Zobrazeno 1 - 10
of 189
pro vyhledávání: '"Kristof Van Laerhoven"'
Publikováno v:
Frontiers in Computer Science, Vol 6 (2024)
Research into the detection of human activities from wearable sensors is a highly active field, benefiting numerous applications, from ambulatory monitoring of healthcare patients via fitness coaching to streamlining manual work processes. We present
Externí odkaz:
https://doaj.org/article/94abbca1cfe545ab82d4540bd5a9c76d
Publikováno v:
Frontiers in Robotics and AI, Vol 11 (2024)
Background: Assistive Robotic Arms are designed to assist physically disabled people with daily activities. Existing joysticks and head controls are not applicable for severely disabled people such as people with Locked-in Syndrome. Therefore, eye tr
Externí odkaz:
https://doaj.org/article/56a060378796441686dff2a53b5e3c05
Autor:
Sebastian Böttcher, Solveig Vieluf, Elisa Bruno, Boney Joseph, Nino Epitashvili, Andrea Biondi, Nicolas Zabler, Martin Glasstetter, Matthias Dümpelmann, Kristof Van Laerhoven, Mona Nasseri, Benjamin H. Brinkman, Mark P. Richardson, Andreas Schulze-Bonhage, Tobias Loddenkemper
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-16 (2022)
Abstract Wearable recordings of neurophysiological signals captured from the wrist offer enormous potential for seizure monitoring. Yet, data quality remains one of the most challenging factors that impact data reliability. We suggest a combined data
Externí odkaz:
https://doaj.org/article/d4d2f367dc3f422ba120b1c039f07516
Autor:
Paul Lukowicz, Anton Nijholt, Kaleem Siddiqi, Marcello Pelillo, Kristof Van Laerhoven, Luca Viganò, Nicola Zannone
Publikováno v:
Frontiers in Computer Science, Vol 4 (2022)
Externí odkaz:
https://doaj.org/article/4189edd0b73f418daea0bc5c60b6ea85
Publikováno v:
Frontiers in Computer Science, Vol 4 (2022)
Many human activities consist of physical gestures that tend to be performed in certain sequences. Wearable inertial sensor data have as a consequence been employed to automatically detect human activities, lately predominantly with deep learning met
Externí odkaz:
https://doaj.org/article/94b51b274be247d0909bad321047d3d3
Autor:
Florian Wolling, Kristof Van Laerhoven
Publikováno v:
Frontiers in Computer Science, Vol 4 (2022)
With a smaller form factor and a larger set of applications, body-worn devices have evolved into a collection of simultaneously deployed hardware units, rather than into a single all-round wearable. The sensor data, logged by such devices across the
Externí odkaz:
https://doaj.org/article/c688cdaf3fc448ac904dc86478df0eb5
Publikováno v:
Sensors, Vol 23, Iss 13, p 5879 (2023)
We present a benchmark dataset for evaluating physical human activity recognition methods from wrist-worn sensors, for the specific setting of basketball training, drills, and games. Basketball activities lend themselves well for measurement by wrist
Externí odkaz:
https://doaj.org/article/30b36450f72e4fb4b67f7086c6a1b6c4
Autor:
Jochen Kempfle, Kristof Van Laerhoven
Publikováno v:
Frontiers in Computer Science, Vol 3 (2021)
As depth cameras have gotten smaller, more affordable, and more precise, they have also emerged as a promising sensor in ubiquitous systems, particularly for detecting objects, scenes, and persons. This article sets out to systematically evaluate how
Externí odkaz:
https://doaj.org/article/76d6100f042d49ea986636e49f137044
Autor:
Sebastian Böttcher, Elisa Bruno, Nikolay V Manyakov, Nino Epitashvili, Kasper Claes, Martin Glasstetter, Sarah Thorpe, Simon Lees, Matthias Dümpelmann, Kristof Van Laerhoven, Mark P Richardson, Andreas Schulze-Bonhage
Publikováno v:
JMIR mHealth and uHealth, Vol 9, Iss 11, p e27674 (2021)
BackgroundVideo electroencephalography recordings, routinely used in epilepsy monitoring units, are the gold standard for monitoring epileptic seizures. However, monitoring is also needed in the day-to-day lives of people with epilepsy, where video e
Externí odkaz:
https://doaj.org/article/3fc8433520384ee283207c63c4644df8
Autor:
Kristof Van Laerhoven
Publikováno v:
Frontiers in Computer Science, Vol 3 (2021)
Externí odkaz:
https://doaj.org/article/fb6a51b648f645438cb5b65bc97033ff