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A Deep Learning Approach for the Assessment of Signal Quality of Non-Invasive Foetal Electrocardiography

Sensors (Basel, Switzerland), 2022-04, Vol.22 (9), p.3303

2022

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Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis

NPJ digital medicine, 2024-02, Vol.7 (1), p.33-33, Article 33

2024

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Patient Clustering for Vital Organ Failure Using ICD Code with Graph Attention

IEEE transactions on biomedical engineering, 2023-08, Vol.70 (8), p.1-9

2023

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Measuring and Localizing Individual Bites Using a Sensor Augmented Plate During Unrestricted Eating for the Aging Population

IEEE journal of biomedical and health informatics, 2020-05, Vol.24 (5), p.1509-1518

2020

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Self-Supervised Machine Learning to Characterise Step Counts from Wrist-Worn Accelerometers in the UK Biobank

Medicine and science in sports and exercise, 2024-05

2024

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Bridging the gap between real-life data and simulated data by providing a highly realistic fall dataset for evaluating camera-based fall detection algorithms

Healthcare technology letters, 2016-03, Vol.3 (1), p.6-11

2016

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Detection of Chewing Motion Using a Glasses Mounted Accelerometer Towards Monitoring of Food Intake Events in the Elderly

International Conference on Biomedical and Health Informatics, 2018, Vol.64, p.73-77

2018

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Improving the accuracy of existing camera based fall detection algorithms through late fusion

2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017, Vol.2017, p.2667-2671

2017

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Detection of chewing motion in the elderly using a glasses mounted accelerometer in a real-life environment

2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017, Vol.2017, p.4521-4524

2017

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Measuring weight and location of individual bites using a sensor augmented smart plate

2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018-07, Vol.2018, p.5558-5561

2018

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Quantifying Eating Behavior With a Smart Plate in Patients With Arm Impairment After Stroke

2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 2019, p.1-4

2019

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A Deep Learning Approach for the Assessment of Signal Quality of Non-Invasive Foetal Electrocardiography

Digital health technologies and machine learning augment patient reported outcomes to remotely characterise rheumatoid arthritis

Patient Clustering for Vital Organ Failure Using ICD Code with Graph Attention

Measuring and Localizing Individual Bites Using a Sensor Augmented Plate During Unrestricted Eating for the Aging Population

Self-Supervised Machine Learning to Characterise Step Counts from Wrist-Worn Accelerometers in the UK Biobank

Bridging the gap between real-life data and simulated data by providing a highly realistic fall dataset for evaluating camera-based fall detection algorithms

Detection of Chewing Motion Using a Glasses Mounted Accelerometer Towards Monitoring of Food Intake Events in the Elderly

Improving the accuracy of existing camera based fall detection algorithms through late fusion

Detection of chewing motion in the elderly using a glasses mounted accelerometer in a real-life environment

Measuring weight and location of individual bites using a sensor augmented smart plate

Quantifying Eating Behavior With a Smart Plate in Patients With Arm Impairment After Stroke

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