Go to:
Logótipo
Você está em: Start > Publications > View > A Kinect-Based System for Upper-Body Function Assessment in Breast Cancer Patients
Map of Premises
Principal
Publication

A Kinect-Based System for Upper-Body Function Assessment in Breast Cancer Patients

Title
A Kinect-Based System for Upper-Body Function Assessment in Breast Cancer Patients
Type
Article in International Scientific Journal
Year
2015
Authors
Moreira, R
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Magalhaes, A
(Author)
Other
The person does not belong to the institution. The person does not belong to the institution. The person does not belong to the institution. Without AUTHENTICUS Without ORCID
Journal
Title: Journal of ImagingImported from Authenticus Search for Journal Publications
Vol. 1 No. 1
Pages: 134-155
Publisher: MDPI
Other information
Authenticus ID: P-00K-A45
Abstract (EN): Common breast cancer treatment techniques, such as radiation therapy or the surgical removal of the axillary lymphatic nodes, result in several impairments in women's upper-body function. These impairments include restricted shoulder mobility and arm swelling. As a consequence, several daily life activities are affected, which contribute to a decreased quality of life (QOL). Therefore, it is of extreme importance to assess the functional restrictions caused by cancer treatment, in order to evaluate the quality of procedures and to avoid further complications. Although the research in this field is still very limited and the methods currently available suffer from a lack of objectivity, this highlights the relevance of the pioneer work presented in this paper, which aims to develop an effective method for the evaluation of the upper-body function, suitable for breast cancer patients. For this purpose, the use of both depth and skeleton data, provided by the Microsoft Kinect, is investigated to extract features of the upper-limbs motion. Supervised classification algorithms are used to construct a predictive model of classification, and very promising results are obtained, with high classification accuracy.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 22
Documents
We could not find any documents associated to the publication.
Related Publications

Of the same authors

A Kinect-Based System to Assess Lymphedema Impairments in Breast Cancer Patients (2015)
Article in International Conference Proceedings Book
Moreira, R; Magalhaes, A; Oliveira, HP

Of the same journal

Skin Cancer Image Classification Using Artificial Intelligence Strategies: A Systematic Review (2024)
Another Publication in an International Scientific Journal
Vardasca, R; Joaquim Mendes; Magalhaes, C
Visible and Thermal Image-Based Trunk Detection with Deep Learning for Forestry Mobile Robotics (2021)
Article in International Scientific Journal
da Silva, DQ; Filipe Neves Santos; Armando Jorge Sousa; Filipe, V
Synthesizing Human Activity for Data Generation (2023)
Article in International Scientific Journal
Romero, A; Pedro Carvalho; Luís Corte-Real; Pereira, A
Preventing Wine Counterfeiting by Individual Cork Stopper Recognition Using Image Processing Technologies (2018)
Article in International Scientific Journal
Valter Costa; Armando Sousa; Ana Reis
Photo2Video: Semantic-Aware Deep Learning-Based Video Generation from Still Content (2022)
Article in International Scientific Journal
Viana, P; Maria Teresa Andrade; Pedro Carvalho; Vilaca, L; Teixeira, IN; Costa, T; Jonker, P

See all (12)

Recommend this page Top
Copyright 1996-2025 © Faculdade de Medicina Dentária da Universidade do Porto  I Terms and Conditions  I Acessibility  I Index A-Z
Page created on: 2025-08-13 at 22:42:31 | Privacy Policy | Personal Data Protection Policy | Whistleblowing | Electronic Yellow Book