LSTM-CNN: An efficient diagnostic network for Parkinson's disease utilizing dynamic handwriting analysis

X Wang, J Huang, M Chatzakou, K Medijainen… - Computer Methods and …, 2024 - Elsevier
Background and objectives: Dynamic handwriting analysis, due to its noninvasive and
readily accessible nature, has emerged as a vital adjunctive method for the early diagnosis …

Handwriting dynamics assessment using deep neural network for early identification of Parkinson's disease

I Kamran, S Naz, I Razzak, M Imran - Future Generation Computer Systems, 2021 - Elsevier
The etiology of Parkinson's disease (PD) remains unclear. Symptoms usually appear after
approximately 70% of dopamine-producing cells have stopped working normally. PD cannot …

Multiple-fine-tuned convolutional neural networks for Parkinson's disease diagnosis from offline handwriting

M Gazda, M Hireš, P Drotár - IEEE Transactions on Systems …, 2021 - ieeexplore.ieee.org
Existing decision support system frameworks for diagnosing Parkinson's disease (PD)
through handwriting, speech, or gait characteristics share very similar pipelines. Although in …

A significantly enhanced neural network for handwriting assessment in Parkinson's disease detection

A Zhao, J Li - Multimedia Tools and Applications, 2023 - Springer
In recent years, machining learning aided diagnosis can provide non-invasive, low-cost
tools to support clinicians and assist the diagnosis and monitoring of neurodegenerative …

Dynamic and static handwriting assessment in Parkinson's disease: a synergistic approach with C-Bi-GRU and VGG19

S Ali, A Hashmi, A Hamza, U Hayat… - Journal of Computing …, 2023 - publikasi2.dinus.ac.id
Parkinson's disease (PD) is a neurodegenerative disorder causing a decline in dopamine
levels, impacting the peripheral nervous system and motor functions. Current detection …

Development of a Handwriting Drawings Assessment System for Early Parkinson's Disease Identification with Deep Learning Methods

J Zhang, Y Lee, TM Chung, H Park - International Conference on Future …, 2023 - Springer
Parkinson's disease (PD) is a prevalent neurodegenerative disorder, and early detection
plays a crucial role in timely treatment to prevent further harm to patients. In recent years …

Detection of Parkinson's disease from handwriting using deep learning: a comparative study

C Taleb, L Likforman-Sulem, C Mokbel… - Evolutionary …, 2023 - Springer
Degenerative disorders such as Parkinson's disease (PD) have an influence on daily
activities due to rigidity of muscles, tremor or cognitive impairment. Micrographia, speech …

Dynamically enhanced static handwriting representation for Parkinson's disease detection

M Diaz, MA Ferrer, D Impedovo, G Pirlo… - Pattern Recognition …, 2019 - Elsevier
Computer aided diagnosis systems can provide non-invasive, low-cost tools to support
clinicians. These systems have the potential to assist the diagnosis and monitoring of …

Multi-Model Fusion of CNNs for Identification of Parkinson's Disease Using Handwritten Samples

S Naz, I Kamran, S Gul, F Hadi, F Khalifa - IEEE Access, 2023 - ieeexplore.ieee.org
When approximately seventy percent of dopamine-producing nerve cells cease to function
normally, the symptoms of Parkinson's disease (PD) manifest, marking an irreversible …

Sequence-based dynamic handwriting analysis for Parkinson's disease detection with one-dimensional convolutions and BiGRUs

M Diaz, M Moetesum, I Siddiqi, G Vessio - Expert Systems with Applications, 2021 - Elsevier
Parkinson's disease (PD) is commonly characterized by several motor symptoms, such as
bradykinesia, akinesia, rigidity, and tremor. The analysis of patients' fine motor control …