Vibroarthrographic signals for the low-cost and computationally efficient classification of aging and healthy knees

Abstract Knee disorders are a common but easily overlooked disease and are often caused by natural or early aging. However, the aging process is difficult for the patient to self-diagnose until it deteriorates to osteoarthritis (OA). Vibroarthrographic (VAG) signals make the aging process visible and may contribute to reducing the incidence of disability caused by delayed medical diagnosis. Recently, although many studies have used VAG signals to diagnose knee joint disease, they have not yet been used in the diagnosis of knee aging. In this paper, a method is proposed to observe the aging process of the knee through VAG signal analysis. The accuracy of classifying naturally aging and healthy knees with this method is 0.9275, and the area under the receiver operating characteristic curve is 0.8928. The paper has filled the gap of using VAG signal to diagnose the natural knee aging process and laid the foundation for the non-invasive diagnosis of early knee aging.