SBIR-STTR Award

Open Call for Robotics, 3D Printing, Autonomous Systems, and Other Immersive Training Solutions with Defense-Related Dual-Purpose Technologies/Solutions with a Clear Air Force Stakeholder Need
Award last edited on: 2/8/2021

Sponsored Program
SBIR
Awarding Agency
DOD : AF
Total Award Amount
$75,000
Award Phase
1
Solicitation Topic Code
AF191-004
Principal Investigator
Dan Vanwinkle

Company Information

Ascend Innovations Inc

241 Taylor Street
Dayton, OH 45459
   (937) 228-6011
   hello@ascend-innovations.com
   www.ascend-innovations.com
Location: Single
Congr. District: 10
County: Montgomery

Phase I

Contract Number: FA3002-19-P-A116
Start Date: 3/6/2019    Completed: 3/6/2020
Phase I year
2019
Phase I Amount
$75,000
The BATDOK Training Platform is a comprehensive mobile tool for training military medical personnel to more efficiently provide end-to-end patient documentation and care from point-of-injury through hand-off at the hospital. BATDOK integrates six vital functionalities (Assess, Document, Collaborate, Reference, Coordinate, Transfer) to enhance training of medical personnel. Current training techniques are inefficient in both resource allocation and for providing prioritized situational awareness to medical providers on the care continuum. Integrating a BATDOK application that can simulate sensor input data enables trainees to be exposed to a variety of patient encounters and will more closely align training with real life experiences. The application can incorporate real or simulated information from various sensors that are widely available and appropriate for field use. Sensor data is securely transmitted to the medic's mobile device for vital signs. Physiological monitoring data can be further transmitted for remote monitoring through the device or tactical radio network to health care providers and training participants. BATDOK can be designed with a training interface to track and analyze trainee response and performance, comparing trainee decisions to real life treatments and outcomes for each patient. Training data can then be analyzed to look for individual or aggregate level optimizations.

Phase II

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Start Date: 00/00/00    Completed: 00/00/00
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