The Technology and Communication Translational Research Group is led by Saturnino Luz. This group investigates potential uses and benefits of computing technology and robotics for cognitive decline. This is done through analysis of verbal interactions and paralinguistic signals, and in providing support and therapy for elderly persons experiencing cognitive decline, and those who may have dementia.
Companion robots such as PARO have been employed in care facilities in Japan and several other countries, with positive results in terms of improving social interactions and reducing stress among the residents. Such devices also offer new opportunities for assessing the health and cognitive well-being of older persons through embedded sensors, multimodal signal processing and machine learning methods. We aim to develop technology which can do this kind of monitoring longitudinally, more conveniently and more frequently than is currently possible with existing procedures.
In addition to investigating these data-intensive methods, our group is interested in the broader implications of the use of robotics and computational devices to improve well-being and gather health-relevant data in daily life, such as how to ensure that this is done in an efficient, unobtrusive, acceptable and dignified manner.
S. Luz. Longitudinal monitoring and detection of Alzheimer’s type dementia from spontaneous speech data. In Computer Based Medical Systems. IEEE Press, 2017
K. Moustafa, S. Luz, and L. Longo. Assessment of mental workload: A comparison of machine learning methods and subjective assessment techniques. In International Symposium on Human Mental Workload: Models and Applications, pages 30–50. Springer, 2017.
J. Su and S. Luz. Predicting Cognitive Load Levels from Speech Data. In A. Esposito, M. Faundez-Zanuy, A. M. Esposito, G. Cordasco, T. Drugman, J. Solé-Casals, and F. C. Morabito, editors, Recent Advances in Nonlinear Speech Processing, number 48, pages 255–263. Springer, 2016.
S. Luz and B. Kane. Perspectives on intelligent systems support for multidisciplinary medical teams. In AAAI Spring Symposium Series, pages 272–275, 2016.
F. Haider, L. Cerrato, N. Campbell, and S. Luz. Presentation quality assessment using acoustic information and hand movements. In Proceeding of the IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP’16, pages 2812–2816. IEEE, 2016.
B. Kane and S. Luz. Medical teamwork, collaboration and patient-centred care. Behaviour & Information Technology, 34(6):543–547, 2015.
S. Luz. The non-verbal structure of patient case discussions in multidisciplinary medical team meetings. ACM Transactions on Information Systems, 30(3):17:1–17:24, 2012.
SAAM: Supporting Active Ageing through Multimodal coaching. European Commission, Horizon 2020. 2017-2020; €3,996,000.
INCA: Interaction Analytics for Automatic Assessment of Communication Quality in Primary Care. Health Research Board, 2016-2019; €313,000.
Genealogies of Knowledge. AHRC, 2016-2020, £796,000.
METALOGUE: Multi-perspective Multimodal Dialogue systems with metacognitive abilities, EU FP7, 2013-2016, €310,000.