Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Duarte Folgado"'
Autor:
Pedro Santos Rocha, Nuno Bento, Hanna Svärd, Diana Monteiro Lopes, Sandra Hespanhol, Duarte Folgado, André Valério Carreiro, Mamede de Carvalho, Bruno Miranda
Publikováno v:
Brain Sciences, Vol 14, Iss 11, p 1082 (2024)
Background: Speech production is a possible way to monitor bulbar and respiratory functions in patients with amyotrophic lateral sclerosis (ALS). Moreover, the emergence of smartphone-based data collection offers a promising approach to reduce freque
Externí odkaz:
https://doaj.org/article/fb4828adaac64237b50adaf265af5d6d
Autor:
Maria Lua Nunes, Duarte Folgado, Carlos Fujao, Luis Silva, Joao Rodrigues, Pedro Matias, Marilia Barandas, Andre V. Carreiro, Sara Madeira, Hugo Gamboa
Publikováno v:
IEEE Access, Vol 10, Pp 83221-83235 (2022)
Musculoskeletal disorders (MSD) are a highly prevalent work-related health problem. Biomechanical exposure to hazardous postures during work is a risk factor for the development of MSD. This study focused on developing an inertial sensor-based approa
Externí odkaz:
https://doaj.org/article/0b58100b5ab743dcbbc1f1b04910205d
Autor:
Duarte Folgado, Marília Barandas, Margarida Antunes, Maria Lua Nunes, Hui Liu, Yale Hartmann, Tanja Schultz, Hugo Gamboa
Publikováno v:
SoftwareX, Vol 18, Iss , Pp 101049- (2022)
Subsequence search and distance measures are crucial tools in time series data mining. This paper presents our Python package entitled TSSEARCH, which provides a comprehensive set of methods for subsequence search and similarity measurement in time s
Externí odkaz:
https://doaj.org/article/492e6ffd3a4d489f86f7b2d6669ee270
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 2, Iss 4, Pp 505-532 (2020)
Uncertainty is ubiquitous and happens in every single prediction of Machine Learning models. The ability to estimate and quantify the uncertainty of individual predictions is arguably relevant, all the more in safety-critical applications. Real-world
Externí odkaz:
https://doaj.org/article/6c2c05ad99db48e9be9d919967d0f1b0
Publikováno v:
Biosensors, Vol 12, Iss 12, p 1182 (2022)
Biosignal-based technology has been increasingly available in our daily life, being a critical information source. Wearable biosensors have been widely applied in, among others, biometrics, sports, health care, rehabilitation assistance, and edutainm
Externí odkaz:
https://doaj.org/article/bfe7ed4d21574f089093e0f36c1e3a68
Autor:
Luís Silva, Mariana Dias, Duarte Folgado, Maria Nunes, Praneeth Namburi, Brian Anthony, Diogo Carvalho, Miguel Carvalho, Elazer Edelman, Hugo Gamboa
Publikováno v:
Sensors, Vol 22, Iss 11, p 4247 (2022)
Cumulative fatigue during repetitive work is associated with occupational risk and productivity reduction. Usually, subjective measures or muscle activity are used for a cumulative evaluation; however, Industry 4.0 wearables allow overcoming the chal
Externí odkaz:
https://doaj.org/article/8c3d53d75fd14f20b681339f5a960c9f
Autor:
Marília Barandas, Duarte Folgado, Letícia Fernandes, Sara Santos, Mariana Abreu, Patrícia Bota, Hui Liu, Tanja Schultz, Hugo Gamboa
Publikováno v:
SoftwareX, Vol 11, Iss , Pp - (2020)
Time series feature extraction is one of the preliminary steps of conventional machine learning pipelines. Quite often, this process ends being a time consuming and complex task as data scientists must consider a combination between a multitude of do
Externí odkaz:
https://doaj.org/article/8426de6615a84dc88bc61b621831f955
Autor:
Carlos Resende, Duarte Folgado, João Oliveira, Bernardo Franco, Waldir Moreira, Antonio Oliveira-Jr, Armando Cavaleiro, Ricardo Carvalho
Publikováno v:
Sensors, Vol 21, Iss 14, p 4676 (2021)
Industry 4.0, allied with the growth and democratization of Artificial Intelligence (AI) and the advent of IoT, is paving the way for the complete digitization and automation of industrial processes. Maintenance is one of these processes, where the i
Externí odkaz:
https://doaj.org/article/9fe3012259024717a0ef41d8b9bbc3ec
Publikováno v:
Sensors, Vol 19, Iss 3, p 501 (2019)
Modern smartphones and wearables often contain multiple embedded sensors which generate significant amounts of data. This information can be used for body monitoring-based areas such as healthcare, indoor location, user-adaptive recommendations and t
Externí odkaz:
https://doaj.org/article/1fdf68fa7abe446481b37b196af64f65
Publikováno v:
Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d3c08c7c7d665fc6fc5ad11a7c17ba24
https://doi.org/10.5220/0011694700003414
https://doi.org/10.5220/0011694700003414