相关论文: Exploring Motion Boundaries in an End-to-End Netwo…
In the past few years, there are several researches on Parkinson's disease (PD) recognition using single-photon emission computed tomography (SPECT) images with deep learning (DL) approach. However, the DL model's complexity usually results…
Orofacial deficits are common in people with Parkinson's disease (PD) and their evolution might represent an important biomarker of disease progression. We are developing an automated system for assessment of orofacial function in PD that…
In this paper we evaluate the suitability of handwriting patterns as potential biomarkers to model Parkinson disease (PD). Although the study of PD is attracting the interest of many researchers around the world, databases to evaluate…
Parkinson's disease (PD) is a progressive neurodegenerative disorder that, in addition to directly impairing functional mobility, is frequently associated with vocal impairments such as hypophonia and dysarthria, which typically manifest in…
A large scale computational model of the basal ganglia (BG) network is proposed to describes movement disorder including deep brain stimulation (DBS). The model of this complex network considers four areas of the basal ganglia network: the…
Contactless and non-invasive estimation of mechanical properties of physical media from optical observations is of interest for manifold engineering and biomedical applications, where direct physical measurements are not possible.…
Computer-aided assessment of physical rehabilitation entails evaluation of patient performance in completing prescribed rehabilitation exercises, based on processing movement data captured with a sensory system. Despite the essential role…
Inertial sensors are crucial for recognizing pedestrian activity. Recent advances in deep learning have greatly improved inertial sensing performance and robustness. Different domains and platforms use deep-learning techniques to enhance…
Passive and non-obtrusive health monitoring using wearables can potentially bring new insights into the user's health status throughout the day and may support clinical diagnosis and treatment. However, identifying segments of free-living…
This work proposes the use of 3D convolutional variational autoencoders (CVAEs) to trace the changes and symptomatology produced by neurodegeneration in Parkinson's disease (PD). In this work, we present a novel approach to detect and…
This paper reviews related work and state-of-the-art publications for recognizing motor symptoms of Parkinson's Disease (PD). It presents research efforts that were undertaken to inform on how well traditional machine learning algorithms…
In this work, we explore various neural network architectures using Magnetic Resonance (MR) T1 images of the brain to identify Parkinson's Disease (PD), which is one of the most common neurodegenerative and movement disorders. We propose…
Parkinson's disease (PD) is a progressive neurodegenerative movement disorder where motor dysfunction gradually increases as the disease progress. In addition to administering dopaminergic PD-specific drugs, attending neurologists strongly…
Sepsis is a life threatening condition that requires timely detection in intensive care settings. Traditional machine learning approaches, including Naive Bayes, Support Vector Machine (SVM), Random Forest, and XGBoost, often rely on manual…
Accurate and interpretable gait analysis plays a crucial role in the early detection of Parkinsons disease (PD),yet most existing approaches remain limited by single-modality inputs, low robustness, and a lack of clinical transparency. This…
Parkinson's disease (PD) is a chronic neurodegenerative disease. Early diagnosis is essential to mitigate the progressive deterioration of patients' quality of life. The most characteristic motor symptoms are very mild in the early stages,…
Parkinson's disease (PD) severity diagnosis is crucial for early detecting potential patients and adopting tailored interventions. Diagnosing PD based on facial expression is grounded in PD patients' "masked face" symptom and gains growing…
Parkinson's Disease (PD) medication management presents unique challenges due to heterogeneous disease progression and treatment response. Neurologists must balance symptom control with optimal dopaminergic dosing based on functional…
Resting-state EEG (rs-EEG) has been demonstrated to aid in Parkinson's disease (PD) diagnosis. In particular, the power spectral density (PSD) of low-frequency bands ({\delta} and {\theta}) and high-frequency bands ({\alpha} and \b{eta})…
Parkinson's disease (PD) is a chronic, degenerative neurological disorder. PD cannot be prevented, slowed or cured as of today but highly effective symptomatic treatments are available. We consider relevant estimands and treatment effect…