Name
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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-19390-8_26 | PATTERN RECOGNITION AND IMAGE ANALYSIS (IBPRIA 2015) |
Field | DocType | Volume |
Activities of daily living,Breast cancer,Radial basis function kernel,Pattern recognition,Computer science,Lymphedema,Artificial intelligence,Supervised training,Linear discriminant analysis,Physical medicine and rehabilitation,Axillary lymph nodes | Conference | 9117 |
ISSN | Citations | PageRank |
0302-9743 | 1 | 0.41 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rita Moreira | 1 | 1 | 0.41 |
| André Magalhães | 2 | 18 | 2.25 |
| Hélder P. Oliveira | 3 | 63 | 13.99 |