21 citations · 36 across the 9 of their papers we have counts for
10 papers
A Hybrid Edge Classifier: Combining TinyML-Optimised CNN with RRAM-CMOS ACAM for Energy-Efficient Inference
Kieran Woodward, Eiman Kanjo, Georgios Papandroulidakis +2
In recent years, the development of smart edge computing systems to process information locally is on the rise. Many near-sensor machine learning (ML) approaches have been implemen…
Enviro-IoT: Calibrating Low-Cost Environmental Sensors in Urban Settings
Thomas Johnson, Kieran Woodward
Low-cost miniaturised sensors offer significant advantage to monitor the environment in real-time and accurately. The area of air quality monitoring has attracted much attention in…
DigitalExposome: Quantifying the Urban Environment Influence on Wellbeing based on Real-Time Multi-Sensor Fusion and Deep Belief Network
Thomas Johnson, Eiman Kanjo, Kieran Woodward
In this paper, we define the term 'DigitalExposome' as a conceptual framework that takes us closer towards understanding the relationship between environment, personal characterist…
Combining Deep Transfer Learning with Signal-image Encoding for Multi-Modal Mental Wellbeing Classification
Kieran Woodward, Eiman Kanjo, Athanasios Tsanas
The quantification of emotional states is an important step to understanding wellbeing. Time series data from multiple modalities such as physiological and motion sensor data have…
TangToys: Smart Toys that can Communicate and Improve Children's Wellbeing
Kieran Woodward, Eiman Kanjo, David J Brown +1
Children can find it challenging to communicate their emotions especially when experiencing mental health challenges. Technological solutions may help children communicate digitall…
Sensor Data and the City: Urban Visualisation and Aggregation of Well-Being Data
Thomas Johnson, Eiman Kanjo, Kieran Woodward
The growth of mobile sensor technologies have made it possible for city councils to understand peoples' behaviour in urban spaces which could help to reduce stress around the city.…
On-Device Transfer Learning for Personalising Psychological Stress Modelling using a Convolutional Neural Network
Kieran Woodward, Eiman Kanjo, David J. Brown +1
Stress is a growing concern in modern society adversely impacting the wider population more than ever before. The accurate inference of stress may result in the possibility for per…
LabelSens: Enabling Real-time Sensor Data Labelling at the point of Collection on Edge Computing
Kieran Woodward, Eiman Kanjo, Andreas Oikonomou
In recent years, machine learning has developed rapidly, enabling the development of applications with high levels of recognition accuracy relating to the use of speech and images.…
Challenges of Designing and Developing Tangible Interfaces for Mental Well-being
Kieran Woodward, Eiman Kanjo, David Brown
Mental well-being technologies possess many qualities that give them the potential to help people receive assessment and treatment who may otherwise not receive help due to fear of…
Beyond Mobile Apps: A Survey of Technologies for Mental Well-being
Kieran Woodward, Eiman Kanjo, David Brown +4
Mental health problems are on the rise globally and strain national health systems worldwide. Mental disorders are closely associated with fear of stigma, structural barriers such…