Cardiovascular diseases (CVDs) are the primary cause of mortality worldwide. The healthcare sector in India currently shows promise for substantial changes, specifically in the utilization and importance of the Internet of Medical Things (IoMT). Edge computing is necessary to make the IoMT more scalable, portable, reliable, and responsive. Security and privacy concerns impede the development and deployment of IoMT devices. The technology of blockchain can resolve security and privacy concerns. In this work, we implement a lightweight binary neural network (BNN) in a Cortex-M4 microcontroller (MCU) to enable the detection of four different types of heart illnesses present in a single-lead electrocardiogram (ECG) signal, in addition to proposing a blockchain-enabled HeartCare framework. The end-user can identify ailments and subsequently disseminate ECG results to medical professionals via a privacy-preserving blockchain-enabled framework. To acquire the ECG signal, a reusable fabric electrode was proposed and successfully fabricated. Finally, the BNN model is being trained utilising ECG databases of patients from the Indian continent, in addition to other state-of-the-art databases. The post-deployment validation of the proposed framework was conducted rigorously in alignment with the ACC/AHA Guidelines, resulting in an overall accuracy of 95.93% and a sensitivity of 95.90% for our BNN model.