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Students Win Prize, Start Company for Alzheimer’s Detection

Synapto device prototype

Synapto device prototype (University of Maryland)

29 August 2017. A team of undergraduate students won first prize in a National Institutes of Health biomedical engineering contest for a headset device to diagnose early-stage Alzheimer’s disease. The engineering students at University of Maryland in College Park, who received notice of the award on Friday, are also starting a company to take their invention to market.

The team led by Dhruv Patel designed the device to provide a less-expensive and easier-to-use technology to diagnose Alzheimer’s disease in its earliest stages, before symptoms appear. Alzheimer’s disease is a progressive neurodegenerative condition affecting growing numbers of older people worldwide. The disease affects the neurons or nerve cells in the brain that become damaged, lose their connections, and stop functioning, with the function loss extending to memory, language, reasoning, and social behavior.

Today’s techniques for detecting Alzheimer’s, say the students, involve complex imaging techniques such as PET and MRI scans, or invasive procedures like spinal taps. As a result, individuals usually wait until symptoms appear before getting a full diagnosis. “It can take up to two years after clinical symptoms arise for patients to receive a proper diagnosis,” says Patel in a university statement, “and by then, he or she may have already seen significant progression of the disease.”

The device designed by Patel and colleagues adapts electroencephalogram, or EEG, technology configured on a frame and worn on the head. EEG devices measure brain activity through electrodes, which detect electrical signals from the firing of neurons. In this case, the headset, fitted with electrodes, measures brain waves, looking particularly for signaling patterns characteristic of Alzheimer’s disease, in response to specific auditory tones.

In addition to the headset, the Synapto system includes software that analyzes the EEG signals, using mathematical tools. Patel says the signals then are compared to EEG patterns characteristic of healthy individuals, and added to machine-learning models to predict the probability of the individual developing Alzheimer’s disease.

The Synapto team entered a prototype of the invention in the 2017 Design by Biomedical Undergraduate Teams, or Debut, challenge sponsored by National Institute of Biomedical Imaging and Bioengineering, part of National Institutes of Health, and VentureWell, a not-for-profit organization that supports emerging entrepreneurs in science and technology. The Maryland team walked away with Debut’s first-prize, a cash award of $20,000.

In judging the entries, VentureWell put an emphasis on market potential and ability to patent the invention. These factors probably entered into the decision of Patel and fellow Maryland biomedical engineering student (and team member) Megha Guggari to found the recent start-up company Synapto LLC for commercializing the device. The team members expect the device’s simplicity and ease of use to encourage more routine testing for Alzheimer’s disease in regular physical check-ups.

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