Universal retinal diagnostic system  – Medical and Health Robotics Group, QUT. (October 2014 – to date)

Vision: Enhance quality of life for all living with retinal disorders, through technology and person-focused innovation.

(a) human-centred collaborative design approach to improve retinal screening

(b) development of plenoptoscope (light field fundus camera-Provisional patent number : 2017901153 and  2018900513 ) and

(c) accurate automated diagnosis of retinal conditions using machine learning techniques

Robotic Knee Arthroscopy – Medical and Health Robotics Group, QUT. (October 2014 – to date)

Knee arthroscopy is a well-established, minimally invasive, diagnosis and treatment procedure of knee disorders and injuries. With the number of estimated worldwide cases exceeding 4 million each year, knee arthroscopy costs the healthcare system over 15 billion dollars annually. The procedure involves gaining access into the knee joint using sharp instruments to make ports/entry points. Through these points, the arthroscope is then inserted. Images from the arthroscopic camera are magnified and displayed on a monitor for the surgeons to view, examine and then rectify the damage using shaving or sharp instruments.

Despite its efficacy, there are reported complications that range from the minute to the more debilitating. The reasons behind these problems are multifactorial but can be grouped into operator inexperience, rigid anatomy, poor intra-articular vision and lack of a tissue demarcation between diseased and healthy tissue. However, we have a solution.

Our research is developing robotic knee arthroscopy techniques and devices to improve clinical outcomes for patients and reduce the cost of arthroscopy procedures and promoting a sustainable health care system. The aim is to develop techniques and systems to enable surgeons to routinely step out of the control loop of a number of surgical procedures and allow robots to carry out direct actions on patients. This will give the surgeon the role of supervisor rather than controller. Particularly, research will develop robotic vision systems that are capable of mapping knee joints in real-time via arthroscopically sourced video streams. The research will also explore control schemes that allow robots to hold and manipulate both the arthroscope and the surgical tools.

Improved healing in large segmental bone defects in small animals under the influence of BMP2 – Trauma Group, Institute of Health and Biomedical Innovation, QUT. (Feb 2014- Sept 2014)

Role of osteocytes (bone cell) in Osteoarthritis – Bone Group, Institute of Health and Biomedical Innovation, QUT. (October 2010 – Dec 2014)

TCam-2 cells as a viable in vitro model of testicular cancer – Department of Anatomy and Developmental Biology, Monash University, Monash Univerisy. (Aug 2008 – Feb 2010)