AIMC Topic: Tremor

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Unraveling Parkinson's disease motor subtypes: A deep learning approach based on spatiotemporal dynamics of EEG microstates.

Neurobiology of disease
BACKGROUND: Despite prior studies on early-stage Parkinson's disease (PD) brain connectivity and temporal patterns, differences between tremor-dominant (TD) and postural instability/gait difficulty (PIGD) motor subtypes remain poorly understood. Our ...

Explainable machine learning for movement disorders - Classification of tremor and myoclonus.

Computers in biology and medicine
BACKGROUND: Treatment for essential tremor (ET) and cortical myoclonus (CM) differs. As their clinical distinction can be difficult, with large inter- and intra-observer variability, there is a need for additional diagnostic tools.

Multi-Objective Optimization-Based Assist-as-Needed Controller for Improved Quality of Assistance in Rehabilitation Robotics.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Assist-as-needed (AAN) is a paradigm in rehabilitation robotics based on the fact that more active participation from human users promotes faster recovery of motor functions. Moreover, the patients and public engaged and involved in our research desi...

Predicting Early Stage Drug Induced Parkinsonism using Unsupervised and Supervised Machine Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Drug Induced Parkinsonism (DIP) is the most common, debilitating movement disorder induced by antipsychotics. There is no tool available in clinical practice to effectively diagnose the symptoms at the onset of the disease. In this study, the variati...

Technology-Based Objective Measures Detect Subclinical Axial Signs in Untreated, de novo Parkinson's Disease.

Journal of Parkinson's disease
BACKGROUND: Technology-based objective measures (TOMs) recently gained relevance to support clinicians in the assessment of motor function in Parkinson's disease (PD), although limited data are available in the early phases.

Multiple-Instance Learning for In-The-Wild Parkinsonian Tremor Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Parkinson's Disease (PD) is a neurodegenerative disorder that manifests through slowly progressing symptoms, such as tremor, voice degradation and bradykinesia. Automated detection of such symptoms has recently received much attention by the research...

Automated assessment of symptom severity changes during deep brain stimulation (DBS) therapy for Parkinson's disease.

IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
Deep brain stimulation (DBS) is currently being used as a treatment for symptoms of Parkinson's disease (PD). Tracking symptom severity progression and deciding the optimal stimulation parameters for people with PD is extremely difficult. This study ...

A fuzzy neural network sliding mode controller for vibration suppression in robotically assisted minimally invasive surgery.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: It is very important for robotically assisted minimally invasive surgery to achieve a high-precision and smooth motion control. However, the surgical instrument tip will exhibit vibration caused by nonlinear friction and unmodeled dynamic...

Multistep prediction of physiological tremor based on machine learning for robotics assisted microsurgery.

IEEE transactions on cybernetics
For effective tremor compensation in robotics assisted hand-held device, accurate filtering of tremulous motion is necessary. The time-varying unknown phase delay that arises due to both software (filtering) and hardware (sensors) in these robotics i...