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Multi-Disciplinary Design Methodology for the Development of Product , Process , and Research Innovation
COMMON ENGINEERING
Dr Issac Lim Sing Sheng Lecturer PhD Mechanical Engineering
Research expertise : Product design , ecoefficiency , innovation , patent circumnavigation , creative pedagogy , entrepreneurship , TRIZ
E : lim . sing . sheng @ monash . edu T : + 603 5514 9659
The design stage in the product development process has the single largest effect on any product ’ s overall impact on the environment . Product designers need to be assisted with design support that will enable them to improve the eco-innovation of their design . Current design supports for eco-innovation focus on setting design targets but lacks in helping designers to develop actual design solutions .
To address this , a TRIZ-based design methodology was developed . The TRIZEE design methodology was found to be usable by even designers with minimal design experience , applicable in improving the ecoinnovation of a diverse range of products , and effective for actual product development .
Continuous improvement of the methodology is ongoing through the integration of diverse design tools , patent analysis as well as learnings from its application in industry and research case studies .
Digital Signal Processing : Smart Healthcare
Dr Khong , Wei Leong Lecturer PhD Electrical and Electronics Engineering
Research expertise : Image and Signal Processing , Health Sciences , Machine Learning
E : khong . weileong @ monash . edu T : + 603 5515 9707
Smart healthcare is a new form of healthcare system that establishes better diagnostic tools and devices for improving the quality of life . To date , there are many health care devices that have been developed for measuring vital signs but most of them are of single subject assessment with limited parameter measurements , and inconvenient for continuous measurements monitoring due to their contact basis . Furthermore , the bulky size and pricey equipment might also be the barrier which hinder users from frequently monitoring their health status .
As an alternative approach , this research aims to extract the vital signs through video image processing techniques using an ordinary RGB camera . Digital signal processing is applied to remove unwanted noises to extract a clean bio-signal . This research is very beneficial in simultaneously extracting multiple vital signs and promises high potential due to its non-contact basis , harmless and suitability for continuous monitoring . Besides , developing the techniques as a smartphone app would make it more convenient to operate and economical .
The iterative innovation process using the TRIZEE design methodology
Figure depicts the blind source separation method for reducing motion artefacts from the video signals
Figure shows the native app used for processing video images
R E S E A R C H E R P R O F I L E 2022 / 2023