Differential diagnosis of common tremor syndromes

Dual target deep brain stimulation for complex essential and dystonic tremor - A 5-year follow up

BACKGROUND

Essential tremor (ET) is characterized by action tremor of the upper limbs, head tremor and voice tremor. Dystonic tremor (DT) is produced by muscle contractions in a body affected by dystonia. Deep brain stimulation (DBS) of ventral intermediate nucleus of the thalamus (VIM) is the most well-known advanced treatment for medication-refractory tremor. However, decline in efficacy overtime has led to explore other targets. This study aimed to measure the efficacy of bilateral dual targeting ViM/caudal Zona Incerta (cZI) stimulation on tremor control. A secondary aim was to evaluate if there was a difference in the efficacy between ET and DT.

METHODS

36 patients were retrospectively recruited at the Walton NHS Foundation Trust, Liverpool, UK. Patients were assessed pre-operatively, and then at 1-year, 3-years, and 5-years post-operatively with the following scales: Fahn-Tolosa-Marin tremor rating (FTMTR) scale, EuroQol-5D, and Hospital Anxiety and Depression Scale.

RESULTS

Bilateral ViM-cZI DBS significantly improved overall tremor score by 45.1% from baseline to 3-years post-operatively (p < 0.001). It continued to show improvement in overall FTMTR score by 30.7% at 5-years but this failed to meet significance. However, there was no significant improvement of mood or quality of life (QoL) scores. ET group on average showed a significant better clinical outcome compared to the DT group (p > 0.001).

CONCLUSIONS

Our study found that bilateral ViM-cZI DBS treatment had a favourable effect on motor symptoms sustained over the 5-years in tremor patients, especially in ET group. There was limited effect on mood and QoL with similar trends in outcomes for both tremor types.

Explainable artificial intelligence for searching frequency characteristics in Parkinson's disease tremor

The distinction between Parkinson's disease (PD) and essential tremor (ET) tremors is subtle, posing challenges in differentiation. To accurately classify the PD and ET, BiLSTM-based recurrent neural networks are employed to classify between normal patients (N), PD patients, and ET patients using accelerometry data on their lower arm (L), hand (H), and upper arm (U) as inputs. The trained recurrent neural network (RNN) has reached 80% accuracy. The neural network is analyzed using layer-wise relevance propagation (LRP) to understand the internal workings of the neural network. A novel explainable AI method, called LRP-based approximate linear weights (ALW), is introduced to identify the similarities in relevance when assigning the class scores in the neural network. The ALW functions as a 2D kernel that linearly transforms the input data directly into the class scores, which significantly reduces the complexity of analyzing the neural network. This new classification method reconstructs the neural network's original function, achieving a 73% PD and ET tremor classification accuracy. By analyzing the ALWs, the correlation between each input and the class can also be determined. Then, the differentiating features can be subsequently identified. Since the input is preprocessed using short-time Fourier transform (STFT), the differences between the magnitude of tremor frequencies ranging from 3 to 30 Hz in the mean N, PD, and ET subjects are successfully identified. Aside from matching the current medical knowledge on frequency content in the tremors, the differentiating features also provide insights about frequency contents in the tremors in other frequency bands and body parts.

Comparative Effectiveness of Transcutaneous Afferent Patterned Stimulation Therapy for Essential Tremor: A Randomized Pragmatic Clinical Trial

Background

Transcutaneous afferent patterned stimulation (TAPS) is a wrist-worn, non-invasive therapy delivering calibrated stimulation to the median and radial nerves. Previous randomized controlled studies have demonstrated the efficacy and safety of TAPS therapy in some patients with essential tremor (ET), but evidence supporting therapeutic benefits of TAPS versus standard of care (SOC) is lacking. This randomized prospective study evaluated the clinical benefit of adding TAPS treatment to SOC versus SOC alone.

Methods

This randomized pragmatic trial recruited patients from a large health plan's Commercially Insured and Medicare Advantage population. All 310 patients received a TAPS device and were randomized 1:1 to either one month adding TAPS therapy to usual care (TX arm) or usual care with tremor assessment only (SOC arm). The pre-specified endpoints were changes in tremor power measured by motion sensors on the device (primary) and improvement in Bain & Findley Activities of Daily Living (BF-ADL) upper limb scores (secondary) between TX and SOC in all patients who completed the one-month study.

Results

276 patients completed the one-month study (N = 133 TX, N = 143 SOC). The study met the primary and secondary endpoints, with significantly reduced tremor power in TX compared with SOC (0.017 (0.003) versus 0.08 (0.014) (m/s2)2; geometric mean (SE); p < 0.0001) and greater improvement in the BF-ADL score in TX than SOC (1.6 (0.43) vs 0.2 (0.37) points; mean (SE); p < 0.05). No serious device-related adverse events were reported.

Discussion

This trial demonstrates that adding TAPS treatment to SOC significantly improves tremor power and BF-ADLs in patients with ET compared to SOC alone over one month of home use.

Highlights

This study found that adding TAPS treatment to SOC significantly improves tremor power and BF-ADL scores in patients with ET compared to SOC alone over one month of home use. This real-world evidence study suggests that non-invasive TAPS therapy is a safe and valuable treatment option for patients with ET.

FiMec tremor stabilization spoon: design and active stabilization control of two DoF robotic eating devices for hand tremor patients

This article is about vibration-damping robotic eating devices designed for use by people who have difficulty in eating due to hand tremors due to neuromuscular system disorder. The robotic eating device has two degrees of freedom (DoF). It contains an active controller structure to absorb vibrations in the y- and z-directions. In the handle part of the robotic eating device, there are two DC motors placed on the y- and z-axis, a three-axis IMU inertia sensor, an embedded system board, and a power unit. To absorb the vibration measured from the IMU sensor, the position control of the two motors to which the spoon is connected is provided by PID controllers. The part of the spoon (the pit surface) where the food is placed is tried to be kept constant. To test the vibration-damping performance of the control method, the dynamic model of the spoon along the eating kinematic trajectory was simulated in the SimMechanics environment using vibration data from ten tremor patients. The results show that the stabilization method can absorb the vibration in the hand of the person in the range of 84-99.409% and successfully provide the stabilization of the spoon tip. This damping rate is promising for providing a healthy diet for hand tremor patients.

Detecting Minor Symptoms of Parkinson's Disease in the Wild Using Bi-LSTM with Attention Mechanism

Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor and nonmotor impairment with various implications on patients' quality of life. Since currently available therapies are only symptomatic, identifying individuals with prodromal, preclinical, or early-stage PD is crucial, as they would be ideal candidates for future disease-modifying therapies. Our analysis aims to develop a robust model for accurate PD detection using accelerometer data collected from PD and non-PD individuals with mild or no tremor during phone conversations. An open-access dataset comprising accelerometer recordings from 22 PD patients and 11 healthy controls (HCs) was utilized. The data were preprocessed to extract relevant time-, frequency-, and energy-related features, and a bidirectional long short-term memory (Bi-LSTM) model with attention mechanism was employed for classification. The performance of the model was evaluated using fivefold cross-validation, and metrics of accuracy, precision, recall, specificity, and f1-score were computed. The proposed model demonstrated high accuracy (98%), precision (99%), recall (98%), specificity (96%), and f1-score (98%) in accurately distinguishing PD patients from HCs. Our findings indicate that the proposed model outperforms existing approaches and holds promise for detection of PD with subtle symptoms, like tremor, in the wild. Such symptoms can present in the early or even prodromal stage of the disease, and appropriate mobile-based applications may be a practical tool in real-life settings to alert individuals at risk to seek medical assistance or give patients feedback in monitoring their symptoms.

Multimodal Care of a Patient With Functional Movement Disorders Following a Motor Vehicle Accident: A Case Report

Objective

The purpose of this case report was to describe the multimodal care of a patient with the sudden onset of truncal tremors.

Clinical Features

A 30-year-old female patient presented for chiropractic care with truncal tremors following a motor vehicle accident. Initial outcome measures included the Neck Disability Index (50%) and Oswestry Disability Index (62). The patient's truncal tremors became worse during spinal cord compression testing that included passive cervical flexion and slouched posture. The Romberg test was positive for swaying. Assessments of active range of motions of the cervical, thoracic, and lumbar spine were moderately reduced in all ranges. Case history, physical examinations, diagnostic imaging, and neurology consultations led to a diagnosis of functional truncal tremors. The patient was being concurrently managed by other health care providers. Magnetic resonance imaging studies were ordered by a neurologist and primary medical physician, which showed no structural abnormalities in brain neuroanatomy or spine.

Intervention and Outcome

The multimodal chiropractic care included whole-body vibration therapy (WBVT), spinal manipulative therapy (SMT), and acupuncture therapy. The treatment plan included 8 weekly appointments in which the patient received WBVT and SMT. During treatment weeks 2 to 6, the patient received acupuncture therapy, which occurred immediately following their treatment appointment for WBVT and SMT. The patient practiced stress reduction techniques, as advised by the neurologist, eliminated caffeine, and performed daily yoga exercises for 30 minutes. The Romberg test was negative after the third treatment. The patient was discharged after chiropractic visit 12, 95 days post-accident, as she reached maximal medical improvement. Truncal tremors were still present, but the patient described them as "barely noticeable."

Conclusion

The patient reported improvement under a course of chiropractic care using a multimodal approach, including behavioral, pharmacological, and manual therapies. This case study suggests that WBVT, SMT, and acupuncture therapy may assist some patients with functional movement disorders.

Structural brain differences in essential tremor and Parkinson's disease deep brain stimulation patients

BACKGROUND

Essential tremor (ET) and Parkinson's disease (PD) are the most common tremor disorders and are common indications for deep brain stimulation (DBS). In some patients, PD and ET symptoms overlap and diagnosis can be challenging based on clinical criteria alone. The objective of this study was to identify structural brain differences between PD and ET DBS patients to help differentiate these disorders and improve our understanding of the different brain regions involved in these pathologic processes.

METHODS

We included ET and PD patients scheduled to undergo DBS surgery in this observational study. Patients underwent 3T brain MRI while under general anesthesia as part of their procedure. Cortical thicknesses and subcortical volumes were quantified from T1-weighted images using automated multi-atlas segmentation. We used logistic regression analysis to identify brain regions associated with diagnosis of ET or PD.

RESULTS

149 ET and 265 PD patients were included. Smaller volumes in the pallidum and thalamus and reduced thickness in the anterior orbital gyrus, lateral orbital gyrus, and medial precentral gyrus were associated with greater odds of ET diagnosis. Conversely, reduced volumes in the caudate, amygdala, putamen, and basal forebrain, and reduced thickness in the orbital part of the inferior frontal gyrus, supramarginal gyrus, and posterior cingulate were associated with greater odds of PD diagnosis.

CONCLUSIONS

These findings identify structural brain differences between PD and ET patients. These results expand our understanding of the different brain regions involved in these disorders and suggest that structural MRI may help to differentiate patients with these two disorders.

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.

Diagnostic Uncertainties in Tremor

The approach and diagnosis of patients with tremor may be challenging for clinicians. According to the most recent consensus statement by the Task Force on Tremor of the International Parkinson Movement Disorder Society, the differentiation between action (i.e., kinetic, postural, intention), resting, and other task- and position-specific tremors is crucial to this goal. In addition, patients with tremor must be carefully examined for other relevant features, including the topography of the tremor, since it can involve different body areas and possibly associate with neurological signs of uncertain significance. Following the characterization of major clinical features, it may be useful to define, whenever possible, a particular tremor syndrome and to narrow down the spectrum of possible etiologies. First, it is important to distinguish between physiological and pathological tremor, and, in the latter case, to differentiate between the underlying pathological conditions. A correct approach to tremor is particularly relevant for appropriate referral, counseling, prognosis definition, and therapeutic management of patients. The purpose of this review is to outline the possible diagnostic uncertainties that may be encountered in clinical practice in the approach to patients with tremor. In addition to an emphasis on a clinical approach, this review discusses the important ancillary role of neurophysiology and innovative technologies, neuroimaging, and genetics in the diagnostic process.

Computational study and validation of a novel passive hand tremor attenuator

Tremors are a prevalent movement disorder due to a nervous system condition that leads to involuntary muscle movements observed in patients. This paper converts the tremorous anatomical human arm model to a single degree of freedom (SDOF) forced vibration problem. The mathematical modelling with Euler-Lagrange's equation is performed for the SDOF human arm model with two different potential vibration absorbers. A computational study is conducted on MATLAB Simulink by MathWorks Inc. (Natick, MA) to compare two absorbers, and the results are verified on the multibody dynamics simulation solution software, MSC Adams by Hexagon AB. It is concluded that the T beam-shaped vibration absorber represented a higher amplitude reduction, up to 80%, compared to the inertial mass absorber, which had an amplitude reduction of 65% over the range of frequencies. Experiments conducted with the T beam absorber prototype also support the computational findings. Future research focuses on designing an ergonomic wearable device with a proposed T-beam absorber that can passively attenuate the tremor at various frequencies.

4D printing of soft orthoses for tremor suppression

Tremor is an involuntary and oscillatory movement disorder that makes daily activities difficult for affected patients. Hand tremor-suppression orthoses are noninvasive, wearable devices designed to mitigate tremors. Various studies have shown that these devices are effective, economical, and safe; however, they have drawbacks such as large weight, awkward shape, and rigid parts. This study investigates different types of tremor-suppression orthoses and discusses their efficiency, mechanism, benefits, and disadvantages. First, various orthoses (with passive, semi-active, and active mechanisms) are described in detail. Next, we look at how additive manufacturing (AM) has progressed recently in making sensors and actuators for application in tremor orthoses. Then, the materials used in AM are further analyzed. It is found that traditional manufacturing problems can be solved with the help of AM techniques, like making orthoses that are affordable, lighter, and more customizable. Another concept being discussed is using smart materials and AM methods, such as four-dimensional (4D) printing, to make orthoses that are more comfortable and efficient.

Graphic abstract

Objective quantification of the severity of postural tremor based on kinematic parameters: A multi-sensory fusion study

BACKGROUND

Current clinical assessments of essential tremor (ET) are primarily based on expert consultation combined with reviewing patient complaints, physician expertise, and diagnostic experience. Thus, traditional evaluation methods often lead to biased diagnostic results. There is a clinical demand for a method that can objectively quantify the severity of the patient's disease.

METHODS

This study aims to develop an artificial intelligence-aided diagnosis method based on multi-sensory fusion wearables. The experiment relies on a rigorous clinical trial paradigm to collect multi-modal fusion of signals from 98 ET patients. At the same time, three clinicians scored independently, and the consensus score obtained was used as the ground truth for the machine learning models.

RESULTS

Sixty kinematic parameters were extracted from the signals recorded by the nine-axis inertial measurement unit (IMU). The results showed that most of the features obtained by IMU could effectively characterize the severity of the tremors. The accuracy of the optimal model for three tasks classifying five severity levels was 97.71%, 97.54%, and 97.72%, respectively.

CONCLUSIONS

This paper reports the first attempt to combine multiple feature selection and machine learning algorithms for fine-grained automatic quantification of postural tremor in ET patients. The promising results showed the potential of the proposed approach to quantify the severity of ET objectively.

A Portable Non-Contact Tremor Vibration Measurement and Classification Apparatus

Tremors are the most common type of movement disorder and affect the lives of those experiencing them. The efficacy of tremor therapies varies according to the aetiology of the tremor and its correct diagnosis. This study develops a portable measurement device capable of non-contact measurement of the tremor, which could assist in tremor diagnosis and classification. The performance of this device was assessed through a validation process using a shaker at a controlled frequency to measure human tremors, and the device was able to measure vibrations of 50 Hz accurately, which is more than twice the frequency of tremors produced by humans. Then, the device is tested to measure the tremors for two different activation conditions: rest and postural, for both hand and leg. The measured non-contact tremor vibration data successfully led to tremor classification in the subjects already diagnosed using a contact accelerometer.

Analyzing the Effects of Parameters for Tremor Modulation via Phase-Locked Electrical Stimulation on a Peripheral Nerve

(1) Background: Non-invasive neuromodulation is a promising alternative to medication or deep-brain stimulation treatment for Parkinson's Disease or essential tremor. In previous work, we developed and tested a wearable system that modulates tremor via the non-invasive, electrical stimulation of peripheral nerves. In this article, we examine the proper range and the effects of various stimulation parameters for phase-locked stimulation. (2) Methods: We recruited nine participants with essential tremor. The subjects performed a bean-transfer task that mimics an eating activity to elicit kinetic tremor while using the wearable stimulation system. We examined the effects of stimulation with a fixed duty cycle, at different stimulation amplitudes and frequencies. The epochs of stimulation were locked to one of four phase positions of ongoing tremor, as measured with an accelerometer. We analyzed stimulation-evoked changes of the frequency and amplitude of tremor. (3) Results: We found that the higher tremor amplitude group experienced a higher rate of tremor power reduction (up to 65%) with a higher amplitude of stimulation when the stimulation was applied at the ±peak of tremor phase. (4) Conclusions: The stimulation parameter can be adjusted to optimize tremor reduction, and this study lays the foundation for future large-scale parameter optimization experiments for personalized peripheral nerve stimulation.

Brain iron deposition and movement disorders in hereditary haemochromatosis without liver failure: A cross-sectional study

BACKGROUND AND PURPOSE

Hereditary haemochromatosis (HH) is the most common inherited disorder of systemic iron excess in Northern Europeans. Emerging evidence indicates that brain iron overload occurs in HH. Despite this observation, there is a paucity of literature regarding central neurological manifestations, in particular movement disorders, in HH. The current study documents deep gray matter (DGM) nuclei iron deposition, movement disorders, and clinicoradiological correlations in HH without liver failure.

METHODS

This is a cross-sectional study. Consecutive subjects with HFE-haemochromatosis without liver disease were recruited from an outpatient gastroenterology clinic. Age- and sex-matched healthy controls (HCs) were enrolled. Iron content in individual DGM nuclei was measured as mean susceptibility on magnetic resonance imaging using quantitative susceptibility mapping-based regions of interest analysis. Occurrence and phenotype of movement disorders were documented and correlated with patterns of DGM nuclei iron deposition in subjects with HH.

RESULTS

Fifty-two subjects with HH and 47 HCs were recruited. High magnetic susceptibility was demonstrated in several DGM nuclei in all HH subjects compared to HCs. Thirty-five subjects with HH had movement disorders. Magnetic susceptibility in specific DGM nuclei correlated with individual movement disorder phenotypes. Serum ferritin, phlebotomy frequency, and duration were poor predictors of brain iron deposition.

CONCLUSIONS

Abnormal brain iron deposition can be demonstrated on imaging in all subjects with HH without liver failure. A significant proportion of these subjects manifest movement disorders. Peripheral iron measurements appear not to correlate with brain iron deposition. Therefore, routine neurological examination and quantitative brain iron imaging are recommended in all subjects with HH.

Computer models evaluating hand tremors in Parkinson's disease patients

One of the most characteristic signs of Parkinson's disease (PD) is hand tremor. The MDS-UPDRS scale evaluates different aspects of the disease. The tremor score is a part of the MDS-UPDRS scale, which provides instructions for rating it, by observation, with an integer from 0 to 4. Nevertheless, this form of assessment is subjective and dependent on visual acuity, clinical judgment, and even the mood of the individual examiner. On the other hand, in many cases, existing computational models proposed to resolve the disadvantages of the MDS-UPDRS scale may have uncertainty in differentiating a category of a slight Parkinson tremor from voluntary movements. In this study, 554 measurements from Parkinson's patients, and 60 measurements from healthy subjects, were recorded with inertial sensors placed on the back of each hand. Five biomechanical indicators characterised the hand tremor. With these indicators, the three fuzzy inference models proposed can differentiate, in the first instance, the presence of postural or resting tremor from a normal movement of the hand, and if detected, to determine its severity. The fuzzy inference models allowed following the criteria of the MDS-UPDRS scale, providing an evaluation with an accuracy of two decimal digits and which, due to its simplicity, can be implemented in clinical environments. The assessments of three experts validated the computer model.

Cerebello-Thalamo-Cortical Network Dynamics in the Harmaline Rodent Model of Essential Tremor

Essential Tremor (ET) is a common movement disorder, characterised by a posture or movement-related tremor of the upper limbs. Abnormalities within cerebellar circuits are thought to underlie the pathogenesis of ET, resulting in aberrant synchronous oscillatory activity within the thalamo-cortical network leading to tremors. Harmaline produces pathological oscillations within the cerebellum, and a tremor that phenotypically resembles ET. However, the neural network dynamics in cerebellar-thalamo-cortical circuits in harmaline-induced tremor remains unclear, including the way circuit interactions may be influenced by behavioural state. Here, we examined the effect of harmaline on cerebello-thalamo-cortical oscillations during rest and movement. EEG recordings from the sensorimotor cortex and local field potentials (LFP) from thalamic and medial cerebellar nuclei were simultaneously recorded in awake behaving rats, alongside measures of tremor using EMG and accelerometery. Analyses compared neural oscillations before and after systemic administration of harmaline (10 mg/kg, I.P), and coherence across periods when rats were resting vs. moving. During movement, harmaline increased the 9-15 Hz behavioural tremor amplitude and increased thalamic LFP coherence with tremor. Medial cerebellar nuclei and cerebellar vermis LFP coherence with tremor however remained unchanged from rest. These findings suggest harmaline-induced cerebellar oscillations are independent of behavioural state and associated changes in tremor amplitude. By contrast, thalamic oscillations are dependent on behavioural state and related changes in tremor amplitude. This study provides new insights into the role of cerebello-thalamo-cortical network interactions in tremor, whereby neural oscillations in thalamocortical, but not cerebellar circuits can be influenced by movement and/or behavioural tremor amplitude in the harmaline model.

Fitts Law-Based Performance Metrics to Quantify Tremor in Individuals with Essential Tremor

Current methods of evaluating essential tremor (ET) either rely on subjective ratings or use limited tremor metrics (i.e., severity/amplitude and frequency). In this study, we explored performance metrics from Fitts law tasks that replicate and expand existing tremor metrics, to enable low-cost, home-based tremor quantification and analyze the cursor movements of individuals using a 3D mouse while performing a collection of drawing tasks. We analyzed the 3D mouse cursor movements of 11 patients with ET and three controls, on three computer-based tasksa spiral navigation (SPN) task, a rectangular track navigation (RTN) task, and multi-directional tapping/clicking (MDT)with several performance metrics (i.e., outside area (OA), throughput (TP in Fitts law), path efficiency (PE), and completion time (CT)). Using an accelerometer and scores from the Essential Tremor Rating Assessment Scale (TETRAS), we correlated the proposed performance metrics with the baseline tremor metrics and found that the OA of the SPN and RTN tasks were strongly correlated with baseline tremor severity (R²=0.57 and R²=0.83). We also found that the TP in the MDT tasks were strongly correlated with tremor frequency (R²=0.70). In addition, as the OA of the SPN and RTN tasks was correlated with tremor severity and frequency, it may represent an independent metric that increases the dimensionality of the characterization of an individuals tremor. Thus, this pilot study of the analysis of those with ET-associated tremor performing Fitts law tasks demonstrates the feasibility of introducing a new tremor metric that can be expanded for repeatable multi-dimensional data analyses.

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.

Visualisation of Parkinsonian, essential and physiological tremor planes in 3Dspace

Based on the fact that tremors display some distinct 3D spatial characteristics, we decided to visualise tremor planes in 3D space. We obtained 3-axial linear accelerometer signals of hand tremors from 58 patients with Parkinson´s disease (PD), 37 with isolated resting tremor (iRT), 75 with essential tremor (ET), and 44 healthy volunteers with physiological tremor (Ph). For each group analysis was done with subsequent spatial 3D regression of the input data i.e. along the x, y and z axes; the projected vector lengths in the individual (vertical transversal XY, vertical longitudinal XZ and horizontal YZ) reference frame planes and their angles. Most meaningful and statistically significant differences were found in the analyses of the 3D vector lengths. The tremor of the PD and the iRT group was oriented mainly in the horizontal YZ plane. The tremors of the patients with ET and Ph were oriented approximately in the midway between the all three referential planes with less tilt toward the vertical longitudinal XZ plane.

Automatic Resting Tremor Assessment in Parkinson's Disease Using Smartwatches and Multitask Convolutional Neural Networks

Resting tremor in Parkinson's disease (PD) is one of the most distinctive motor symptoms. Appropriate symptom monitoring can help to improve management and medical treatments and improve the patients' quality of life. Currently, tremor is evaluated by physical examinations during clinical appointments; however, this method could be subjective and does not represent the full spectrum of the symptom in the patients' daily lives. In recent years, sensor-based systems have been used to obtain objective information about the disease. However, most of these systems require the use of multiple devices, which makes it difficult to use them in an ambulatory setting. This paper presents a novel approach to evaluate the amplitude and constancy of resting tremor using triaxial accelerometers from consumer smartwatches and multitask classification models. These approaches are used to develop a system for an automated and accurate symptom assessment without interfering with the patients' daily lives. Results show a high agreement between the amplitude and constancy measurements obtained from the smartwatch in comparison with those obtained in a clinical assessment. This indicates that consumer smartwatches in combination with multitask convolutional neural networks are suitable for providing accurate and relevant information about tremor in patients in the early stages of the disease, which can contribute to the improvement of PD clinical evaluation, early detection of the disease, and continuous monitoring.

Essential Tremor - A Cerebellar Driven Disorder?

Abnormal tremors are the most common of all movement disorders. In this review we focus on the role of the cerebellum in Essential Tremor, a highly debilitating but poorly treated movement disorder. We propose a variety of mechanisms driving abnormal burst firing of deep cerebellar nuclei neurons as a key initiator of tremorgenesis in Essential Tremor. Targetting these mechanisms may generate more effective treatments for Essential Tremor.

Impaired Hand Dexterity Function in a Non-human Primate Model with Chronic Parkinson's Disease

Symptoms of Parkinson’s disease (PD) caused by loss of dopaminergic neurons are accompanied by movement disorders, including tremors, rigidity, bradykinesia, and akinesia. Non-human primate (NHP) models with PD play an essential role in the analysis of PD pathophysiology and behavior symptoms. As impairments of hand dexterity function can affect activities of daily living in patients with PD, research on hand dexterity function in NHP models with chronic PD is essential. Traditional rating scales previously used in the evaluation of animal spontaneous behavior were insufficient due to factors related to subjectivity and passivity. Thus, experimentally designed applications for an appropriate apparatus are necessary. In this study, we aimed to longitudinally assess hand dexterity function using hand dexterity task (HDT) in NHP-PD models. To validate this assessment, we analyzed the alteration in Parkinsonian tremor signs and the functionality of presynaptic dopaminergic neuron using positron emission tomography imaging of dopamine transporters in these models. In addition, a significant inverse correlation between HDT and DAT level was identified, but no local bias was found. The correlation with intention tremor signs was lower than the resting tremor. In conclusion, the evaluation of HDT may reflect behavioral symptoms of NHP-PD models. Furthermore, HDT was effectively used to experimentally distinguish intention tremors from other tremors.

Functional Recovery in Parkinson's Disease: Current State and Future Perspective

Parkinson’s disease (PD) is one of the most frequent neurodegenerative disorders, affecting not only the motor function but also limiting the autonomy of affected people. In the last decade, the physical exercises of different intensities carried out by kinetic therapeutic activities, by robotic technologies or with the participation of sensory cues, have become increasingly appreciated in the management of Parkinson’s disease impairments. The aim of this paper was to evaluate the impact of physical exercises with and without physical devices on the motor and cognitive variables of PD patients. In order to achieve our objectives, we performed a systematic review of available original articles based on the impact of kinetic therapeutic activity. Through the search strategy, we selected original papers that were laboriously processed using characteristics related to physical therapy, or the tools used in physiological and psychological rehabilitation strategies for PD patients. In this study, we presented the most current intervention techniques in the rehabilitation programs of patients with Parkinson’s disease, namely the use of assisted devices, virtual imagery or the performing of physical therapies that have the capacity to improve walking deficits, tremor and bradykinesia, to reduce freezing episodes of gait and postural instability, or to improve motor and cognitive functions.

Movement Disorder as Unusual Manifestation of Chiari Malformation Type II in a Newborn

Chiari malformation type II (CM-II) is a hindbrain developmental malformation. Movement disorders are rarely described as associated with this condition. We describe the case of a newborn affected by CM-II presenting with head and neck tremors a few days after myelomeningocele repair surgery. Later, self-resolving episodes of expiratory apneas arose. Cranial ultrasounds showed progressive ventricular dilatation. She underwent ventriculoperitoneal shunt followed by craniocervical bony decompression. After surgery, both apnea and tremors disappeared. This particular presentation of CM-II is very rare and potentially difficult to diagnose.

Rebound effect in deep brain stimulation for essential tremor and symptom severity estimation from neural data

Deep brain stimulation (DBS) is a safe and established treatment for essential tremor (ET). However, there remains considerable room for improvement due to concerns associated with the initial implant surgery, semi-regular revision surgeries for battery replacements, and side effects including paresthesia, gait ataxia, and emotional disinhibition that have been associated with continuous, or conventional, DBS (cDBS) treatment. Adaptive DBS (aDBS) seeks to ameliorate some of these concerns by using feedback from either an external wearable or implanted sensor to modulate stimulation parameters as needed. aDBS has been demonstrated to be as or more effective than cDBS, but the purely binary control system most commonly deployed by aDBS systems likely still provides sub-optimal treatment and may introduce new issues. One example of these issues is rebound effect, in which the tremor symptoms of an ET patient receiving DBS therapy temporarily worsen after cessation of stimulation before leveling out to a steady state. Here is presented a quantitative analysis of rebound effect in 3 patients receiving DBS for ET. Rebound was evident in all 3 patients by both clinical assessment and inertial measurement unit data, peaking by the latter at T_p = 6.65 minutes after cessation of stimulation. Using features extracted from neural data, linear regression was applied to predict tremor severity, with $R_{avg{\text{ }}}^2 = 0.82$. These results strongly suggest that rebound effect and the additional information made available by rebound effect should be considered and exploited when designing novel aDBS systems.

An Overview of Acoustic-Based Interventions to Improve Motor Symptoms in Parkinson's Disease

Parkinson’s disease (PD) is characterized by motor and cognitive deficits that negatively impact on activities of daily living. While dopaminergic medications are used to attenuate motor symptoms, adjuvant therapies such as acoustic-based non-pharmacological interventions are used as a complement to standard drug treatments. At present, preliminary studies of acoustic-based interventions such as rhythmic-auditory stimulation (RAS) and vibroacoustic therapy (VAT) suggest two competing hypotheses: (1) RAS may recruit alternative motor networks that may bypass faulty spatiotemporal motor networks of movement in PD; or (2) the use of RAS enhances BG function through entrainment of beta oscillatory activities. In this mini review article, we discuss the mechanisms underlying the role of acoustic-based interventions and how it may serve to improve motor deficits such as gait impairments and tremors. We further provide suggestions for future work that may use a combination of RAS, VAT, and physical therapy to improve motor function in PD.

The external phenotype of aging

Aging is widely studied as a physiological process. Segmental aging can also occur prematurely in Mendelian disorders, and these can act this way as excellent sources of information, specifically for the underlying mechanisms. Adequate recognition of such aging characteristics in Mendelian disorders needs a well-defined phenotype of aging. Here the external phenotype of aging is described that can be recognized in the consulting room without major additional studies. Existing definitions of the signs and symptoms in Elements of Morphology or Human Phenotype Ontology are added or a new definition is suggested if none is available.

A Wearable System for Attenuating Essential Tremor Based on Peripheral Nerve Stimulation

OBJECTIVE

Currently available treatments for kinetic tremor can cause intolerable side effects or be highly invasive and expensive. Even though several studies have shown the positive effects of external feedback (i.e., electrical stimulation) for suppressing tremor, such approaches have not been fully integrated into wearable real-time feedback systems.

METHOD

We have developed a wireless wearable stimulation system that analyzes upper limb tremor using a three-axis accelerometer and that modulates/attenuates tremor using peripheral-nerve electrical stimulation with adjustable stimulation parameters and a real-time tremor detection algorithm. We outfitted nine subjects with tremor with a wearable system and a set of surface electrodes placed on the skin overlying the radial nerve and tested the effects of stimulation with nine combinations of parameters for open- and closed-loop stimulation on tremor. To quantify the effects of the stimulation, we measured tremor movements, and analyzed the dominant tremor frequency and tremor power.

RESULTS

Baseline tremor power gradually decreased over the course of 18 stimulation trials. During the last trial, compared with the control trial, the reduction rate of tremor power was 42.17 ± 3.09%. The dominant tremor frequency could be modulated more efficiently by phase-locked closed-loop stimulation. The tremor power was equally reduced by open- and closed-loop stimulation.

CONCLUSION

Peripheral nerve stimulation significantly affects tremor, and stimulation parameters need to be optimized to modulate tremor metrics. Clinical Impact: This preliminary study lays the foundation for future studies that will evaluate the efficacy of the proposed closed-loop peripheral nerve stimulation method in a larger group of patients with kinetic tremor.

PHTNet: Characterization and Deep Mining of Involuntary Pathological Hand Tremor using Recurrent Neural Network Models

The global aging phenomenon has increased the number of individuals with age-related neurological movement disorders including Parkinson's Disease (PD) and Essential Tremor (ET). Pathological Hand Tremor (PHT), which is considered among the most common motor symptoms of such disorders, can severely affect patients' independence and quality of life. To develop advanced rehabilitation and assistive technologies, accurate estimation/prediction of nonstationary PHT is critical, however, the required level of accuracy has not yet been achieved. The lack of sizable datasets and generalizable modeling techniques that can fully represent the spectrotemporal characteristics of PHT have been a critical bottleneck in attaining this goal. This paper addresses this unmet need through establishing a deep recurrent model to predict and eliminate the PHT component of hand motion. More specifically, we propose a machine learning-based, assumption-free, and real-time PHT elimination framework, the PHTNet, by incorporating deep bidirectional recurrent neural networks. The PHTNet is developed over a hand motion dataset of 81 ET and PD patients collected systematically in a movement disorders clinic over 3 years. The PHTNet is the first intelligent systems model developed on this scale for PHT elimination that maximizes the resolution of estimation and allows for prediction of future and upcoming sub-movements.

The Rehapiano-Detecting, Measuring, and Analyzing Action Tremor Using Strain Gauges

We have developed a device, the Rehapiano, for the fast and quantitative assessment of action tremor. It uses strain gauges to measure force exerted by individual fingers. This article verifies the device's capability to measure and monitor the development of upper limb tremor. The Rehapiano uses a precision, 24-bit, analog-to-digital converter and an Arduino microcomputer to transfer raw data via a USB interface to a computer for processing, database storage, and evaluation. First, our experiments validated the device by measuring simulated tremors with known frequencies. Second, we created a measurement protocol, which we used to measure and compare healthy patients and patients with Parkinson's disease. Finally, we evaluated the repeatability of a quantitative assessment. We verified our hypothesis that the Rehapiano is able to detect force changes, and our experimental results confirmed that our system is capable of measuring action tremor. The Rehapiano is also sensitive enough to enable the quantification of Parkinsonian tremors.

Wearable Sensors for Estimation of Parkinsonian Tremor Severity during Free Body Movements

Tremor is one of the main symptoms of Parkinson's Disease (PD) that reduces the quality of life. Tremor is measured as part of the Unified Parkinson Disease Rating Scale (UPDRS) part III. However, the assessment is based on onsite physical examinations and does not fully represent the patients' tremor experience in their day-to-day life. Our objective in this paper was to develop algorithms that, combined with wearable sensors, can estimate total Parkinsonian tremor as the patients performed a variety of free body movements. We developed two methods: an ensemble model based on gradient tree boosting and a deep learning model based on long short-term memory (LSTM) networks. The developed methods were assessed on gyroscope sensor data from 24 PD subjects. Our analysis demonstrated that the method based on gradient tree boosting provided a high correlation (r = 0.96 using held-out testing and r = 0.93 using subject-based, leave-one-out cross-validation) between the estimated and clinically assessed tremor subscores in comparison to the LSTM-based method with a moderate correlation (r = 0.84 using held-out testing and r = 0.77 using subject-based, leave-one-out cross-validation). These results indicate that our approach holds great promise in providing a full spectrum of the patients' tremor from continuous monitoring of the subjects' movement in their natural environment.

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.

Split spinal cord malformations in 4 Holstein Friesian calves

Background

The split spinal cord malformation (SSCM) is an uncommon congenital malformation of the vertebral canal in which parts of the spinal cord are longitudinally duplicated. In SSCM Type I, each spinal cord has its own dura tube. In the SSCM Type II, both parts of the spinal cord are surrounded by a common dura tube.

Cases presentation

During the clinical examination one calf showed ambulatory paresis and 3 calves non-ambulatory paraparesis. Calf 4 additionally had a congenital tremor. The examination of calf 4 using magnetic resonance imaging (MRI) showed a median hydrosyringomyelia at the level of the 4th lumbar vertebra. The caudal part of this liquid-filled cavity was split longitudinally through a thin septum. From there, the spinal cord structures duplicated with an incomplete division, so that the transverse section of the spinal cord appeared peanut-shaped and in each half a central canal could be observed. The pathological-anatomical examination after euthanasia showed a duplication of the spinal cord in the area of the lumbar vertebral column in all calves. The histopathological examination revealed two central lumbar vertebral column channels. The two spinal cord duplicates were each surrounded by two separate meninges in calf 2 (SSCM type I); in the other calves (1, 3, 4, and) the two central canals and the spinal cord were covered by a common meninx (SSCM type II). A pedigree analysis of calves 2, 3 and 4 showed a degree of relationship suggestive of a hereditary component. This supports the hypothesis of a possible recessive inheritance due to common ancestors, leading to partial genetic homozygosity.

Conclusions

The clinical appearance of SSCM can vary widely. In calves with congenital paralysis SSCM should always be considered as a differential diagnosis. A reliable diagnosis intra vitam is possible only with laborious imaging procedures such as MRI. Further studies on the heritability of this malformation are necessary to confirm a genetic cause of this disease.

The prevalence of essential tremor in Edirne and its counties accompanied comorbid conditions

Objective: We aimed to determine the prevalence and risk factors of Essential Tremor (ET) in Edirne and its districts, located in Western Thrace, which is the most western part of Turkey. Methods: In this study, 3008 individuals who could communicate and agreed to participate in the study were evaluated. To obtain the data from the applicants in 30 Family Health Centres in Edirne and its districts, a face-to-face questionnaire that consisted of 37 questions was prepared by the researchers. The questionnaire included general information, questions to evaluate potential concomitant comorbid conditions and questions regarding the symptomatology used in ET diagnosis, as well as questions to evaluate ET severity, was examined with the spiral test. Patients were classified by using the Washington Heights-Inwood Genetic Study of Essential Tremor (WHIGET) diagnostic and clinical evaluation scale. According to the diagnostic criteria for ET (used in participants who were examined and in those whose medical records were reviewed) were similar to those used in astudy conducted in Turkey. Results: Of 3008 individuals, 173 were diagnosed with ET according to the questionnaire results from Edirne and its districts, and the prevalence of ET was 5.8%. Approximately, 43.4% of the patients with ET were male, and 56.6% were female, which was not significantly different (p > 0.05). Participants with tremor related to alcohol withdrawal, hyperthyroidism, anxiety, depression other known causes of tremor were not considered to have ET. Thyroid disease was identified in 0.0% of the cases, and the control group was detected in 1.4%, which was not significantly different (p = 0.170). Psychiatric disease was identified in 0.0% of the cases, and the control group was detected in 1.3%, which was not significantly different (p = 0.271). Conclusions: ET prevalence studies will increase the awareness of the community and provide early diagnosis and treatment, as well as serve as a basis to reduce morbidity and improve the quality of life.

Tremor after long term lithium treatment; is it cortical myoclonus?

Introduction

Tremor is a common side effect of treatment with lithium. Its characteristics can vary and when less rhythmical, distinction from myoclonus can be difficult.

Methods

We identified 8 patients on long-term treatment with lithium that developed upper limb tremor. All patients were assessed clinically and electrophysiologically, with jerk-locked averaging (JLA) and cross-correlation (CC) analysis, and five of them underwent brain MRI examination including spectroscopy (MRS) of the cerebellum.

Results

Seven patients (6 female) had action and postural myoclonus and one a regular postural and kinetic tremor that persisted at rest. Mean age at presentation was 58 years (range 42-77) after lengthy exposure to lithium (range 7-40 years). During routine monitoring all patients had lithium levels within the recommended therapeutic range (0.4-1 mmol/l). There was clinical and/or radiological evidence (on cerebellar MRS) of cerebellar dysfunction in 6 patients. JLA and/or CC suggested a cortical generator of the myoclonus in seven patients. All seven were on antidepressants and three additionally on neuroleptics, four of them had gluten sensitivity and two reported alcohol abuse.

Conclusions

A synergistic effect of different factors appears to be contributing to the development of cortical myoclonus after chronic exposure to lithium. We hypothesise that the cerebellum is involved in the generation of cortical myoclonus in these cases and factors aetiologically linked to cerebellar pathology like gluten sensitivity and alcohol abuse may play a role in the development of myoclonus. Despite the very limited evidence in the literature, lithium induced cortical myoclonus may not be so rare.

Familial adult myoclonic epilepsy: A new expansion repeats disorder

Familial adult myoclonic epilepsy (FAME), also described with different acronyms (ADCME, BAFME, FEME, FCTE and others), is a high-penetrant autosomal dominant condition featuring cortical hand tremors, myoclonic jerks, and occasional/rare convulsive seizures. Prevalence is unknown since this condition is often under-recognized, but it is estimated to be less than 1/35,000. The disease usually starts in the second decade of life and has been genetically associated with at least 4 different loci (8q24, 2p11.1-q12.2, 5p15.31-p15 and 3q26.32-3q28). Recently, the expansion of non coding TTTTA and TTTCA repeats has been identified as the causative mutation in Japanese families linked to the 8q24. The diagnosis is supported by clinical features and electrophysiological investigations as jerk-locked back averaging, C-reflex, and somatosensory-evoked potential. Photic stimulation, emotional stress, and sleep deprivation may trigger both tonic-clonic and myoclonic seizures. FAME has a slow but progressive clinical course occurring with intellectual disability and worsening of both tremor and myoclonus although with a less severe decline compared to other progressive myoclonic epilepsies. Valproate, levetiracetam, and benzodiazepines are considered the first-line treatments.

Analyses of physiological wrist tremor with increased muscle activity during bench press exercise

[Purpose]

To date, there have been no studies on the response of wrist tremor to increased muscle activity during exercise. This study aimed to evaluate the wrist tremor response with increasing muscle activity during bench press exercise.

[Methods]

Triceps muscle activity and wrist tremor response were measured by electromyography and an accelerometer, respectively, during bench press exercise in 11 healthy men without weight-training experience. Subjects performed bench press at 30% repetition maximum (RM), and the rating of perceived exertion (RPE) and lactate concentration were measured before and after exercise. One week later, an equivalent number of bench presses at 30% RM was performed without weight load as a control trial (CT).

[Results]

RPEs and lactate concentrations significantly increased after resistance exercise (30% RM) from 7.4 to 14.3 and 1.7 to 4.9, respectively (P<.01), but no such difference was observed in the CT. Muscle activity linearly increased during the 30% RM exercise, and wrist tremors were shown to linearly decrease. A strong negative correlation was observed between the two variables (r=−0.88, P<.001).

[Conclusion]

We found that wrist tremors during resistance exercise, as measured using an accelerometer, can be used to predict muscle activity.

Robot-assisted tremor control for performance enhancement of retinal microsurgeons

Pars plana vitrectomy is a challenging, minimally invasive microsurgical procedure due to its intrinsic manoeuvres and physiological limits that constrain human capability. An important human limitation is physiological hand tremor, which can significantly increase the risk of iatrogenic retinal damage resulting from unintentional manoeuvres that affect anatomical and functional surgical outcomes. The limitations imposed by normal physiological tremor are more evident and challenging during ‘micron-scale’ manoeuvres such as epiretinal membrane and internal limiting membrane peeling, and delicate procedures requiring coordinated bimanual surgery such as tractional retinal detachment repair. Therefore, over the previous three decades, attention has turned to robot-assisted surgical devices to overcome these challenges. Several systems have been developed to improve microsurgical accuracy by cancelling hand tremor and facilitating faster, safer and more effective microsurgeries. By markedly reducing tremor, microsurgical precision is improved to a level beyond present human capabilities. In conclusion, robotics offers potential advantages over free-hand microsurgery as it is currently performed during ophthalmic surgery and opens the door to a new class of revolutionary microsurgical modalities. The skills transfer that is beyond human capabilities to robotic technology is a logical next step in microsurgical evolution.

Could Wearable and Mobile Technology Improve the Management of Essential Tremor?

Essential tremor (ET) is the most common movement disorder. Individuals exhibit postural and kinetic tremor that worsens over time and patients may also exhibit other motor and non-motor symptoms. While millions of people are affected by this disorder worldwide, several barriers impede an optimal clinical management of symptoms. In this paper, we discuss the impact of ET on patients and review major issues to the optimal management of ET; from the side-effects and limited efficacy of current medical treatments to the limited number of people who seek treatment for their tremor. Then, we propose seven different areas within which mobile and wearable technology may improve the clinical management of ET and review the current state of research in these areas.

[Pathophysiology of tremor]

Tremor is clinically defined as a rhythmic, oscillating movement of parts of the body, which functionally leads to impairment of the coordination and execution of targeted movements. It can be a symptom of a primary disease, such as resting tremor in Parkinson's disease or occur as an independent disease, such as essential or orthostatic tremor. For the development of tremor, cerebral components as well as mechanisms at the spinal and muscular level play an important role. This review presents the results of new imaging and electrophysiological studies that have led to important advances in our understanding of the pathophysiology of tremor. We discuss pathophysiological models for the development of resting tremor in Parkinson's disease, essential and orthostatic tremor. We describe recent developments starting from the classical generator model, with an onset of pathological oscillations in distinct cerebral regions, to a network perspective in which tremor arises and spreads through existing anatomical or newly emerged pathological brain networks. In particular translational approaches are presented and discussed. These could serve in the future as a basis for the development of new therapeutic strategies.

Design of a noninvasive and smart hand tremor attenuation system with active control: a simulation study

This paper presents the design and simulation of a handheld device for people with hand tremor, such as Parkinson's and essential tremor patients. This device can be used as a pen for smartphones or as a spoon. The designed system includes two links, which are connected to two servomotors, which are mounted in orthogonal directions. To attenuate the effect of hand tremor on the tip of device, PID and computed torque methods are used to actively control the system. These controllers are used to control the rotation of the motors for moving the links in opposite directions of the hand tremor. Performance of the device with mentioned controllers is studied for different applications and finally, the results of both controllers are discussed and compared. Based on the presented results in this study, the designed device is able to suppress the hand tremor up to 75% during eating and 65% during following a spiral pattern. Graphical abstract Design of a noninvasive and smart hand tremor attenuation system: a simulation study.

Current understanding of the molecular mechanisms in Parkinson's disease: Targets for potential treatments

Gradual degeneration and loss of dopaminergic neurons in the substantia nigra, pars compacta and subsequent reduction of dopamine levels in striatum are associated with motor deficits that characterize Parkinson’s disease (PD). In addition, half of the PD patients also exhibit frontostriatal-mediated executive dysfunction, including deficits in attention, short-term working memory, speed of mental processing, and impulsivity. The most commonly used treatments for PD are only partially or transiently effective and are available or applicable to a minority of patients. Because, these therapies neither restore the lost or degenerated dopaminergic neurons, nor prevent or delay the disease progression, the need for more effective therapeutics is critical. In this review, we provide a comprehensive overview of the current understanding of the molecular signaling pathways involved in PD, particularly within the context of how genetic and environmental factors contribute to the initiation and progression of this disease. The involvement of molecular chaperones, autophagy-lysosomal pathways, and proteasome systems in PD are also highlighted. In addition, emerging therapies, including pharmacological manipulations, surgical procedures, stem cell transplantation, gene therapy, as well as complementary, supportive and rehabilitation therapies to prevent or delay the progression of this complex disease are reviewed.

Clinical Assessments in Parkinson's Disease: Scales and Monitoring

Measurement of disease state is essential in both clinical practice and research in order to assess the severity and progression of a patient's disease status, effect of treatment, and alterations in other relevant factors. Parkinson's disease (PD) is a complex disorder expressed through many motor and nonmotor manifestations, which cause disabilities that can vary both gradually over time or come on suddenly. In addition, there is a wide interpatient variability making the appraisal of the many facets of this disease difficult. Two kinds of measure are used for the evaluation of PD. The first is subjective, inferential, based on rater-based interview and examination or patient self-assessment, and consist of rating scales and questionnaires. These evaluations provide estimations of conceptual, nonobservable factors (e.g., symptoms), usually scored on an ordinal scale. The second type of measure is objective, factual, based on technology-based devices capturing physical characteristics of the pathological phenomena (e.g., sensors to measure the frequency and amplitude of tremor). These instrumental evaluations furnish appraisals with real numbers on an interval scale for which a unit exists. In both categories of measures, a broad variety of tools exist. This chapter aims to present an up-to-date summary of the most relevant characteristics of the most widely used scales, questionnaires, and technological resources currently applied to the assessment of PD. The review concludes that, in our opinion: (1) no assessment methods can substitute the clinical judgment and (2) subjective and objective measures in PD complement each other, each method having strengths and weaknesses.