Knowledge Representation in Noninvasive and Invasive Comprehensive Intelligent Cardiovascular Diseases Diagnosis in e-Home Healthcare

A cardiovascular diseases (CVDs) knowledge hierarchical representation (KHR) is pioneered to perform noninvasive and invasive comprehensive diagnosis in e-home healthcare, thus to achieve high-precise diagnostic accuracy. The clinical diagnosis actually maps the sampled cardiovascular parameters (CPs) into the relevant CVDs through using medical knowledge and depending on pathological characters of the disease. The CPs include noninvasive physical information such as electrocardiography (ECG), sphygmography (SPG), and heart sound (HS) data as well as invasive chemical information such as blood test parameters (BTPs) data. CVDs are divided into different categories with the allowance of producing new variants. Tackle such complex and diversified data, a frame-based KHR is proposed which represents the CPs, disease categories and their pathological relationships hierarchically. It is noteworthy that such a KHR is suitable to knowledge changes with the re-usable shell design structure. In addition, a versatile KHR inference mechanism (KHR-IM) is introduced to realize this KHR. With such an organic combination of noninvasive and invasive diagnosis, it establishes not only a solid mainstay for realizing more accurately the functionality of entire system, but also provides people with a reliable health monitor and management.