Different effects of essential tremor and Parkinsonian tremor on multiscale dynamics of hand tremor

Dopaminergic versus anticholinergic treatment effects on physiologic complexity of hand tremor in Parkinson's disease: A randomized crossover study

AIMS

Parkinsonian tremor (PT) is regulated by numerous neurophysiological components across multiple temporospatial scales. The dynamics of tremor fluctuation are thus highly complex. This study aimed to explore the effects of different medications on tremor complexity, and how the underlying factors contribute to such tremor complexity.

METHODS

In this study, 66 participants received a 2-mg dose of benzhexol or a pre-determined dose of levodopa at two study visits in a randomized order. Before and after taking the medications, tremor fluctuation was recorded using surface electromyography electrodes and accelerometers in resting, posture, and weighting conditions with and without a concurrent cognitive task. Tremor complexity was quantified using multiscale entropy.

RESULTS

Tremor complexity in resting (p = 0.002) and postural condition (p < 0.0001) was lower when participants were performing a cognitive task compared to a task-free condition. After taking levodopa and benzhexol, participants had increased (p = 0.02-0.03) and decreased (p = 0.03) tremor complexity compared to pre-medication state, respectively. Tremor complexity and its changes as induced by medications were significantly correlated with clinical ratings and their changes (β = -0.23 to -0.39; p = 0.002-0.04), respectively.

CONCLUSION

Tremor complexity may be a promising marker to capture the pathophysiology underlying the development of PT, aiding the characterization of the effects medications have on PT regulation.

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

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

Classification of Parkinson's disease stages with a two-stage deep neural network

Introduction

Parkinson's disease is one of the most prevalent neurodegenerative diseases. In the most advanced stages, PD produces motor dysfunction that impairs basic activities of daily living such as balance, gait, sitting, or standing. Early identification allows healthcare personnel to intervene more effectively in rehabilitation. Understanding the altered aspects and impact on the progression of the disease is important for improving the quality of life. This study proposes a two-stage neural network model for the classifying the initial stages of PD using data recorded with smartphone sensors during a modified Timed Up & Go test.

Methods

The proposed model consists on two stages: in the first stage, a semantic segmentation of the raw sensor signals classifies the activities included in the test and obtains biomechanical variables that are considered clinically relevant parameters for functional assessment. The second stage is a neural network with three input branches: one with the biomechanical variables, one with the spectrogram image of the sensor signals, and the third with the raw sensor signals.

Results

This stage employs convolutional layers and long short-term memory. The results show a mean accuracy of 99.64% for the stratified k-fold training/validation process and 100% success rate of participants in the test phase.

Discussion

The proposed model is capable of identifying the three initial stages of Parkinson's disease using a 2-min functional test. The test easy instrumentation requirements and short duration make it feasible for use feasible in the clinical context.

Identification and Characterization of Short-Term Motor Patterns in Rest Tremor of Individuals with Parkinson's Disease

(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.

Antioxidative role of Traditional Chinese Medicine in Parkinson's disease

ETHNOPHARMACOLOGICAL RELEVANCE

Neuroprotective Traditional Chinese Medicine (TCM) has been practiced in alternative medicine from early days. TCM-derived neuroprotective compounds, such as Chrysin, Cannabidiol, Toonasinoids, and β-asaron, exert significant effectiveness's towards Parkinson's disease (PD). Further, these neuroprotective TCM showed antioxidative, anti-inflammatory, anti-tumor, anti-septic, analgesic properties. Recent research showed that the reduction in the reactive oxygen species (ROS) decreased the α-synuclein (α-syn) toxicity and enhanced the dopaminergic neuron regenerations, the main hallmarks of PD. Therefore, the neuroprotective effects of novel TCM due to its antiradical activities needed deep investigations.

AIMS OF THE STUDY

This review aims to enlighten the neuroprotective TCM and its components with their antioxidative properties to the scientific community for future research.

METHOD

The relevant information on the neuroprotective TCM was gathered from scientific databases (PubMed, Web of Science, Google Scholar, ScienceDirect, SciFinder, Wiley Online Library, ACS Publications, and CNKI). Information was also gained from MS and Ph.D. thesis, books, and online databases. The literature cited in this review dates from 2001 to June 2, 0201.

RESULTS

Novel therapies for PD are accessible, mostly rely on Rivastigmine and Donepezil, offers to slow down the progression of disease at an early stage but embraces lots of disadvantages. Researchers are trying to find a potential drug against PD, which is proficient at preventing or curing the disease progress, but still needed to be further identified. Oxidative insult and mitochondrial dysfunction are thought to be the main culprit of neurodegenerations. Reactive oxygen species (ROS) are the only causative agent in all interactions, leading to PD, from mitochondrial dysfunctions, α-syn aggregative toxicity, and DA neurons degenerations. It is evident from the redox balance, which seems an imperative therapeutic approach against PD and was necessary for the significant neuronal activities.

CONCLUSION

Our study is explaining the newly discovered TCM and their neuroprotective and antioxidative properties. But also bring up the possible treatment approaches against PD for future researchers.

The Multiscale Dynamics of Beat-to-Beat Blood Pressure Fluctuation Links to Functions in Older Adults

Background

The blood pressure (BP) is regulated by multiple neurophysiologic elements over multiple temporal scales. The multiscale dynamics of continuous beat-to-beat BP series, which can be characterized by “BP complexity”, may, thus, capture the subtle changes of those elements, and be associated with the level of functional status in older adults. We aimed to characterize the relationships between BP complexity and several important functions in older adults and to understand the underlying factors contributing to BP complexity.

Method

A total of 400 older adults completed a series of clinical and functional assessments, a finger BP assessment of at least 10 min, and blood sample and vessel function tests. Their hypertensive characteristics, cognitive function, mobility, functional independence, blood composition, arterial stiffness, and endothelial function were assessed. The complexity of systolic (SBP) and diastolic (DBP) BP series was measured using multiscale entropy.

Results

We observed that lower SBP and DBP complexity was significantly associated with poorer functional independence (β > 0.17, p < 0.005), cognitive function (β > 0.45, p = 0.01), and diminished mobility (β < −0.57, p < 0.003). Greater arterial stiffness (β < −0.48, p = 0.02), decreased endothelial function (β > 0.42, p < 0.03), and excessed level of blood lipids (p < 0.03) were the main contributors to BP complexity.

Conclusion

Blood pressure complexity is closely associated with the level of multiple functional statuses and cardiovascular health in older adults with and without hypertension, providing novel insights into the physiology underlying BP regulation. The findings suggest that this BP complexity metric would serve as a novel marker to help characterize and manage the functionalities in older adults.