Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/66362
Título: | Developing a framework for promoting physical activity in a Boccia game scenario |
Autor(es): | Silva, Vinicius Corrêa Alves Ramos, João Ricardo Martins Leite, Pedro Soares, Filomena Novais, Paulo Arezes, P. Sousa, Filipe Figueira, Carina Santos, Antonio |
Palavras-chave: | Activity monitoring Boccia Microsoft Kinect wearable and non-wearable devices Pandlet |
Data: | 2-Nov-2019 |
Editora: | Taylor & Francis Ltd |
Revista: | Computer Methods in Biomechanics and Biomedical Engineering-Imaging and Visualization |
Citação: | Vinícius Silva, João Ramos, Pedro Leite, Filomena Soares, PauloNovais, Pedro Arezes, Filipe Sousa, Carina Figueira & António Santos (2019) Developing aframework for promoting physical activity in a Boccia game scenario, Computer Methods inBiomechanics and Biomedical Engineering: Imaging & Visualization, 7:5-6, 632-642, DOI:10.1080/21681163.2018.1538816 |
Resumo(s): | The traditional keyboard has been replaced by tactile screens or other types of implicit interfaces. An example of such interface is the Microsoft Kinect system, which makes use of a depth sensing system to enable the user-machine interaction. Allied to the physical activity, this hardware may be used to track and monitor the user when he/she is exercising, but also to diminish a sedentary lifestyle. In this paper, it is proposed a system based on such non-wearable and wearable devices to monitor the elderly while playing Boccia. This system allows to recognise the game movements as well as it registers other physiological variables of the player. The results show the comparison of different methods and approaches to recognise two main gestures used during a Boccia game. Firstly, the non-wearable and wearable approaches were compared by training an SVM model using data from Kinect and the Pandlet. From the results obtained, the accuracy for the model with Kinect was higher. Then, in order to improve the gesture recognition, several models were trained with the accelerometer data from the Pandlet. The results showed that the RBF SVM had better results achieving a cross-validation accuracy of 95%. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/66362 |
DOI: | 10.1080/21681163.2018.1538816 |
ISSN: | 2168-1163 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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RI86_Developing a framework for promoting physical activity in a Boccia game scenario.pdf Acesso restrito! | 1,94 MB | Adobe PDF | Ver/Abrir |