Next generation of endovascular catheter-based cardiac procedures using soft robotics

Challenge:

Beating-heart procedures represent a less invasive alternative to standard open-heart surgery with fewer perioperative complications, and shorter recovery time. However, several engineering challenges still preclude performing reconstructive surgical procedures via endovascular approach, which currently can mostly be done on the open and stopped heart.

Current endovascular catheter-based platforms still provide limited distal dexterity, lack sensor feedback, and cannot apply significant number of forces. Furthermore, the highly dynamic environment given by the beating heart, makes precise positioning of the tool very challenging, resulting in significant risks in manipulating delicate intracardiac structures. Robotic catheters have been explored in cardiovascular conditions like endoscopic cardiac, vascular/endovascular surgery, ablation therapy for atrial fibrillation and percutaneous coronary intervention. Though promising, its application is challenged by environmental problems (continuous heart pulsation, blood flow) and engineering limitations (maintaining sufficient contact forces, avoid puncturing the cardiac wall, micro-fabrication, and poor tip navigation control through tortuous vascular geometry). This project proposes to overcome above challenges by exploring micro-fabrication, mathematical modelling, developing control strategies, biomedical imaging and experimental validation for long-slender robotic catheters.

Objective:

The proposed project aims to develop a new class of endovascular soft robotic actuator for stable, precise, remote based control of rapid, repeatable catheters for in-vitro imaging in cardiac phantom, animal cadaver and minimally invasive and safe patient care.

Key areas of research:

• Design, prototyping soft robotic structures
• Developing novel actuation techniques
• Obtaining in-situ imaging and using AI/ML algorithms for cancer diagnosis.
• Data analysis using CNN mathematical modelling. 

Possible areas of impact:

Novel Collaboration for synergizing interdisciplinary research (soft robotics, clinical science, medical imaging, AI and ML) for surgical intervention in cardiovascular diseases.

Training provided:

Research will include working with synthetic biochemical compound, cancerous tissues, mechanical and electronic circuit designs, prototyping and pre-clinical in-vitro testing of surgical medical devices: 

1. Exploring novel actuation methods, 
2. Soft robotic fabrication and control technique, 
3. Integration of sensors, camera interfaces into soft robotic devices, 
4. AI/ML modelling and data analysis using CNN.

Academic entry requirements:

Candidates must have (or expect to obtain) a minimum of a UK upper second-class honours degree (2.1) in an Mechanical/Electrical Engineering discipline, Materials Science technology, Physical Sciences (Physics, Chemistry, Biology), Medical Sciences, Biotechnology or in any related subject.

Candidates with the following skills are desirable:

Proficiency in Data Analysis/AI/Machine learning (Python, MATLAB), programming (Micro-controller/processors), mechanical CAD design (SolidWorks, hands-on experience of 3D printing, laser cutting, 3D scanning).

How to apply:

Applicants must apply via the University’s online application system at https://www.york.ac.uk/study/postgraduate-research/apply/. Please read the application guidance first so that you understand the various steps in the application process. To apply, please select the PhD in Electronic Engineering for October 2023 entry. Please specify in your PhD application that you would like to be considered for this studentship.

Applications for this studentship will be considered on a first-come, first-served basis and the position will be filled as soon as a suitable applicant is identified.