Available Technologies
# of Displayed Technologies: 6 / 6
Applied Category Filter (Click To Remove): Ear, Nose, & Throat/ENT
Convolutional Neural Network to Assess Phayngeal and Laryngeal Pathology and Function on Nasopharyngolaryngoscopy
TS-063154 — Worldwide, 686,000 new head and neck (H&N) cancers are diagnosed yearly, and 375,000 people will die annually. Human papillomavirus (HPV) is responsible for an increasing subset of H&N malignancies called oropharyngeal squamous cell carcinomas (OPSCC). Although it has a better prognosis than…
- College: College of Engineering (COE)
- Inventors: Krening, Samantha; Gifford, Ryan; Jhawar, Sachin; VanKoevering, Kyle
- Licensing Officer: Hampton, Andrew
3D Clinical Image-based Pre-surgical planning Tool
TS-053757 —
Modernity has brought with it increased complexity in many areas of our lives, an important one being the healthcare industry. Surgical procedures require increased precision while employing intricate methods. With approximately 20 million surgeries performed each year in the United States alone, …
- College: College of Medicine (COM)
- Inventors: Powell, Kimerly; Adunka, Oliver; Hittle, Bradley; Keith, Jason; Kerwin, Thomas "Thomas"; Stredney, Donald; Wiet, Gregory
- Licensing Officer: Randhawa, Davinder
Mini-PCDH15 for treatment of deafness
TS-050433 — A gene therapy solution for Usher Syndrome Type 1F.
Mutations in PCDH15 cause Usher 1F, a recessive syndrome characterized by profound congenital deafness and absence of vestibular function, and progressive blindness beginning in the second decade. Because patients who lack hearing and balance rely on vision for communication and mobility, the late…
- College: College of Arts & Sciences
- Inventors: Sotomayor, Marcos
- Licensing Officer: Dahlman, Jason "Jay"
Machine-Learning Algorithm for Improved Speech Intelligibility in Noise
TS-042266 — A monaural machine-learning algorithm for classifying time-frequency units in an unknown signal, which results in marked speech-intelligibly improvements in noisy signals.
A primary complaint of hearing-impaired (HI) listeners is poor speech recognition in background noise. This issue can be quite debilitating and persists despite considerable efforts to improve hearing technology. Despite considerable effort, monaural (single-microphone) algorithms capable of incre…
- College: College of Arts & Sciences
- Inventors: Healy, Eric; Vasko, Jordan
- Licensing Officer: Dahlman, Jason "Jay"
Machine-Learning Algorithm for Improved Speech Intelligibility in Noise
TS-038074 — A monaural machine-learning algorithm for classifying time-frequency units in an unknown signal, which results in marked speech-intelligibly improvements in noisy signals.
Wireless carriers receive daily complaints about poor speech recognition in background noise during calls and are constantly looking for methods to improve especially in light of recent forays into VOIP. The ability to discriminate between speech and noise in an audio signal then is an extremely i…
- College: College of Arts & Sciences
- Inventors: Healy, Eric; Vasko, Jordan
- Licensing Officer: Dahlman, Jason "Jay"
Multi-carrier processing in auditory prosthetic devices
TS-014871 — Encoding strategy for improvement of speech understanding in a noisy environment for audiotory prosthetic devices.
There are about 275 million adults globally with moderate to severe hearing loss and 360 million adults with mild hearing loss. The current solutions to allow these people to hear better include hearing aids, hearing loss counseling, cochlear implants, alerting devices, and other communication aid…
- College: College of Arts & Sciences
- Inventors: Apoux, Frederic; Healy, Eric
- Licensing Officer: Dahlman, Jason "Jay"
