A Kinect-Based System to Assess Lymphedema Impairments in Breast Cancer Patients

Abstract

Common breast cancer treatments, as the removal of axillary lymph nodes, cause severe impairments in women's upper-body function. As a result, several daily activities are affected which contributes to a decreased QOL. Thus, the assessment of functional restrictions after treatment is essential to avoid further complications. This paper presents a pioneer work, which aims to develop an upper-body function evaluation method, traduced by the identification of lymphedema. Using the Kinect, features of the upper-limbs motion are extracted and supervised learning algorithms are used to construct a predictive classification model. Very promising results are obtained, with high classification accuracy.