Clinical neurophysiology of Parkinson’s disease and parkinsonism

Clinical Neurophysiology Practice, Journal Year: 2022, Volume and Issue: 7, P. 201 - 227

Published: Jan. 1, 2022

This review is part of the series on clinical neurophysiology movement disorders. It focuses Parkinson’s disease and parkinsonism. The topics covered include pathophysiology tremor, rigidity bradykinesia, balance gait disturbance myoclonus in disease. use electroencephalography, electromyography, long latency reflexes, cutaneous silent period, studies cortical excitability with single paired transcranial magnetic stimulation, plasticity, intraoperative microelectrode recordings recording local field potentials from deep brain electrocorticography are also reviewed. In addition to advancing knowledge pathophysiology, neurophysiological can be useful refining diagnosis, localization surgical targets, help develop novel therapies for

Language: Английский

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The effects of transcranial direct current stimulation on gait in patients with Parkinson’s disease: a systematic review

Translational Neurodegeneration, Journal Year: 2021, Volume and Issue: 10(1)

Published: June 29, 2021

Abstract Background Gait problems are an important symptom in Parkinson’s disease (PD), a progressive neurodegenerative disease. Transcranial direct current stimulation (tDCS) is neuromodulatory intervention that can modulate cortical excitability of the gait-related regions. Despite increasing number tDCS studies PD, efficacy this technique for improving gait has not been systematically investigated yet. Here, we aimed to explore effects on based available experimental studies. Methods Using PRISMA (Preferred Reporting Items Systematic Reviews and Meta-Analyses) approach, PubMed, Web Science, Scopus, PEDro databases were searched randomized clinical trials assessing effect patients with PD. Results Eighteen included systematic review. Overall, targeting motor cortex supplementary area bilaterally seems be promising rehabilitation Studies dorosolateral prefrontal or cerebellum showed more heterogeneous results. More needed compare different protocols, including protocols applying alone and/or combination conventional treatment Conclusions approach Anodal over areas shown positive gait, but other less promising. However, heterogeneities methods results have made it difficult draw firm conclusions. Therefore, explorations required optimize efficacy.

Language: Английский

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Review—Emerging Portable Technologies for Gait Analysis in Neurological Disorders

Frontiers in Human Neuroscience, Journal Year: 2022, Volume and Issue: 16

Published: Feb. 3, 2022

The understanding of locomotion in neurological disorders requires technologies for quantitative gait analysis. Numerous modalities are available today to objectively capture spatiotemporal and postural control features. Nevertheless, many obstacles prevent the application these their full potential research especially clinical practice. These include required expert knowledge, time data collection, missing standards analysis reporting. Here, we provide a technological review wearable vision-based portable motion tools that emerged last decade with recent applications such as Parkinson's disease Multiple Sclerosis. goal is enable reader understand individual strengths limitations order make an informed decision own investigations applications. We foresee ongoing developments toward user-friendly automated devices will allow closed-loop applications, long-term monitoring, telemedical consulting real-life environments.

Language: Английский

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Proof of Concept in Artificial-Intelligence-Based Wearable Gait Monitoring for Parkinson’s Disease Management Optimization

Biosensors, Journal Year: 2022, Volume and Issue: 12(4), P. 189 - 189

Published: March 23, 2022

Parkinson’s disease (PD) is the second most common progressive neurodegenerative disorder, affecting 6.2 million patients and causing disability decreased quality of life. The research oriented nowadays toward artificial intelligence (AI)-based wearables for early diagnosis long-term PD monitoring. Our primary objective monitoring assessment gait in patients. We propose a wearable physiograph qualitative quantitative assessment, which performs bilateral tracking foot biomechanics unilateral arm balance. Gait patterns are assessed by means correlation. surface plot correlation coefficient matrix, generated from recorded signals, classified using convolutional neural networks into physiological or PD-specific gait. novelty given proposed AI-based decisional support procedure assessment. A proof concept validated clinical environment on five healthy controls, proving to be feasible solution ubiquitous PD. management demonstrates complexity human body. platform empowering multidisciplinary, AI-evidence-based decision assessments optimal dosing between drug non-drug therapy could lay foundation affordable precision medicine.

Language: Английский

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Wearable biofeedback device to assess gait features and improve gait pattern in people with parkinson’s disease: a case series

Journal of NeuroEngineering and Rehabilitation, Journal Year: 2024, Volume and Issue: 21(1)

Published: June 26, 2024

Abstract Introduction People with Parkinson’s Disease (PD) show abnormal gait patterns compromising their independence and quality of life. Among all alterations due to PD, reduced step length, increased cadence, decreased ground-reaction force during the loading response push-off phases are most common. Wearable biofeedback technologies offer possibility provide correlated single or multi-modal stimuli associated specific events performance, hence promoting subjects’ awareness disturbances. Moreover, portability applicability in clinical home settings for rehabilitation increase efficiency management PD. The Vibrotactile Bidirectional Interface (BI) is a device designed extract features real-time deliver customized vibrotactile stimulus at waist PD subjects synchronously phases. aims this study were measure effect BI on parameters usually compromised by typical bradykinetic assess its usability safety practice. Methods In case series, seven (age: 70.4 ± 8.1 years; H&Y: 2.7 0.3) used performed test 10-meter walkway (10mWT) two-minute walk (2MWT) as pre-training (Pre-trn) post-training (Post-trn) assessments. Gait tests executed random order (Bf) without (No-Bf) activation stimulus. All three training sessions 40 min familiarize themselves walking activities. A descriptive analysis (i.e., speed, distance, double-support phase) was carried out. 2-sided Wilcoxon sign-test differences between Bf No-Bf assessments ( p < 0.05). Results After improved speed (Pre-trn_No-Bf: 0.72(0.59,0.72) m/sec; Post-trn_Bf: 0.95(0.69,0.98) = 0.043) length 0.87(0.81,0.96) meters; 1.05(0.96,1.14) 0.023) using 10mWT. Similarly, distance 97.5 (80.3,110.8) 118.5(99.3,129.3) 0.028) duration phase 29.7(26.8,31.7) %; 27.2(24.6,28.7) 0.018) 2MWT. An immediate detected cadence 108(103.8,116.7) step/min; Pre-trn_Bf: 101.4(96.3,111.4) Pre-trn, Post-trn (Post-trn_No-Bf: 112.5(97.5,124.5) 0.043). SUS scores 77.5 five 80.3 two subjects. terms safety, completed protocol any adverse events. Conclusion seems be usable safe users. Temporal have been measured providing detailed outcomes. short period suggests improvements people This research serves preliminary support future integration an instrument assessment both hospital remote environments. Trial registration registered (DGDMF.VI/P/I.5.i.m.2/2019/1297) approved General Directorate Medical Devices Pharmaceutical Service Italian Ministry Health ethics committee Lombardy region (Milan, Italy).

Language: Английский

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Techniques for the detection and management of freezing of gait in Parkinson's disease – A systematic review and future perspectives

MethodsX, Journal Year: 2023, Volume and Issue: 10, P. 102106 - 102106

Published: Jan. 1, 2023

Freezing of Gait (FoG) is one the most critical debilitating motor symptoms advanced Parkinson's disease (PD) with a higher rate occurrence in aged people. PD affects cardinal functioning and leads to non-motor symptoms, including cognitive neurobehavioral abnormalities, autonomic dysfunctions sleep disorders. Since its pathogenesis complex unclear yet, this paper targets studies done on pathophysiology epidemiology FoG PD. disorder features vary from festination (involuntary hurrying walking) freezing gait (breakdown repetitive movement steps despite intention walk) patients. Hence, it difficult assess clinical trials. Therefore, current research emphasizes wearable sensor-based systems over pharmacology surgical methods.•This presents technological review various techniques used for assessment comprehensive comparison.•Researchers are aiming at development wireless assistive devices (a) predict episode different environment, (b) acquire long-term data real-time analysis, (c) cue patients.•We summarize work till now future directions needed suitable cueing mechanism overcome FoG.

Language: Английский

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Context Recognition Algorithms for Energy-Efficient Freezing-of-Gait Detection in Parkinson’s Disease

Sensors, Journal Year: 2023, Volume and Issue: 23(9), P. 4426 - 4426

Published: April 30, 2023

Freezing of gait (FoG) is a disabling clinical phenomenon Parkinson’s disease (PD) characterized by the inability to move feet forward despite intention walk. It one most troublesome symptoms PD, leading an increased risk falls and reduced quality life. The combination wearable inertial sensors machine learning (ML) algorithms represents feasible solution monitor FoG in real-world scenarios. However, traditional detection process all data indiscriminately without considering context activity during which occurs. This study aimed develop lightweight, context-aware algorithm that can activate systems only under certain circumstances, thus reducing computational burden. Several approaches were implemented, including ML deep (DL) recognition methods, as well single-threshold method based on acceleration magnitude. To train evaluate algorithms, from single sensor extracted using three different datasets encompassing total eighty-one PD patients. Sensitivity specificity for ranged 0.95 0.96 0.80 0.93, respectively, with one-dimensional convolutional neural network providing best results. threshold approach performed better than ML- DL-based methods when evaluating effect awareness performance. Overall, allow discarding more 55% non-FoG less 4% episodes. results indicate classifier reduce burden significantly affecting rate. Thus, implementation present energy-efficient long-term monitoring ambulatory free-living settings.

Language: Английский

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Effectiveness of Therapies Based on Mirror Neuron System to Treat Gait in Patients with Parkinson’s Disease—A Systematic Review

Journal of Clinical Medicine, Journal Year: 2022, Volume and Issue: 11(14), P. 4236 - 4236

Published: July 21, 2022

Parkinson's disease (PD) is a neurodegenerative that alters gait patterns from early stages. The visuo-motor training strategies such as action observation (AO) and motor imagery (MI) are based on the activity of mirror neuron system (MNS) facilitate re-learning. main purpose this systematic review was to analyze current scientific evidence about effectiveness MNS's treatments (AO MI) treat in patients with PD. Searches were completed databases PubMed, Web Science, PEDro between November December 2021. following keywords used: "Parkinson disease", "mirror neurons", "gait", "action observation", "motor imagery". Randomized control trials last 5 years written English or Spanish included. Two independent reviewers screened articles applied eligibility criteria, third reviewer assisted process. A total six included for final revision. risk bias assessed Scale. effects AO MI using different outcome measures referenced terms severity, quality life, balance, gait. Training effective improving

Language: Английский

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Physical Rehabilitation of Patients with Parkinson’s Disease

Cambridge University Press eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 238 - 251

Published: Jan. 7, 2025

Language: Английский

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Predicting Freezing of Gait in Parkinson’s Disease: A Machine-Learning-Based Approach in ON and OFF Medication States

Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(6), P. 2120 - 2120

Published: March 20, 2025

Background: Freezing of gait (FoG) is a debilitating motor symptom Parkinson’s disease (PD), characterized by sudden episodes where patients struggle to initiate or sustain movement, often describing sensation their feet being “glued the ground.” This study investigates potential machine-learning (ML) models predict FoG severity in PD patients, focusing on influence dopaminergic medication comparing parameters ON and OFF states. Methods: Specifically, this employed spatiotemporal features develop predictive model for severity, leveraging random forest regressor identify most influential associated with each state. The results indicate that achieved higher performance OFF-medication condition (R² = 0.82, MAE 2.25, MSE 15.23) compared ON-medication 0.52, 4.16, 42.00). Results: These findings suggest treatment alters dynamics, potentially reducing reliability predictions when are medicated. Feature importance analysis revealed distinct characteristics across In condition, step length parameters, particularly left mean, were dominant predictors, alongside swing time stride width, indicating role spatial temporal control without medication. contrast, under width speed emerged as followed stepping frequency, reflecting how influences stability movement rhythm. Conclusions: highlight need account medication-induced variability, ensuring more reliable detection. By integrating ML-based prediction, contributes development personalized intervention strategies experiencing episodes.

Language: Английский

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