Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Xiaomeng, Su"'
Publikováno v:
Journal of NeuroEngineering and Rehabilitation, Vol 21, Iss 1, Pp 1-29 (2024)
Abstract Background Technological advancements in functional neuroimaging and motion capture have led to the development of novel methods that facilitate the diagnosis and rehabilitation of motor deficits. These advancements allow for the synchronous
Externí odkaz:
https://doaj.org/article/a2c45a48a8764a938ea043c167523982
Autor:
Olav F. P. Larsen, William G. Tresselt, Emanuel A. Lorenz, Tomas Holt, Grethe Sandstrak, Tor I. Hansen, Xiaomeng Su, Alexander Holt
Publikováno v:
Frontiers in Human Neuroscience, Vol 18 (2024)
This study explores the synchronization of multimodal physiological data streams, in particular, the integration of electroencephalography (EEG) with a virtual reality (VR) headset featuring eye-tracking capabilities. A potential use case for the syn
Externí odkaz:
https://doaj.org/article/c275050a3bfb4833b256b08bb2225562
Autor:
Piyush Swami, Klaus Gramann, Elise Klæbo Vonstad, Beatrix Vereijken, Alexander Holt, Tomas Holt, Grethe Sandstrak, Jan Harald Nilsen, Xiaomeng Su
Publikováno v:
Frontiers in Human Neuroscience, Vol 17 (2023)
To investigate event-related activity in human brain dynamics as measured with EEG, triggers must be incorporated to indicate the onset of events in the experimental protocol. Such triggers allow for the extraction of ERP, i.e., systematic electrophy
Externí odkaz:
https://doaj.org/article/ec06abd05dbf427dbae90f787f4aa541
Publikováno v:
Journal of NeuroEngineering and Rehabilitation, Vol 19, Iss 1, Pp 1-12 (2022)
Abstract Background Balance training exercise games (exergames) are a promising tool for reducing fall risk in elderly. Exergames can be used for in-home guided exercise, which greatly increases availability and facilitates independence. Providing bi
Externí odkaz:
https://doaj.org/article/79267ed7f7e643f8991b570c5cfa93c1
Autor:
Merete Endresen Moan, Elise Klæbo Vonstad, Xiaomeng Su, Beatrix Vereijken, Marit Solbjør, Nina Skjæret-Maroni
Publikováno v:
Frontiers in Aging Neuroscience, Vol 13 (2021)
Use of VR-games is considered a promising treatment approach in stroke rehabilitation. However, there is little knowledge on the use and expectations of patients and health professionals regarding the use of treadmill walking in a fully immersive vir
Externí odkaz:
https://doaj.org/article/f85e5376d9e0473d8c6174099ea5386d
Autor:
Elsa Cardoso, Xiaomeng Su
Publikováno v:
Applied Sciences, Vol 12, Iss 9, p 4625 (2022)
Business Intelligence and Analytics (BIA) systems play an essential role in organizations, providing actionable insights that enable business users to make more informed, data-driven decisions. However, many Higher Education (HE) institutions do not
Externí odkaz:
https://doaj.org/article/ee009888ddc9423eb0c4ff64909f234d
Autor:
Larsen, Olav F. P., Tresselt, William G., Lorenz, Emanuel A., Holt, Tomas, Sandstrak, Grethe, Hansen, Tor I., Xiaomeng Su, Holt, Alexander
Publikováno v:
Frontiers in Human Neuroscience; 2024, p1-10, 10p
Autor:
Xiaomeng Su, Elsa Cardoso
Publikováno v:
International Journal of Business Intelligence Research. 12:1-26
Maturity models of Business Intelligence and Analytics (BIA) have been previously used to assess BIA development progress in organizations in many sectors, such as healthcare and business. However, there is a lack of studies reporting up-to-date know
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1effa5d3d90d4016414518b3a96c00ac
https://doi.org/10.4018/ijbir.297061
https://doi.org/10.4018/ijbir.297061
Publikováno v:
Sensors, Vol 20, Iss 23, p 6940 (2020)
Using standard digital cameras in combination with deep learning (DL) for pose estimation is promising for the in-home and independent use of exercise games (exergames). We need to investigate to what extent such DL-based systems can provide satisfyi
Externí odkaz:
https://doaj.org/article/e6f3ea23cc2342af9a71c10be3d5e17b
The content of dissolved gas in transformer oil is an important characteristic to reflect the operating condition of transformers. To overcome the problems that the traditional transformer oil chromatography gas prediction model cannot effectively us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::404e0c2daf007638cb8b8a63458af8cb
https://doi.org/10.22541/au.166976016.64632334/v1
https://doi.org/10.22541/au.166976016.64632334/v1
