projects

Cognitive Intervention Therapy (CIT) is a form of treatment designed to improve (or delay the loss of) cognitive function in persons with Mild Cognitive Impairment (MCI) - such as dementia or early-stage Alzheimers - and offers an important, more accessible option than traditional, pharmacological treatments. Digitised forms of CIT, such as “gamified” cognitive training tasks, or Socially-Assistive Robots (SARs), propose significant advantages in addressing numerous constraints of traditional interventions; including off-site therapy and precise data monitoring of therapy promoting person-centred care (PCC). 

Personalisation of these digitized CIT, delivered through SARs, can help in improving the efficacy of these therapies, through long-term engagement with the treatment as well as improving (cognitive-based) task performance. How to achieve these personalised treatments for persons with MCI remains an ongoing challenge. 

One way to approach this is for socially-assistive robot partners to personalise the therapy based on a user’s “emotional” (affective) state, which can be detected through a combination of verbal and non-verbal social signals from the human partner. Utilising this affective information to personalise the digitised CIT underpins a novel approach for motivating and engaging users to adhere to therapy, and can improve the viability of social robots as long-term therapeutic interventions for patient-centred care. 

The key aim of this research is to investigate whether a “personalised” social robot partner (which can adapt its interactions based on a human partner’s emotional state) can be used as a viable therapeutic tool to improve cognitive function (memory) in pre-clinical or Alzheimer's disease prodromal stage patients (with Mild Cognitive Impairment). 

The ability to adapt to ever-changing physical and social environments is crucial for the survival and well-being of any species. In biology, species who live in a society tend to live longer, healthier lives, and exhibit different types of adaptation compared to species that don't. This process of adaptation can give rise to interesting behaviours and social dynamics, and may even play a part in how and why "social emotions" emerge. 

Starting with the notion that all cognition and life is rooted in preserving an organism's stability (homeostasis, and allostasis), this research seeks to understand how and why social interactions and social relationships can play such a critical role in an individual's long-term stability (self-regulation) and adaptability in uncertain conditions. 

 
I am interested in exploring the link between (affective) interactions with the social environment and its (adaptive) effects on internal physiology, how this gives rise to socially-affective phenomena, and how social affect influences motivations, decision-making and (ultimately) higher-order (embodied) intelligence and cognition.

I use a biologically-inspired Artificial Life approach to model and test some of these potential effects, and use the findings to (a) better understand (and formulate new theories for) potential mechanisms of socially-affective adaptation, intelligence, and affective cognition in real-world (human and non-human) animals, and (b) inform the development of socially-adaptive models for autonomous agents (such as robots).