Faculty: The Florey/Faculty of Medicine and Health Sciences
Members: Giancarlo Alloca, Sherie Ma, Karen Sitte, Andrew Gundlach, Hong Nguyen
Somnivore is a machine learning based platform engineered to accelerate sleep science, from data acquisition to sleep scoring and end-points analysis. We are addressing several problems afflicting the field, from speed, accuracy and user-friendliness. Our current target market is sleep researchers, with the future option of extending support towards clinicians and eventually the consumer market.
Somnivore is software that uses machine learning for fast and accurate analysis and scoring of sleep data. It surpasses current manual scoring methods, which are time-consuming and time-inefficient, and current automated methods, which are inflexible and inaccurate. This platform provides users with full control over the scoring and review of data via a user-friendly interface. Our initial target market is sleep researchers, followed by clinicians and human diagnostic sleep laboratories, and eventually the consumer market.