Zobrazeno 1 - 10
of 252
pro vyhledávání: '"Neil M White"'
Autor:
A. Ali, Y. Wei, J. Tyson, Harry Akerman, A. I. R. Jackson, R. Lane, D. Spencer, Neil M. White
Publikováno v:
IEEE Access, Vol 12, Pp 180913-180925 (2024)
Currently available devices for monitoring respiratory rate (RR) are cumbersome and expensive (such as capnography and plethysmography), requiring skilled clinicians to operate and analyse. In contrast, the inexpensive and lightweight ones (e.g. repo
Externí odkaz:
https://doaj.org/article/66288350b5f44eddafb04c0dac5b1b2c
Autor:
Amjad Ali, Yang Wei, Yomna Elsaboni, Jack Tyson, Harry Akerman, Alexander I. R. Jackson, Rod Lane, Daniel Spencer, Neil M. White
Publikováno v:
Sensors, Vol 24, Iss 20, p 6513 (2024)
In this work, a flexible textile-based capacitive respiratory sensor, based on a capacitive sensor structure, that does not require direct skin contact is designed, optimised, and evaluated using both computational modelling and empirical measurement
Externí odkaz:
https://doaj.org/article/a993e9cec3c74870b0dda964baa9a876
Autor:
Christopher Duckworth, Francis P. Chmiel, Dan K. Burns, Zlatko D. Zlatev, Neil M. White, Thomas W. V. Daniels, Michael Kiuber, Michael J. Boniface
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Abstract A key task of emergency departments is to promptly identify patients who require hospital admission. Early identification ensures patient safety and aids organisational planning. Supervised machine learning algorithms can use data describing
Externí odkaz:
https://doaj.org/article/404d9950339044a28d5e3a7b9f106d13
Autor:
Michael Kraft, Neil M White
MEMS for automotive and aerospace applications reviews the use of Micro-Electro-Mechanical-Systems (MEMS) in developing solutions to the unique challenges presented by the automotive and aerospace industries.Part one explores MEMS for a variety of au
Autor:
Abiodun Komolafe, Bahareh Zaghari, Russel Torah, Alex S. Weddell, Hamideh Khanbareh, Zois Michail Tsikriteas, Mark Vousden, Mahmoud Wagih, Ulises Tronco Jurado, Junjie Shi, Sheng Yong, Sasikumar Arumugam, Yi Li, Kai Yang, Guillaume Savelli, Neil M. White, Steve Beeby
Publikováno v:
IEEE Access, Vol 9, Pp 97152-97179 (2021)
Wearable devices are ideal for personalized electronic applications in several domains such as healthcare, entertainment, sports and military. Although wearable technology is a growing market, current wearable devices are predominantly battery powere
Externí odkaz:
https://doaj.org/article/5ec30d98667941c883798000566b0568
Publikováno v:
Lubricants, Vol 11, Iss 4, p 164 (2023)
In bearing applications, the presence of stray and parasitic currents in combination with lubricants has been studied for almost a century and has been found to cause fluting and corrugation damages under high current densities. However, recent resea
Externí odkaz:
https://doaj.org/article/0d7daf5a71e540818cc1e1e2a751cf2c
Autor:
Irfan Ullah, Mahmoud Wagih, Yixuan Sun, Yi Li, Kata Hajdu, Rémi Courson, Catherine Dreanno, Enora Prado, Abiodun Komolafe, Nick R. Harris, Neil M. White, Steve Beeby
Publikováno v:
IEEE Transactions on Biomedical Circuits and Systems. :1-16
Publikováno v:
Sensors, Vol 22, Iss 1, p 392 (2022)
The reliability of rolling element bearings has been substantially undermined by the presence of parasitic and stray currents. Electrical discharges can occur between the raceway and the rolling elements and it has been previously shown that these di
Externí odkaz:
https://doaj.org/article/6a794969d0884c378335156089016f24
Publikováno v:
Sensors, Vol 21, Iss 22, p 7740 (2021)
This work presents a novel type of actuator that improves over the standard cantilever by permitting daisy-chaining while minimising stress to the joint connecting to the load. A detailed structural and functional comparison of the proposed device ag
Externí odkaz:
https://doaj.org/article/d271ac98b06b42d1ac65260860cfaff6
Autor:
Neil M. White, F. P. Chmiel, Michael Boniface, Daniel Burns, Christopher Duckworth, T. Daniels, Michael Kiuber, Zlatko Zlatev
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Scientific Reports
Scientific Reports
A key task of emergency departments is to promptly identify patients who require hospital admission. Early identification ensures patient safety and aids organisational planning. Supervised machine learning algorithms can use data describing historic