DOI: https://doi.org/10.36347/sjet.2025.v13i10.002

Pages: 800-806

Wearable medical devices used for cardiovascular diagnostics provided a myriad of benefits to patients and care providers alike. Their prominence in the medical field is due to the increased amount of comfort and accessibility available in comparison to frequent physician visits when facing cardiovascular issues. However, along with the advantages from the usage of these devices, there also exist certain challenges that require the attention of the medical world. Wearable devices for cardiovascular diagnostics encounter challenges in technical performance, clinical validation, and implementation. There exist difficulties with certain engineering designs of some devices, qualitative problems with data accuracy and processing, and limitations in diagnostic validation and evidence, even when devices show promise for long‐term monitoring and arrhythmia detection. Implementation barriers present additional complexities, particularly regarding healthcare system integration, regulatory compliance, and privacy considerations. Wearable devices for cardiovascular diagnostics face significant challenges across multiple domains that impact their clinical adoption and effectiveness. Technical performance limitations, including reduced lead counts and compromised signal quality, affect device reliability and data accuracy. Clinical validation remains a crucial challenge, with studies indicating limitations in diagnostic validation and evidence bases, despite these devices showing promise for long-term monitoring and arrhythmia detection. Implementation barriers present additional complexities, particularly regarding healthcare system integration, regulatory compliance, and privacy considerations. While these devices demonstrate potential for transforming cardiovascular diagnostics through continuous monitoring and early detection capabilities, significant technical and operational hurdles persist. Data processing, standardization, and integration into existing clinical workflows