EarSwitch: From Dream to Hypothesis; Boot-strapping to Production
Dr. Nick Gompertz
EarSwitch® Ltd was founded by Dr Nick Gompertz (a UK NHS doctor of 30 years), to improve the lives of people who are non-verbal, or “locked in” due to severe neuro-disabilities.
The concept was conceived whilst a medical student for people with MND/ALS. However, Nick did not achieve this until 30 years later, after he watched a children’s TV documentary about an inspirational boy with severe cerebral palsy. Jonathan Bryan at age 13, despite being non-verbal, had written a book by simply gazing at letters stuck on a board, whilst his mother watched on and wrote down the letters he looked at.
Nick will discuss the journey from concept to product, including the current and future potential of EarSwitch technologies; to improve peoples lives ranging from general consumer applications, to accessibility control, and also racially inclusive medical grade real-world data.
Dr Nick Gompertz
(a UK NHS doctor of 30 years) founded EarSwitch® Ltd
to improve the lives of people who are non-verbal, or “locked in” due to severe neuro-disabilities. Having proven the concept of the EarSwitch® for hands-free control from voluntary eardrum movement, Nick realised the unique characteristics of the ear for racially inclusive core biometric monitoring (EarMetrics®), and for complex control (EarControl™). Nick is driven to improve people's lives through ubiquitous sensing from earables and hearing aids, ranging from general consumer applications to accessibility control, and also racially inclusive medical grade real-world data..
OmniBuds: Your Music, Your Health, Your AI Companion
Dr. Alessandro Montanari
Imagine earables that effortlessly monitor vital signs while listening to music; recognise activities and contexts you are immersed in; all with advanced on-device AI features at your fingertips. These are OmniBuds.
is a principal research scientist in the Pervasive Systems Department at Nokia Bell Labs, leading the Device Forms team. He works on the architectural and algorithmic challenges of building the next-generation wearable systems for human sensing, exploiting ultra-low-power machine learning and advanced signal processing.