1215 BOULDER ST STE 101 BOULDER, CO 80302 Get Directions
1215 BOULDER ST STE 101 BOULDER, CO 80302 Get Directions
Hemorrhagic shock is a leading cause of death on the battlefield and in civilian trauma settings. There exist no published methods or products able to rapidly, accurately and non-invasively detect bleeding in human subjects. A device that quickly and reliably detects and estimates the level of blood loss, as well as predicts a patient's individual risk for cardiovascular collapse under varying physiological and environmental conditions, has significant impact opportunities. We have developed a machine learning framework for the real-time analysis of physiological data. This work is an outgrowth of our experience building an image-based robot navigation system under the DARPA-sponsored Learning Applied to Ground Robots (LAGR) program. Our LAGR robot's navigation system uses machine learning techniques to process > 100 million data points/second. This high speed data processing methodology enables our robot to learn sets of fast, efficient density based models in real-time, to navigate in unknown, outdoor unstructured environments. As the robot moves through its environment the navigation system chooses whether to apply current models, discard inappropriate models or acquire new one models, all without human intervention.
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