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Resting tremor is the most common presenting motor symptom in Parkinson's disease (PD). The supplementary motor area (SMA) is a main target of the basal-ganglia-thalamo-cortical circuit and has direct, facilitatory connections with the primary motor cortex (M1), which is important for the execution of voluntary movement. Dopamine potentially modulates SMA and M1 activity, and both regions have been implicated in resting tremor. This study investigated SMA-M1 connectivity in individuals with PD ON and OFF dopamine medication, and whether SMA-M1 connectivity is implicated in resting tremor. Dual-site transcranial magnetic stimulation was used to measure SMA-M1 connectivity in PD participants ON and OFF levodopa. Resting tremor was measured using electromyography and accelerometry. Stimulating SMA inhibited M1 excitability OFF levodopa, and facilitated M1 excitability ON levodopa. ON medication, SMA-M1 facilitation was significantly associated with smaller tremor than SMA-M1 inhibition. The current findings contribute to our understanding of the neural networks involved in PD which are altered by levodopa medication and provide a neurophysiological basis for the development of interventions to treat resting tremor.

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The article is of a review nature and is devoted to tremor, one of the maladaptive and difficult-to-treat symptoms of Parkinson's disease (PD). Along with the classic rest tremor, patients with PD may experience tremor of other modalities: postural tremor, kinetic tremor, which reflects a multimodal mechanism of tremor formation involving multiple neurotransmitter systems. The unpredictable response to therapeutic options, the ambiguous response to levodopa, also reflects the role of multiple underlying pathophysiological processes. Among the drug methods of tremor correction, preference is given to dopamine receptor agonists - due to the spectrum of their pharmaceutical action, high efficiency in relation to all leading motor and a number of non-motor manifestations. The evidence for advanced neurosurgical, non-invasive modalities is mixed, and there are insufficient comparative studies to assess their efficacy in patients with tremor-dominant forms of PD.

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Introduction: Parkinson's disease (PD) is a neurodegenerative disorder commonly characterized by motor impairments. The development of mobile health (m-health) technologies, such as wearable and smart devices, presents an opportunity for the implementation of clinical tools that can support tasks such as early diagnosis and objective quantification of symptoms. Objective: This study evaluates a framework to monitor motor symptoms of PD patients based on the performance of standardized exercises such as those performed during clinic evaluation. To implement this framework, an m-health tool named Monipar was developed that uses off-the-shelf smart devices. Methods: An experimental protocol was conducted with the participation of 21 early-stage PD patients and 7 healthy controls who used Monipar installed in off-the-shelf smartwatches and smartphones. Movement data collected using the built-in acceleration sensors were used to extract relevant digital indicators (features). These indicators were then compared with clinical evaluations performed using the MDS-UPDRS scale. Results: The results showed moderate to strong (significant) correlations between the clinical evaluations (MDS-UPDRS scale) and features extracted from the movement data used to assess resting tremor (i.e., the standard deviation of the time series: r = 0.772, p < 0.001) and data from the pronation and supination movements (i.e., power in the band of 1-4 Hz: r = -0.662, p < 0.001). Conclusion: These results suggest that the proposed framework could be used as a complementary tool for the evaluation of motor symptoms in early-stage PD patients, providing a feasible and cost-effective solution for remote and ambulatory monitoring of specific motor symptoms such as resting tremor or bradykinesia.

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Parkinson's disease (PD) is one of the most common neurological ailments. With diverse motor affectations (postural instability, resting tremor, bradykinesia, and rigidity), people with Parkinson's disease (PwP) have a broad spectrum of non-motor symptoms. These include autonomic function changes, cognitive deterioration, neuropsychiatric difficulties, and sleep interruptions. Psychological disturbances, such as anxiety and sadness, are common among PwP. This discomfort is often accompanied by a decrease in general functioning, both at work and in social contacts. Furthermore, people who are experiencing psychological distress have a quick decrease in both physical and cognitive capacities. Furthermore, Pwp who also suffer from anxiety and depression are more likely to acquire dementia. It is worth noting that studies have shown good outcomes in the treatment of physical disabilities in PWP and the various therapeutics available for each affected body part, such as in the legs when they have walking problems, resting tremor in their hands, or micrography, which is a common symptom in these patients. The medical research databases PubMed/Medline, Google Scholar, and the Cochrane Library were used to look for relevant materials. Upon meticulous scrutiny, a thorough investigation was conducted on the papers at hand. A total of 10 publications were meticulously selected based on stringent qualifying criteria. The present investigation examines various perspectives regarding the physical rehabilitation of individuals diagnosed with PD. The majority of therapeutic interventions employed revolve around cutting-edge technologies, such as virtual reality (VR), combined with exercise regimens. These interventions have demonstrated notable statistical significance in terms of enhancing various physical aspects, including endurance, performance, gait capacity, perception, and overall independence in daily life activities. One of the gathered studies makes use of the therapeutic benefits of yoga to help PwP deal with their anxiety and improve their mental health. Based on the aforementioned information, further investigation is required to ascertain the optimal approach for physical rehabilitation management and develop diverse strategies aimed at assisting individuals with PD in attaining physical autonomy.

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PURPOSE: Cerebellum modulates the amplitude of resting tremor in Parkinson's disease (PD) via cerebello-thalamo-cortical (CTC) circuit. Tremor-related white matter alterations have been identified in PD patients by pathological studies, but in vivo evidence is limited; the influence of such cerebellar white matter alterations on tremor-related brain network, including CTC circuit, is also unclear. In this study, we investigated the cerebral and cerebellar white matter alterations in PD patients with resting tremor using diffusion tensor imaging (DTI). METHODS: In this study, 30 PD patients with resting tremor (PDWR), 26 PD patients without resting tremor (PDNR), and 30 healthy controls (HCs) from the Parkinson's Progression Markers Initiative (PPMI) cohort were included. Tract-based spatial statistics (TBSS) and region of interest-based analyses were conducted to determine white matter difference. Correlation analysis between DTI measures and clinical characteristics was also performed. RESULTS: In the whole brain, TBSS and region of interest-based analyses identified higher fractional anisotropy (FA) value, lower mean diffusivity (MD) value, and lower radial diffusivity (RD) in multiple fibers. In the cerebellum, TBSS analysis revealed significantly higher FA value, decreased RD value as well as MD value in multiple cerebellar tracts including the inferior cerebellar peduncle (ICP) and middle cerebellar peduncle (MCP) when comparing the PDWR with HC, and higher FA value in the MCP when compared with PDNR. CONCLUSION: We identified better white matter integrity in the cerebrum and cerebellum in PDWR indicating a potential association between the cerebral and cerebellar white matter and resting tremor in PD.

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Background: Valproic acid is associated with increased risks of tremor and parkinsonism. Case Report: A 67-year-old man with a diagnosis of epilepsy who had been treated with valproic acid (VPA) for 32 years noticed right-dominant upper-limb resting tremor accompanied by mild rigidity and bradykinesia. He was initially diagnosed with tremor-dominant Parkinson's disease (TDPD), but dopamine transporter single-photon emission computed tomography demonstrated no nigrostriatal degeneration. At 3 months after discontinuing VPA, his symptoms dramatically improved. Discussion: VPA-induced tremor usually consists of postural or kinetic tremor without asymmetry. Our case indicated that careful evaluation is needed, even in cases of asymmetrical resting tremor and mild parkinsonism resembling TDPD after long term exposure to VPA. Highlights: We report an atypical case of valproic acid-induced tremor and parkinsonism that mimics tremor-dominant Parkinson's disease. Physicians should not exclude the possible relation to valproic acid in patients presenting unilateral resting tremor and parkinsonism even in the absence of long-term side effects.

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BACKGROUND: A representative symptom of Parkinson's disease (PD) is resting tremor. The clinical manifestation of scans without evidence of dopaminergic deficit (SWEDD) is similar to it of PD, though the phenomenology of SWEDD is not well known. OBJECTIVE: In the present study, the resting tremor of 9 SWEDD patients was quantitatively compared with that of 11 PD patients. METHODS: Four 3-axis gyro sensors were attached on the index finger, thumb, dorsum of the hand, and arm of the more tremulous side. Root mean square (RMS) angular speed and angular displacement as well as irregularity of angular speed and displacement were derived from the sensor data. RESULTS: Although disease duration and Hoehn and Yahr stages were comparable, SWEDD patients exhibited different tremor features from PD patients. Significantly faster RMS angular speed and greater RMS angular displacement (p< 0.05) were observed in PD patients than in SWEDD patients. The irregularity of angular displacement of pitch direction at the dorsum of the hand was greater in SWEDD patients than in PD patients (p< 0.05). CONCLUSION: These results indicate that quantitative indices obtained from resting tremor task could be important biomarkers for identifying potential patients with SWEDD among patients diagnosed with PD.

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We report a patient with tremor-dominant Parkinson's disease who had a mild cavitation bioeffect during magnetic resonance-guided focused ultrasound thalamotomy. During the aligning phase with low-energy sonication, cavitation caused mild dysarthria and paresthesia, prompting treatment cessation. At the same time, tremor and rigidity improved. MRI revealed extensive high-intensity lesions in the thalamus 1 day after the procedure followed by steroid infusion, which resulted in resolution of adverse events. Tremor and rigidity improved 1.5 years after the procedure. Although cavitation can relieve tremors and rigidity, it should be carefully monitored due to potential permanent adverse events by unpredictable and unknown behaviors.

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Treatment of tremors, such as in essential tremor (ET) and Parkinson's disease (PD) is mostly ineffective. Exact tremor pathomechanisms are unknown and relevant animal models are missing. GABA-A receptor is a target for tremorolytic medications, but current non-selective drugs produce side effects and have safety liabilities. The aim of this study was a search for GABA-A subunit-specific tremorolytics using different tremor-generating mechanisms. Two selective positive allosteric modulators (PAMs) were tested. Zolpidem, targeting GABA-A α1, was not effective in models of harmaline-induced ET, pimozide- or tetrabenazine-induced tremulous jaw movements (TJMs), while the novel GABA-A α2/3 selective MP-III-024 significantly reduced both the harmaline-induced ET tremor and pimozide-induced TJMs. While zolpidem decreased the locomotor activity of the rats, MP-III-024 produced small increases. These results provide important new clues into tremor suppression mechanisms initiated by the enhancement of GABA-driven inhibition in pathways controlled by α2/3 but not α1 containing GABA-A receptors. Tremor suppression by MP-III-024 provides a compelling reason to consider selective PAMs targeting α2/3-containing GABA-A receptors as novel therapeutic drug targets for ET and PD-associated tremor. The possibility of the improved tolerability and safety of this mechanism over non-selective GABA potentiation provides an additional rationale to further pursue the selective α2/3 hypothesis.

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In resting tremor, the body part is in complete repose and often dampens or subsides entirely with action. The most frequent cause of resting tremors is known as idiopathic Parkinson's disease (PD). For examination, neurologists of patients with PD include tests such as finger-to-nose tests, walking back and forth in the corridor, and the pull test. This evaluation is focused on Unified Parkinson's disease rating scale (UPDRS), which is subjective as well as based on some daily life motor activities for a limited time frame. In this study, severity analysis is performed on an imbalanced dataset of patients with PD. This is the reason why the classification of various data containing imbalanced class distribution has endured a notable drawback of the performance achievable by various standard classification learning algorithms. In this work, we used resampling techniques including under-sampling, over-sampling, and a hybrid combination. Resampling techniques are incorporated with renowned classifiers, such as XGBoost, decision tree, and K-nearest neighbors. From the results, it is concluded that the Over-sampling method performed much better than under-sampling and hybrid sampling techniques. Among the over-sampling techniques, random sampling has obtained 99% accuracy using XGBoost classifier and 98% accuracy using the decision tree. Besides, it is observed that different resampling methods performed differently with various classifiers.

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BACKGROUND: Imaging studies investigating cerebellar gray matter (GM) in essential tremor (ET) showed conflicting results. Moreover, no large study explored the cerebellum in ET patients with resting tremor (rET), a syndrome showing enhanced blink reflex recovery cycle (BRrc). OBJECTIVE: To investigate cerebellar GM in ET and rET patients using voxel-based morphometry (VBM) analysis. METHODS: Seventy ET patients with or without resting tremor and 39 healthy controls were enrolled. All subjects underwent brain 3 T-MRI and BRrc recording. We compared the cerebellar GM volumes between ET (n = 40) and rET (n = 30) patients and controls through a VBM analysis. Moreover, we investigated possible correlations between cerebellar GM volume and R2 component of BRrc. RESULTS: rET and ET patients had similar disease duration. All rET patients and none of ET patients had enhanced BRrc. No differences in the cerebellar volume were found when ET and rET patients were compared to each other or with controls. By considering together the two tremor syndromes in a large patient group, the VBM analysis showed bilateral clusters of reduced GM volumes in Crus II in comparison with controls. The linear regression analysis in rET patients revealed a cluster in the left Crus II where the decrease in GM volume correlated with the R2BRrc increase. CONCLUSION: Our study suggests that ET and rET are different tremor syndromes with similar mild cerebellar gray matter involvement. In rET patients, the left Crus II may play a role in modulating the brainstem excitability, encouraging further studies on the role of cerebellum in these patients.

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Tremor is one of the most common movement disorders, though it can arise in the context of several unrelated neurological disorders whose pharmacology and anatomical origins differ greatly. Treatment of tremors can take advantage of several medications and neurosurgical treatments. Medications useful for treating tremor are discussed in this review, including those for action tremor as seen in essential tremor, the resting tremor of Parkinson's disease, orthostatic tremor, cerebellar tremor, Holmes tremor, dystonic tremor, and drug-induced tremors. A medication that is useful for most types of tremors is the beta-blocker propranolol, though even in essential tremor it can fail to be effective at tremor control. This article is part of the Special Issue "Tremor" edited by Daniel D. Truong, Mark Hallett, and Aasef Shaikh.

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Background: Resting tremor is a cardinal symptom of Parkinson's disease (PD) that contributes to the physical, emotional, and economic burden of the disease. Objective: The goal of this study was to investigate the safety, tolerability, and preliminary effectiveness of a novel wearable vibrotactile stimulation device on resting tremor in individuals with PD. Methods: Using a randomized cross-over design, subjects received two different vibrotactile stimulation paradigms (high amplitude patterned and low amplitude continuous) on two separate laboratory visits. On each visit, resting tremor was video recorded for 10 min at baseline and while the vibrotactile stimulation was applied. Tremor severity was scored by a blinded clinician. Results: Both vibration paradigms were well safe and well tolerated and resulted in a reduction in resting tremor severity with a moderate effect size (n = 44, p < 0.001, r = 0.37-0.54). There was no significant difference between the two vibration paradigms (p = 0.14). Conclusion: Short durations of vibrotactile stimulation delivered via wearable devices were safe and well tolerated and may attenuate resting tremor severity in individuals with PD. The sample size as well as the potential preliminary effectiveness revealed by two arms of the study could not eliminate the potential for a placebo effect.

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INTRODUCTION: Resting limb tremor (RLT) is a well known feature in parkinsonism. There is very little information on resting head tremor (RHT) in parkinsonism, and none in pathologically confirmed cases. The association between RLT and RHT remains uncertain. METHODS: A Caucasian male developed upper limb tremor and voice changes at age 70. He was first assessed at our clinic at age 72. At age 73 he developed resting head tremor (RHT) which prevented him from falling asleep. His status was documented in longitudinal follow-up at our clinic. He had a total of 14 clinical evaluations and four videos made over 6 years. Autopsy of the brain and spinal cord was performed. RESULTS: The resting head tremor improved on antiparkinsonian drugs and resolved completely after four years. Coincident with RHT remission, the upper limb tremor worsened and interfered with feeding, and his lower limb resting tremor became more pronounced. During his course he developed slow, scanning speech and all the cardinal motor findings of parkinsonism. There was no ophthalmoplegia. Post-mortem neuropathological examination revealed prominent progressive supranuclear palsy (PSP) changes and minor Lewy body pathology. CONCLUSION: This is the first autopsy confirmed case of parkinsonism with RHT. He had dual pathology. Dissociation between RHT and RLT indicates that the oscillatory brain centers for the two were different in this case.

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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.

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OBJECTIVES: Essential tremor with resting tremor (rET) often exhibits severer clinical features and more extensive functional impairment than essential tremor without resting tremor (ETwr). However, the pathophysiology of rET is still unclear. This study aims to use resting-state functional magnetic resonance imaging (rs-fMRI) to explore the alterations of brain activity between the drug-naïve patients of rET and ETwr. METHODS: We recruited 19 patients with rET, 31 patients with ETwr and 25 healthy controls (HCs) to undergo a 3.0-T rs-fMRI examination. The differences of regional brain spontaneous activity between the rET, ETwr and HCs, as well as between total ET (rET + ETwr) and HCs were measured by amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). The relationships between the altered brain measurements and the clinical scores were analyzed. RESULTS: Compared with HCs, both ET subgroups showed significantly decreased ALFF or fALFF values in the basal ganglia, inferior orbitofrontal gyrus and insula. The rET group specifically showed decreased ALFF values in the hippocampus and motor cortices, while the ETwr group specifically evidenced increased ALFF and fALFF values in the cerebellum. DISCUSSION: Regional spontaneous activity in rET and ETwr share common changes and have differences, which may suggest that the functional activities in the limbic system and cerebellum are different between the two subtypes. Improved insights into rET and ETwr subtypes and the different brain spontaneous activity will be valuable for improving our understanding of the pathophysiology of the disease.

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The pathophysiological mechanism of resting tremor in Parkinson's disease remains obscure. Spinal/peripheral mechanisms may modulate oscillatory activity from central origin, thereby changing amplitude and frequency of tremor in Parkinson's disease.

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The aim of this study is comparing the accuracies of machine learning algorithms to classify data concerning healthy subjects and patients with Parkinson's Disease (PD), toward different time window lengths and a number of features. Thirty-two healthy subjects and eighteen patients with PD took part on this study. The study obtained inertial recordings by using an accelerometer and a gyroscope assessing both hands of the subjects during hand resting state. We extracted time and temporal frequency domain features to feed seven machine learning algorithms: k-nearest-neighbors (kNN); logistic regression; support vector classifier (SVC); linear discriminant analysis; random forest; decision tree; and gaussian Naïve Bayes. The accuracy of the classifiers was compared using different numbers of extracted features (i.e., 272, 190, 136, 82, and 27) from different time window lengths (i.e., 1, 5, 10, and 15 s). The inertial recordings were characterized by oscillatory waveforms that, especially in patients with PD, peaked in a frequency range between 3 and 8 Hz. Outcomes showed that the most important features were the mean frequency, linear prediction coefficients, power ratio, power density skew, and kurtosis. We observed that accuracies calculated in the testing phase were higher than in the training phase. Comparing the testing accuracies, we found significant interactions among time window length and the type of classifier (p < 0.05). The study found significant effects on estimated accuracies, according to their type of algorithm, time window length, and their interaction. kNN presented the highest accuracy, while SVC showed the worst results. kNN feeding by features extracted from 1 and 5 s were the combination with more frequently highest accuracies. Classification using few features led to similar decision of the algorithms. Moreover, performance increased significantly according to the number of features used, reaching a plateau around 136. Finally, the results of this study suggested that kNN was the best algorithm to classify hand resting tremor in patients with PD.

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Introduction: Deep brain stimulation (DBS) is an effective therapy for resting tremor in Parkinson's disease (PD). However, quick and objective biomarkers for quantifying the efficacy of DBS intraoperatively are lacking. Therefore, we aimed to study how DBS modulates the intraoperative neuromuscular pattern of resting tremor in PD patients and to find predictive surface electromyography (sEMG) biomarkers for quantifying the intraoperative efficacy of DBS. Methods: Intraoperative sEMG of 39 PD patients with resting tremor was measured with the DBS on and off, respectively, during the intraoperative DBS testing stage. Twelve signal features (time and frequency domains) were extracted from the intraoperative sEMG data. These sEMG features were associated with the clinical outcome to evaluate the efficacy of intraoperative DBS. Also, an sEMG-based prediction model was established to predict the clinical improvement rate (IR) of resting tremor with DBS therapy. Results: A typical resting tremor with a peak frequency of 4.93 ± 0.98 Hz (mean ± SD) was measured. Compared to the baseline, DBS modulated significant neuromuscular pattern changes in most features except for the peak frequency, by decreasing the motor unit firing rate, amplitude, or power and by changing the regularity pattern. Three sEMG features were detected with significant associations with the clinical improvement rate (IR) of the tremor scale: peak frequency power (R = 0.37, p = 0.03), weighted root mean square (R = 0.42, p = 0.01), and modified mean amplitude power (R = 0.48, p = 0.003). These were adopted to train a Gaussian process regression model with a leave-one-out cross-validation procedure. The prediction values from the trained sEMG prediction model (1,000 permutations, p = 0.003) showed a good correlation (r = 0.47, p = 0.0043) with the true IR of the tremor scale. Conclusion: DBS acutely modulated the intraoperative resting tremor, mainly by suppressing the amplitude and motor unit firing rate and by changing the regularity pattern, but not by modifying the frequency pattern. Three features showed strong robustness and could be used as quick intraoperative biomarkers to quantify and predict the efficacy of DBS in PD patients with resting tremor.