Innovation Design Engineering (MA/MSc)
Isaac Huang is a Taiwanese designer with backgrounds in industrial design and computer science. He is interested in technology and likes to bring innovative ideas into lives. He doesn’t really like rules and doesn’t mind breaking them if necessary.
Before studying Innovation Design Engineering. He and his partner got funding from the Taiwan Ministry of Culture and founded a company. It is committed to original design and illustrated goods.
Olfaction is one of the most primitive senses in organisms. It allows us to distinguish a rotten egg from fresh ones and notices something is burning in a distance. About 3% of our genes dedicated to olfaction, which is second only to the ones for the immune system. These facts show how important our sense of smell is. However, what really makes olfaction so different from other senses is the connection between the olfactory bulb and the amygdala. It allows olfactory stimuli to trigger emotions and memories directly and be possible for the treatment of psychological problems.
In the UK, two-thirds of adults have suffered mental health problems. Mental illness can not only debilitate people’s physical health but also cause tremendous economic loss. Recently, more and more research has shown that people who constantly use a computer can develop stress, depression and other mental disorders. However, nowadays, many British people spend more than 6 hours per day on their computers.
What if computers could predict users’ upcoming emotions, then benefit users through olfactory ways?
o-assist is a personal olfactory assistant and mood improver designed for computer users. Based on experiments, I found that some events on computers usually result in negative moods and the way people use computers reveals their upcoming emotions. In addition, research has proven that some scents are helpful to improve people’s negative emotions So o-assist analyses users’ behavior base on the data collected from users’ different applications and the I/O devices. After the data is fed in, o-assist runs its algorithm and forecasts users’ moods, then releases specific smells to improve them at particular moments.
For instance, many different emotions can be easily aroused when people get various notifications on computers like emails and chat messages. According to some keywords in these, o-assist forecast what kinds of emotions that the users are going to experience, then release corresponding scents to improve these experiences.
Data from the I/O devices allows o-assist to provide a better experience. For example, teleconferencing usually makes people nervous. By the signal from the user’s microphone, o-assist detects when the user talks in a meeting, then giving off a kind of lavender smell to calm the user’s nerves at a specified time.
The ability of forecasting makes o-assist so unique compared to other olfactory products in the market. It also reveals the potential that machines might take care of human mental health actively in the future.
How it works
06.Settings - o-assist predict users’ upcoming emotions base on the data collected from users’ different applications and the I/O devices. So users can set up what application they like to get data from. In other words, whether users need olfactory helps when using them or not.
08. Feedback - Like other machine learning algorithms, users’ feedback helps o-assist to make more precise predictions. Users can check recent olfactory activities of o-assist then give feedback to each activity to enhance its’ performance.