Original paper
AI-Based Stroke Disease Prediction System Using Real-Time Electromyography Signals
Abstract
Stroke is a leading cause of disabilities in adults and the elderly which can result in numerous social or economic difficulties. If left untreated, stroke can lead to death. In most cases, patients with stroke have been observed to have abnormal bio-signals (i.e., ECG). Therefore, if individuals are monitored and have their bio-signals measured and accurately assessed in real-time, they can receive appropriate treatment quickly. However, most...
Paper Details
Title
AI-Based Stroke Disease Prediction System Using Real-Time Electromyography Signals
Published Date
Sep 28, 2020
Journal
Volume
10
Issue
19
Pages
6791 - 6791
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History