Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Alessandro Masullo"'
Autor:
Catherine Morgan, Emma L. Tonkin, Alessandro Masullo, Ferdian Jovan, Arindam Sikdar, Pushpajit Khaire, Majid Mirmehdi, Ryan McConville, Gregory J. L. Tourte, Alan Whone, Ian Craddock
Publikováno v:
Scientific Data, Vol 10, Iss 1, Pp 1-18 (2023)
Abstract Parkinson’s disease (PD) is a neurodegenerative disorder characterised by motor symptoms such as gait dysfunction and postural instability. Technological tools to continuously monitor outcomes could capture the hour-by-hour symptom fluctua
Externí odkaz:
https://doaj.org/article/a3ac80e9fe4146b6846fcf793a04bd2c
Autor:
Catherine Morgan, Alessandro Masullo, Majid Mirmehdi, Hanna Kristiina Isotalus, Ferdian Jovan, Ryan McConville, Emma L. Tonkin, Alan Whone, Ian Craddock
Publikováno v:
Digital Biomarkers, Vol 7, Iss 1, Pp 92-103 (2023)
Introduction: Technology holds the potential to track disease progression and response to neuroprotective therapies in Parkinson’s disease (PD). The sit-to-stand (STS) transition is a frequently occurring event which is important to people with PD.
Externí odkaz:
https://doaj.org/article/d5c5bf7978494f0b8f0d6fc6e4608757
Autor:
Sabrina Grant, Emma Tonkin, Ian Craddock, Ashley Blom, Michael Holmes, Andrew Judge, Alessandro Masullo, Miquel Perello Nieto, Hao Song, Michael Whitehouse, Peter Flach, Rachael Gooberman-Hill
Publikováno v:
JMIR Perioperative Medicine, Vol 6, p e36172 (2023)
BackgroundThe current assessment of recovery after total hip or knee replacement is largely based on the measurement of health outcomes through self-report and clinical observations at follow-up appointments in clinical settings. Home activity-based
Externí odkaz:
https://doaj.org/article/cdaa3d57685f4be9b7270a28bf9308c8
Publikováno v:
JMIR Formative Research, Vol 6, Iss 9, p e33606 (2022)
BackgroundCalorimetry is both expensive and obtrusive but provides the only way to accurately measure energy expenditure in daily living activities of any specific person, as different people can use different amounts of energy despite performing the
Externí odkaz:
https://doaj.org/article/ff7d9cf48b284fd688251834ea1f9672
Autor:
Farnoosh Heidarivincheh, Ryan McConville, Catherine Morgan, Roisin McNaney, Alessandro Masullo, Majid Mirmehdi, Alan L. Whone, Ian Craddock
Publikováno v:
Sensors, Vol 21, Iss 12, p 4133 (2021)
Parkinson’s disease (PD) is a chronic neurodegenerative condition that affects a patient’s everyday life. Authors have proposed that a machine learning and sensor-based approach that continuously monitors patients in naturalistic settings can pro
Externí odkaz:
https://doaj.org/article/13197e3250b842ff86ef7341875fcfd4
Publikováno v:
Sensors, Vol 20, Iss 9, p 2576 (2020)
The use of visual sensors for monitoring people in their living environments is critical in processing more accurate health measurements, but their use is undermined by the issue of privacy. Silhouettes, generated from RGB video, can help towards all
Externí odkaz:
https://doaj.org/article/75515befb43440cab5af48d564b0b9d3
Publikováno v:
VISIGRAPP (5: VISAPP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0623b8330b45de1c32cd349e0f445c24
https://doi.org/10.5220/0010202903280337
https://doi.org/10.5220/0010202903280337
Publikováno v:
Computer Vision – ACCV 2020 ISBN: 9783030695378
ACCV (4)
ACCV (4)
Meta-learning approaches have addressed few-shot problems by finding initialisations suited for fine-tuning to target tasks. Often there are additional properties within training data (which we refer to as context), not relevant to the target task, w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5877cc91827eaf1f03df25cb5814eef8
https://doi.org/10.1007/978-3-030-69538-5_5
https://doi.org/10.1007/978-3-030-69538-5_5
Autor:
Raf Theunissen, Alessandro Masullo, Stefano Discetti, Jean-Marie Buchlin, Marco Raiola, Andrea Ianiro, M.A. Mendez
Publikováno v:
Mendez, M A, Raiola, M, Masullo, A, Discetti, S, Ianiro, A, Theunissen, R & Buchlin, J-M 2017, ' POD-based Background Removal for Particle Image Velocimetry ', Experimental Thermal and Fluid Science, vol. 80, pp. 181-192 . https://doi.org/10.1016/j.expthermflusci.2016.08.021
e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
e-Archivo: Repositorio Institucional de la Universidad Carlos III de Madrid
Universidad Carlos III de Madrid (UC3M)
e-Archivo. Repositorio Institucional de la Universidad Carlos III de Madrid
instname
State-of-art preprocessing methods for Particle Image Velocimetry (PIV) are severely challenged by time dependent light reflections and strongly non-uniform background. In this work, a novel image preprocessing method is proposed. The method is based
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::243d1b59756f9ef2d0bb97beabe39228
https://doi.org/10.1016/j.expthermflusci.2016.08.021
https://doi.org/10.1016/j.expthermflusci.2016.08.021
Publikováno v:
ICCV Workshops
The re-identification of people in private environments is a rather complicated task, not only from a technical standpoint but also for the ethical issues connected to it. The lack of a privacy-sensitive technology to monitor specific individuals pre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53423b3439cf498e391838887abcafce
https://doi.org/10.1109/iccvw.2019.00199
https://doi.org/10.1109/iccvw.2019.00199