Gait-Based Parkinson’s Disease Detection Using Recurrent Neural Networks for Wearable Systems
Parkinson’s disease is one of the neurodegenerative conditions that has seen a significant increase in prevalence in recent decades. The lack of specific screening tests and notable disease biomarkers, combined with the strain on healthcare systems, leads to delayed detection of the disease, which w...
Saved in:
| Main Authors: | Carlos Rangel-Cascajosa, Francisco Luna-Perejón, Saturnino Vicente-Diaz, Manuel Domínguez-Morales |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Big Data and Cognitive Computing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-2289/9/7/183 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Wearable Surface Electromyography System to Predict Freeze of Gait in Parkinson’s Disease Patients
by: Anna Moore, et al.
Published: (2024-12-01) -
Objective assessment of gait and posture symptoms in Parkinson’s disease using wearable sensors and machine learning
by: Lingyan Ma, et al.
Published: (2025-08-01) -
Evaluation of Spatio-Temporal Gait Variability during Obstacle Crossing in Parkinson\'s Disease
by: Elaheh Azadian, et al.
Published: (2023-12-01) -
Quantitative analysis of gait parameters in Parkinson’s disease and the clinical significance
by: Wenchao Yin, et al.
Published: (2025-08-01) -
Diagnostic prediction model for levodopa-induced dyskinesia in Parkinson’s disease
by: Bruno Lopes SANTOS-LOBATO, et al.
Published: (2020-04-01)