Готові списки джерел за темами / Parkinson’s tremor

Добірка наукової літератури з теми "Parkinson’s tremor"

Автор: Grafiati
Опубліковано: 30 травня 2022
Оновлено: 31 травня 2022

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Статті в журналах з теми "Parkinson’s tremor"

1

Rana, Abdul Qayyum, and Mohamad Saleh. "Relationship between resting and action tremors in Parkinson’s disease." Journal of Neurosciences in Rural Practice 07, no. 02 (April 2016): 232–37. http://dx.doi.org/10.4103/0976-3147.176192.

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ABSTRACT Objective: To determine the relationship between resting tremor (RT) and action tremor (AT) in Parkinson’s disease (PD) patients. Methods: A retrospective study of RT and AT severity was conducted in 100 PD patients. The severity rating for each type of tremor in the upper extremities was assessed. The disparity in tremor severity between extremities for each tremor type was compared to that of the other two to identify commonalities in the laterality of the tremor manifestation. Results: Overall, RT is predictive of AT on the same side, but not the opposing side of the body. Patients with less intense resting right upper limb (RRU) tremor and moderately intense RRU tremor were significantly more likely to have an action right upper limb (ARU) tremor (−1.53, P = 0.020; −1.88, P = 0.005, respectively). Similarly, patients with less intense resting left upper limb (RLU) tremor and moderately intense RLU tremors were significantly more likely to have an action left upper limb (ALU) tremor (−3.49, P = 0.000; −1.86, P = 0.017, respectively). In addition, RRU and ALU tremors were associated with an increase in RLU and ARU tremors, respectively. Conclusion: Tremors are common findings in PD patients, and often impair quality of life. By identifying and classifying the relationship between resting and ATs in PD patients, our study sheds light onto the importance of better understanding and future management of this debilitating symptomology.
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2

Louis, Elan D. "Essential tremor: a nuanced approach to the clinical features." Practical Neurology 19, no. 5 (July 4, 2019): 389–98. http://dx.doi.org/10.1136/practneurol-2018-002183.

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Essential tremor is the most common form of tremor in humans. Given neurologists’ high exposure to this condition, and its seemingly straightforward phenotype, it might seem easy to diagnose. However, 30%–50 % of patients labelled as having ‘essential tremor’ have other diagnoses, mostly Parkinson’s disease and dystonia. The tremor of essential tremor is neither non-descript nor featureless but is multifaceted and highly patterned. This review focuses on its clinical features, beginning with a discussion of tremors and then briefly discussing its additional motor features, and presents several aids to help distinguish essential tremor from Parkinson’s disease and dystonia. Careful attention to certain clinical nuances will aid the diagnosis and care of patients with essential tremor.
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3

Brindha, A., K. A. Sunitha, and S. Robert Wilson. "TREMOR CLASSIFICATION USING WEARABLE IOT BASED SENSORS." IOP Conference Series: Materials Science and Engineering 1219, no. 1 (January 1, 2022): 012024. http://dx.doi.org/10.1088/1757-899x/1219/1/012024.

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Abstract Tremors, a significant symptom of movement disorder, affects a part of the body ranging from slight to severe. These Tremors are symptoms of various neurological diseases such as Parkinson’s disease (PD), Essential tremors (ET), Physiological tremors (PT), Cerebellar tremor, Dystonic tremor, Psychogenic tremor, and many more. Tremor features and types differ for various neurological disorders. During the early stages of the disease, clinical examination of tremors plays a significant role in diagnose management. This work aims to develop a wearable assistive system with an Inertial Measurement Unit (IMU) sensor to classify the tremor of three different neurological disorders based on the tremor position and frequency. This research has been carried out in SRM Medical college and Research Centre with 15 patients. The type of neurodegenerative disease of the subject with tremor is evaluated based on the tremor position and tremor frequency level. The data is collected, transmitted, and processed using the IMU sensor with Internet of things (IoT) and Node MCU board. The decision tree algorithm is used for the classification of tremors. ET, PD, and PT tremors are classified based on the tremor frequency and tremor position. A high rate of accuracy is achieved for the developed system when compared with the Neurologist results. The proposed device quantitatively classified the tremor based on the frequency and position among the three different neurological disorders, i.e., ET, PD, and PT tremors.
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4

Persad, A., and K. Meguro. "P.123 Normal pressure hydrocephalus with associated tremor." Canadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques 46, s1 (June 2019): S45—S46. http://dx.doi.org/10.1017/cjn.2019.215.

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Background: Normal pressure hydrocephalus is a frequent cause of cognitive and functional impairment. Many symptoms are shared between Parkinson’s disease and normal pressure hydrocephalus. Only few studies examine extrapyramidal signs in NPH, and only one case report exists describing tremor improvement with shunting. Methods: We performed a retrospective chart review of our NPH database. We selected patients who had both NPH and question of Parkinsonism due to tremor. Results: Six patients with both NPH diagnosis and tremor were identified. Three patients were treated for Parkinson’s disease and followed by neurology. After shunting, all three improved and attempt was made to wean medications, which led to functional decline. The other three patients improved with shunting and after titration of the shunt had resolution of tremor. Conclusions: We provide evidence that NPH can result in tremor, treatable by shunting. We also emphasize that those patients do exist who have both diseases. This likely exists along a continuum. Careful consideration of NPH should be undertaken in those patients with suspected Parkinson’s disease and imaging findings reminiscent of NPH.
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5

He, Ya-Chao, Pei Huang, Qiong-Qiong Li, Qian Sun, Dun-Hui Li, Tian Wang, Jun-Yi Shen, et al. "Mutation Analysis ofHTRA2Gene in Chinese Familial Essential Tremor and Familial Parkinson’s Disease." Parkinson's Disease 2017 (2017): 1–6. http://dx.doi.org/10.1155/2017/3217474.

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Анотація:
Background.HTRA2has already been nominated as PARK13 which may cause Parkinson’s disease, though there are still discrepancies among these results. Recently, Gulsuner et al.’s study found thatHTRA2p.G399S is responsible for hereditary essential tremor and homozygotes of this allele develop Parkinson’s disease by examining a six-generation family segregating essential tremor and essential tremor coexisting with Parkinson’s disease. We performed this study to validate the condition ofHTRA2gene in Chinese familial essential tremor and familial Parkinson’s disease patients, especially essential tremor.Methods. We directly sequenced all eight exons, exon-intron boundaries, and part of the introns in 101 familial essential tremor patients, 105 familial Parkinson’s disease patients, and 100 healthy controls.Results. No exonic variant was identified, while one exon-intron boundary variant (rs2241028) and one intron variant (rs2241027) were detected, both with no clinical significance and uncertain function. There was no difference in allele, genotype, and haplotype between groups.Conclusions.HTRA2exonic variant might be rare among Chinese Parkinson’s disease and essential tremor patients with family history, andHTRA2may not be the cause of familial Parkinson’s disease and essential tremor in China.
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6

Vivar, Guillermina, Dora-Luz Almanza-Ojeda, Irene Cheng, Juan Carlos Gomez, J. A. Andrade-Lucio, and Mario-Alberto Ibarra-Manzano. "Contrast and Homogeneity Feature Analysis for Classifying Tremor Levels in Parkinson’s Disease Patients." Sensors 19, no. 9 (May 4, 2019): 2072. http://dx.doi.org/10.3390/s19092072.

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Early detection of different levels of tremors helps to obtain a more accurate diagnosis of Parkinson’s disease and to increase the therapy options for a better quality of life for patients. This work proposes a non-invasive strategy to measure the severity of tremors with the aim of diagnosing one of the first three levels of Parkinson’s disease by the Unified Parkinson’s Disease Rating Scale (UPDRS). A tremor being an involuntary motion that mainly appears in the hands; the dataset is acquired using a leap motion controller that measures 3D coordinates of each finger and the palmar region. Texture features are computed using sum and difference of histograms (SDH) to characterize the dataset, varying the window size; however, only the most fundamental elements are used in the classification stage. A machine learning classifier provides the final classification results of the tremor level. The effectiveness of our approach is obtained by a set of performance metrics, which are also used to show a comparison between different proposed designs.
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7

Perez Akly, Manuel S., Carla V. Stefani, Lucía Ciancaglini, José S. Bestoso, Jorge A. Funes, Diego J. Bauso, and Cristina H. Besada. "Accuracy of nigrosome-1 detection to discriminate patients with Parkinson’s disease and essential tremor." Neuroradiology Journal 32, no. 6 (May 31, 2019): 395–400. http://dx.doi.org/10.1177/1971400919853787.

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Purpose The use of susceptibility weighted imaging in high field magnetic resonance imaging scanners can detect the nigrosome-1 area located in the caudo-lateral region of the pars compacta in the substantia nigra. This structure comprises a significant amount of dopaminergic neurons and degenerates in the early stages of Parkinson’s disease. Essential tremor is a neurological condition that in some cases could be confused with the early stages of Parkinson’s disease with a possible error in clinical diagnosis. Our purpose is to evaluate the accuracy of nigrosome-1 detection by high resolution magnetic resonance imaging to discriminate Parkinson’s disease from essential tremor. Methods A case–control study compared patients with a clinical diagnosis of Parkinson’s disease and essential tremor. Magnetic resonance imaging studies were performed using a 3T magnetic resonance imaging scanner. The susceptibility weighted imaging sequence was obtained in the axial plane with an isotropic voxel of 0.75 mm. Two independent neuroradiologists evaluated the images without access to clinical patient data. Results Sixteen patients were included in each group (Parkinson’s disease and essential tremor). Average age: Parkinson’s disease group: 71.3 (SD 6.3) and essential tremor group: 68.3 (SD 12.3). For the first evaluator, the nigrosome-1 area was absent in 15 patients with Parkinson’s disease and in two with essential tremor and for the second evaluator was absent in 15 patients with Parkinson’s disease and four with essential tremor. The sensitivity/specificity for the diagnosis of Parkinson’s disease was 93.75%/87.5% for the first evaluator and 93.75%/75% for the second evaluator. Conclusion The detection of the nigrosome-1 area is a useful tool in the differential diagnosis between Parkinson’s disease and essential tremor, with high sensitivity and specificity.
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Luft, Frauke, Sarvi Sharifi, Winfred Mugge, Alfred C. Schouten, Lo J. Bour, Anne-Fleur van Rootselaar, Peter H. Veltink, and Tijtske Heida. "A Power Spectral Density-Based Method to Detect Tremor and Tremor Intermittency in Movement Disorders." Sensors 19, no. 19 (October 4, 2019): 4301. http://dx.doi.org/10.3390/s19194301.

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There is no objective gold standard to detect tremors. This concerns not only the choice of the algorithm and sensors, but methods are often designed to detect tremors in one specific group of patients during the performance of a specific task. Therefore, the aim of this study is twofold. First, an objective quantitative method to detect tremor windows (TWs) in accelerometer and electromyography recordings is introduced. Second, the tremor stability index (TSI) is determined to indicate the advantage of detecting TWs prior to analysis. Ten Parkinson’s disease (PD) patients, ten essential tremor (ET) patients, and ten healthy controls (HC) performed a resting, postural and movement task. Data was split into 3-s windows, and the power spectral density was calculated for each window. The relative power around the peak frequency with respect to the power in the tremor band was used to classify the windows as either tremor or non-tremor. The method yielded a specificity of 96.45%, sensitivity of 84.84%, and accuracy of 90.80% of tremor detection. During tremors, significant differences were found between groups in all three parameters. The results suggest that the introduced method could be used to determine under which conditions and to which extent undiagnosed patients exhibit tremors.
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van Nuland, Annelies J., Rick C. Helmich, Michiel F. Dirkx, Heidemarie Zach, Ivan Toni, Roshan Cools, and Hanneke E. M. den Ouden. "Effects of dopamine on reinforcement learning in Parkinson’s disease depend on motor phenotype." Brain 143, no. 11 (November 2020): 3422–34. http://dx.doi.org/10.1093/brain/awaa335.

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Abstract Parkinson’s disease is clinically defined by bradykinesia, along with rigidity and tremor. However, the severity of these motor signs is greatly variable between individuals, particularly the presence or absence of tremor. This variability in tremor relates to variation in cognitive/motivational impairment, as well as the spatial distribution of neurodegeneration in the midbrain and dopamine depletion in the striatum. Here we ask whether interindividual heterogeneity in tremor symptoms could account for the puzzlingly large variability in the effects of dopaminergic medication on reinforcement learning, a fundamental cognitive function known to rely on dopamine. Given that tremor-dominant and non-tremor Parkinson’s disease patients have different dopaminergic phenotypes, we hypothesized that effects of dopaminergic medication on reinforcement learning differ between tremor-dominant and non-tremor patients. Forty-three tremor-dominant and 20 non-tremor patients with Parkinson’s disease were recruited to be tested both OFF and ON dopaminergic medication (200/50 mg levodopa-benserazide), while 22 age-matched control subjects were recruited to be tested twice OFF medication. Participants performed a reinforcement learning task designed to dissociate effects on learning rate from effects on motivational choice (i.e. the tendency to ‘Go/NoGo’ in the face of reward/threat of punishment). In non-tremor patients, dopaminergic medication improved reward-based choice, replicating previous studies. In contrast, in tremor-dominant patients, dopaminergic medication improved learning from punishment. Formal modelling showed divergent computational effects of dopaminergic medication as a function of Parkinson’s disease motor phenotype, with a modulation of motivational choice bias and learning rate in non-tremor and tremor patients, respectively. This finding establishes a novel cognitive/motivational difference between tremor and non-tremor Parkinson’s disease patients, and highlights the importance of considering motor phenotype in future work.
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10

Raihan, Md Zahid, and Tipu Zahed Aziz. "Deep Brain Stimulation in Sub-Thalamic Nucleus in idiopathic Parkinson’s disease – our initial experience in four cases." Bangladesh Journal of Neurosurgery 9, no. 1 (August 30, 2019): 78–83. http://dx.doi.org/10.3329/bjns.v9i1.42931.

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Parkinson’s Disease ( PD ) is a chronic neurodegenerative disease . It’s cardinal features are resting tremor, Rigidity, Akinesia and postural instability. Idiopathic Parkinson’s disease develops mainly due to degeneration of Dopaminergic neurons of Substantia Nigra. The role of Subthalamic Nucleus ( STN ) in the development of Parkinsonian Tremmor and other cardinal features is not completely understood yet. However previous studies in monkeys , administration of MPTP ( 1-methyl-4-phenyl- 1.2.3.6.-tetrahydropyridine ) proved that sub thalamic nucleus has a direct role in the development of Parkinsonian tremor and other features. We used no Micro Electrode Recording (MER) system,only studied clinically that Parkinsonian tremor stopped immediately after placement of electrode and same thing happened after micro stimulation of the sensorymotor region of the sub thalamic nucleus .Then high frequency deep brain stimulation ( DBS ) of these same four patients were assessed six months after surgery which led to a significant reduction of Parkinsonian tremor as well as other cardinal features of PD ( p< 0.001 ) . Both postural and resting tremor disappeared completely in three cases and significantly reduced in one case Bang. J Neurosurgery 2019; 9(1): 78-83
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Дисертації з теми "Parkinson’s tremor"

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E, N. Shaban, and V. Abousetta S. "Online EMG signal analysis for Parkinson’s tremor determination." Thesis, Boston, USA, 2020. http://openarchive.nure.ua/handle/document/11838.

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In this paper, we introduced a general development of software for quantifying the severity of the Parkinson's tremor. The extracted features from the surface EMG of the wrist and hand muscles were the input of the designed model of the application. Using the application that can record reliably the EMG signals and quantify the levels of tremor may contribute to the early diagnosis of the disorder online.
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2

Shaban, N. E., and V. S. Abousetta. "Online EMG signal analysis for Parkinson’s tremor determination." Thesis, Boston, USA, 2020. http://openarchive.nure.ua/handle/document/13654.

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In this paper, we introduced a general development of software for quantifying the severity of the Parkinson's tremor. The extracted features from the surface EMG of the wrist and hand muscles were the input of the designed model of the application. Using the application that can record reliably the EMG signals and quantify the levels of tremor may contribute to the early diagnosis of the disorder online.
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3

Wolz, Martin, Antje Hähner, Linda Meixner, Matthias Löhle, Heinz Reichmann, Thomas Hummel, and Alexander Storch. "Accurate Detection of Parkinson’s Disease in Tremor Syndromes Using Olfactory Testing." Karger, 2014. https://tud.qucosa.de/id/qucosa%3A70557.

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Background/Aims: The diagnostic value of olfactory testing for the discrimination of tremor-dominant Parkinson’s disease (PD) from other tremor disorders remains enigmatic. We evaluated whether olfactory testing can accurately detect PD in tremor patients. Methods: A retrospective analysis of 299 consecutive subjects referred for the differential diagnosis of a tremor disorder was done. Olfactory testing was performed using ‘Sniffin’ Sticks’, resulting in a composite TDI score of odor threshold (T), discrimination (D), and identification (I). Receiver operating curve (ROC) plots were used to calculate sensitivity/specificity for the detection of PD. Results: Of all subjects, 167 (55.9%) had PD and 85 (28.4%) had essential tremor (ET). The mean TDI score in PD was significantly reduced compared to those in ET and other tremor disorders with no differences between ET and other tremor disorders. ROC analysis revealed strong correlations of TDI scores with PD [area under the curve: 0.85 (95% CI: 0.80–0.89); p < 0.001]. The highest Youden index was observed for a TDI score <25 (Youden index: 0.58). Using this cutoff score and that generated from normative data of healthy controls, the TDI score provided high sensitivity (negative predictive value) and specificity (positive predictive value) of approximately 80% for detecting PD. Conclusion: Olfactory testing is a useful, easily applied and inexpensive diagnostic test which is helpful to detect PD among tremor patients.
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4

Perumal, Shyam Vignesh. "Gait and Tremor Monitoring System for Patients with Parkinson’s Disease Using Wearable Sensors." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6353.

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Анотація:
Typically, a Parkinson’s disease (PD) patient would display instances of tremor and bradykinesia (slowness of movement) at an early stage of the disease and later develop gait disturbances and postural instability. So, it is important to measure the tremor occurrences in subjects to detect the onset of PD. Also, it is equally essential to monitor the gait impairments that the patient displays, as the order at which the PD symptoms appear in subjects vary from one to another. The primary goal of this thesis is to develop a monitoring system for PD patients using wearable sensors. To achieve that objective, our work focused first on identifying the most significant features that would best distinguish between PD and normal healthy subjects. Here, the various gait and tremor features were extracted from the raw data collected from the wearable sensors and further analyzed using statistical analysis and pattern classification techniques to pick the most significant features. In statistical analysis, the analysis of variance (ANOVA) test was conducted to differentiate the subjects based on the values of the mean. Further, pattern classification was carried out using the Linear Discriminant Analysis (LDA) algorithm. The analysis of our results shows that the features of heel force, step distance, stance and swing phases contributed more significantly to achieving a better classification between a PD and a normal subject, in comparison with other features. Moreover, the tremor analysis based on the frequency-domain characteristics of the signal including amplitude, power distribution, frequency dispersion, and median frequency was carried out to identify PD tremor from different types of artifacts.
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5

Chen, Alice. "Should Highly-Skilled Parkinson’s Disease Patients Undergo Deep Brain Stimulation or Thalamotomy?" Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/cmc_theses/2052.

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Parkinson’s disease (PD) is a neurodegenerative disorder characterized by a resting tremor combined with varying degrees of rigidity and bradykinesia. Introduced in the 1950s, thalamotomy is used as a surgical procedure to improve brain function in patients and serves as an effective treatment method for the PD tremor where connections within the thalamus are cut. In 1987, deep brain stimulation (DBS), chronic electrical stimulation of deep neural structures using electrodes, was introduced as a clinical treatment for medically refractory tremor in patients with PD. Though thalamotomy has historically been the primary treatment method for PD, an increasing number of patients have chosen to undergo DBS as it has become increasingly touted as an alternative to ablative therapies. The proposed study examines the advantages and disadvantages of both treatment methods to improve cardinal features in highly-skilled, career-oriented PD patients who actively use motor functions in their work. As an alternative to a simple finger-tapping test used for normal PD patients, a more complex strength-dexterity (S-D) test would be performed on 50 skilled patients to evaluate and compare the effectiveness of tremor suppression between both surgeries. The goal of this experiment is to determine which treatment produces the most short-term benefits for the patient to continue with his or her career with minimal future management required. The results of this study will help determine the preferred treatment method when taking into consideration other external factors such as cost, continual management, and preference for short-term vs. long-term results.
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6

Manohar, Jayashankar. "Detecting Parkinson Tremor Using Bluetooth." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-208250.

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Анотація:
Wearable technology is used today for many different applications such as heart rate monitoring and other clinical applications. This thesis aims at developing a Parkinson tremor monitoring application and contributes to optimizing the power consumptionof the system. The monitoring application is developed by implementing software on an embedded hardware prototype to collect accelerometer sensor data to store it in an SD card and to transfer the sensor data via Bluetooth to PC or mobile devices. Since the wearable device has to consume limited energy supplied by the battery, this project also includes reducing the energy consumption of the system by duty cycling the hardware peripherals of the system.
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7

Erickson-Davis, Cordelia R. "Neurofeedback training for Parkinsonian tremor and bradykinesia /." Connect to online version, 2006. http://ada.mtholyoke.edu/setr/websrc/pdfs/www/2006/153.pdf.

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8

Cheung, Marcus Ting Hin. "Personalized stimuli as treatment for resting tremor in Parkinson's disease." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/62554.

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Resting tremor in Parkinson’s disease (PD) affects quality of life and individuals’ ability to complete activities of daily living. Resting tremor has been shown to respond to transcranial alternating current stimulation (tACS) when delivered out of phase with the tremor. The present work aimed to further investigate potential tACS-based treatment mechanisms by designing and delivering personalized stimuli and extend our understanding of Parkinsonian resting tremor. Nine participants with tremor dominant PD received fourteen unique tACS stimuli to Primary Motor Cortex (M1) and Supplementary Motor Area (SMA). Effect on tremor was measured before and during stimulation via a 9 degree of freedom (DoF) motion sensor. The first principal component score was obtained from Principal Component Analysis (PCA) of these measures and the power of the data was compared before and during stimulation using a two-sample t-test. Four custom stimuli were designed by weighted linear combination of the data with the greatest effect on tremor; two of which were designed to be suppressive and two were designed to be augmentative towards tremor. Average power was calculated following delivery of the personalized and non-personalized stimuli. Regardless of whether tACS was delivered as a personalized or non-personalized stimuli, results indicate an increased average power during stimulation compared to no stimulation and an overall trend towards augmentation of tremor across participants. Supporting analyses, including Multivariate Empirical Mode Decomposition (MEMD) reinforce this finding, showing no clear trend towards any specific frequencies contributing to tremor suppression. The present results suggest that a broad spectrum frequency-based approach is not an effective means of suppressing tremor in people with PD and a phase-based or more targeted frequency approach may have more promise as a treatment mechanism for resting tremor in PD.
Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate
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9

Burgess, Jonathan G. "Identifying tremor-related characteristics of basal ganglia nuclei in Parkinson's disease." Thesis, University of Reading, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.541954.

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10

Davidson, Andrew Doran. "Fundamental Principles of Tremor Propagation in the Upper Limb." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6509.

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Анотація:
Although tremor is the most common movement disorder, there exist few effective tremor-suppressing devices, in part because the characteristics of tremor throughout the upper limb are unknown. To clarify, optimally suppressing tremor requires a knowledge of the mechanical origin, propagation, and distribution of tremor throughout the upper limb. Here we present the first systematic investigation of how tremor propagates between the shoulder, elbow, forearm, and wrist. We simulated tremor propagation using a linear, time-invariant, lumped-parameter musculoskeletal model relating joint torques and the resulting joint displacements. The model focused on the seven main degrees of freedom (DOF) from the shoulder to the wrist and included coupled joint inertia, damping, and stiffness. We deliberately implemented a simple model to focus first on the most basic effects. Simulating tremorogenic joint torque as a sinusoidal input, we used the model to establish fundamental principles describing how input parameters (torque location and frequency) and joint impedance (inertia, damping, and stiffness) affect tremor propagation. We expect that the methods and principles presented here will serve as the groundwork for future refining studies to understand the origin, propagation, and distribution of tremor throughout the upper limb in order to enable the future development of optimal tremor-suppressing devices.
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Книги з теми "Parkinson’s tremor"

1

Susan, Grube, and Patil Parag G, eds. Deep brain stimulation: A new life for people with Parkinson's, dystonia and essential tremor. New York, NY: Demos Health, 2012.

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2

Molnar, Gregory F. Neuronal firing rates in motor thalamus of Parkinson's disease (PD) and Essential tremor (ET) patients. Ottawa: National Library of Canada, 2000.

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3

Walsh, Richard A. Parkinson’s Disease or Essential Tremor? Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190607555.003.0016.

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Анотація:
Fragile X-associated tremor ataxia syndrome is a heredodegenerative syndrome that presents in older men as a tremor syndrome with less prominent ataxia and cognitive impairment initially. The underlying genetic cause, a premutation in the FMR1 gene, results in a toxic accumulation of mRNA. The full mutation, a triple-repeat expansion of more than 200 CGG repeats, gives rise to a reduction in FMR1 protein expression and fragile X, a neurodevelopmental disorder that may be identified in successive male generations. The prevalence of carrier status is high in the general population, and it is likely that most movement disorders clinics will have one or more patients with this syndrome, potentially carrying a label of essential tremor.
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de Bie, Robertus M. A., and Susanne E. M. Ten Holter. A Tremor with an Abnormal Posture. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190607555.003.0018.

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Dystonic tremors are a commonly misdiagnosed group of primary tremor disorders, typically mistaken for Parkinson’s disease or essential tremor. Like most movement disorders, this is a clinical diagnosis, so the overlap in some features between all of these disorders can be confusing to less experienced and even more experienced physicians. A tremor in the presence of a dystonia is a dystonic tremor syndrome, regardless of the clinical features. Treatment of dystonic tremor can be challenging without the same gratifying response seen to levodopa in tremor associated with Parkinson’s disease or to beta-blockers and primidone in essential tremor. Deep-brain stimulation remains an option in the most disabling cases.
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Walsh, Richard A. Parkinson’s Disease with an Unusual Tremor. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190607555.003.0009.

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Multiple system atrophy represents a form of atypical parkinsonism that is challenging to manage and results in rapidly progressive disability and dependence in the absence of effective disease-modifying or symptomatic therapies. Two syndromes are recognized, both associated with autonomic dysfunction—MSA-C and MSA-P, with a predominance of parkinsonian and cerebellar features, respectively. Magnetic resonance imaging can assist with an early diagnosis, demonstrating certain features that can be considered diagnostic in the right clinical context. The typical changes described may not be apparent on an initial scan, so it is worth repeating imaging 1 or 2 years later if the clinical features and course are typical of multiple system atrophy.
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de Bie, Robertus M. A. The Stand-Alone Tremor. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190607555.003.0022.

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Essential tremor is defined as long-standing bilateral hand/arm tremor that is visible and may occur persistently during posture-holding, simple movements, and action. The tremor may be slightly asymmetrical. Other areas of the body that may be affected are head and neck (most frequently), the voice, and legs. Head tremor without limb tremor is accepted as essential tremor, although this definition remains controversial. Essential tremor is a progressive disease and manifests at any age. Tremor in Parkinson’s disease mostly starts unilaterally. A no–no or yes–yes tremor of the head indicates essential tremor, whereas a tremor of the jaw or tongue fits with Parkinson’s disease. The cogwheel phenomenon may also occur in patients with essential tremor. Toxins and medications as the cause for postural/kinetic tremor must be ruled out. Pharmacological options for essential tremor can be unsatisfactory.
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Kaplan, Tamara, and Tracey Milligan. Movement Disorders 1: Tourette’s Syndrome, Essential Tremor, and Parkinson’s Disease (DRAFT). Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190650261.003.0011.

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The video in this chapter explores movement disorders, and focuses on Tourette’s Syndrome, Essential tremor, and Parkinson’s Disease. It outlines the characteristics of each, such as motor and vocal tics in Tourette’s Syndrome, postural or kinetic tremor in Essential tremor, and the four hallmark features of Parkinson’s Disease (bradykinesia, resting tremor, cogwheel rigidity, and postural instability).
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de Bie, Robertus M. A. Beyond Tremor, Slowness, and Stiffness. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190607555.003.0004.

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Parkinson’s disease may be accompanied by a variety of nonmotor symptoms, such as autonomic, cognitive, psychiatric, sensory, and sleep disorders. These may even precede the motor symptoms, and in a considerable proportion of patients nonmotor symptoms are the major determinant of disability, especially in the more advanced stages of the disease. The patient in this chapter is experiencing two nonmotor symptoms—pain and insomnia. If present, it should be determined whether nonmotor symptoms fluctuate, because many are worse in the “off” period. The most common cause for insomnia is untreated or undertreated nocturnal parkinsonism, which is very responsive to levodopa therapy. If a medical condition requiring further evaluation is excluded and a temporal relationship between pain and the medication schedule is recognized, the emphasis should be on adjusting dopaminergic medication accordingly.
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Fletcher, Nicholas. Tremor, ataxia, and cerebellar disorders. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780198569381.003.0898.

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Tremors are characterized by rhythmic oscillations of one or more body parts. Although typically seen in the upper limbs, almost any area may be involved, including the trunk, head, facial muscles, and legs. Sometimes, tremor is not visible at all but may be heard or palpated, for example, in vocal or orthostatic tremor, respectively. In neurological practice, the diagnosis and treatment of tremor is an everyday problem. A common scenario is the distinction between essential tremor and Parkinson’s disease. In this chapter, the wide range of tremors are discussed, with their aetiolology, pathophysiology, diagnosis and management described.Ataxia is a term used to describe a wide range of neurological disorders affecting muscle coordination, speech and balance that reflect dysfunction of a part of the central nervous system involved in motor function. Many of ataxias have a cerebellar pathology as root cause, although it must be remembered that ataxia, clumsiness, disordered ocular motility, dysarthria, and even kinetic or intention tremor are not always caused by cerebellar disease. This chapter describes the wide range of cerebellar disorders and ataxias, as are non-cerebellar ataxias such as Friedreich’s ataxia.
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Bowker, Lesley K., James D. Price, Ku Shah, and Sarah C. Smith. Neurology. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198738381.003.0007.

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This chapter provides information on the ageing brain and nervous system, tremor, neuropathic pain/neuralgia, presentation of Parkinson’s disease, management of Parkinson’s disease, diseases masquerading as Parkinson’s disease, epilepsy and its drug treatment, neuroleptic malignant syndrome, motor neuron disease, peripheral neuropathies, subdural haematoma, sleep and insomnia, and other sleep disorders.
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Частини книг з теми "Parkinson’s tremor"

1

Bhidayasiri, Roongroj, and Daniel Tarsy. "Tremor-Dominant Parkinson’s Disease." In Current Clinical Neurology, 8–9. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-60327-426-5_4.

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Beuter, Anne, and Roderick Edwards. "Tremor in Parkinson’s Disease." In Advances in Behavioral Biology, 51–60. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0179-4_6.

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Matsumoto, Joseph Y. "Tremor Disorders: Overview." In Parkinson’s Disease and Movement Disorders, 273–81. Totowa, NJ: Humana Press, 2000. http://dx.doi.org/10.1007/978-1-59259-410-8_21.

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Alanis, Valeria P., Hiram A. Cantú, Umberto León, Alejandro Melo, Julio C. Salinas, Diego Velasco, and Jorge de-J. Lozoya-Santos. "Parkinson’s Tremor Data Analysis Device." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 199–208. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73323-4_19.

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Hubble, Jean Pintar. "Essential Tremor: Diagnosis and Treatment." In Parkinson’s Disease and Movement Disorders, 283–95. Totowa, NJ: Humana Press, 2000. http://dx.doi.org/10.1007/978-1-59259-410-8_22.

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Pourfar, Michael, Martin Niethammer, and David Eidelberg. "Metabolic Networks in Parkinson’s Disease." In Mechanisms and Emerging Therapies in Tremor Disorders, 403–15. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4027-7_22.

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Nguyen, J. P., S. Raoul, C. Deligny, V. Roualdes, and Y. Keravel. "Management of Tremors other than Essential Tremor and Parkinson’s Disease." In Textbook of Stereotactic and Functional Neurosurgery, 1757–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-69960-6_105.

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DeLong, Mahlon R., and Stewart A. Factor. "Deep Brain Stimulation for Tremor in Parkinson’s Disease." In Current Clinical Neurology, 21–23. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-97897-0_5.

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Kobayashi, Kazutaka, Y. Katayama, M. Kasai, H. Oshima, C. Fukaya, and T. Yamamoto. "Localization of thalamic cells with tremor-frequency activity in Parkinson’s disease and essential tremor." In Neurosurgical Re-Engineering of the Damaged Brain and Spinal Cord, 137–39. Vienna: Springer Vienna, 2003. http://dx.doi.org/10.1007/978-3-7091-6081-7_29.

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Lopez, María José Enciso, and Ángel Luis Rodríguez Morales. "Postural Tremor Reduction System Design for Parkinson’s Disease Patients." In IFMBE Proceedings, 1191–99. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30648-9_155.

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Тези доповідей конференцій з теми "Parkinson’s tremor"

1

Wang, Jiamin, Sunit K. Gupta, and Oumar Barry. "Towards Data-Driven Modeling of Pathological Tremors." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22147.

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Abstract Understanding the dynamics of pathological tremors (e.g., Parkinson’s Disease, Essential Tremor) is crucial to developing effective treatments for these neurological disorders. This paper studies the data-driven modeling of periodic and quasiperiodic tremors. A general neuromusculoskeletal model is proposed to serve as the theoretical basis of this study. The Parkinsonian tremor data is first observed in terms of periodicity, frequency composition, and chaotic characteristics, which confirm tremor is a nonlinear dynamics problem. Two data-driven models are then proposed to predict the nonlinear dynamics of tremor: (1) a model-free approach via long short-term memory recurrent neural network, and (2) a model-based approach via extended dynamical mode decomposition. These models are compared to existing models and the results show that the proposed models outperform existing models for long term prediction of tremor.
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Winston, Sam E., Riley C. Dehmer, and Timothy A. Doughty. "Parkinsons Disease: Tremor Suppression With Wearable Device." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-70910.

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Abstract Parkinson’s Disease (PD) is a neurodegenerative disorder that affects nearly a million people in the United States. Hand tremors are a well-known symptom associated with PD and result in anxiety, frustration, and malnutrition. While there is no cure, several approaches attempt to treat the symptoms. Many are invasive, including the use of pharmaceuticals and surgery [1]. Noninvasive technologies are often cumbersome and do not address the conspicuous nature experiencing tremors in public. This study is motivated by design criteria established from previous research [2], with a goal of an affordable, purely mechanical solution. In both cases, human subject testing echoed lab tests in effective tremor reduction. The extension to a wearable device gives the user the ability to hold or handle any object, or no object, with a significant reduction in tremor. Two separate wearable devices were tested for effectiveness while the simulated user ‘held’ two different objects to simulate different applications. Biomechanical modeling of the human hand informed the development of an adjustable mechanical hand-tremor system for testing. Models of the devices and the hand-device interface were used to simulate the dynamic response of the coupled systems. Each device was secured to the mechanical hand-tremor system and harmonic stimulus and response data was collected over the range of typical tremor frequencies. The results demonstrate the versatility of both designs for reducing the oscillations associated with tremors. The Ratio of Reduction (RoR) was defined to compare the tremor amplitude of the hand-tremor system with and without the device. Both designs were considered effective for each object with a max RoR of 28.09 for Device A and a max RoR of 99.32 for Device B.
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Shah, Vrutangkumar V., Sachin Goyal, and Harish Palanthandalam-Madapusi. "A Biomechanical Approach to Diagnosis and Monitoring of Parkinson’s Disease." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46781.

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Parkinson’s disease is an idiopathic and degenerative disorder of the central nervous system. Among the symptoms, the tremor at rest is one of the prominent symptoms. The challenge however is that there are no definitive diagnostic test that can confirm the presence or severity of Parkinson’s disease. This is a serious handicap especially since the drugs usually prescribed to control these symptoms have serious side effects and their dosages have to be tuned extensively. Also, the exact origin of tremor is unknown. There have been recent efforts [19] to understand the mechanism behind the Parkinsonian tremor, from a control-system perspectives. From these efforts, it appears that increased sensorimotor loop delay may be a cause for Parkinsonian tremor and thus serve as a key distinguishing feature. In the current work, we adopted this hypothesis and with the help of a relatively straightforward analysis of the motor control loop along with the help of some simulation and experimental examples, we first attempt to explain several qualitative observations relating to Parkinson’s Disease. Further, we explore the possibilities of for progress tracking, diagnosis, and early diagnosis before onset of tremor using biomechanical means.
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Brooks, Joseph Bruno Bidin, Fábio César Prosdócimi, Lara Fenley Granzotto, and Matheus Garcez Jorge Mariani. "Camptocormia and genetic Parkinson’s disease caused by the mutation of the LRRK2 gene. Case report." In XIII Congresso Paulista de Neurologia. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1516-3180.183.

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Context: Parkinsonism is a clinical syndrome characterized by bradykinesia, tremor at rest, muscle stiffness and postural instability. Parkinson’s disease is the most common cause of parkinsonism. Pathogenic mutations in the leucine- rich repeat kinase 2 gene (LRRK2) have been identified in PARK8-linked autosomal dominant parkinsonism. This mutation is the most common and explains about 1–7% of family cases of parkinsonism of European and American origin and 1–3% of sporadic PD. This case report was approved by the Ethics Committee of Universidade Metropolitana de Santos. Case Report: The present case relates to a 40-year-old, white man, who presented insidious and progressive parkinsonism for 6 years, akinetic-rigid and asymmetric (Hoehn Yahr 2.5 scale) associated with early camptocormia and non-motor symptoms and partial response to levodopa. The classic phenotype of late-onset parkinsonism was found on the paternal side of the patient’s family, suggesting family inheritance. Exome sequencing showed heterozygous mutation PARK8 LRRK2 (Gly2019Ser). Conclusions: The presentation of this case was aimed at alerting to Parkinson’s genetic disease in adults with family inheritance associated with early camptocormia. The presentation of this case was aimed at alerting to Parkinson’s genetic disease in adults with family inheritance associated with early camptocormia.
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Zanini, Rafael Anicet, and Esther Luna Colombini. "Parkinson sEMG signal prediction and generation with Neural Networks." In Concurso de Teses e Dissertações da SBC. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/ctd.2021.15759.

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Parkinson’s Disease (PD) is a neurodegenerative disorder characterized by symptoms like resting and action tremors, which cause severe impairments to the patient’s life. Recently, many assistance techniques have been proposed to minimize the disease’s impact on patients’ life. However, most of these methods depend on data from PD’s surface electromyography (sEMG), which is scarce. In this work, we propose the first methods, based on Neural Networks, for predicting, generating, and transferring the style of patient-specific PD sEMG tremor signals. This dissertation contributes to the area by i) comparing different NN models for predicting PD sEMG signals to anticipate resting tremor patterns ii) proposing the first approach based on Deep Convolutional Generative Adversarial Networks (DCGANs) to generate PD’s sEMG tremor signals; iii) applying Style Transfer (ST) for augmenting PD’s sEMG signals with publicly available datasets of non-PD subjects; iv) proposing metrics for evaluating the PD’s signal characterization in sEMG signals. These new data created by our methods could validate treatment approaches on different movement scenarios, contributing to the development of new techniques for tremor suppression in patients.
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Ly, Khoi, Aimee Cloutier, and James Yang. "Quantitative Motor Assessment, Detection, and Suppression of Parkinson’s Disease Hand Tremor: A Literature Review." In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/detc2016-59095.

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Parkinson’s disease (PD) is difficult to detect before the onset of symptoms; further, PD symptoms share characteristics with symptoms of other diseases, making diagnosis of PD a challenging task. Without proper diagnosis and treatment, PD symptoms including tremor, bradykinesia, and cognitive problems deteriorate quickly into patients’ late life. Among them, the most distinguishable manifestations of PD are rest and postural tremor. Tremor is defined as an involuntary shaking or quivering movement of the hands or feet. Unified Parkinson’s Disease Rating Scale (UPDRS), Hoehn and Yahr (H&Y) scales are the most common rating scales that quantify the severity of PD. Due to the lack of consistency in these diagnostic tests, researchers are looking for devices for quantification and detection that can provide more objective PD motor assessments. Additionally, since there is currently no cure for PD, temporary PD symptom suppression is an active research area for improving patients’ quality of life. In this survey, the current state of research on Parkinson’s disease hand tremor quantification, detection, and suppression is discussed, especially focusing on electromechanical devices. The future direction of research on these devices is also considered.
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Tuleasca, C., E. Najdenovska, A. Griffa, N. Girard, J. Champoudry, T. Witjas, J. Régis, et al. "Resting-State fMRI Reveals Tremor Network Alterations in Parkinson’s Disease versus Essential Tremor." In Joint Annual Meeting 2017: Swiss Society of Neurosurgery, Swiss Society of Neuroradiology. Georg Thieme Verlag KG, 2017. http://dx.doi.org/10.1055/s-0037-1603859.

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Doughty, Timothy A., and Nicholas Bankus. "Mechanical Modeling and Design for Reduction of Parkinsonian Hand Tremor." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-39073.

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Most of the active research in reducing Parkinsonian tremor involves invasive surgeries or medical treatment. In this paper hand tremors associated with Parkinson’s Disease (PD) are studied and passive vibration control methods are developed and tested. Patients with PD are surveyed regarding difficulties with hand tremor during the act of eating. The result leads to design criteria for an enhanced eating utensil and the establishment of meaningful testing methods for measuring hand tremor. Tremor data collected from several PD patients provides insight into the nature of the motion and allows for the development of test fixture and prototypes. This experimental data is coupled with linear model identification testing for the free response of a “healthy” hand undergoing the same motions. The resulting differential equation model, where the system input is realized as actuation through the biomechanics of the forearm and wrist, is used in the design of an eating utensil for vibration reduction. With self-excitation and the existence of harmonics, the tremor data is also used to develop a nonlinear differential equation model, where the complete neurological/mechanical system is realized with an equivalent mechanical system. This nonlinear model is shown to mimic the tremor data and is used to enhance the development of the vibration absorber. A prototype of the vibration absorber is built, validated on the test fixture, and tremor reduction data is collected again with PD patients.
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Zhu, Na, and Nathaniel S. Miller. "Assessment of Parkinson’s Disease Tremor and Correlation Analysis With Applied Signal Processing." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10622.

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Abstract Accurate measurement and assessment of Parkinson’s disease (PD) tremor is important for patients, clinicians, and researchers to track changes in disease progression and the effectiveness of therapeutic interventions. This study measured resting, postural, and kinetic tremor from patient’s most-affected hand with accelerometers and gyrometers, thus the linear and rotational motions in the x, y, z directions were obtained. Data were collected when patients were both ON and OFF their anti-PD medications. A bandpass filter was applied to extract raw tremor information and several signal processing algorithms were used to analyze the data in both time and frequency domains, including the correlations between motions at different directions. The results of medication effectiveness on PD tremor and the correlational analyses will be discussed.
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Zhu, Linda, Nathaniel S. Miller, Charlotte Tang, Sriram Pendyala, Quinn Hanses, and Lacie Gladding. "Reliability Check of an Assessment System for Parkinson’s Disease Tremor Monitoring With Portable Devices." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-71144.

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Abstract Tremor, or an involuntary and oscillatory movement of a body part, is a cardinal symptom of Parkinson’s disease (PD) that can significantly impact activities of daily living in people with PD (PwPD). Although tremor can be mitigated with anti-PD medications, medication effectiveness is mixed for PwPD. Therefore, daily monitoring and assessment of tremor are of interest to PwPD, clinicians, and researchers. While several sensors and wearable devices have been developed and introduced to the consumer market, high costs limit their accessibility. The current research is two-fold. First, an assessment system based on multiple algorithms is developed for evaluating the reliability of measurements of PD symptoms: hand tremor and finger/hand movement speed. Second, an Android mobile application was designed and developed to capture finger-tapping frequencies and measurements of several PD symptoms like hand tremor. A healthy young adult participant produced a self-generated tremor for this study. The participant held the portable device and conducted self-measurements by following in-app instructions. Resting tremor was measured while the participant rested his upper extremity on the arm of a chair, postural tremor was measured while he maintained a position against gravity, and kinetic tremor was measured during a movement task. Data collection took approximately fifteen minutes. The linear and rotational motions, respectively, were collected by accelerometers and gyroscopes embedded within the mobile device. The results were captured and delivered to a cloud database. An assessment system with multiple algorithms provided a final evaluation of the participant’s tremor. The process included three parts. First, calculation of root-mean-square (RMS) values at all linear and rotational directions was conducted to provide tremor strength. Second, fast Fourier transform (FFT) extracted the peak frequency at each direction. The powers of peaks were compared and the highest peak was defined as the dominant frequency and that frequency’s corresponding direction of motion. Third, hand and motion correlation analysis was used to find any coherence of tremor on 3-D motions. To test the reliability of motion measurement, the same motion input was applied to multiple devices simultaneously. The outputs of different types of mobile devices were evaluated, while considering various factors and models of mobile devices in the market (i.e., device size, weight, operating system, sampling frequency, and accuracy during the measurement). Multiple trials were conducted to test the reliability of the assessment system and the performance of the mobile app. Additionally, the mobile application supports finger tapping tests that measure hand movement speed, which is commonly impaired in PwPD. Both tremor and movement speed measurements can be used to evaluate disease progression over time and could support focused medication adjustments based on symptom data.
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Звіти організацій з теми "Parkinson’s tremor"

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Ni, Jiachun, Qiong Jiang, Gang Mao, Yi Yang, Qin Wei, Changcheng Hou, Xiangdong Yang, Wenbin Fan, and Zengjin Cai. The effectiveness and safety of acupuncture for constipation associated with Parkinson’s disease: Protocol for a systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, February 2022. http://dx.doi.org/10.37766/inplasy2022.2.0091.

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Review question / Objective: Is acupuncture a safe and effective therapy for constipation associated with Parkinson’s disease? Our aim is to assess the effectiveness and safety of acupuncture for constipation associated with PD and give guidance to future research direction. Condition being studied: Parkinson’s disease (PD) is a prevalent degenerative disease of nervous system characterized mainly by static tremor, bradykinesia, myotonia, postural gait disorders and other non-motor symptoms. According to variations on race, ethnicity, age and sex, the incidence of PD ranges from 8 to 20.5 per 100, 000 individuals annually. One global research shows that there were 6.1 million individuals suffer from PD in 2016 and will be 12 million patients around the world. According to several outcomes of case-control studies, the prevalence of constipation in PD varies from 28% to 61%. Constipation, as a common gastrointestinal disease which refers to the clinical presentation of reduced spontaneous complete bowel movement, dyschezia, feeling of incomplete defecation and outlet obstruction, is demonstrated to antedate the motor symptom and it's severity is related to the progression of PD. Acupuncture has been proved to act on the pathogenesis of constipation associated with PD. The proposed systematic review we're about to present is the first advanced evidence-based medical evidence in this area.
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Wang, Xiao, Hong Shen, Yujie Liang, Yixin Wang, Meiqi Zhang, and Hongtao Ma. Effectiveness of Tango Intervention on Motor Symptoms in Patients with Parkinson's Disease: A Protocol for Systematic Review and Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, May 2022. http://dx.doi.org/10.37766/inplasy2022.5.0009.

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Review question / Objective: Parkinson's disease (PD) is a degenerative neurological disease caused by the loss of dopaminergic neurons in the pars compacta of the substantia nigra of the brain, resulting in lesions in the basal ganglia. The main motor symptoms of PD include resting tremor, rigidity, akinesia or bradykinesia and postural instability. As an exercise intervention based on musical accompaniment, tango dance has shown positive effects on the rehabilitation of motor symptoms in PD patients in recently. In this study, we systematically reviewed the efficacy of tango intervention in alleviating the motor symptoms of patients with PD. Condition being studied: Parkinson. Information sources: The following electronic databases will be searched: PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science Core collection, and China National Knowledge Infrastructure Database (CNKI) and WanFang Database.
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Fu, Chengwei, Ziqiang Xia, Menghan Feng, Zhicheng Zhou, and Bo Liu. Comparative efficacy of noninvasive brain stimulation for the treatment of Parkinson disease: a systematic review and network meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, March 2022. http://dx.doi.org/10.37766/inplasy2022.3.0151.

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Анотація:
Review question / Objective: A variety of noninvasive brain stimulation have been applied in patients with Parkinson disease, but it is still controversial which is the best. Condition being studied: Parkinson disease(PD) is a highly prevalent neurodegenerative disease characterized by tremor, bradykinesia, rigidity. Currently, a series of noninvasive brain stimulation(NIBS) have been developed for PD. Some meta-analysis has proved the efficacy of NIBS. However, it is still unclear which NIBS is best. Therefore, we will conduct the problem by network meta-analysis.
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