Projects in the Robotics Engineering and Computing in Healthcare (REACH)

An overview of the research projects undertaken by REACH.


Assistive robots have the potential to provide support for a range of care-related tasks such as physical and social assistance, physiotherapy and rehabilitation. However, the close human-robot interaction (HRI) causes safety challenges. The research work is based around a series of experiments designed to validate a range of practical use-cases, derived from potential end-users, occupational and physiotherapists, paid carers and regulators, and potential commercial manufacturing partners. The use-cases cover functionality and more generalisable HRI aspects such as adaptive and intelligent performance and multi-modal interaction, which will impact on safety relating to human factors, such as: trust, attention, perception, and learning.

Project duration: 2019-2021.

Adaptive home robotic assistance for people with stroke

The final goal of this research is to develop personalised home assistance for people with stroke promoting their independence and rehabilitation. This project focuses on two main objectives:

  • understanding different motor patterns of sit-to-stand (STS) in individuals with stroke
  • development of a user-centric adaptive control approach for a STS robot

Project duration: 2021-2022.

Anchor Robotics Personalised Assistive Robotics Studio

At the Bristol Robotics Laboratory (BRL), the Anchor Robotics Personalised Assistive Robotics Studio is an in-house facility to develop, test and implement assistive robots and heterogeneous sensor systems in a realistic environment, bringing together our expertise in robotics, human-robot interaction, intelligent learning systems and person-centred design. This helps develop pragmatic solutions and reduce time to market.

The studio provides a ‘Living Lab’ environment. The ‘Living Lab’ concept refers to a set of methodologies and tools for the co-creation and validation of innovation together with the end-users. Designed to resemble a typical single level home, the studio comprises an open-plan living, dining and kitchen area and a bathroom and bedroom. The studio has been instrumented with a network of wireless sensors linked to a Smart Home Controller Hub, wi-fi cameras and an ADSL connection. Our approach to research and design is to take a person-centred approach:

  • understanding people’s context of use and perspectives on robotic assistive technology
  • investigating potential barriers and constraints and criteria for acceptability
  • considering ethical issues and social and cultural impact of the technology

We strive to seek user input using a range of participatory design methods. It is important to us to consider all stakeholders’ perspectives and address the challenges of effective communication between end-users and technical researchers.

We aim to work in multi-disciplinary teams including clinicians, carers, physiotherapists, occupational therapists, user experience designers and psychologists. Iterative prototyping and evaluation is central to our user-centred approach, ensuring that systems are useful, usable and accepted.


Objective characterisation of movement disorders to identify people with Multiple Sclerosis likely to benefit from deep brain stimulation. 

View CHARMED-MS project webpage.


Facilitating physical activity and exercises in people aged over 55 years.

Project duration: 2022-2024.


Connected and autonomous vehicles will play a significant role in a future transport system and unlock enormous social benefits at the same time. Empowerment through trusted secure mobility.

FLOURISH is an Innovate UK-funded three year project with academic partners associated with the EPSRC. FLOURISH looks to enable the delivery of many of these benefits by helping to ensure that connected and autonomous vehicle are developed with the user in mind and are technically secure, trustworthy and private.

View the FLOURISH website.

MoDA-VR (Movement Disorders Assessment in Virtual Reality)

The objective of our collaboration is to develop a virtual reality (VR) system to improve the diagnosis of movement disorders by enabling tests that cannot be conducted in the real world.

View the MoDA-VR project webpage.


Pulse Oximetry from the EardruM.


Automated extrinsic calibration of a markerless 3D human motion capture system. 

View PoseCalib project webpage.

SciRoC (Smart Cities Robot Competitions)

The SciRoc project coordinates the European Robotics Leagues, in which teams compete in benchmarked competitions in domains including care, industry and emergency. We run landmark contests in the heart of European Smart Cities, to show citizens the state of the art in believable and relatable everyday scenarios, and engage with them to equip them with the facts to ask, ‘What sort of future do we want?’

Project duration: 2019-2021.

View the SciRoc website.

Supportive Surveillance?

Co-design of automated timely interventions to enhance treatment of Obsessive Compulsive Disorder (OCD). 

View Supportive Surveillance? project webpage.

TEETACSI (Tracking Expert Eyes to Train AI for Clinical Signal Interpretation)

Managing our society’s growing burden of neurological disorders will require significant advances in our ability to efficiently assess a patient’s neurological state. Electroencephalography (EEG) is already, and will increasingly be, an important tool in this effort; it is the only clinically convenient measurement technique with adequate time-resolution to capture human thought processes. However, its use in current practice is severely restricted by the availability of trained neurophysiologists to interpret the recordings.

Numerous studies have attempted automated interpretation of EEG by techniques such as deep learning [Craik et al, 2019]. Such approaches tend to be heavily dependent on time-consuming manual pre-processing and annotation, or restricted to applications/conditions in which these are not required. In realistic clinical conditions, the state-of-the-art technique exhibits an accuracy of 90% in detecting features of interest [Golmohammadi et al, 2019], insufficient for confident clinical use, particularly as the ability to accurately classify these features is even lower.

The aim of this project is to improve on this performance by replicating human expertise in identifying which sections of a signal to focus.

View TEETACSI project webpage.

Telepresence teaching in higher education as reasonable adjustment pilot project

COVID-19 has provided a challenge for safe teaching delivery that has always been present for many disabled academics. Our learning regarding the use of telepresence robots potentially offers a solution and may contribute to a more inclusive learning environment. The aims are to:

  • ascertain the experience of academics using telepresence robots in HE teaching who are shielding due to the COVID-19 pandemic
  • consider whether telepresence could be offered as a reasonable adjustment and to identify the strategic and practical requirements for the HE institution
  • evaluate the student experience of a learning environment that includes telepresence assisted teaching. 

Project duration: 2021-2022.

Robotics Engineering And Computing for Healthcare

We research robotics technologies, intelligent sensors and machine learning to realise person-focused innovative healthcare solutions.

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