Research on Estimation of Kyphosis Degree Based on Monocular Camera for Achieving Furniture’s Adaptive Height Adjustment

Senile kyphosis, characterized by the curvature of the back caused by osteoporosis and muscle degeneration, can impair mobility and even lead to more severe issues such as fractures. In order to address this problem, this study proposes an intelligent furniture system based on a monocular camera, aiming to estimate the degree of kyphosis and automatically adjust the furniture height using a low-cost RGB camera to assist individuals in improving their hunchback in daily life. When using a monocular camera to capture human body posture information, the traditional algorithm obtains keypoints about the human body, including body length and angle, but lacks relevant details on the back. Typically, these algorithms only provide information on the keypoints of the shoulders and hips and do not provide insight into the condition of the back or estimate the degree of kyphosis. In order to solve this limitation, in addition to using traditional algorithms, this study analyzes and extracts the back curve. When using the back curve and other keypoints of the human body, the degree of kyphosis can be estimated. Based on these estimations, the intelligent furniture system can automatically adjust the height of the furniture. Experimental results demonstrate that our system can detect the degree of kyphosis in individuals and adjust the furniture height according to individual needs. Users can obtain more comfortable posture support through this adaptive adjustment, reducing discomfort and health issues associated with kyphosis.