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

• Published in: Current directions in biomedical engineering Vol. 9; no. 1; pp. 327 - 330
• Main Authors: Hoyer, Ingo, Roßman, Özgü, Utz, Alexander, Straczek, Lukas, Akboyraz, Onur, Hessel, Sebastian, Lüdecke, André, Seidl, Karsten
• Format: Journal Article
• Language: English
• Published: De Gruyter 01-09-2023
• Subjects: Analog Frontend; Biosignals; CMOS; ECG; Hardware Accelerators; Mixed-Signal-IC; RISC-V
• ISSN: 2364-5504; 2364-5504
• DOI: 10.1515/cdbme-2023-1082

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.