Publication number: 20240075895
Abstract: Embodiments are disclosed for crash detection on one or more mobile devices (e.g., smartwatch and/or smartphone). In some embodiments, a method comprises: detecting, with at least one processor, a crash event on a crash device; extracting, with the at least one processor, multimodal features from sensor data generated by multiple sensing modalities of the crash device; computing, with the at least one processor, a plurality of crash decisions based on a plurality of machine learning models applied to the multimodal features; and determining, with the at least one processor, that a severe vehicle crash has occurred involving the crash device based on the plurality of crash decisions and a severity model.
Type:
Application
Filed:
September 6, 2023
Publication date:
March 7, 2024
Inventors:
Vinay R. Majjigi, Sriram Venkateswaran, Aniket Aranake, Tejal Bhamre, Alexandru Popovici, Parisa Dehleh Hossein Zadeh, Yann Jerome Julien Renard, Yi Wen Liao, Stephen P. Jackson, Rebecca L. Clarkson, Henry Choi, Paul D. Bryan, Mrinal Agarwal, Ethan Goolish, Richard G. Liu, Omar Aziz, Alvaro J. Melendez Hasbun, David Ojeda Avellaneda, Sunny Kai Pang Chow, Pedro O. Varangot, Tianye Sun, Karthik Jayaraman Raghuram, Hung A. Pham
Publication number: 20240071593
Abstract: Systems and methods are disclosed that provide smart alerts to users, e.g., alerts to users about diabetic states that are only provided when it makes sense to do so, e.g., when the system can predict or estimate that the user is not already cognitively aware of their current condition, e.g., particularly where the current condition is a diabetic state warranting attention. In this way, the alert or alarm is personalized and made particularly effective for that user. Such systems and methods still alert the user when action is necessary, e.g., a bolus or temporary basal rate change, or provide a response to a missed bolus or a need for correction, but do not alert when action is unnecessary, e.g., if the user is already estimated or predicted to be cognitively aware of the diabetic state warranting attention, or if corrective action was already taken.
Type:
Application
Filed:
October 24, 2023
Publication date:
February 29, 2024
Inventors:
Anna Leigh DAVIS, Scott M. BELLIVEAU, Naresh C. BHAVARAJU, Leif N. BOWMAN, Rita M. CASTILLO, Alexandra Elena CONSTANTIN, Rian W. DRAEGER, Laura J. DUNN, Gary Brian GABLE, Arturo GARCIA, Thomas HALL, Hari HAMPAPURAM, Christopher Robert HANNEMANN, Anna Claire HARLEY-TROCHIMCZYK, Nathaniel David HEINTZMAN, Andrea Jean JACKSON, Lauren Hruby JEPSON, Apurv Ullas KAMATH, Katherine Yerre KOEHLER, Aditya Sagar MANDAPAKA, Samuel Jere MARSH, Gary A. MORRIS, Subrai Girish PAI, Andrew Attila PAL, Nicholas POLYTARIDIS, Philip Thomas PUPA, Eli REIHMAN, Ashley Anne RINDFLEISCH, Sofie Wells SCHUNK, Peter C. SIMPSON, Daniel S. SMITH, Stephen J. VANSLYKE, Matthew T. VOGEL, Tomas C. WALKER, Benjamin Elrod WEST, Atiim Joseph WILEY