PhD Studentship - Flexible and Intent-Aware Exoskeleton for Gait Assistance

Application deadline: All year round

How to apply: uom.link/pgr-apply-fap

Funding is available to cover the tuition fees, as well as a tax free stipend at standard UKRI rate (£19,237 for 2024/25) for up to 4 years. The stipend normally increases each year. The expected start date is September 2025.

Gait deficits affect millions of individuals worldwide due to various conditions such as stroke, spinal cord injuries, cerebral palsy, multiple sclerosis, and age-related mobility issues. These impairments lead to gait asymmetry, increased metabolic expenditure, poor balance control, and a heightened risk of falls.

Current wearable exoskeletons, primarily based on rigid actuation and transmission mechanisms, suffer from high mechanical impedance, movement misalignment, and pose safety risks. Soft exoskeletons are fully wearable, clothing-like devices that wrap around users’ limbs and work in parallel with their muscles and ligaments. They transmit tensile forces through specified load paths over the user's body to generate assistive torque at the biological joints. The intrinsic compliance of soft exoskeletons provides them with extremely low inertia and ensures they always align with the biological joints.

Research Aims

This PhD project seeks to tackle fundamental challenges in the design and control of soft exoskeletons for gait rehabilitation. Key objectives include:

• Effective Actuation: Developing methods to actuate the exoskeleton in ways that are efficient, safe, and comfortable for users.
• Customized Design Optimization: Tailoring exoskeleton designs to individual body shapes and gait patterns to maximize efficacy.
• Advanced Control Algorithms: Creating learning-based control systems that adapt to the user's movements.

Role and Responsibilities

The successful candidate will:

• Engage in the mechatronic design and system integration of soft exoskeleton prototypes.
• Develop and implement learning-based control algorithms.
• Test and validate the developed technologies in exemplar scenarios.
• Collaborate with team members working on human biomechanics modelling and functional near-infrared spectroscopy (fNIRS)-based brain assessment to evaluate and refine the exoskeleton's effectiveness.

Applicants should have or expect to achieve at least a UK 2.1 honours degree or its international equivalent) in Control Engineering, Computer Science, Mechatronic Engineering or related disciplines. Experience in robotic manipulation, human biomechanics modelling, and human-robot interaction will be an advantage.

Applicants will also need to meet the English Language requirements for the University indicated on https://www.manchester.ac.uk/study/international/admissions/language-requirements/

Please contact Dr Zhenhong Li - zhenhong.li@manchester.ac.uk, before you apply. Please include a CV.

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