Pint of Robotics: Dr Aiqin Liu, Dr Duygu Sarikaya, and Saul Castañeda Lizarraga

Speaker 1: Dr Aiqin Liu (Faculty of Biological Sciences, University of Leeds).

Dr Aiqin Liu (CEng, MIMechE) is a Lecturer in Human Biomechanics at the School of Biomedical Sciences at the University of Leeds. Her research interest focus on Rehabilitation assistive technology, Knee rehabilitation biomechanics, Joint Replacement, and Regenerative Medicine.

Title: Empower your knee & Move free-Intelligent Robotic Knee Device.

Abstract: Dr Liu is to deliver a presentation on her research project focused on the development of an innovative knee rehabilitation technology. The project has received funding from UKRI and the Wellcome Trust. Specifically, her team has successfully designed and implemented a prototype of a robotic knee exoskeleton, intended to aid, and monitor the rehabilitation process of the population suffering from knee osteoarthritis.

The primary objective of this knee device is to provide clinicians with scientific evidence to evaluate the progress of rehabilitation while empowering patients to actively manage their own rehabilitation journey. By offering real-time muscle support, the exoskeleton assists patients in achieving their exercise goals and performing daily activities. The device's design has been guided by user-centred strategies, as Dr Liu has actively collaborated with both patients and clinicians throughout the development process.

Dr Liu eagerly awaits your valuable feedback and comments on this research project, as it will play a vital role in shaping future investigations in this field.

Speaker 2:  Dr Duygu Sarikaya (School of Computing, University of Leeds).

Dr Sarikaya is a Lecturer at University of Leeds, School of Computing. Her research interests span defining the technologies of future, artificial intelligence powered, healthcare applications. More specifically, sheworks on surgical vision and perception, and medical image computing.

She received her MS and PhD from State University of New York at Buffalo, and my BS from TOBB University of Economics and Technology. She is a Fulbright alumna. She was formerly an Assistant Professor at Gazi University, a Post-doctoral Researcher at MediCIS, INSERM, Universite de Rennes 1 working on Connected Optimized Network & Data in Operating Rooms Project with multiple academic and industrial partners, funded by BPI France, a Project Coordinator / Researcher at ATLAS Program, Roswell Park Comprehensive Cancer Center working in close collaboration with clinicians on Deep Blue Project, funded by the Roswell Alliance Foundation, and a Research Assistant at Vision and Perceptual Machines Lab at State University of New York at Buffalo on a National Institutes of Health (NIH) project in collaboration with Roswell Park Comprehensive Cancer Center. She organized the First and Second International Workshops on Context-Aware Operating Theaters in conjunction with MICCAI, co-organized the second International Surgical Data Science Workshop in conjunction with CARS, and a series of the Joint AE-CAI, CARE and OR 2.0 Workshops in conjunction with MICCAI.

She served as a board member of Women in MICCAI, and formerly was a member of the Student Board and the Educational Initiative at MICCAI.

Title: Complementing Surgeons with Situation Awareness using Computer Vision.

Abstract: Surgical robotic tools and digitally enhanced operating theaters have been giving surgeons a helping hand for years. While they provide great control, precision, and flexibility to the surgeons, they don’t yet address the cognitive assistance needs in the operating theater. We are on the verge of a new wave of innovations in artificial intelligence-powered surgical theater technologies, and surgery is increasingly becoming data-driven. We believe that situation awareness is a key step towards automation in surgery, and we envision situation-aware operating theater technologies that are able to use data to perceive their environment, comprehend ongoing activities and processes, project outcomes of a number of possible actions, and complement the surgical team by providing real-time guidance during complex tasks and unexpected events. The recent advances in computer vision and machine learning, combined with surgical knowledge representation can answer these needs. In this talk, we will explore how we can reduce the problem of situation awareness in the operating theater to a set of computer vision and machine learning problems.

Speaker 3: Saul Castañeda Lizarraga (School of Mechanical Engineering, University of Leeds).

Title: Wire embedding tool for mechatronic devices fabrication in multi axis additive manufacture system

Abstract: The layer-by-layer building process defines the additive manufacturing technologies. This type of building has brought new ways of designing passive structures that are used as cases, shells, or structural parts that are used as the main body or assembled with other structural parts.

With a modification in that building process, the layer by layer structure can be use to embed electronic components and/or PCBs (Printed Circuit Boards) to the printed part. The work on embedding electronics will allow the additive manufacturing process to be considered in the industry as the main production process for complex builds with the integration of another manufacturing process in the same system.

The principal aim of this work is to test and demonstrated the use of different manufacturing processes to build functional devices within the same additive manufacturing process and the same multifunctional system. Showing suitable approaches for interconnecting embedded electronic components. These approaches will eventually be integrated into our Additive Robot Manufacturing System (ARMS) and demonstrated in a single complex process.