ArticleBiomedicines2022
Modified SqueezeNet Architecture for Parkinson's Disease Detection Based on Keypress Data.
Article in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Modelling and Correcting the Effects of Tremor on Touchscreen Interaction.Sensors (Basel, Switzerland) · 2026Article
- Non-Invasive Voice-Based Early Detection of Parkinson's Disease via Spectral Feature Analysis and Machine Learning Techniques.Bioengineering (Basel, Switzerland) · 2026Article
- Detection of early-stage Parkinson's disease using wearable sensors at multiple body locations and convolutional neural networks.Scientific reports · 2026Article
- Multi-attention Mechanism for Enhanced Pseudo-3D Prostate Zonal Segmentation.Journal of imaging informatics in medicine · 2025Article
- A Deep Learning Framework for Early Parkinson's Disease Detection: Leveraging Spiral and Wave Handwriting Tasks with EfficientNetV2-S.Diagnostics (Basel, Switzerland) · 2025Article
- Quantifying device type and handedness biases in a remote Parkinson's disease AI-powered assessment.NPJ digital medicine · 2025Article
- Retinal image-based disease classification using hybrid deep architecture with improved image features.International ophthalmology · 2025Article
- Convolutional neural network based detection of early stage Parkinson's disease using the six minute walk test.Scientific reports · 2024Article
- Segmenting and classifying lung diseases with M-Segnet and Hybrid Squeezenet-CNN architecture on CT images.PloS one · 2024Article
- Detecting Parkinson's disease from shoe-mounted accelerometer sensors using convolutional neural networks optimized with modified metaheuristics.PeerJ. Computer science · 2024Article
- Intelligent Breast Mass Classification Approach Using Archimedes Optimization Algorithm with Deep Learning on Digital Mammograms.Biomimetics (Basel, Switzerland) · 2023Article
- Keystroke Biometrics as a Tool for the Early Diagnosis and Clinical Assessment of Parkinson's Disease.Diagnostics (Basel, Switzerland) · 2023Article
- Table Tennis Track Detection Based on Temporal Feature Multiplexing Network.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parkinson's disease (PD) is the most common form of Parkinsonism, which is a group of neurological disorders with PD-like motor impairments. The disease affects over 6 million people worldwide and is characterized by motor and non-motor symptoms. The affected person has trouble in controlling movements, which may affect simple daily-life tasks, such as typing on a computer. We propose the application of a modified SqueezeNet convolutional neural network (CNN) for detecting PD based on the subject's key-typing patterns. First, the data are pre-processed using data standardization and the Synthetic Minority Oversampling Technique (SMOTE), and then a Continuous Wavelet Transformation is applied to generate spectrograms used for training and testing a modified SqueezeNet model. The modified SqueezeNet model achieved an accuracy of 90%, representing a noticeable improvement in comparison to other approaches.
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