  The first ACM/IEEE TinyML Design Contest (TDC) held at the 41st International
Conference on Computer-Aided Design (ICCAD) in 2022 is a challenging,
multi-month, research and development competition. TDC'22 focuses on real-world
medical problems that require the innovation and implementation of artificial
intelligence/machine learning (AI/ML) algorithms on implantable devices. The
challenge problem of TDC'22 is to develop a novel AI/ML-based real-time
detection algorithm for life-threatening ventricular arrhythmia over low-power
microcontrollers utilized in Implantable Cardioverter-Defibrillators (ICDs).
The dataset contains more than 38,000 5-second intracardiac electrograms
(IEGMs) segments over 8 different types of rhythm from 90 subjects. The
dedicated hardware platform is NUCLEO-L432KC manufactured by
STMicroelectronics. TDC'22, which is open to multi-person teams world-wide,
attracted more than 150 teams from over 50 organizations. This paper first
presents the medical problem, dataset, and evaluation procedure in detail. It
further demonstrates and discusses the designs developed by the leading teams
as well as representative results. This paper concludes with the direction of
improvement for the future TinyML design for health monitoring applications.
