CUSCO: An Unobtrusive Custom Secure Audio-Visual Recording System for Ambient Assisted Living.

Journal: Sensors (Basel, Switzerland)

Volume: 24

Issue: 5

Year of Publication: 2024

Affiliated Institutions:  National Institute for Public Health and the Environment, MA Bilthoven, The Netherlands. School of Engineering, The University of Edinburgh, Edinburgh EH JW, UK. Usher Institute, Edinburgh Medical School, The University of Edinburgh, Edinburgh EH YL, UK.

Abstract summary 

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.

Authors & Co-authors:  Albert Haider Luz

Study Outcome 

Source Link: Visit source

Statistics
Citations :  Prati A., Shan C., Wang K.I.K. Sensors, vision and networks: From video surveillance to activity recognition and health monitoring. J. Ambient Intell. Smart Environ. 2019;11:5–22.
Authors :  3
Identifiers
Doi : 1506
SSN : 1424-8220
Study Population
Male,Female
Mesh Terms
Humans
Other Terms
ambient intelligence;cooperative work;healthcare;human-behaviour tracking;multimodal recording devices;privacy preservation
Study Design
Study Approach
Country of Study
Publication Country
Switzerland