Socially Assistive Robot Support to aid recovery after critical illness

This project aims to use case studies and technical robot pilots to evaluate the feasibility and acceptability of using SARs for patients recovering after critical care.
Description of the Project: 

Critical illness can affect individuals at any age and for a wide range of medical and surgical conditions. Recovery can be prolonged, and complicated by fatigue, impaired attention and limited engagement with rehabilitation for physical and mental health reasons. Socially assistive robots provide an opportunity for bespoke rehabilitation programmes to be developed by health care professionals, then delivered by the robot, from the time of recovery from critical care, through the rest of the inpatient journey, to the transition home. This project aims to use case studies and robot pilots to evaluate the feasibility and acceptability of using Socially Assistive Robots (SARs) to support patients recovering after critical care. 

This PhD will develop robot pilots that aim to support patients who are rehabilitating after a critical illness. They will work with their supervisor at HWU and pilot in the assistive living lab and in the hospital a small number of technical pilots (e.g. physiotherapy exercise) by the robot. They will also undertake  a series of case studies with qualitative feedback from patients and staff to evaluate the potential for service implementation of SARs these studies will also take place in years 1 and 4 of the PhD, with years 2 & 3 focused on the robot pilots. 

Resources required: 
SARs robots, Assistive Living Lab (Lyell Building and then National Robotarium), HRI Lab
Project number: 
200027
First Supervisor: 
University: 
Heriot-Watt University
First supervisor university: 
Heriot-Watt University
Essential skills and knowledge: 
MSc in Robotics or closely aligned subject would be key.
Desirable skills and knowledge: 
ROS, Python
References: 

A. Richards-Belle et al., “Psychological Outcomes following a nurse-led Preventative Psychological Intervention for critically ill patients (POPPI): Protocol for a cluster-randomised clinical trial of a complex intervention,” BMJ Open, vol. 8, no. 2, 2018. 

B. H. Cuthbertson et al., “The PRaCTICaL study of nurse led, intensive care follow-up programmes for improving long term outcomes fromcritical illness: A pragmatic randomised controlled trial,” BMJ, vol. 339, no. 7728, p. 1016, 2009. 

J. Fasola and M. Mataric, “A Socially Assistive Robot Exercise Coach for the Elderly,” J. Human-Robot Interact., vol. 2, no. 2, 2013. 

D. D. Bellamy and P. Caleb-Solly, “Collaborative HRI and Machine Learning for Constructing Personalised Physical Exercise Databases,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, vol. 11649 LNAI, pp. 209–220. 

E. Stowell, T. K. O’Leary, E. Kimani, M. K. Paasche-Orlow, T. Bickmore, and A. G. Parker, “Investigating Opportunities for Crowdsourcing in Church-Based Health Interventions,” in Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 2020, pp. 1–12. 

K. Winkle, P. Caleb-Solly, A. Turton, and P. Bremner, “Social Robots for Engagement in Rehabilitative Therapies: Design Implications from a Study with Therapists,” in Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction - HRI ’18, 2018, pp. 289–297, doi: 10.1145/3171221.3171273. 

K. K. Miller, R. E. Porter, E. DeBaun-Sprague, M. V. Puymbroeck, and A. A. Schmid, “Exercise after Stroke: Patient Adherence and Beliefs after Discharge from Rehabilitation,” Topics in Stroke Rehabilitation, vol. 24, no. 2, pp. 142–148, Feb. 2017, doi: 10.1080/10749357.2016.1200292. 

D. Hebesberger, T. Koertner, C. Gisinger, J. Pripfl, and C. Dondrup, “Lessons learned from the deployment of a long-term autonomous robot as companion in physical therapy for older adults with dementia: A mixed methods study,” in ACM/IEEE International Conference on Human-Robot Interaction, 2016, vol. 2016-April, pp. 27–34, doi: 10.1109/HRI.2016.7451730. 

E. Wade, A. R. Parnandi, and M. J. Matarić, “Using Socially Assistive Robotics to Augment Motor Task Performance in Individuals Post – Stroke,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, 2011, pp. 2403–2408