Details

Autor(en) / Beteiligte

• Hoyer, Ingo
• Roßman, Özgü
• Utz, Alexander
• Straczek, Lukas
• Akboyraz, Onur
• Hessel, Sebastian
• Lüdecke, André
• Seidl, Karsten

Titel

The ARTEMIS project: Mixed-Signal IC for Edge-AI-based Classification of ECG Signals

Ist Teil von

• Current directions in biomedical engineering, 2023-09, Vol.9 (1), p.327-330

Ort / Verlag

De Gruyter

Erscheinungsjahr

2023

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Atrial fibrillation (AF) is a common heart arrhythmia and is closely associated with causing strokes. Diagnosis is usually performed with Holter monitors over longer periods of time, causing discomfort to the patient. The proposed mixed-signal integrated circuit (IC) is designed for small patch electrocardiogram (ECG) devices and combines, an analog front-end (AFE) with tailored recording channel characteristics and 12-bit successive-approximation-register analog digital converter (SAR ADC) as well as an RISC-V based microcontroller (μC) for edge artificial intelligence (AI)-based AF-detection. The digital signal processing is supported with hardware accelerators. Including 160 kB of SRAM, the system on chip (SoC) requires 25.56 mm² in silicon area in a 180 nm technology. The recording channel shows promising simulation results with an input impedance of 230 MΩ, an input referred noise of below 1.6 μVrms and a CMMR of 95 dB. The digital part enables the integration of AI-based classification on the IC. Due to the flexibility of the software-based classification approach, this IC can also be used to detect other arrhythmias.