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Tremor

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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...

Improved detection of Parkinsonian resting tremor with feature engineering and Kalman filtering.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Accurate and reliable detection of tremor onset in Parkinson's disease (PD) is critical to the success of adaptive deep brain stimulation (aDBS) therapy. Here, we investigated the potential use of feature engineering and machine learning m...

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.

Mixed-reality assistive robotic power chair simulator for Parkinson's tremor testing.

Medical engineering & physics
This note describes the development of a mixed-reality assistive robotic wheel chair simulator for testing of Parkinson's tremor mitigation and operator assistance. It consists of a power chair (PCh), roller dynamometer, head mounted virtual reality ...

Parkinson's Disease EMG Data Augmentation and Simulation with DCGANs and Style Transfer.

Sensors (Basel, Switzerland)
This paper proposes two new data augmentation approaches based on Deep Convolutional Generative Adversarial Networks (DCGANs) and Style Transfer for augmenting Parkinson's Disease (PD) electromyography (EMG) signals. The experimental results indicate...

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...

Parkinson's Disease Tremor Detection in the Wild Using Wearable Accelerometers.

Sensors (Basel, Switzerland)
Continuous in-home monitoring of Parkinson's Disease (PD) symptoms might allow improvements in assessment of disease progression and treatment effects. As a first step towards this goal, we evaluate the feasibility of a wrist-worn wearable accelerome...

Learning fine-grained estimation of physiological states from coarse-grained labels by distribution restoration.

Scientific reports
Due to its importance in clinical science, the estimation of physiological states (e.g., the severity of pathological tremor) has aroused growing interest in machine learning community. While the physiological state is a continuous variable, its cont...