.95, 0.91, 0.95 respectively. Most of patients showed good acceptance of the system., Comparison With Existing Method(s): This commodity hardware contributes to quantify tremor objectively in a consulting-room by customized Android smart devices as clinical monitoring tool., Conclusions: The NetMD system for tremor analysis is feasible, well-correlated with clinical scores, reliable and well-accepted by patients to tremor follow-up. Therefore, it could be an option to objectively quantify tremor in ET patients during their regular follow-up., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Essential tremor (ET) is one of the most prevalent movement disorders. Being that it is a common disorder, its diagnosis is considered routine. However, misdiagnoses may occur regularly. Over the past decade, several studies have identified brain morphometric changes in ET, but these changes remain poorly understood. Here, we tested the informativeness of measuring cortical thickness for the purposes of ET diagnosis, applying feature selection and machine learning methods to a study sample of 18 patients with ET and 18 age- and sex-matched healthy control subjects. We found that cortical thickness features alone distinguished the two, ET from controls, with 81% diagnostic accuracy. More specifically, roughness (i.e., the standard deviation of cortical thickness) of the right inferior parietal and right fusiform areas was shown to play a key role in ET characterization. Moreover, these features allowed us to identify subgroups of ET patients as well as healthy subjects at risk for ET. Since treatment of tremors is disease specific, accurate and early diagnosis plays an important role in tremor management. Supporting the clinical diagnosis with novel computer approaches based on the objective evaluation of neuroimage data, like the one presented here, may represent a significant step in this direction.

Essential tremor (ET) has been associated with a spectrum of clinical features, with both motor and nonmotor elements, including cognitive deficits. We employed resting-state functional magnetic resonance imaging (fMRI) to assess whether brain networks that might be involved in the pathogenesis of nonmotor manifestations associated with ET are altered, and the relationship between abnormal connectivity and ET severity and neuropsychological function.Resting-state fMRI data in 23 ET patients (12 women and 11 men) and 22 healthy controls (HC) (12 women and 10 men) were analyzed using independent component analysis, in combination with a "dual-regression" technique, to identify the group differences of resting-state networks (RSNs) (default mode network [DMN] and executive, frontoparietal, sensorimotor, cerebellar, auditory/language, and visual networks). All participants underwent a neuropsychological and neuroimaging session, where resting-state data were collected.Relative to HC, ET patients showed increased connectivity in RSNs involved in cognitive processes (DMN and frontoparietal networks) and decreased connectivity in the cerebellum and visual networks. Changes in network integrity were associated not only with ET severity (DMN) and ET duration (DMN and left frontoparietal network), but also with cognitive ability. Moreover, in at least 3 networks (DMN and frontoparietal networks), increased connectivity was associated with worse performance on different cognitive domains (attention, executive function, visuospatial ability, verbal memory, visual memory, and language) and depressive symptoms. Further, in the visual network, decreased connectivity was associated with worse performance on visuospatial ability.ET was associated with abnormal brain connectivity in major RSNs that might be involved in both motor and nonmotor symptoms. Our findings underscore the importance of examining RSNs in this population as a biomarker of disease., Competing Interests: The authors have no conflicts of interest to disclose.

Objective: Pathological tremors are symptomatic to several neurological disorders that are difficult to differentiate and the way by which central oscillatory networks entrain tremorogenic contractions is unknown. We considered the alternative hypotheses that tremor arises from one oscillator (at the tremor frequency) or, as suggested by recent findings from the superimposition of two separate inputs (at the tremor frequency and twice that frequency)., Approach: Assuming one central oscillatory network we estimated analytically the relative amplitude of the harmonics of the tremor frequency in the motor neuron output for different temporal behaviors of the oscillator. Next, we analyzed the bias in the relative harmonics amplitude introduced by superimposing oscillations at twice the tremor frequency. These findings were validated using experimental measurements of wrist angular velocity and surface electromyography (EMG) from 22 patients (11 essential tremor, 11 Parkinson's disease). The ensemble motor unit action potential trains identified from the EMG represented the neural drive to the muscles., Main Results: The analytical results showed that the relative power of the tremor harmonics in the analytical models of the neural drive was determined by the variability and duration of the tremor bursts and the presence of the second oscillator biased this power towards higher values. The experimental findings accurately matched the analytical model assuming one oscillator, indicating a negligible functional role of secondary oscillatory inputs. Furthermore, a significant difference in the relative power of harmonics in the neural drive was found across the patient groups, suggesting a diagnostic value of this measure (classification accuracy: 86%). This diagnostic power decreased substantially when estimated from limb acceleration or the EMG. SIGNFICANCE: The results indicate that the neural drive in pathological tremor is compatible with one central network providing neural oscillations at the tremor frequency. Moreover, the regularity of this neural oscillation varies across tremor pathologies, making the relative amplitude of tremor harmonics a potential biomarker for diagnostic use.

The pathophysiology of essential tremor (ET), the most common movement disorder, is not fully understood. We investigated which factors determine the variability in the phase difference between neural drives to antagonist muscles, a long-standing observation yet unexplained. We used a computational model to simulate the effects of different levels of voluntary and tremulous synaptic input to antagonistic motoneuron pools on the tremor. We compared these simulations to data from 11 human ET patients. In both analyses, the neural drive to muscle was represented as the pooled spike trains of several motor units, which provides an accurate representation of the common synaptic input to motoneurons. The simulations showed that, for each voluntary input level, the phase difference between neural drives to antagonist muscles is determined by the relative strength of the supraspinal tremor input to the motoneuron pools. In addition, when the supraspinal tremor input to one muscle was weak or absent, Ia afferents provided significant common tremor input due to passive stretch. The simulations predicted that without a voluntary drive (rest tremor) the neural drives would be more likely in phase, while a concurrent voluntary input (postural tremor) would lead more frequently to an out-of-phase pattern. The experimental results matched these predictions, showing a significant change in phase difference between postural and rest tremor. They also indicated that the common tremor input is always shared by the antagonistic motoneuron pools, in agreement with the simulations. Our results highlight that the interplay between supraspinal input and spinal afferents is relevant for tremor generation., (Copyright © 2015 the authors 0270-6474/15/358925-13$15.00/0.)

Tremor in essential tremor (ET) is generated by pathological oscillations at 4-12 Hz, likely originating at cerebello-thalamo-cortical pathways. However, the way in which tremor is represented in the output of the spinal cord circuitries is largely unknown because of the difficulties in identifying the behavior of individual motor units from tremulous muscles. By using novel methods for the decomposition of multichannel surface EMG, we provide a systematic analysis of the discharge properties of motor units in nine ET patients, with concurrent recordings of EEG activity. This analysis allowed us to infer the contribution of common synaptic inputs to motor neurons in ET. Motor unit short-term synchronization was significantly greater in ET patients than in healthy subjects. Furthermore, the strong association between the degree of synchronization and the peak in coherence between motor unit spike trains at the tremor frequency indicated that the high synchronization levels were generated mainly by common synaptic inputs specifically at the tremor frequency. The coherence between EEG and motor unit spike trains demonstrated the presence of common cortical input to the motor neurons at the tremor frequency. Nonetheless, the strength of this input was uncorrelated to the net common synaptic input at the tremor frequency, suggesting a contribution of spinal afferents or secondary supraspinal pathways in projecting common input at the tremor frequency. These results provide the first systematic analysis of the neural drive to the muscle in ET and elucidate some of its characteristics that determine pathological tremulous muscle activity., (Copyright © 2015 the American Physiological Society.)

Background: Essential tremor (ET) is characterised by postural and action tremors with a frequency of 4-12 Hz. Previous studies suggest that the tremor activity originates in the cerebello-thalamocortical pathways. Alprazolam is a short-acting benzodiazepine that attenuates tremors in ET. The mechanisms that mediate the therapeutic action of alprazolam are unknown; however, in healthy subjects, benzodiazepines increase cortical beta activity. In this study, we investigated the effect of alprazolam both on beta and tremor-related cortical activity and on alterations in tremor presentation in ET patients. Therefore, we characterised the dynamics of tremor and cortical activity in ET patients after alprazolam intake., Methods: We recorded hand tremors and contralateral cortical activity in four recordings before and after a single dose of alprazolam. We then computed the changes in tremors, cortico-muscular coherence, and cortical activity at the tremor frequency and in the beta band., Results: Alprazolam significantly attenuated tremors (EMG: 76.2 ± 22.68%), decreased cortical activity in the tremor frequency range and increased cortical beta activity in all patients (P<0.05). At the same time, the cortico-muscular coherence at the tremor frequency became non-significant (P<0.05). We also found a significant correlation (r = 0.757, P<0.001) between the reduction in tremor severity and the increased ratio of cortical activity in the beta band to the activity observed in the tremor frequency range., Conclusions: This study provides the first quantitative analysis of tremor reduction following alprazolam intake. We observed that the tremor severity decreased in association with an increased ratio of beta to tremor-related cortical activity. We hypothesise that the increase in cortical beta activity may act as a blocking mechanism and may dampen the pathological oscillatory activity, which in turn attenuates the observed tremor.

Background: Pathological tremor is the most prevalent movement disorder. Current treatments do not attain a significant tremor reduction in a large proportion of patients, which makes tremor a major cause of loss of quality of life. For instance, according to some estimates, 65% of those suffering from upper limb tremor report serious difficulties during daily living. Therefore, novel forms for tremor management are required. Since muscles intrinsically behave as a low pass filter, and tremor frequency is above that of volitional movements, the authors envisioned the exploitation of these properties as a means of developing a novel treatment alternative. This treatment would rely on muscle co-contraction for tremor management, similarly to the strategy employed by the intact central nervous system to stabilize a limb during certain tasks., Methods: We implemented a neuroprosthesis that regulated the level of muscle co-contraction by injecting current at a pair of antagonists through transcutaneous neurostimulation. Co-contraction was adapted to the instantaneous parameters of tremor, which were estimated from the raw recordings of a pair of solid state gyroscopes with a purposely designed adaptive algorithm. For the experimental validation, we enrolled six patients suffering from parkinsonian or essential tremor of different severity, and evaluated the effect of the neuroprosthesis during standard tasks employed for neurological examination., Results: The neuroprosthesis attained significant attenuation of tremor (p<0.001), and reduced its amplitude up to a 52.33±25.48%. Furthermore, it alleviated both essential and parkinsonian tremor in spite of their different etiology and symptomatology. Tremor severity was not a limiting factor on the performance of the neuroprosthesis, although there was a subtle trend towards larger attenuation of more severe tremors. Tremor frequency was not altered during neurostimulation, as expected from the central origin of Parkinson's disease and essential tremor. All patients showed a good tolerance to neurostimulation in terms of comfort and absence of pain, and some spontaneously reported that they felt that tremor was reduced when the neuroprosthesis was activated., Conclusions: The results presented herein demonstrate that the neuroprosthesis provides systematic attenuation of the two major types of tremor, irrespectively from their severity. This study sets the basis for the validation of the neuroprosthesis as an alternative, non-invasive means for tremor management.

We describe a wearable orthosis and an associated algorithm for the simultaneous assessment and treatment of essential tremor, one of the most common movement disorders in humans involving an overactivity of the olivo-cerebellar pathways. A motor providing effective viscosity is fixed on a wearable orthosis in the upper limbs. The motor is controlled by a personal computer with software processing in real time the position and rate of rotation of the joint detected by a chip gyroscope. The orthosis can be used in a monitoring mode and in an active mode. The range of tremor suppression of the signals above the orthosis operational limit ranges from about 3% (percentile 5) to about 79% (percentile 95) in relation to energy in the monitoring mode. Considering both postural and kinetic, the mean tremor energy decreased from 55.49 +/- 22.93 rad2 s(-3) in the monitoring mode to 15.66 +/- 7.29 rad2 s(-3) in the active mode. Medians of power reduction were below 60% for the wrist and the elbow. In addition to supplying new information on the interactions between kinematics, dynamics and tremor genesis, this non-invasive technique is an alternative to current therapies. This new approach will provide new insights into the understanding of motor control.

This paper describes a new treatment for essential tremor. A wearable orthosis, which can be adapted to each configuration of each joint of the upper limb, is able to apply effective dynamic force between consecutive segments of the upper limb and change its biomechanical characteristics. The orthosis is controlled by a computer with a dedicated software application that distinguishes between real time tremor and voluntary movement. The wearable orthosis is able to detect position, rate and acceleration of rotation of the joint by means of a chip gyroscope. This technology was evaluated in six patients suffering from essential tremor. The technique is non invasive and represents an alternative to medication and deep brain stimulation.

(1) Background: Vibrotactile stimulation has been studied for tremor, but there is little evidence for Essential Tremor (ET). (2) Methods: This research employed a dataset from a previous study, with data collected from 18 individuals subjected to four vibratory stimuli. To characterise tremor changes before, during, and after stimuli, time and frequency domain features were estimated from the signals. Correlation and regression analyses verified the relationship between features and clinical tremor scores. (3) Results: Individuals responded differently to vibrotactile stimulation. The 250 Hz stimulus was the only one that reduced tremor amplitude after stimulation. Compared to the baseline, the 250 Hz and random frequency stimulation reduced tremor peak power. The clinical scores and amplitude-based features were highly correlated, yielding accurate regression models (mean squared error of 0.09). (4) Conclusions: The stimulation frequency of 250 Hz has the greatest potential to reduce tremors in ET. The accurate regression model and high correlation between estimated features and clinical scales suggest that prediction models can automatically evaluate and control stimulus-induced tremor. A limitation of this research is the relatively reduced sample size. [ABSTRACT FROM AUTHOR]

Tremor is defined as a rhythmic, involuntary oscillatory movement of a body part. Although everyone exhibits a certain degree of tremor, some pathologies lead to very disabling tremors. These pathological tremors constitute the most prevalent movement disorder, and they imply severe difficulties in performing activities of daily living. Although tremors are currently managed through pharmacotherapy or surgery, these treatments present significant associated drawbacks: drugs often induce side effects and show decreased effectiveness over years of use, while surgery is a hazardous procedure for a very low percentage of eligible patients. In this context, recent research demonstrated the feasibility of managing upper limb tremors through wearable technologies that suppress tremors by modifying limb biomechanics or applying counteracting forces. Furthermore, recent experiments with transcutaneous afferent stimulation showed significant tremor attenuation. In this regard, this article reviews the devices developed following these tremor management paradigms, such as robotic exoskeletons, soft robotic exoskeletons, and transcutaneous neurostimulators. These works are presented, and their effectiveness is discussed. The article also evaluates the different metrics used for the validation of these devices and the lack of a standard validation procedure that allows the comparison among them. [ABSTRACT FROM AUTHOR]

Objective: Although the cerebello‐thalamo‐cortical network has often been suggested to be of importance in the pathogenesis of essential tremor (ET), the origins of tremorgenic activity in this disease are not fully understood. We used a combination of cortical thickness imaging and neurophysiological studies to analyze whether the severity of tremor was associated with anatomical changes in the brain in ET patients. Methods: Magnetic resonance imaging (MRI) and a neurophysiological assessment were performed in 13 nondemented ET patients. High field structural brain MRI images acquired in a 3T scanner and analyses of cortical thickness and surface were carried out. Cortical reconstruction and volumetric segmentation was performed with the FreeSurfer image analysis software. We used high‐density surface electromyography (hdEMG) and inertial measurement units (IMUs) to quantify the tremor severity in upper extrimities of patients. In particular, advanced computer tool was used to reliably identify discharge patterns of individual motor units from surface hdEMG and quantify motor unit synchronization. Results: We found significant association between increased motor unit synchronization (i.e., more severe tremor) and cortical changes (i.e., atrophy) in widespread cerebral cortical areas, including the left medial orbitofrontal cortex, left isthmus of the cingulate gyrus, right paracentral lobule, right lingual gyrus, as well as reduced left supramarginal gyrus (inferior parietal cortex), right isthmus of the cingulate gyrus, left thalamus, and left amygdala volumes. Interpretation: Given that most of these brain areas are involved in controlling movement sequencing, ET tremor could be the result of an involuntary activation of a program of motor behavior used in the genesis of voluntary repetitive movements. [ABSTRACT FROM AUTHOR]

Background: Traditional studies on the neural mechanisms of tremor use coherence analysis to investigate the relationship between cortical and muscle activity, measured by electroencephalograms (EEG) and electromyograms (EMG). This methodology is limited by the need of relatively long signal recordings, and it is sensitive to EEG artifacts. Here, we analytically derive and experimentally validate a new method for automatic extraction of the tremor-related EEG component in pathological tremor patients that aims to overcome these limitations. Methods: We exploit the coupling between the tremor-related cortical activity and motor unit population firings to build a linear minimum mean square error estimator of the tremor component in EEG. We estimated the motor unit population activity by decomposing surface EMG signals into constituent motor unit spike trains, which we summed up into a cumulative spike train (CST). We used this CST to initialize our tremor-related EEG component estimate, which we optimized using a novel approach proposed here. Results: Tests on simulated signals demonstrate that our new method is robust to both noise and motor unit firing variability, and that it performs well across a wide range of spectral characteristics of the tremor. Results on 9 essential (ET) and 9 Parkinson's disease (PD) patients show a ~2-fold increase in amplitude of the coherence between the estimated EEG component and the CST, compared to the classical EEG-EMG coherence analysis. Conclusions: We have developed a novel method that allows for more precise and robust estimation of the tremor-related EEG component. This method does not require artifact removal, provides reliable results in relatively short datasets, and tracks changes in the tremor-related cortical activity over time. [ABSTRACT FROM AUTHOR]

BACKGROUND Much attention has been given to the use of inertial sensors for remote monitoring of individuals suffering from neurological pathologies. However, the focus has been mostly on the detection of symptoms like tremor or dyskinesia, not on identifying specific activities carried out by subjects. The objective of this study was to develop an automated segmentation and recognition methodology, from inertial sensor data, to identify tasks and motor patterns during activities of daily living. This will enable clinicians to contextualize the symptoms of these diseases and improve their treatment. METHODS We designed and tested a methodology to automatically label continuous upper-limb activity from IMUs (Inertial Measurement Units). Three classification problems are considered: the task itself, the precision level required by the task with respect to movement ( fine or gross ) and the trajectory of the task ( distal or proximal ). These problems were identified by tremor experts as clinically important aspects to be monitored in tremor patients while performing daily activities. The proposed methodology reveals the relation between the functional context or activity and the patient's on-going tremor to clinicians. RESULTS Overall task identification rate was 86%. Task precision and task trajectory are classified with 79% and 89% accuracy, respectively. Aligning the semantic nature of the activity with the tremor location and intensity can also provide novel and relevant information for clinical monitoring of tremor and help clinicians and researchers as a useful tool to develop new therapies or strategies and novel anti-tremor medications to combat context dependent tremor. CONCLUSIONS The present study describes the development of a comprehensive methodology based on machine learning techniques to segment and detect activities of daily living in people with tremor using inertial sensors, which aims at facilitating detailed interpretation of tremor movements by neurologists. [ABSTRACT FROM AUTHOR]