Maryland undergrads win NIH award for early Alzheimer’s diagnosis tool

A team of undergraduate students at the University of Maryland won the top prize in the NIH Design by Biomedical Undergraduate Teams challenge for their development of low-cost tools to diagnosis Alzheimer’s disease before symptom presentation.

The team, referred to as Synapto, included David Boegner, Megha Guggari, Chris Look, Anoop Patel and Dhruv Patel of the University of Maryland Department of Engineering, and Megan Forte and Brianna Sheard of the university’s Department of Chemical and Biomolecular Engineering.

“This represents a monumental achievement, not simply for the engineering community, but for the wider world of human health research,” Darryll J. Pines, PhD, dean of the University of Maryland A. James Clark School of Engineering, said in a press release. “As rising sophomores, these seven students in many ways represent the future of biomedical innovation. Through collaborations with faculty and researchers across a range of disciplines, they have transformed ideas into innovation that could one day change how Alzheimer's and other diseases are diagnosed.”

Synapto received $20,000 from the NIH’s National Institute of Biomedical Imaging and Bioengineering for developing a portable electroencephalogram (EEG) that utilizes a special headset and new software analysis tool to identify Alzheimer’s disease before an individual exhibits clinical symptoms.

The device analyzes changes in brainwaves in response to special auditory tones.

“It can take up to 2 years after clinical symptoms arise for patients to receive a proper diagnosis, and by then, he or she may have already seen significant progression of the disease,” Dhruv Patel, team captain of Synapto, said in the release. “To address this, our technique allows us to characterize an Alzheimer's patient's brainwave using a variety of mathematical analytical tools and compare it with a healthy patient's brainwave to create a machine-learning model that can then accurately predict the probability of the patient having the disease.”

The NIH challenge awarded $65,000 in prizes and received 41 eligible entries from 22 universities across 16 U.S. states. The National Institute of Biomedical Imaging and Bioengineering chose three winning teams; judging on the addressed problem significance, impact on clinical care, design innovation, and evidence of a working prototype.

“Alzheimer's disease is the sixth leading cause of death in the United States, costing the nation close to $259 billion this year,” Patel said in the release. “Diagnosing the disease early on allows patients to open up treatment options, manage the disease properly, and slow its progression.”

All challenge winners will be recognized at the annual Biomedical Engineering Society conference in Phoenix on October 12.

A team of undergraduate students at the University of Maryland won the top prize in the NIH Design by Biomedical Undergraduate Teams challenge for their development of low-cost tools to diagnosis Alzheimer’s disease before symptom presentation.

The team, referred to as Synapto, included David Boegner, Megha Guggari, Chris Look, Anoop Patel and Dhruv Patel of the University of Maryland Department of Engineering, and Megan Forte and Brianna Sheard of the university’s Department of Chemical and Biomolecular Engineering.

“This represents a monumental achievement, not simply for the engineering community, but for the wider world of human health research,” Darryll J. Pines, PhD, dean of the University of Maryland A. James Clark School of Engineering, said in a press release. “As rising sophomores, these seven students in many ways represent the future of biomedical innovation. Through collaborations with faculty and researchers across a range of disciplines, they have transformed ideas into innovation that could one day change how Alzheimer's and other diseases are diagnosed.”

Synapto received $20,000 from the NIH’s National Institute of Biomedical Imaging and Bioengineering for developing a portable electroencephalogram (EEG) that utilizes a special headset and new software analysis tool to identify Alzheimer’s disease before an individual exhibits clinical symptoms.

The device analyzes changes in brainwaves in response to special auditory tones.

“It can take up to 2 years after clinical symptoms arise for patients to receive a proper diagnosis, and by then, he or she may have already seen significant progression of the disease,” Dhruv Patel, team captain of Synapto, said in the release. “To address this, our technique allows us to characterize an Alzheimer's patient's brainwave using a variety of mathematical analytical tools and compare it with a healthy patient's brainwave to create a machine-learning model that can then accurately predict the probability of the patient having the disease.”

The NIH challenge awarded $65,000 in prizes and received 41 eligible entries from 22 universities across 16 U.S. states. The National Institute of Biomedical Imaging and Bioengineering chose three winning teams; judging on the addressed problem significance, impact on clinical care, design innovation, and evidence of a working prototype.

“Alzheimer's disease is the sixth leading cause of death in the United States, costing the nation close to $259 billion this year,” Patel said in the release. “Diagnosing the disease early on allows patients to open up treatment options, manage the disease properly, and slow its progression.”

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All challenge winners will be recognized at the annual Biomedical Engineering Society conference in Phoenix on October 12.