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Scientific Reports|March 25, 2025
Optimising TinyML with quantization and distillation of transformer and mamba models for indoor localisation on edge devicesThanaphon Suwannaphong, Ferdian Jovan, Ian Craddock, et al.
JMIR Human Factors|July 7, 2022
Acceptability of an In-home Multimodal Sensor Platform for Parkinson Disease: Nonrandomized Qualitative StudyCatherine Morgan, Emma L Tonkin, Ian Craddock, et al.
JMIR Mhealth and Uhealth|November 29, 2021
"A Question of Trust" and "a Leap of Faith"-Study Participants' Perspectives on Consent, Privacy, and Trust in Smart Home Research: Qualitative StudyMari-Rose Kennedy, Richard Huxtable, Giles Birchley, et al.
Scientific Data|August 22, 2018
Residential wearable RSSI and accelerometer measurements with detailed location annotationsDallan Byrne, Michal Kozlowski, Raul Santos-Rodriguez, et al.
Health Expectations : an International Journal of Public Participation in Health Care and Health Policy|October 6, 2018
User involvement in digital health: Working together to design smart home health technologyAlison Burrows, Ben Meller, Ian Craddock, et al.
JMIR Formative Research|September 14, 2022
Personalized Energy Expenditure Estimation: Visual Sensing Approach With Deep LearningToby Perrett, Alessandro Masullo, Dima Damen, et al.
Sensors (Basel, Switzerland)|March 20, 2020
From Bits of Data to Bits of Knowledge-An On-Board Classification Framework for Wearable Sensing SystemsPawel Zalewski, Letizia Marchegiani, Atis Elsts, et al.
Journal of Medical Imaging (Bellingham, Wash.)|July 23, 2016
MARIA M4: clinical evaluation of a prototype ultrawideband radar scanner for breast cancer detectionAlan W Preece, Ian Craddock, Mike Shere, et al.
Data in Brief|February 12, 2019
A dataset for room level indoor localization using a smart home in a boxRyan McConville, Dallan Byrne, Ian Craddock, et al.
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