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Background: The cardinal motor symptoms of Parkinson's disease (PD) include rigidity, bradykinesia, and rest tremor. Rigidity and bradykinesia correlate with contralateral nigrostriatal degeneration and striatal dopamine deficit, but association between striatal dopamine function and rest tremor has remained unclear. Objective: The aim of this study was to investigate the possible link between dopamine function and rest tremor using Parkinson's Progression Markers Initiative dataset, the largest prospective neuroimaging cohort of patients with PD. Methods: Clinical, [123I]N‐ω‐fluoropropyl‐2β‐carbomethoxy‐3β‐(4‐iodophenyl)nortropane ([123I]FP‐CIT) single photon emission computed tomography (SPECT), and structural magnetic resonance imaging data from 354 early PD patients and 166 healthy controls were included in this study. We employed a novel approach allowing nonlinear registration of individual scans accurately to a standard space and voxelwise analyses of the association between motor symptoms and striatal dopamine transporter (DAT) binding. Results: Severity of both rigidity and bradykinesia was negatively associated with contralateral striatal DAT binding (PFWE < 0.05 [FWE, family‐wise error corrected]). However, rest tremor amplitude was positively associated with increased ipsilateral DAT binding (PFWE < 0.05). The association between rest tremor and binding remained the same controlling for Hoehn & Yahr stage, Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS‐UPDRS) part III score, bradykinesia–rigidity score, or motor phenotype. The association between rest tremor and binding was independent of bradykinesia‐rigidity and replicated using 2‐year follow‐up data (PFWE < 0.05). Conclusion: In agreement with the existing literature, we did not find a consistent association between rest tremor and contralateral dopamine defect. However, our results demonstrate a link between rest tremor and increased or less decreased ipsilateral DAT binding. Our findings provide novel information about the association between dopaminergic function and parkinsonian rest tremor. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Background: Subtle parkinsonian signs, i.e., rest tremor and bradykinesia, are considered soft signs for defining essential tremor (ET) plus. Objectives: Our study aimed to further characterize subtle parkinsonian signs in a relatively large sample of ET patients from a clinical and neurophysiological perspective. Methods: We employed clinical scales and kinematic techniques to assess a sample of 82 ET patients. Eighty healthy controls matched for gender and age were also included. The primary focus of our study was to conduct a comparative analysis of ET patients (without any soft signs) and ET-plus patients with rest tremor and/or bradykinesia. Additionally, we investigated the asymmetry and side concordance of these soft signs. Results: In ET-plus patients with parkinsonian soft signs (56.10% of the sample), rest tremor was clinically observed in 41.30% of cases, bradykinesia in 30.43%, and rest tremor plus bradykinesia in 28.26%. Patients with rest tremor had more severe and widespread action tremor than other patients. Furthermore, we observed a positive correlation between the amplitude of action and rest tremor. Most ET-plus patients had an asymmetry of rest tremor and bradykinesia. There was no side concordance between these soft signs, as confirmed through both clinical examination and kinematic evaluation. Conclusions: Rest tremor and bradykinesia are frequently observed in ET and are often asymmetric but not concordant. Our findings provide a better insight into the phenomenology of ET and suggest that the parkinsonian soft signs (rest tremor and bradykinesia) in ET-plus may originate from distinct pathophysiological mechanisms. [ABSTRACT FROM AUTHOR]

Introduction: Distinguishing tremor-dominant Parkinson's disease (tPD) from essential tremor with rest tremor (rET) can be challenging and often requires dopamine imaging. This study aimed to differentiate between these two diseases through a machine learning (ML) approach based on rest tremor (RT) electrophysiological features and structural MRI data. Methods: We enrolled 72 patients including 40 tPD patients and 32 rET patients, and 45 control subjects (HC). RT electrophysiological features (frequency, amplitude, and phase) were calculated using surface electromyography (sEMG). Several MRI morphometric variables (cortical thickness, surface area, cortical/subcortical volumes, roughness, and mean curvature) were extracted using Freesurfer. ML models based on a tree-based classification algorithm termed XGBoost using MRI and/or electrophysiological data were tested in distinguishing tPD from rET patients. Results: Both structural MRI and sEMG data showed acceptable performance in distinguishing the two patient groups. Models based on electrophysiological data performed slightly better than those based onMRI data only (mean AUC: 0.92 and 0.87, respectively; p = 0.0071). The top-performing model used a combination of sEMG features (amplitude and phase) and MRI data (cortical volumes, surface area, andmean curvature), reaching AUC: 0.97 ± 0.03 and outperformingmodels using separately either MRI (p = 0.0001) or EMG data (p = 0.0231). In the best model, the most important feature was the RT phase. Conclusion: Machine learning models combining electrophysiological and MRI data showed great potential in distinguishing between tPD and rET patients and may serve as biomarkers to support clinicians in the differential diagnosis of rest tremor syndromes in the absence of expensive and invasive diagnostic procedures such as dopamine imaging. [ABSTRACT FROM AUTHOR]

Motor subtypes in Parkinson's Disease (PD) are unstable over time, limiting mechanistic insights and biomarker discovery. We focused on Rest Tremor (RT) as a symptom to test for phenotype stability and link it to specific circuits and disease mechanisms. Using the PPMI cohort data over 5 years we found that RT is more stable than classical Tremor-Dominant definitions, a stability also seen for RT response to therapy. At time of diagnosis, the population of therapy-resistant RT patients was enriched with a brain-first PD profile as predicted by a-Synuclein origin site and connectome (SOC) model. Resistant-RT patients have lower gastrointestinal and cardiovascular symptoms, lower prevalence of probable REM-Sleep behaviour disorder, and higher dopaminergic asymmetry compared to therapy-responsive or no tremor patients. Treating RT as a distinct phenomenon revealed a relative phenotypic stability with treatment response being linked to different patterns of disease progression.

Objective: To investigate the performance of structural MRI cortical and subcortical morphometric data combined with blink-reflex recovery cycle (BRrc) values using machine learning (ML) models in distinguishing between essential tremor (ET) with resting tremor (rET) and classic ET. Methods: We enrolled 47 ET, 43 rET patients and 45 healthy controls (HC). All participants underwent brain 3 T-MRI and BRrc examination at different interstimulus intervals (ISIs, 100--300 msec). MRI data (cortical thickness, volumes, surface area, roughness, mean curvature and subcortical volumes) were extracted using Freesurfer on T1-weighted images. We employed two decision tree-based ML classification algorithms (eXtreme Gradient Boosting [XGBoost] and Random Forest) combining MRI data and BRrc values to differentiate between rET and ET patients. Results: ML models based exclusively on MRI features reached acceptable performance (AUC: 0.85--0.86) in differentiating rET from ET patients and from HC. Similar performances were obtained by ML models based on BRrc data (AUC: 0.81--0.82 in rET vs. ET and AUC: 0.88--0.89 in rET vs. HC). ML models combining imaging data (cortical thickness, surface, roughness, and mean curvature) together with BRrc values showed the highest classification performance in distinguishing between rET and ET patients, reaching AUC of 0.94 ± 0.05. The improvement in classification performances when BRrc data were added to imaging features was confirmed by both ML algorithms. Conclusion: This study highlights the usefulness of adding a simple electrophysiological assessment such as BRrc to MRI cortical morphometric features for accurately distinguishing rET from ET patients, paving the way for a better classification of these ET syndromes. [ABSTRACT FROM AUTHOR]

This article outlines the creation of a health detection system designed to identify rest tremors in Parkinson's disease (PD). The system leverages internet of things (IoT) technology to measure frequencies derived from human activities, excluding other symptoms such as heartbeat and voice recording. The core components include the Arduino Nano microcontroller and the Node ESP MCU 8266 V3 for data processing. The system employs an accelerometer sensor positioned at the body's center axis to gauge the frequency of motor symptoms associated with resting tremors, particularly when the hands are at rest in the lap. The findings indicate that 9 samples displayed symptoms of rest tremor. The recorded p-value, standing at 0.884, signifies a robust correlation between the two variables at a significant threshold of 0.01 or 1%. [ABSTRACT FROM AUTHOR]

IntroductionDistinguishing tremor-dominant Parkinson's disease (tPD) from essential tremor with rest tremor (rET) can be challenging and often requires dopamine imaging. This study aimed to differentiate between these two diseases through a machine learning (ML) approach based on rest tremor (RT) electrophysiological features and structural MRI data.MethodsWe enrolled 72 patients including 40 tPD patients and 32 rET patients, and 45 control subjects (HC). RT electrophysiological features (frequency, amplitude, and phase) were calculated using surface electromyography (sEMG). Several MRI morphometric variables (cortical thickness, surface area, cortical/subcortical volumes, roughness, and mean curvature) were extracted using Freesurfer. ML models based on a tree-based classification algorithm termed XGBoost using MRI and/or electrophysiological data were tested in distinguishing tPD from rET patients.ResultsBoth structural MRI and sEMG data showed acceptable performance in distinguishing the two patient groups. Models based on electrophysiological data performed slightly better than those based on MRI data only (mean AUC: 0.92 and 0.87, respectively; p = 0.0071). The top-performing model used a combination of sEMG features (amplitude and phase) and MRI data (cortical volumes, surface area, and mean curvature), reaching AUC: 0.97 ± 0.03 and outperforming models using separately either MRI (p = 0.0001) or EMG data (p = 0.0231). In the best model, the most important feature was the RT phase.ConclusionMachine learning models combining electrophysiological and MRI data showed great potential in distinguishing between tPD and rET patients and may serve as biomarkers to support clinicians in the differential diagnosis of rest tremor syndromes in the absence of expensive and invasive diagnostic procedures such as dopamine imaging.

ObjectiveTo investigate the performance of structural MRI cortical and subcortical morphometric data combined with blink-reflex recovery cycle (BRrc) values using machine learning (ML) models in distinguishing between essential tremor (ET) with resting tremor (rET) and classic ET.MethodsWe enrolled 47 ET, 43 rET patients and 45 healthy controls (HC). All participants underwent brain 3 T-MRI and BRrc examination at different interstimulus intervals (ISIs, 100–300 msec). MRI data (cortical thickness, volumes, surface area, roughness, mean curvature and subcortical volumes) were extracted using Freesurfer on T1-weighted images. We employed two decision tree-based ML classification algorithms (eXtreme Gradient Boosting [XGBoost] and Random Forest) combining MRI data and BRrc values to differentiate between rET and ET patients.ResultsML models based exclusively on MRI features reached acceptable performance (AUC: 0.85–0.86) in differentiating rET from ET patients and from HC. Similar performances were obtained by ML models based on BRrc data (AUC: 0.81–0.82 in rET vs. ET and AUC: 0.88–0.89 in rET vs. HC). ML models combining imaging data (cortical thickness, surface, roughness, and mean curvature) together with BRrc values showed the highest classification performance in distinguishing between rET and ET patients, reaching AUC of 0.94 ± 0.05. The improvement in classification performances when BRrc data were added to imaging features was confirmed by both ML algorithms.ConclusionThis study highlights the usefulness of adding a simple electrophysiological assessment such as BRrc to MRI cortical morphometric features for accurately distinguishing rET from ET patients, paving the way for a better classification of these ET syndromes.

Introduction: Parkinson’s disease (PD) is a neurodegenerative disorder with different motor and neurocognitive symptoms. Tremor is a well-known symptom of this disease. Increasing evidence suggested that the cerebellum may substantially contribute to tremors as a clinical symptom of PD. However, the theoretical foundations behind these observations are not yet fully understood. Methods: In this study, a computational model is proposed to consider the role of the cerebellum and to show the effectiveness of cerebellar transcranial alternating current stimulation (tACS) on the rest tremor in participants with PD. The proposed model consists of the cortex, cerebellum, spinal circuit-muscular system (SC-MS), and basal ganglia blocks as the most critical parts of the brain, which are involved in generating rest tremors. The cortex, cerebellum, and SCMS blocks were modeled using Van der Pol oscillators that interacted through synchronization procedures. Basal ganglia are considered as a regulator of the coupling weights defined between oscillators. In order to evaluate the global behavior of the model, we applied tACS on the cerebellum of fifteen PD patients for 15 min at each patient’s peak frequency of their rest tremors. A tri-axial accelerometer recorded rest tremors before, during, and after the tACS. Results and Discussion: The simulation of the model provides a suggestion for the possible role of the cerebellum on rest tremors and how cerebellar tACS can affect these tremors. Results of human experiments also showed that the online and offline effects of cerebellar tACS could lead to the reduction of rest tremors significantly by about %76 and %68, respectively. Our findings suggest that the cerebellar tACS could serve as a reliable, therapeutic technique to suppress the PD tremor. [ABSTRACT FROM AUTHOR]

Rest tremor is one of the most prominent clinical features of Parkinson's disease (PD). Here, we hypothesized that corticobasal ganglia neurons tend to fire in a pattern that matches PD tremor frequency, suggesting a resonance phenomenon. We recorded spiking activity in the primary motor cortex (M1) and globus pallidus external segment of 2 female nonhuman primates, before and after parkinsonian state induction with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine. The arm of nonhuman primates was passively rotated at seven different frequencies surrounding and overlapping PD tremor frequency. We found entrainment of the spiking activity to arm rotation and a significant sharpening of the tuning curves in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine state, with a peak response at frequencies that matched the frequency of PD tremor. These results reveal increased sensitivity of the cortico-basal ganglia network to tremor frequency and could indicate that this network acts not only as a tremor switch but is involved in setting its frequency. [ABSTRACT FROM AUTHOR]

IntroductionParkinson’s disease (PD) is a neurodegenerative disorder with different motor and neurocognitive symptoms. Tremor is a well-known symptom of this disease. Increasing evidence suggested that the cerebellum may substantially contribute to tremors as a clinical symptom of PD. However, the theoretical foundations behind these observations are not yet fully understood.MethodsIn this study, a computational model is proposed to consider the role of the cerebellum and to show the effectiveness of cerebellar transcranial alternating current stimulation (tACS) on the rest tremor in participants with PD. The proposed model consists of the cortex, cerebellum, spinal circuit-muscular system (SC-MS), and basal ganglia blocks as the most critical parts of the brain, which are involved in generating rest tremors. The cortex, cerebellum, and SC-MS blocks were modeled using Van der Pol oscillators that interacted through synchronization procedures. Basal ganglia are considered as a regulator of the coupling weights defined between oscillators. In order to evaluate the global behavior of the model, we applied tACS on the cerebellum of fifteen PD patients for 15 min at each patient’s peak frequency of their rest tremors. A tri-axial accelerometer recorded rest tremors before, during, and after the tACS.Results and DiscussionThe simulation of the model provides a suggestion for the possible role of the cerebellum on rest tremors and how cerebellar tACS can affect these tremors. Results of human experiments also showed that the online and offline effects of cerebellar tACS could lead to the reduction of rest tremors significantly by about %76 and %68, respectively. Our findings suggest that the cerebellar tACS could serve as a reliable, therapeutic technique to suppress the PD tremor.

Introduction: There is some debate on the relationship between essential tremor with rest tremor (rET) and the classic ET syndrome, and only few MRI studies compared ET and rET patients. This study aimed to explore structural cortical differences between ET and rET, to improve the knowledge of these tremor syndromes. Methods: Thirty-three ET patients, 30 rET patients and 45 control subjects (HC) were enrolled. Several MR morphometric variables (thickness, surface area, volume, roughness, mean curvature) of brain cortical regions were extracted using Freesurfer on T1-weighted images and compared among groups. The performance of a machine learning approach (XGBoost) using the extracted morphometric features was tested in discriminating between ET and rET patients. Results: rET patients showed increased roughness and mean curvature in some fronto-temporal areas compared with HC and ET, and these metrics significantly correlated with cognitive scores. Cortical volume in the left pars opercularis was also lower in rET than in ET patients. No differences were found between ET and HC. XGBoost discriminated between rET and ET with mean AUC of 0.86 ± 0.11 in cross-validation analysis, using a model based on cortical volume. Cortical volume in the left pars opercularis was the most informative feature for classification between the two ET groups. Conclusion: Our study demonstrated higher cortical involvement in fronto-temporal areas in rET than in ET patients, which may be linked to the cognitive status. A machine learning approach based on MR volumetric data demonstrated that these two ET subtypes can be distinguished using structural cortical features. [ABSTRACT FROM AUTHOR]

A 50-year-old male presented with a four-year history of gradually progressive rest tremor in the distal right lower limb and then spreading to the left lower limb in last 10-12 months. He developed right arm rest and action tremor two years later. Magnetic resonance imaging scans showed progressive frontotemporal and asymmetrical mesial temporal atrophy. Genetic testing revealed a heterozygous c.915+16C>T pathogenic variant in intron 9 of the MAPT gene. Presentation with rest tremor should not exclude frontotemporal dementia-parkinsonism due to a MAPT variant as a differential diagnosis though rest tremor is a rare presentation. [ABSTRACT FROM AUTHOR]

(1) Background: The dynamics of hand tremors involve nonrandom and short-term motor patterns (STMPs). This study aimed to (i) identify STMPs in Parkinson's disease (PD) and physiological resting tremor and (ii) characterize STMPs by amplitude, persistence, and regularity. (2) Methods: This study included healthy (N = 12, 60.1 ± 5.9 years old) and PD (N = 14, 65 ± 11.54 years old) participants. The signals were collected using a triaxial gyroscope on the dorsal side of the hand during a resting condition. Data were preprocessed and seven features were extracted from each 1 s window with 50% overlap. The STMPs were identified using the clustering technique k-means applied to the data in the two-dimensional space given by t-Distributed Stochastic Neighbor Embedding (t-SNE). The frequency, transition probability, and duration of the STMPs for each group were assessed. All STMP features were averaged across groups. (3) Results: Three STMPs were identified in tremor signals (p < 0.05). STMP 1 was prevalent in the healthy control (HC) subjects, STMP 2 in both groups, and STMP3 in PD. Only the coefficient of variation and complexity differed significantly between groups. (4) Conclusion: These results can help professionals characterize and evaluate tremor severity and treatment efficacy. [ABSTRACT FROM AUTHOR]

Motor subtypes in Parkinson's Disease (PD) are unstable over time, limiting mechanistic insights and biomarker discovery. We focused on Rest Tremor (RT) as a symptom to test for phenotype stability and link it to specific circuits and disease mechanisms. Using the PPMI cohort data over 5 years we found that RT is more stable than classical Tremor-Dominant definitions, a stability also seen for RT response to therapy. At time of diagnosis, the population of therapy-resistant RT patients was enriched with a brain-first PD profile as predicted by a-Synuclein origin site and connectome (SOC) model. Resistant-RT patients have lower gastrointestinal and cardiovascular symptoms, lower prevalence of probable REM-Sleep behaviour disorder, and higher dopaminergic asymmetry compared to therapy-responsive or no tremor patients. Treating RT as a distinct phenomenon revealed a relative phenotypic stability with treatment response being linked to different patterns of disease progression. • Presence of Rest Tremor (RT) in PD represents a temporally stable phenotype. • RT is more stable than traditional motor subtypes like Tremor-Dominant. • Brain-first PD features are over-represented in patients with therapy-resistant RT. • RT-based phenotyping may refine PD subtyping and uncover disease mechanisms. [ABSTRACT FROM AUTHOR]

Background: Essential tremor (ET) is characterized by action tremor, although rest tremor may also occur. Despite this, rest tremor has not been studied extensively. A dearth of studies compare the relationship of rest tremor to other types of tremors in ET.Methods: Two-hundred-and-thirteen ET cases underwent detailed neurological examination, including evaluations of rest, simple kinetic, postural, and intention tremors. A movement disorders neurologist assessed the prevalence of each type of tremor. Each instance of tremor was classified as either symmetrical (present and equally severe on both sides of the body) or asymmetrical (only present on or more severe on one side of the body). Asymmetrical rest tremor that co-occurred with other types of asymmetrical tremors in a given case was further classified as either concordant (i.e., asymmetry on the same side of the body) or discordant (i.e., asymmetry on opposite sides of the body). Chi-square analyses examined the prevalence of concordant versus discordant pairings.Results: Sixty-two cases (29.2%) had rest tremor while seated. Fifteen (7.4%) had rest tremor while standing. Among asymmetric tremor pairings, concordant pairings occurred 2-2.7 times more frequently than discordant pairings - for pairings involving rest tremor while seated, 73.2% were concordant and 26.8% discordant (p < 0.001); for pairings involving rest tremor while standing, 66.7% were concordant and 33.3% were discordant (p = 0.25).Conclusions: Rest tremor often lateralized with other tremor types. These data add to our knowledge of the phenotypic manifestations of ET. [ABSTRACT FROM AUTHOR]

Introduction: The recently released classification has revised the nosology of tremor, defining essential tremor (ET) as a syndrome and fueling an enlightened debate about some newly conceptualized entities such as ET-plus. As a result, precise information of demographics, clinical features, and about the natural history of these conditions are lacking. Methods: The ITAlian tremor Network (TITAN) is a multicenter data collection platform, the aim of which is to prospectively assess, according to a standardized protocol, the phenomenology and natural history of tremor syndromes. Results: In the first year of activity, 679 patients have been recruited. The frequency of tremor syndromes varied from 32% of ET and 41% of ET-plus to less than 3% of rare forms, including focal tremors (2.30%), task-specific tremors (1.38%), isolated rest tremor (0.61%), and orthostatic tremor (0.61%). Patients with ET-plus were older and had a higher age at onset than ET, but a shorter disease duration, which might suggest that ET-plus is not a disease stage of ET. Familial aggregation of tremor and movement disorders was present in up to 60% of ET cases and in about 40% of patients with tremor combined with dystonia. The body site of tremor onset was different between tremor syndromes, with head tremor being most commonly, but not uniquely, associated with dystonia. Conclusions: The TITAN study is anticipated to provide clinically relevant prospective information about the clinical correlates of different tremor syndromes and their specific outcomes and might serve as a basis for future etiological, pathophysiological, and therapeutic research. [ABSTRACT FROM AUTHOR]

Background: Rest tremor (RT) can be observed in several positions (seated, standing, lying down) but it is unknown whether the tremor features may vary across them. This study aimed to compare the RT electrophysiological features across different positions in tremor-dominant Parkinson's disease (PD) and essential tremor plus (ET with RT, rET). Methods: We consecutively enrolled 90 tremor-dominant PD and 24 rET patients. The RT presence was evaluated in three positions: with the patient seated, the arm flexed at 90°, the forearm supported against gravity, and the hand hanging down from the chair armrest (hand-hanging position), in lying down supine and in standing position. RT electrophysiological features (amplitude, frequency, burst duration, pattern) were compared between the two patient groups and across the different positions. Results: All PD and rET patients showed RT in hand-hanging position. Supine and standing RT were significantly more common in PD (67.8% and 75.6%, respectively) than in rET patients (37.5% and 45.8%, respectively). RT amplitude, frequency and pattern were significantly different between groups in hand-hanging position whereas only pattern was significantly different between PD and rET in both standing and supine positions. In each patient group, all RT electrophysiological features did not significantly vary across different recording positions (p > 0.05). Discussion: In our study, PD and rET showed RT in hand-hanging, supine, and standing positions. RT pattern was the only electrophysiological feature significantly different between PD and rET patients in all these positions, enabling clinicians to perform the RT analysis for diagnostic purposes in different tremor positions. [ABSTRACT FROM AUTHOR]

Abstract Background Parkinson’s disease (PD) is a neurological disease that affects the motor system. The associated motor symptoms are muscle rigidity or stiffness, bradykinesia, tremors, and gait disturbances. The correct diagnosis, especially in the initial stages, is fundamental to the life quality of the individual with PD. However, the methods used for diagnosis of PD are still based on subjective criteria. As a result, the objective of this study is the proposal of a method for the discrimination of individuals with PD (in the initial stages of the disease) from healthy groups, based on the inertial sensor recordings. Methods A total of 27 participants were selected, 15 individuals previously diagnosed with PD and 12 healthy individuals. The data collection was performed using inertial sensors (positioned on the back of the hand and on the back of the forearm). Different numbers of features were used to compare the values of sensitivity, specificity, precision, and accuracy of the classifiers. For group classification, 4 classifiers were used and compared, those being [Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naive Bayes (NB)]. Results When all individuals with PD were analyzed, the best performance for sensitivity and accuracy (0.875 and 0.800, respectively) was found in the SVM classifier, fed with 20% and 10% of the features, respectively, while the best performance for specificity and precision (0.933 and 0.917, respectively) was associated with the RF classifier fed with 20% of all the features. When only individuals with PD and score 1 on the Hoehn and Yahr scale (HY) were analyzed, the best performances for sensitivity, precision and accuracy (0.933, 0.778 and 0.848, respectively) were from the SVM classifier, fed with 40% of all features, and the best result for precision (0.800) was connected to the NB classifier, fed with 20% of all features. Conclusion Through an analysis of all individuals in this study with PD, the best classifier for the detection of PD (sensitivity) was the SVM fed with 20% of the features and the best classifier for ruling out PD (specificity) was the RF classifier fed with 20% of the features. When analyzing individuals with PD and score HY = 1, the SVM classifier was superior across the sensitivity, precision, and accuracy, and the NB classifier was superior in the specificity. The obtained result indicates that objective methods can be applied to help in the evaluation of PD.

Rest tremor is a movement disorder commonly found in diseases like Parkinson's disease (PD) and essential tremor (ET). Rest tremor typically shows slower progression in PD, but more severe progression in ET. However, the underlying white matter organization of rest tremor behind PD and ET remains unclear. This study included 57 ET patients (40 without rest tremor (ETWR), 17 with rest tremor (ETRT)), 68 PD patients (34 without rest tremor (PDWR), 34 with rest tremor (PDRT)), and 62 normal controls (NC). Fixel-based analysis was used to evaluate the structural changes of white matter in rest tremor in these different diseases. The fiber-bundle cross-section (FC) of the right non-decussating dentato-rubro-thalamic tract and several fibers outside the dentato-rubro-thalamic pathway in ETWR were significantly higher than that in NC. The fiber density and cross-section of the left nigro-pallidal in PDWR is significantly lower than that in NC, while the FC of bilateral nigro-pallidal in PDRT is significantly lower than that in NC. ET patients with pure action tremor showed over-activation of fiber tracts. However, when superimposed with rest tremor, ET patients no longer exhibited over-activation of fiber tracts, but rather showed a trend of fiber tract damage. Except for the nigro-pallidal degeneration in all PD, PDRT will not experience further deterioration in fiber organization. These results provide important insights into the unique effects of rest tremor on brain fiber architecture in ET and PD. • Different effects of rest tremor on brain fiber structure in ET and PD patients. • When superimposed with rest tremor, ET patients exhibited a potential for fiber tract damage. • Except for the SN-GP degeneration in all PD, PDRT may not have worse fiber organization. [ABSTRACT FROM AUTHOR]

Abstract Background Facial (lip and jaw) tremor (FT) is associated with Parkinson’s disease (PD) but few studies have been conducted to explore its clinical profile. We performed this study to investigate the prevalence and clinical correlates of FT in PD, and further to evaluate its effect on disease progression. Methods A retrospective, cross-sectional (n = 2224) and longitudinal (n = 674) study was conducted. The presence of FT was based on a ≥ 1 score in the United PD Rating Scale (UPDRS) item 20A. Group comparisons were conducted, followed by a forward binary logistic regression analysis. Inverse probability of treatment weighting (IPTW) based on the propensity score and weighted or unweighted Cox regression models were used to explore the impact of FT on five clinical milestones including death, UPDRS III 11-point increase, Hoehn and Yahr (H&Y) stage reaching 3, dyskinesia development, and Montreal Cognitive Assessment 3-point decrease. Results FT was presented in 403 patients (18.1%), which showed increasing trends with disease duration and H&Y score. Age (P

BACKGROUND AND PURPOSE: Re-emergent tremor (ReT) is the tremor that reappears after a variable period of latency while maintaining posture. Little is known about the mechanisms that contribute to the origin of this silent period (SP). Our aim was to compare the imaging characteristics of patients with and without ReT and find the structural correlate of SP if any. MATERIALS AND METHODS: Fifteen patients with ReT (Group 1) and eighteen patients without ReT (patients with rest tremor and postural tremor, but no latency) were evaluated clinically, electrophysiologically, with diffusion tensor imaging (DTI) and voxel-based morphometry (VBM). DTI parameters of different regions of interest were analyzed and compared with that of 37 healthy age- and gender-matched controls. RESULTS: No statistically significant difference was observed between the two groups in terms of age, duration of disease, levodopa equivalent dose, or severity of the disease. However, in the left supplementary motor area (SMA), there was a significant reduction of fractional anisotropy and an increase of radial diffusivity and mean diffusivity in patients with ReT (Group 1) as compared to patients without ReT (Group 2) and healthy controls. The results of the VBM analysis were not significant. CONCLUSION: The presence of abnormality of SMA suggests that patients with ReT have a different pathophysiological mechanism as compared to patients without ReT. This is a novel finding implicating a possible contribution of the frontal lobe to the genesis of SP in ReT. ReT could be a distinct clinical entity within the tremor dominant subtype.

(1) Background: The dynamics of hand tremors involve nonrandom and short-term motor patterns (STMPs). This study aimed to (i) identify STMPs in Parkinson’s disease (PD) and physiological resting tremor and (ii) characterize STMPs by amplitude, persistence, and regularity. (2) Methods: This study included healthy (N = 12, 60.1 ± 5.9 years old) and PD (N = 14, 65 ± 11.54 years old) participants. The signals were collected using a triaxial gyroscope on the dorsal side of the hand during a resting condition. Data were preprocessed and seven features were extracted from each 1 s window with 50% overlap. The STMPs were identified using the clustering technique k-means applied to the data in the two-dimensional space given by t-Distributed Stochastic Neighbor Embedding (t-SNE). The frequency, transition probability, and duration of the STMPs for each group were assessed. All STMP features were averaged across groups. (3) Results: Three STMPs were identified in tremor signals (p < 0.05). STMP 1 was prevalent in the healthy control (HC) subjects, STMP 2 in both groups, and STMP3 in PD. Only the coefficient of variation and complexity differed significantly between groups. (4) Conclusion: These results can help professionals characterize and evaluate tremor severity and treatment efficacy.

Tremor is a commonly encountered condition in the primary care setting and can manifest at rest, with action, or both. Common causes include Parkinson disease, essential tremor, and drug-induced tremor. In this article, the authors discuss how to examine a patient with tremor and which features of the history and examination can help clue the provider in to the appropriate diagnosis. They also review treatments for varying types of tremor and when referral to a neurologist may be necessary., Competing Interests: Disclosure None of the authors have commercial or financial interests to disclose., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Tremor is the most commonly encountered movement disorder in clinical practice. A wide range of pathologies may manifest with tremor either as a presenting or predominant symptom. Considering the marked etiological and phenomenological heterogeneity, it would be desirable to develop a classification of tremors that reflects their underlying pathophysiology. The tremor task force of the International Parkinson Disease and Movement Disorders Society has worked toward this goal and proposed a new classification system. This system has remained a prime topic of scientific communications on tremor in recent times. The new classification is based on two axes: 1. based on the clinical features, history, and tremor characteristics and 2. based on the etiology of tremor. In this article, we discuss the key aspects of the new classification, review various tremor syndromes, highlight some of the controversies in the field of tremor, and share the potential future perspectives.

Tremor is the most commonly encountered movement disorder in clinical practice. A wide range of pathologies may manifest with tremor either as a presenting or predominant symptom. Considering the marked etiological and phenomenological heterogeneity, it would be desirable to develop a classification of tremors that reflects their underlying pathophysiology. The tremor task force of the International Parkinson Disease and Movement Disorders Society has worked toward this goal and proposed a new classification system. This system has remained a prime topic of scientific communications on tremor in recent times. The new classification is based on two axes: 1. based on the clinical features, history, and tremor characteristics and 2. based on the etiology of tremor. In this article, we discuss the key aspects of the new classification, review various tremor syndromes, highlight some of the controversies in the field of tremor, and share the potential future perspectives. [ABSTRACT FROM AUTHOR]

Abstract Background Tremor is one of the hallmarks and most bothersome symptoms in Parkinson’s disease (PD). The classical PD tremor is present at rest, but postural tremor also occurs. PD tremor can be continuous or intermittently present and can have a re-emergent nature. The tremor intensity is affected by attention and stress level. Observations of PD tremor have indicated increased tremor intensity with time during 30-s tremor assessments. This phenomenon has not previously been studied systematically. Thus, in order to contribute to our understanding of the mechanisms associated with PD tremor, our aim was to investigate the influence of time during a posture holding and a resting task on hand tremor characteristics in persons with PD compared to healthy peers. Method Fifty persons with PD and at least one tremoring hand (tremor intensity exceeding mean + 2SD of a healthy reference group (REF), N = 40) were included from a clinical trial population. Hand accelerations in a rest and postural condition were measured in 30-s assessments while the participants performed a self-paced simple subtraction task with eyes closed to standardize attention without inducing stress. Tremor intensity, maximal power, frequency of maximal power and tremor onset time was calculated for three consecutive 10-s time intervals. Results Tremor intensity and maximal power increased significantly during the 30-s recording in the PD-group in both conditions (1st-3rd time-interval, tremor intensity: rest + 65% p

Abstract Background Parkinson’s disease (PD) tremor comprises asymmetric rest and postural tremor with unilateral onset. Tremor intensity can be amplified by stress and reduced by attention, and the medical treatment is complex. Mirror movements and unintentional synchronization of bimanual movements, possibly caused by insufficient inhibition of inter-hemispheric crosstalk, have been reported in PD, indicating a lag of lateralization. Potential neuroprotective effects of pulsed electromagnetic fields (PEMF) have been reported in-vitro and in rodents, as have influences of PEMF on human tremor. The aim was to investigate the effect of 8 weeks daily transcranial PEMF treatment (T-PEMF) of persons with PD on rest and postural hand tremor characteristics and on inter-hand coherence. Methods Hand accelerations of 50 PD participants with uni- or bilateral tremor participating in a clinical trial were analysed. A rest and postural tremor task performed during serial subtraction was assessed before and after 8 weeks of T-PEMF (30 min/day, 50 Hz, ±50 V, 3 ms squared pulses) or placebo treatment (sham stimulation 30 min/day). Forty matched healthy persons (no treatment) were included as reference. Intensity and inter-hand coherence related measures were extracted. Results The T-PEMF treatment decreased the inter-hand coherence in the PD group with unilateral postural tremor. The PD group with unilateral postural tremor was less clinically affected by the disease than the PD group with bilateral postural tremor. However, no differences between T-PEMF and placebo treatment on either intensity related or coherence related measures were found when all persons with PD were included in the analyses. The peak power decreased and the tremor intensity tended to decrease in both treatment groups. Conclusions Eight weeks of T-PEMF treatment decreased inter-hand coherence in the PD group with unilateral postural tremor, while no effects of T-PEMF treatment were found for the entire PD group. The unilateral postural tremor group was less clinically affected than the bilateral postural tremor group, suggesting that early treatment initiation may be beneficial. In theory, a reduced inter-hand coherence could result from a neuronal treatment response increasing inter-hemispheric inhibition. However, this requires further studies to determine. Studies of even longer treatment periods would be of interest. Trial registration ClinicalTrials.gov, NCT02125032. Registered 29 April 2014, https://clinicaltrials.gov/ct2/show/NCT02125032?term=NCT02125032&rank=1

Background: Parkinson's disease (PD) is a neurological disease that affects the motor system. The associated motor symptoms are muscle rigidity or stiffness, bradykinesia, tremors, and gait disturbances. The correct diagnosis, especially in the initial stages, is fundamental to the life quality of the individual with PD. However, the methods used for diagnosis of PD are still based on subjective criteria. As a result, the objective of this study is the proposal of a method for the discrimination of individuals with PD (in the initial stages of the disease) from healthy groups, based on the inertial sensor recordings.Methods: A total of 27 participants were selected, 15 individuals previously diagnosed with PD and 12 healthy individuals. The data collection was performed using inertial sensors (positioned on the back of the hand and on the back of the forearm). Different numbers of features were used to compare the values of sensitivity, specificity, precision, and accuracy of the classifiers. For group classification, 4 classifiers were used and compared, those being [Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Naive Bayes (NB)].Results: When all individuals with PD were analyzed, the best performance for sensitivity and accuracy (0.875 and 0.800, respectively) was found in the SVM classifier, fed with 20% and 10% of the features, respectively, while the best performance for specificity and precision (0.933 and 0.917, respectively) was associated with the RF classifier fed with 20% of all the features. When only individuals with PD and score 1 on the Hoehn and Yahr scale (HY) were analyzed, the best performances for sensitivity, precision and accuracy (0.933, 0.778 and 0.848, respectively) were from the SVM classifier, fed with 40% of all features, and the best result for precision (0.800) was connected to the NB classifier, fed with 20% of all features.Conclusion: Through an analysis of all individuals in this study with PD, the best classifier for the detection of PD (sensitivity) was the SVM fed with 20% of the features and the best classifier for ruling out PD (specificity) was the RF classifier fed with 20% of the features. When analyzing individuals with PD and score HY = 1, the SVM classifier was superior across the sensitivity, precision, and accuracy, and the NB classifier was superior in the specificity. The obtained result indicates that objective methods can be applied to help in the evaluation of PD. [ABSTRACT FROM AUTHOR]

Background: Facial (lip and jaw) tremor (FT) is associated with Parkinson's disease (PD) but few studies have been conducted to explore its clinical profile. We performed this study to investigate the prevalence and clinical correlates of FT in PD, and further to evaluate its effect on disease progression.Methods: A retrospective, cross-sectional (n = 2224) and longitudinal (n = 674) study was conducted. The presence of FT was based on a ≥ 1 score in the United PD Rating Scale (UPDRS) item 20A. Group comparisons were conducted, followed by a forward binary logistic regression analysis. Inverse probability of treatment weighting (IPTW) based on the propensity score and weighted or unweighted Cox regression models were used to explore the impact of FT on five clinical milestones including death, UPDRS III 11-point increase, Hoehn and Yahr (H&Y) stage reaching 3, dyskinesia development, and Montreal Cognitive Assessment 3-point decrease.Results: FT was presented in 403 patients (18.1%), which showed increasing trends with disease duration and H&Y score. Age (P < 0.001), female (P < 0.001), disease duration (P = 0.001), speech (P = 0.011), rigidity (P = 0.026), rest tremor on limbs (P < 0.001), kinetic tremor on hands (P < 0.001), and axial symptoms (P = 0.013) were independent factors associated with FT. Both unweighted and weighted Cox regression models indicated that baseline FT and FT as the initial symptom were not associated with the five outcomes.Conclusions: Our study suggested that FT was not uncommon and provided a deeper insight into the characteristics of FT in PD. The predict value of FT on long-term progronis of PD may need future longer follwe-up study. [ABSTRACT FROM AUTHOR]

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

Background: The most common type of tremor reported in dystonia patients is postural and kinetic. There is uncertainty regarding the prevalence of rest tremor in dystonia.Objective: This review focuses on the clinical and neurophysiological features of rest tremor in dystonia, its differential diagnosis, and methods to distinguish it from other rest tremor syndromes.Methods: A PubMed search was done, and the available literature identified. Bibliography of the available literature was reviewed for relevant references.Results: Rest tremor in dystonia has been reported with a variable frequency of 1.81-12.05%. The most common body distribution is arm, and it tends to be asymmetric. Most of the affected patients have multifocal and segmental dystonia. Rest tremor is a late-onset phenomenon associated with severe and spreading dystonia. Clinically, it is difficult to distinguish rest tremor in dystonia from other rest tremor syndromes based on tremor characteristics; however, other neurological signs can provide clues to differentiate these syndromes. Surface electromyography and other neurophysiological tests can help differentiate the various rest tremor syndromes.Conclusion: Rest tremor in dystonia can be differentiated from other rest tremor syndromes based on neurophysiological techniques. There is some evidence to suggest that SWEDDs could be a form of dystonic tremor, but further studies are required to clarify this diagnostic dilemma. Data regarding the treatment of rest tremor in dystonia are virtually nonexistent, and there is an urgent need for prospective studies focusing its medical management and to know the surgical targets. [ABSTRACT FROM AUTHOR]

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

Involuntary tremor at rest is observed in patients with Parkinson’s disease (PD) or essential tremor (ET). Electromyography (EMG) studies have shown that phase displacement between antagonistic muscles at prevalent tremor frequency can accurately differentiate resting tremor in PD from that detected in ET. Currently, phase evaluation is qualitative in most cases. The aim of this study is to develop and validate a new mobile tool for the automated and quantitative characterization of phase displacement (resting tremor pattern) in ambulatory clinical settings. A new low-cost, wearable mobile device, called µEMG, is described, based on low-end instrumentation amplifiers and simple digital signal processing (DSP) capabilities. Measurements of resting tremor characteristics from this new device were compared with standard EMG. A good level of agreement was found in a sample of 21 subjects (14 PD patients with alternating resting tremor pattern and 7 ET patients with synchronous resting tremor pattern). Our results demonstrate that tremor analysis using µEMG is easy to perform and it can be used in routine clinical practice for the automated quantification of resting tremor patterns. Moreover, the measurement process is handy and operator-independent.

Background: Parkinson's Disease (PD) can present with dystonia or essential tremor but task specific tremor (TST) preceding PD has been only rarely reported. The relationship between TST and PD is unclear. We report a series of 12 patients with TST who later developed PD. Cases: Patients with TST and PD were identified from our database. Records and imaging were reviewed and descriptive statistics presented. Twelve patients were identified. All 11 patients who had TST of arm developed rest tremor ipsilateral to the TST arm. DaTscan showed reduced dopaminergic uptake in all 11 patients who were scanned. The TST improved with STN and VIM DBS (3/12) and partially to dopaminergic medications (N = 3) and trihexyphenidyl (N = 2). Conclusion: Rest tremor consistently occurring ipsilateral to TST, positive DaTscan, and partial response to dopaminergic medications but not to ET medications suggests TST is a precursor to PD in this population rather than chance occurrence. View Supplementary Video S1 [ABSTRACT FROM AUTHOR]

Background: Currently the most consistent, widely accepted and detailed instrument to rate Parkinson's disease (PD) is the Movement Disorder Society sponsored Unified Parkinson Disease Rating Scale (MDS-UPDRS). However, the motor examination is based upon subjective human interpretation trying to capture a snapshot of PD status. Wearable sensors and machine learning have been broadly used to analyze PD motor disorder, but still most ratings and examinations lay outside MDS-UPDRS standards. Moreover, logical connections between features and output ratings are not clear and complex to derive from the model, thus limiting the understanding of the structure in the data.Methods: Fifty-seven PD patients underwent a full motor examination in accordance to the MDS-UPDRS on twelve different sessions, gathering 123 measurements. Overall, 446 different combinations of limb features correlated to rest tremors amplitude are extracted from gyroscopes, accelerometers, and magnetometers and feed into a fuzzy inference system to yield severity estimations.Results: A method to perform rest tremor quantification fully adhered to the MDS-UPDRS based on wearable sensors and fuzzy inference system is proposed, which enables a reliable and repeatable assessment while still computing features suggested by clinicians in the scale. This quantification is straightforward and scalable allowing clinicians to improve inference by means of new linguistic statements. In addition, the method is immediately accessible to clinical environments and provides rest tremor amplitude data with respect to the timeline. A better resolution is also achieved in tremors rating by adding a continuous range. [ABSTRACT FROM AUTHOR]

Background: s: Over recent years there have been some conflicting reports upon the role of pallidal dopaminergic denervation in rest tremor in Parkinson's disease.Objectives: To clarify this issue we analyzed the clinical and 123I-FP-CIT SPECT data of a large cohort of early Parkinson's disease patients enrolled in the PPMI study.Methods: Pallidal and striatal dopamine transporter uptake ratios were calculated in 382 patients (120 no-tremor, 60 tremor-dominant, and 202 indeterminate) and 150 controls. A region of interest (ROI) approach was used to estimate DAT uptake ratios from 123I-FP-CIT SPECT scans in the caudate nucleus, putamen, and globus pallidus after normalization to a DAT template. DAT uptake ratios for each region were compared between subgroups using ANCOVA and linear regression analyses were performed to evaluate the relationship between severity of rest tremor and regional DAT uptake ratios.Results: PD patients had significantly lower DAT uptake ratios in the pallidum, putamen and caudate as compared to healthy controls (p < 0.001). ANCOVA showed inter-PD subgroup differences in DAT uptake ratios in the putamen and pallidum (p < 0.05) after adjustment for age and disease duration, with post-hoc comparisons revealing significantly higher DAT uptake ratios for the tremor-dominant subgroup as compared to non-tremor and indeterminate subgroups (p < 0.016). There was no significant relationship between rest tremor severity and pallidal DAT either in the tremor-dominant subgroup or in the total PD population.Conclusions: Pallidal dopaminergic denervation appears unrelated to rest tremor severity in early Parkinson's disease. [ABSTRACT FROM AUTHOR]

There are an increased number of patients all over the world suffering from postural tremors and rest tremors, the types of tremors associated with Parkinson’s disease and other neurodegenerative diseases such as amyotrophic lateral sclerosis. Currently, there is no cure for such disease and patients have to deal with their condition to continue their life normally with the existing of some helpful instruments. This work presents a self-stabilising Parkinson’s disease (PD) Tray (platform) that can help them to carry objects that they hold with their hand. The proposed design includes a mechanical platform and en electronic system to control the tray and inhibits any vibrations of the base plate of the tray. An algorithm was developed that would take positional data from an Inertia movement sensors IMU, compute angles in degrees from its Euler angle raw data and then use those angles to control three servo motors in a direction counter to the changes in the IMU’s position. The platform, was capable of stabilising the base of the tray such that objects placed in it would not be dropped. The tray was tested on simulating conditions and the result should that the mean absolute value of the acceleration values in X and Y directions were reduced from 2.23 m/sec2to 0.26 m/sec2in the X direction and from 1.41 m/sec2to 0.34 m/sec2in the Y direction. [ABSTRACT FROM PUBLISHER]

Parkinson’s disease (PD) is a neurodegenerative disorder of the central nervous system and one of its key symptoms is rest tremor. Deep brain stimulation (DBS) effectively suppresses rest tremor in Parkinson’s disease. Despite being a successful treatment option, its underlying principle and the mechanism by which it attenuates tremors is not yet fully understood. Since existing methods for tuning DBS parameters are largely trial and error, understanding how DBS works can help to reduce time and costs, and could also ultimately lead to better treatment strategies for PD. In this paper, we set out to analyze how a high-frequency stimulation applied through DBS can help reduce the low-frequency rest tremors observed in PD patients. We identify key elements in the sensorimotor loop (the feedback loop consisting of sensory feedbacks and motor responses) that play a role in the interaction of high-frequency DBS signal and the low-frequency tremor. Based on the analysis of these elements, we draw insights about the working of DBS and the role of frequency and the nature of stimulation. We verify these observations with numerical examples and a bench top experimental example. [ABSTRACT FROM PUBLISHER]

Objective To assess body distribution and timing of appearance of rest tremor in Parkinson's disease. Methods Information was obtained by a computerized database containing historical information collected at the first visit and data collected during the subsequent follow-up visits. Information on rest tremor developed during the follow-up could be therefore obtained by our own observation in a proportion of patients. Results Among 289 patients, rest tremor was reported at disease onset in 65.4% of cases and detected at last follow-up examination in 74.4% of patients. Analysis of patients who did not report rest tremor at disease onset indicated that 26% of such patients (9% in the overall population) manifested rest tremor over the disease course. Rest tremor spread to new sites in 39% of patients who manifested rest tremor at disease onset. Regardless of tremor presentation at disease onset or during the follow-up, upper limb was the most frequent tremor localization. Over the follow-up, rest tremor developed faster in the upper limb than in other body sites. The risk of developing rest tremor during the follow-up was not affected by sex, side of motor symptom onset and site of tremor presentation. However, age of disease onset > 63 years was associated with an increased risk of rest tremor spread. Conclusions This study provides new information about body distribution and timing of rest tremor appearance during the course of early stages of Parkinson's disease that may help clinicians in patients' counselling. [ABSTRACT FROM AUTHOR]