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.
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Acknowledgments
This work is financed by the FCT Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project UID/EEA/50014/2013
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Moreira, R., Magalhães, A., Oliveira, H.P. (2015). A Kinect-Based System to Assess Lymphedema Impairments in Breast Cancer Patients. In: Paredes, R., Cardoso, J., Pardo, X. (eds) Pattern Recognition and Image Analysis. IbPRIA 2015. Lecture Notes in Computer Science(), vol 9117. Springer, Cham. https://doi.org/10.1007/978-3-319-19390-8_26
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DOI: https://doi.org/10.1007/978-3-319-19390-8_26
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