Aiding Aging Gracefully: Soft Robotics for Wearable Assistive Technologies

   Department of Mechanical Engineering

  Dr Runan Zhang  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

This project addresses an impending global challenge: the aging population, projected to reach 2.1 billion by 2050. As the world's senior and geriatric population grows, there is a pressing need for advanced wearable technology that can assist with daily activities, beyond merely promoting health and preventing disease.

Existing wearable devices, including exoskeleton suits used for rehabilitation, are rigid, bulky, and designed for short-term use in clinical settings. These devices are unsuitable for long-term, everyday use. This project aims to fill this gap by developing a wearable device that is compliant, lightweight, noise-free, and capable of actively assisting the human body.

The key to achieving this is through the novel application of soft robotics technology. Traditional mechanical structures and mechatronic systems, primarily composed of rigid parts, are unsuitable. This project will focus on developing soft sensing and actuation technologies to create an active, compliant wearable device.

The first step is to review and evaluate existing soft robotics technologies and identify suitable candidates. Next, a soft wearable device will be developed, addressing specific healthcare challenges, such as suppressing hand tremors. Special considerations are required to ensure the chosen actuation technique is safe for human interaction.

The system will be designed with the appropriate sensing and actuation bandwidth to match the selected application, considering the specific part of the human body it will assist. Algorithms will be developed to recognize typical daily activities of elderly users, adapt to changes in working conditions, and determine when to apply control actions.

This Ph.D. project provides a unique opportunity to combine design, development, and application of a novel soft wearable system, motion detection algorithms, human behaviour recognition, and system control. It promises a comprehensive research experience, from theoretical concepts and design solutions to practical implementation and experimental evaluation.

Engineering (12) Materials Science (24)

Funding Notes

A variety of competitive funding opportunities are available, and self-funded student is acceptable.

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