Canterbury student to present brain research in Italy

Canterbury student to present brain research in Italy

A University of Canterbury (UC) PhD student will present world-leading research in lapse/microsleep detection at an international conference in Italy this month. This research using advanced signal processing and artificial intelligence has the potential to save lives.

Sudhanshu Ayyagari, a PhD student in the Neural Engineering Research Group in UC’s Department of Electrical and Computer Engineering, is trialling a new technology that uses a passive brain-computer interface device named Elapse to acquire real-time electroencephalographic (EEG) signals from the brain to detect precursory cues to allow detection and prediction of the occurrence of microsleeps in real time.

Microsleeps are brief involuntary lapses of responsiveness. They usually last just a few seconds, but can have life-threatening consequences.

“Long-haul truck drivers, train drivers and airline pilots routinely experience monotonous, extended driving periods in a sedentary position. This can result in drowsiness, lapses in responsiveness and serious accidents. A complete loss of attention, even for a few seconds, while engaged in a critical task such as driving a vehicle can result in minor injuries or multiple fatalities,” says Sudhanshu.

A microsleep that occurs while driving can have fatal results due to the speed of the vehicle and the distance travelled while out of control of the driver. For example, if a person is driving at a speed of 100 km/h and has a microsleep lasting four seconds, the vehicle will travel 111 metres while completely out of the control of the driver.

Sudhanshu says the research enables a new type of system comprising multiple modules not previously available on any brain computer interface (BCI) devices. The current Elapse configuration has been developed to provide a common hardware and software platform to aid research in the fields of cognitive monitoring, particularly microsleep detection.

The Elapse system uses novel machine learning algorithms to maximally acquire new cues for detecting microsleeps from deep neuro-electric activity in the brain and changes in neural connectivity.

“Machine learning enables computer systems to adaptively improve their performance with experience accumulated from observed data. To some extent, anyone using a smartphone is already using some sort of machine intelligence with Apple’s Siri or Google Map’s determination of what counts as your ‘home’ and ‘work’, or Windows Phone’s Cortana,” says Sudhanshu.

Although the focus of his research is on detecting/predicting microsleeps, elements of Sudhanshu’s research may be useful offshoots in other biomedical fields or BCI applications, such as emotion detection, mental workload estimation, sleep apnoea detection, epileptic seizure detection, systems capable of robotics applications, and even robotic mind-control interfaces.

Originally from India, Sudhanshu was drawn to study at UC because of the unique work underway in the Christchurch Neurotechnology Research Program (NeuroTech) – a collaboration between UC’s Department of Electrical and Computer Engineering, the University of Otago, and the New Zealand Brain Research Institute. NeuroTech is a world leader in lapse research. Dr Steve Weddell and Professor Richard Jones (Neurotech’s Director) are supervising Sudhanshu’s project and will also be at the conference.

The 37th International Conference of the IEEE Engineering in Medicine and Biology Conference will be in Milan, Italy, from 25-29 August. Attracting approximately 2,500 attendees from around the world, the conference covers all areas within biomedical engineering and healthcare. The Institute of Electrical and Electronics Engineers (IEEE) is the world’s largest professional organisation for the advancement of technology.

ENDS

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