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Dr Adrian Pranata

Adjunct Research Fellow


Dr Adrian Pranata is Adjunct Research Fellow at Swinburne University of Technology. He is also an Adjunct Senior Research Fellow at Shanghai University of Sports, China. He has a Bachelor of Physiotherapy, Master of Physiotherapy (Musculoskeletal) and PhD. His inter-disciplinary research aims to improve the quality and specificity of assessment and management of chronic musculoskeletal conditions – in particular, low back pain, using novel technologies such as artificial intelligence, robotics and biomechanical modelling.

Adrian is a reviewer for scientific journals including PLoS ONE, Journal of Biomechanics, Clinical Biomechanics and Musculoskeletal Science and Practice. Adrian is also the immediate past-Chair of the Musculoskeletal Physiotherapy Australia (MPA) Victoria and is still active within the Australian Physiotherapy Association committees.

Research interests

Biomedical science; Health Promotion; Health Technology Assessment; Low back pain; Physiotherapy; Exercise; Biomechanics

PhD candidate and honours supervision

Higher degrees by research

Accredited to supervise Masters & Doctoral students as Principal Supervisor.

PhD topics and outlines

Assessment of brain and muscle function during lifting in people with low back pain: This project aims to investigate the use of electromyography and electroencephalography in the assessment of lifting tasks in people with low back pain.

Automation of lumbar muscle ultrasonography using collaborative robots: This project aims to develop and validate the use of collaborative robots in the assessment of lumbar muscle architecture in people with low back pain.

Development of a novel exoskeleton to aid lifting in people with low back pain: This project aims to design and build a novel hydraulic exoskeleton to modify lifting biomechanics in people with low back pain.

Novel assessment of voluntary postural control in people with low back pain: This research project aims to investigate lower limb postural control during a voluntary task using novel technology.

The use of machine learning for lifting assessment in people with low back pain: This project aims to investigate the development and validation of novel machine learning algorithms to predict trunk, hip and knee movements during lifting in people with low back pain.


Available to supervise honours students.

Fields of Research

  • Other Health Sciences - 429900
  • Physiotherapy - 420106
  • Rehabilitation - 420109

Teaching areas

Health Technology Assessment;Sport Science;Physiotherapy;Biomechanics


Also published as: Pranata, Adrian; Pranata, A.
This publication listing is provided by Swinburne Research Bank. If you are the owner of this profile, you can update your publications using our online form.

Recent research grants awarded

  • 2021: Development of a web-based repository system for monitoring of community fitness and muscle strength *; South Yarra Spine & Sports Medicine
  • 2018: A Collaborative Robot System for Photobiomodulation Therapy of Chronic Pain *; IRRobotics_PT
  • 2018: Developing and using VR, AR or Mixed reality for the management of chronic pain *; Medibank Private Limited Fund Scheme

* Chief Investigator