- k ajay kumar reddy ,hemanth d
Brain-based automation and control have been the latest trend in these recent days, as older and disabled population grows, their living independence has become an important social issue and research challenge. To deal with this issue, researchers have developed various assistive robots to assist these individuals in professional and daily life. These older and disabled people can use some special interfaces (e.g., speech and sip-and-puff interfaces) to control assistive robots. Since brain-computer interfaces (BCIs) do not require users to have speech and neuromuscular control capabilities, BCIs have become important interfaces and can work for some severely disabled people with illnesses, such as amyotrophic lateral sclerosis. BCIs rely on translating different brain activities into commands. These brain activities can be recorded with various methods (e.g., magnetoencephalography,near-infrared spectroscopy, electroencephalography (EEG), and functional magnetic resonance imaging). Since EEG is easier to be used and cheaper than other recording methods, EEG signals have been widely applied to develop various BCI systems.
Auto-mobile companies will be the major target for this product.
The person interviewed is an automobile engineer and an alumnus of amrita.
me: good morning sir,
engineer: hello , good morning.
me: we came up with a proposal for cisco thingqubator cohort III
me: so, our idea is " brain-controlled automatic Braking system". what do you say?
engineer: well, seems interesting, it would be great if you deploy the product there are many situations where we even think that this would be implementable but it has always occupied the seat of research
me: do you know anyone who did this ?
engineer: research is going in a few companies have had some demo but it's not truly good and productive
me: examples and experiences on this?
engineer: personally i have not worked anything with the software in the automobile but this will have a future and that's what I feel.
me: what would you say on the idea?
engineer: idea is good, try pitching it to the judges, this has scope and future is completely automated and you will find a wonderful experience in making this product
we propose a new approach of detecting emergency braking intention for brain-controlled vehicles by interpreting electroencephalography (EEG) signals of drivers. Regularization linear discriminant analysis with spatial-frequency features is applied to build the detection model. These spatial-frequency features are selected from the powers of frequency points across sixteen channels by using the sequential forward ﬂoating search. Experimental results from twelve subjects show that on average, the proposed method can detect emergency braking intentions 420 ms after the onset of emergency situations with the system accuracy of over 94%, showing the feasibility of developing a practical system of detecting driver emergency braking intention with the power spectra of EEG signals for brain-controlled vehicles. The majority of accidents can be reduced if we implement this.