Design of Hardware Accelerators for Optimized and Quantized Neural Networks to Detect Atrial Fibrillation in Patch ECG Device with RISC-V

Design of Hardware Accelerators for Optimized and Quantized Neural Networks to Detect Atrial Fibrillation in Patch ECG Device with RISC-V

Atrial Fibrillation (AF) is one of the most common heart arrhythmias. It is known to cause up to 15% of all strokes. In current times, modern detection systems for arrhythmias, such as single-use patch electrocardiogram (ECG) devices, have to be energy efficient, small, and affordable. In this work,...

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Bibliographic Details
Main Authors: Ingo Hoyer, Alexander Utz, André Lüdecke, Holger Kappert, Maurice Rohr, Christoph Hoog Antink, Karsten Seidl
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Sensors
Subjects:
atrial fibrillation
artificial intelligence
quantization
neural networks
RISC-V
Online Access:https://www.mdpi.com/1424-8220/23/5/2703

Internet

https://www.mdpi.com/1424-8220/23/5/2703

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