ContactlessFramework
Financiado
A Novel Framework for Contactless diagnosis and forecasting of Cardiovascular Di...
"In ancient times, doctors have followed unorganized practices to diagnose cardiac arrest conditions of healthcare patients. The followed medical procedures were not very organized and accurate even though cardiac patients were d...
"In ancient times, doctors have followed unorganized practices to diagnose cardiac arrest conditions of healthcare patients. The followed medical procedures were not very organized and accurate even though cardiac patients were diagnosed using devices, such as a stethoscope. However, the latest advancements in the technologies such as contactless remote patient monitoring, AIoMT (Artificial Intelligence of Medical Things), advanced big data and cloud-based analytics and alerts have created a paradigm shift in healthcare and provided 24 x 7 connectivity. The study proposed a VCardiac (Contactless Cardiac Classification and Risk Prediction) Framework to diagnose and identify early stages of heart diseases and forecast their cardiac conditions in advance using the human voice. In this study, a customized dataset termed ""Cardiac-2000"" with 2000 human voice samples will be designed to classify acoustic heartbeat events such as normal, murmur, extra systole, artifact, and other unlabeled heartbeat acoustic events. The average duration of the recorded heartbeat acoustic events would be 10 to 12 seconds. The primary reason for designing a customized dataset ""cardiac-2000"" is to balance the total number of samples into categories such as normal and abnormal heartbeat acoustic events. For performance evaluations of the proposed VCardiac Framework, the collected heartbeat acoustic samples will be classified using LSTM-CNN, RNN, LSTM, Bi-LSTM, CNN, K-means Clustering, and SVM methodologies. Furthermore, the proposed VCardiac Framework will also assist in classifying Age and Gender-wise risks using methodologies such as Kaplan-Meier and Cox-regression survival analysis. These methodologies will also assist in identifying the probability risk and the 10-year risk score prediction. In the end, the proposed VCardiac Framework will be tested for various Signal to Noise ratio conditions for achieving better accuracy, effectiveness, and throughput."
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Duración del proyecto: 23 meses
Fecha Inicio: 2022-07-01
Fecha Fin: 2024-06-30
Fecha Fin: 2024-06-30
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-06-30
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
HORIZON-MSCA-2021-PF-01-01:
MSCA Postdoctoral Fellowships 2021
Cerrada
hace 3 años
Líder del proyecto
LINNEUNIVERSITETET
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5