Cardiovascular diseases remain the leading cause of death worldwide, and most of this burden falls on low- and middle-income countries where access to electrocardiography (ECG) is limited. In the last decade, integrated biopotential front ends, open-source microcontroller platforms and ubiquitous smartphones have made it possible to build ECG monitors at a fraction of the cost of conventional equipment, while consumer wearables have shown that single-lead ECG can be recorded at population scale. This narrative review examines how low-cost, open-source and wearable ECG systems are designed and evaluated for remote cardiac monitoring. We describe the end-to-end architecture (electrodes, analog front ends, microcontrollers, wireless links, gateways and cloud back ends), the signal processing chain (denoising, signal quality assessment, QRS detection, delineation and heart rate variability), and the emerging role of artificial intelligence running on the cloud or directly on the device. We then discuss validation methodology, including reference databases, standardized metrics and agreement analysis, and summarize the regulatory, safety and data protection requirements that separate a research prototype from a medical device. An Arduino-based remote ECG system previously developed by the author is used as a reference case to illustrate common design choices and pitfalls. We conclude that technical feasibility is no longer the bottleneck; rigorous validation in target populations, signal quality management and regulatory-grade engineering now determine clinical impact.