Brain-controlled wearable soft robot with photo-responsive elastomer

Project ID: 2531bd1659

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Research Area(s): Artificial intelligence technologies
Microelectronics design
Assistive technology, rehabilitation and musculoskeletal biomechanics

UCL Lead department: Electronic and Electrical Engineering (EEE)

Department Website

Lead Supervisor: Dai Jiang

Project Summary:

Paralysis affects 70 – 90 million people worldwide, severely limiting independence in daily life and imposing major financial burden on individuals and society. In the UK, the estimated lifetime cost for spinal cord injury (SCI) is £1.12 million per case. There is currently no cure for paralysis. Although implanted brain-spine interfaces restored natural walking after SCI in research, its high invasiveness hinders clinical translation. Non-invasive prosthetics and exoskeletons are increasingly used in clinical practice, but about 30% of users abandon them each year due to low satisfaction in comfort, appearance and functionality.

This project aims to develop wearable mobility-assistance technologies that integrate brain-computer interface (BCI) with soft robotics. The system will incorporate a novel, visible light-responsive thermoplastic elastomer developed at UCL Centre of Biomaterials, which exhibits muscle-like flexible and viscoelastic properties when activated by patterned stimuli from miniaturised LEDs. A non-invasive electroencephalogram (EEG)-based BCI will be used to accurately interpret the user’s intended movements, which will then drive artificial muscles built with the photo-responsive elastomer to facilitate close-to-natural movement.

The first objective of this project is to achieve integrated, energy-efficient computing solutions for fully wearable BCIs. Building on our recent progress in graph-based learning for calibration-free, subject-independent EEG classification, this project will explore neuromorphic approaches to develop low-power accelerators for highly accurate EEG decoding. The second objective is to study the correlation between the optical and mechanical properties of the photo-responsive elastomer and, from this, to design control strategies for coordinating multiple artificial muscle groups to perform purposeful movement. The work will be carried out in state-of-the-art research facilities, under the supervision of a multidisciplinary team of experts in microelectronics, machine learning, and biomaterials.

We are seeking a student with a background in electronics or computer science, and with the curiosity and motivation to learn new skills for multidisciplinary research.