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.
CITATION STYLE
Moreira, R., Magalhães, A., & Oliveira, H. P. (2015). A kinect-based system to assess lymphedema impairments in breast cancer patients. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9117, pp. 228–236). Springer Verlag. https://doi.org/10.1007/978-3-319-19390-8_26
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