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SPIE, Edmund Optics Award Top Companies in Startup Challenge

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EMMETT WARREN, NEWS EDITOR
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Six new companies were awarded funding last week during the 10th annual Photonics West Startup Challenge event. Three top companies were selected by a panel of judges in the fields of health care and deep tech, with prizes of $2500, $5000, and $10,000 awarded for third, second, and first place, respectively. The first-place winner also received an additional check of $5000, presented by marketing director Scott Bass of Edmund Optics, whose company cosponsored the event with SPIE.

Winners pose for group photo on stage at 10th annual Photonics West Startup Challenge event. Courtesy of Photonics Media.

Winners pose for group photo on stage Feb. 5 at the 10th annual Photonics West Startup Challenge event. Courtesy of Photonics Media.

In the health care field, third place went to Eysz Inc., second place to Rubitection, and first place to Odin Technologies LLC for its wearable device known as Lumisense, an optics-based diagnostic device that assesses extremity hemodynamics and helps caregivers identify perfusion injuries and complications.

“We’re developing the next generation of wearable devices to help clinicians to identify nonobvious hemorrhage and compartment syndrome in trauma patients,” said Odin founder and CEO Steven Hansen. “Through early identification, Lumisense allows patients to get the treatment they need sooner, improving outcomes and reducing costs for hospitals.”

Rubitection took second place for its Rubitect Assessment System (RAS), an optical skin health and wellness tool for diagnosis and monitoring with an initial application for early pressure ulcer prevention. RAS uses applied reflectance spectroscopy to identify redness or changes in the coloration of the skin.

“RAS is a technology that’s addressing a global health care problem,” said Rubitection CEO Sanna Gaspard. “It can reliably measure the properties of the skin on all patients independent of skin color, and it can be used easily by an aide or skilled nurse.”

Eysz won third place for its development of Seizure Monitoring Software. Eysz founder and CEO Rachel Kuperman spoke of the importance accurate seizure detection.

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“Detecting and responding to seizures is critical to managing epilepsy,” Kuperman said. “Today, accurately detecting seizures outside of a hospital-based setting is like trying to diagnose a fever without a thermometer.” Kuperman said her company’s software will analyze passive eye movement data, including relative eye position and blink frequency, to measure seizures with loss of consciousness.

In the deep tech field, third place went to Circle Optics, second place went to Labby Inc., and first place went to Sensorics GmbH for its VIS/NIR spectroscopic sensor on chip level.

“Spectroscopy can easily provide reliable data to enable robust and fact-based decision making,” Sensorics CEO Ronny Timmrick said. “Our mission is creating the spectroscopic tools necessary to facilitate this process.” Timmrick credited the win to a combination of viable technology and a successful business model. He said his goal for his spectroscopic sensor is to see it implemented into smartphones to “give everyone the opportunity to measure things in their daily lives, ingredients in food and harmful substances” and other possible applications.

Labby took second place with its farm-efficient milk analyzer technology. “Current milk testing is costly and time consuming,” said founder and CEO Anshuman Das. “Our milk analyzer technology instantly provides quality data to farmers and informs them about individual and herd health. This crucial data lets them be proactive and take preventive measures to ensure maximum profitability.”

Third place went to Circle Optics for its 360° camera, Hydra. “The Hydra is setting a new standard for 360° content capture by making it as easy as a regular point-and-shoot camera,” Circle Optics director of operations Ian Gauger said. “Our breakthrough came from realizing polygonal fields of view — not just circular — are possible.”

“It’s inspiring to see people looking into the future with such ingenuity and vision,” said John Greivenkamp, president of SPIE.

Published: February 2020
Glossary
deep learning
Deep learning is a subset of machine learning that involves the use of artificial neural networks to model and solve complex problems. The term "deep" in deep learning refers to the use of deep neural networks, which are neural networks with multiple layers (deep architectures). These networks, often called deep neural networks or deep neural architectures, have the ability to automatically learn hierarchical representations of data. Key concepts and components of deep learning include: ...
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