Recently, a number of ontology-driven healthcare systems have been leveraged by the Internet-of-Things (IoT) 11 technologies, which offer opportunities to improve abnormal situation detection when integrating medical wearables and cloud 12 infrastructure. Usually, these systems rely on standardised IoT ontologies to represent sensor data observations. The ETSI 13 Smart Applications REFerence ontology (SAREF) is an extensible industry-oriented standard. In this paper, we explain the 14 need for interoperability of IoT healthcare applications and the role of standardised ontologies to achieve semantic 15 interoperability. In particular, we discuss the verbosity problem of SAREF when used for real-time electrocardiography (ECG), 16 emphasizing the requirement of representing time series. We compared the main ontologies in this context, according to 17 quality, message size (payload), IoT-orientation and standardisation. Here we describe the first attempt to extend SAREF for 18 specific e-Health use cases related to ECG data, the SAREF4health extension, which tackles the verbosity problem. Ontology-19 driven conceptual modelling was applied to develop SAREF4health, in which an ECG ontology grounded in the Unified 20 Foundational Ontology (UFO) plays the role of a reference model. The methodology was enhanced by following a 21 standardisation procedure and considering the RDF implementation of the HL7 Fast Healthcare Interoperability Resources 22 (FHIR) standard. The validation of SAREF4health includes the responses to competency questions, as well as the development 23 and tests of an IoT Early Warning System prototype that uses ECG data and collision identification to detect accidents with 24 truck drivers in a port area. This prototype integrates an existing ECG wearable with a cloud infrastructure, demonstrating the 25 performance impact of SAREF4health considering IoT constraints. Our results show that SAREF4health enables the semantic 26 interoperability of IoT solutions that need to deal with frequency-based time series. Design decisions regarding the trade-off 27 between ontology quality and aggregation representation are also discussed.