Zobrazeno 1 - 10
of 281
pro vyhledávání: '"Jesus Favela"'
Publikováno v:
Robotics, Vol 12, Iss 1, p 29 (2023)
Socially assistive robots have been proposed to help people with dementia to conduct activities of daily living, facilitate therapeutic interventions or address problematic symptoms associated with the disease. Psychological symptoms of dementia, suc
Externí odkaz:
https://doaj.org/article/d0ba562caeb446cf99cce0713454a31b
Publikováno v:
CLEI Electronic Journal, Vol 24, Iss 3 (2021)
This special issue of the CLEI Electronic Journal (CLEIej) is dedicated to Digital Healthcare. It contains two accepted papers presenting research related to the COVID-19 pandemic in Latin America.
Externí odkaz:
https://doaj.org/article/b86733e4980e44bea763e4c3f2c6ea0e
Autor:
Netzahualcoyotl Hernandez, Matias Garcia-Constantino, Jessica Beltran, Pascal Hecker, Jesus Favela, Joseph Rafferty, Ian Cleland, Hussein Lopez, Bert Arnrich, Ian McChesney
Publikováno v:
EAI Endorsed Transactions on Pervasive Health and Technology, Vol 5, Iss 19 (2019)
INTRODUCTION: Dementia is a syndrome characterised by a decline in memory, language, and problem-solving thataffects the ability of patients to perform everyday activities. Patients with dementia tend to experience episodes of anxietyand remain for e
Externí odkaz:
https://doaj.org/article/89f293ced10e479aa1d0b3a1f468925d
Publikováno v:
EAI Endorsed Transactions on Pervasive Health and Technology, Vol 5, Iss 17 (2019)
INTRODUCTION: Neural networks are a popular type of algorithm for human activity monitoring which canbuild intelligent systems from labelled data in an automated fashion. Obtaining accurately labelled data is costly; it requires time and effort, whic
Externí odkaz:
https://doaj.org/article/2e329110d20a4c059ac5be10db724da6
Publikováno v:
Sensors, Vol 20, Iss 17, p 4756 (2020)
Activity recognition is one of the most active areas of research in ubiquitous computing. In particular, gait activity recognition is useful to identify various risk factors in people’s health that are directly related to their physical activity. O
Externí odkaz:
https://doaj.org/article/5cfbd246a7ce493fbb2f3420063ecc4e
Autor:
Adrian Acosta-Mitjans, Dagoberto Cruz-Sandoval, Ramon Hervas, Esperanza Johnson, Chris Nugent, Jesus Favela
Publikováno v:
Proceedings, Vol 31, Iss 1, p 71 (2019)
Embodied agents, such as avatars and social robots, are increasingly incorporating a capacity to enact affective states and recognize the mood of their interlocutor. This influences how users perceive these technologies and how they interact with the
Externí odkaz:
https://doaj.org/article/9d99875fe3784ca1ac4ebf9a50cb411b
Publikováno v:
Proceedings, Vol 31, Iss 1, p 64 (2019)
Commercial activity trackers are increasingly being used to support healthcare research. While their accuracy has been questioned, they do provide more precise information on some parameters relevant to wellbeing than self-report, such as steps walke
Externí odkaz:
https://doaj.org/article/728d8c34662a478db79e981e4d596620
Publikováno v:
Proceedings, Vol 31, Iss 1, p 60 (2019)
Activity recognition is an important task in many fields, such as ambient intelligence, pervasive healthcare, and surveillance. In particular, the recognition of human gait can be useful to identify the characteristics of the places or physical space
Externí odkaz:
https://doaj.org/article/fb07972ba64c410eb575de63a2587690
Autor:
Dagoberto Cruz-Sandoval, Jessica Beltran-Marquez, Matias Garcia-Constantino, Luis A. Gonzalez-Jasso, Jesus Favela, Irvin Hussein Lopez-Nava, Ian Cleland, Andrew Ennis, Netzahualcoyotl Hernandez-Cruz, Joseph Rafferty, Jonathan Synnott, Chris Nugent
Publikováno v:
Sensors, Vol 19, Iss 14, p 3035 (2019)
Activity recognition, a key component in pervasive healthcare monitoring, relies on classification algorithms that require labeled data of individuals performing the activity of interest to train accurate models. Labeling data can be performed in a l
Externí odkaz:
https://doaj.org/article/05f9bede14e84735b2a69b9eb9783fc3
Autor:
Luis A. González-Jasso, Jesus Favela
Publikováno v:
Proceedings, Vol 2, Iss 19, p 1210 (2018)
Supervised activity recognition algorithms require labeled data to train classification models. Labeling an activity can be performed trough observation, in controlled conditions, or thru self-labeling. The two first approaches are intrusive, which m
Externí odkaz:
https://doaj.org/article/9198610e66aa47aaadfa8c9bea5f2932