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Professor Kang Lee of the University of Toronto’s Ontario Institute for Studies in Education (OISE) is a global leader in research that is changing the way we detect emotion and behavior such as lying.

Now, his startup is taking that research a step further.

Consumer-facing market research studies require a group of people, a product or service for them to experience, and methodology to collect and analyze their feedback. For companies requesting consumer insight to influence a product’s attributes, packaging or promotion, accurate information can make the difference between success and failure. 

The catch? The best market research exercises can’t consistently determine when people lie. Well-intentioned subjects may do so to please the interviewer, lie to omit inconsistent information or genuinely misjudge their deeper physiological and emotional responses. 

Thanks to the first commercial application for a new patent-pending process to reveal both visible and hidden facial emotions using blood-flow analysis, developed by Lee, market researchers and their clients are one step closer to acquiring more accurate, reliable data. 

Lee is a developmental neuroscientist who studies social cognition and behavior, their underlying cognitive-cultural-neural mechanisms, and the development of social perception, focusing on face processing and deception. His work was . On Feb. 18, 2016, Lee spoke at TED Vancouver about his research.

The invitation to TED’s global event came on the heels of his successful Tedx �鶹ֱ��app talk, “Little Liars: Insights from Children’s Lies.” 

“I’ve studied human face processing and deception for over two decades,” says Lee. “To facilitate this research, I worked with my postdoctoral fellow, Dr. Paul Zheng, to develop a new imaging technology that uses a conventional video camera to reveal facial blood flow changes when people are experiencing various hidden emotions, including emotions associated with lying. We call our technology Transdermal Optical Imaging. Although it was originally developed to study face processing and deception, this versatile technology has many, many business applications, including to marketing research.”

“We recommended that Dr. Lee target market researchers in his first commercial offering since accurately pinpointing customer preferences and the buy response is such an essential focus for the consumer electronics and food and beverage industries, among others,” says Joel Liederman, MaRS Innovation’s vice-president, Physical Sciences. “I’d like to recognize Shatha Qaqish from our team and Kurtis Scissons from the University of Toronto for their work in advancing this technology.”

When Lee disclosed his technology to the University of Toronto’s Innovations and Partnerships Office and MaRS Innovation, commercialization staff from both organizations met with him to understand the invention, develop a go-to-market plan, file patents in key markets, and helped to make introductions to experienced management and investors. 

One such introduction was to Marzio Pozzuoli, a Canadian technology entrepreneur. Impressed with the technology, Pozzoli partnered with Dr. Lee, MaRS Innovation and the University of Toronto to take the technology to market through NuraLogix™ Corporation. 

“I truly believe this company will usher in a new era in man-machine interaction,” says Pozzuoli, now CEO of NuraLogix. “In the very near future, our technology will enable machines to understand how humans are feeling more accurately than any human being can today.”

MaRS Innovation and �鶹ֱ��app staff also helped Lee to secure a $115,000 NSERC I2I grant to hire a developer and adapt his existing lab configuration for the technology – which was bulky and required an expensive camera, outside lighting and headset – to a more user-friendly laptop version. Doing so has increased the technology’s processing speed 90 per cent and reduced the time required for data analysis by a factor of three. 

NuraLogix has also completed two pilot studies in the food and beverages industry with an Ontario-based company that revealed complementary EQ intelligence to the traditional pen and paper questionnaire. In particular, the studies found inconsistencies in subject feedback and expressed opinions about such qualities as after tastes as compared to the data captured by Lee’s technology.