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Augmented Reality Visualisation for ECG Classification and Heart Disease Diagnosis

Year: 2024

Type: conference-paper

Abstract: Augmented Reality (AR) technology is swiftly progressing within the realm of medicine, notably in the domain of biomedical signal processing. It strengthens diagnostic proficiency while fostering interactive 3D virtual environments. The study presents an affordable AR visualisation for Electrocardiography ‘ECG’ arrhythmias classification. The proposal uses two simpli-fied architectures, including Recurrent Neural Networks (RNNs) and Long Short-Term Memory Networks (LSTMs). The models achieved reasonable accuracy performance on the PhysioNet MIT-BIH dataset. The advanced AR visualisation capabilities enable medical professionals to make precise diagnoses and formulate effective treatment plans.

Source: IEEE Forum on Research and Technologies for Society and Industry Innovation (RTSI)

DOI: 10.1109/rtsi61910.2024.10761433

Authors: Kahina Amara, Mohamed Amine Guerroudji, Nadia Zenati, Oussama Kerdjidj, Shadi Atalla, Wathiq Mansoor, Naeem Ramzan

Institutions: Centre de Développement des Technologies Avancées, University of Dubai, University of the West of Scotland

Language: English

Topic: ECG Monitoring and Analysis

Subfield: Cardiology and Cardiovascular Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W4404740908

FWCI: 5.831

Cites: 24

Cited by: 4

Related to: 10