The first ACM/IEEE TinyML Design Contest (TDC) held at the 41st International Conference on Computer-Aided Design (ICCAD) in 2022 is a challenging, multimonth, 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 (VA) over low-power microcontrollers utilized in implantable cardioverter-defibrillators (ICDs). The dataset contains more than 38000 5-s intracardiac electrograms (IEGMs) segments over eight different types of rhythm from 90 subjects. The dedicated hardware platform is NUCLEO-L432KC manufactured by STMicroelectronics. TDC’22, which is open to multiperson teams world-wide, attracted more than 150 teams from over 50 organizations. This article 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 article concludes with the direction of improvement for the future TinyML design for health monitoring applications.