1 code implementation • 3 Aug 2023 • Ferdian Jovan, Catherine Morgan, Ryan McConville, Emma L. Tonkin, Ian Craddock, Alan Whone
A sub-objective aims to evaluate whether indoor localisation, including its in-home gait speed features (i. e. the time taken to walk between rooms), could be used to evaluate motor fluctuations by detecting whether the person with PD is taking levodopa medications or withholding them.
no code implementations • 6 Feb 2023 • Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez, Ian Craddock, Miquel Perello Nieto, Raul Santos-Rodriguez, Weisong Yang, Peter Flach
Here we propose a method to model human biases on temporal annotations and argue for the use of soft labels.
no code implementations • 14 Jul 2022 • Alessandro Masullo, Toby Perrett, Tilo Burghardt, Ian Craddock, Dima Damen, Majid Mirmehdi
We propose a novel approach to multimodal sensor fusion for Ambient Assisted Living (AAL) which takes advantage of learning using privileged information (LUPI).
no code implementations • 12 May 2022 • Ferdian Jovan, Ryan McConville, Catherine Morgan, Emma Tonkin, Alan Whone, Ian Craddock
We use data collected from 10 people with Parkinson's, and 10 controls, each of whom lived for five days in a smart home with various sensors.
no code implementations • 13 Apr 2022 • Bo Tan, Alison Burrows, Robert Piechocki, Ian Craddock, Karl Woodbridge, Kevin Chetty
The experiment results offer potential for promising healthcare applications using Wi-Fi passive sensing in the home to monitor daily activities, to gather health data and detect emergency situations.
1 code implementation • 8 Oct 2021 • Mohammud J. Bocus, Wenda Li, Shelly Vishwakarma, Roget Kou, Chong Tang, Karl Woodbridge, Ian Craddock, Ryan McConville, Raul Santos-Rodriguez, Kevin Chetty, Robert Piechocki
This dataset can be exploited to advance WiFi and vision-based HAR, for example, using pattern recognition, skeletal representation, deep learning algorithms or other novel approaches to accurately recognize human activities.
no code implementations • 3 Jul 2020 • Rafael Poyiadzi, Weisong Yang, Yoav Ben-Shlomo, Ian Craddock, Liz Coulthard, Raul Santos-Rodriguez, James Selwood, Niall Twomey
There is a pressing need to automatically understand the state and progression of chronic neurological diseases such as dementia.
5 code implementations • 16 Aug 2019 • Ryan McConville, Raul Santos-Rodriguez, Robert J. Piechocki, Ian Craddock
We study a number of local and global manifold learning methods on both the raw data and autoencoded embedding, concluding that UMAP in our framework is best able to find the most clusterable manifold in the embedding, suggesting local manifold learning on an autoencoded embedding is effective for discovering higher quality discovering clusters.
Ranked #1 on Image Clustering on pendigits
2 code implementations • 25 Jun 2018 • Ryan McConville, Gareth Archer, Ian Craddock, Herman ter Horst, Robert Piechocki, James Pope, Raul Santos-Rodriguez
In this paper we study the prediction of heart rate from acceleration using a wrist worn wearable.
no code implementations • 4 Feb 2017 • Tom Diethe, Niall Twomey, Meelis Kull, Peter Flach, Ian Craddock
There is a widely-accepted need to revise current forms of health-care provision, with particular interest in sensing systems in the home.
no code implementations • 27 Jul 2016 • Lili Tao, Tilo Burghardt, Majid Mirmehdi, Dima Damen, Ashley Cooper, Sion Hannuna, Massimo Camplani, Adeline Paiement, Ian Craddock
We present a new framework for vision-based estimation of calorific expenditure from RGB-D data - the first that is validated on physical gas exchange measurements and applied to daily living scenarios.