Saturnino Luz

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University of Edinburgh
Country flagUnited Kingdom

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Recent Grants

Grant: Close

SIDE-AD: speech for intelligent cognition change tracking and detection of Alzheimer's disease

Open Date: 2022-10-01

Close Date: 2023-09-01

Grant: Close

Oslo Medical Corpus

Open Date: 2022-01-01

Close Date: 2023-06-01

Grant: Close

Cross-Lingual Embeddings for Less-Represented Languages in European News Media

Open Date: 2019-01-01

Close Date: 2022-03-31

Grant: Close

Supporting Active Ageing through Multimodal coaching

Open Date: 2017-10-01

Close Date: 2021-05-31

Grant: Close

Interaction Analytics for Automatic Assessment of Communication Quality in Primary Care

Open Date: 2016-08-31

Close Date: 2020-02-29

Articles (12)

The ubiquity of digital technology has facilitated detailed recording of human behaviour. Ambient technology has been used to capture behaviours in a broad range of applications ranging from healthcare and monitoring to assessment of cooperative work. However, existing systems often face challenges in terms of autonomy, usability, and privacy. This paper presents a portable, easy-to-use and privacy-preserving system for capturing behavioural signals unobtrusively in home or in office settings. The system focuses on the capture of audio, video, and depth imaging. It is based on a device built on a small-factor platform that incorporates ambient sensors which can be integrated with the audio and depth video hardware for multimodal behaviour tracking. The system can be accessed remotely and integrated into a network of sensors. Data are encrypted in real time to ensure safety and privacy. We illustrate uses of the device in two different settings, namely, a healthy-ageing IoT application, where the device is used in conjunction with a range of IoT sensors to monitor an older person’s mental well-being at home, and a healthcare communication quality assessment application, where the device is used to capture a patient–clinician interaction for consultation quality appraisal. CUSCO can automatically detect active speakers, extract acoustic features, record video and depth streams, and recognise emotions and cognitive impairment with promising accuracy.

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2024

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2024

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2024

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2023

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2022

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2022

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2021

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2021

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2021

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2020

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2020

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2020

Collaborators (11)

Andrew McIntosh

Professor of Biological Psychiatry

University of Edinburgh

UNITED KINGDOM
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Mark Bastin

Reader

University of Edinburgh

UNITED KINGDOM
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Robby van Delden

Assistant Professor

University of Twente

NETHERLANDS
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Keith Smith

University Of Strathclyde

UNITED KINGDOM
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Simon R. Cox

-

UNITED KINGDOM
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Nicklas Linz

Deutsches Forschungszentrum für Künstliche Intelligenz GmbH

GERMANY
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Fasih Haider

University of Edinburgh

UNITED KINGDOM
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Alexandra König

Université Côte d'Azur

FRANCE
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Elliot M. Tucker-Drob

Professor

University of Texas at Austin

UNITED STATES
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Craig Ritchie

Professor

University of Edinburgh

UNITED KINGDOM
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Dennis Reidsma

University of Twente

NETHERLANDS
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