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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

  1. Liquid cooled viscoelastic actuation for robust legged robot locomotion

    SBC: Apptronik, Inc.            Topic: H601

    Apptronik Systems in cooperation with the University of Texass Human Centered Robotics Lab (HCRL), Carnegie Mellon Universitys Robotics Institute and Italys National Research Institute (CNR), will collaborate to develop a new type of exoskeleton that is founded upon Apptroniks Visco-Elastic Liquid Cooled Actuator (VLCA). The fundamental goal of this program is the development of a powered exoskel ...

    STTR Phase II 2017 Department of DefenseSpecial Operations Command
  2. Upper Body Addendum to Proposal S2-0328

    SBC: Apptronik, Inc.            Topic: H601

    This is an Addendum to previously submitted proposal that includes the addition of a powered upper body portion of an exoskeleton. In this addendum we propose the additional requirements of researching, fabricating and integrating a powered upper body to the previously outlined lower body. These two systems together will comprise the entire exoskeleton proposed by the contractor. Through this ...

    STTR Phase II 2017 Department of DefenseSpecial Operations Command
  3. Liquid-cooled actuation to achieve greater degrees of freedom and range of motion in untethered exoskeletons

    SBC: Apptronik, Inc.            Topic: H6018135

    Apptronik Systems Inc., in cooperation with the University of Texas Human Centered Robotics Lab (HCRL) and Huston-Tillotson University Robotics Lab (a historically black college and university HBCU), endeavor to advance the movement capabilities and modularity of the exoskeleton being developed under contract #H92222-17-C-0050. The primary goal of this program is to optimize the range of movement ...

    STTR Phase II 2017 Department of DefenseSpecial Operations Command
  4. Passive Pneumatic Prosthetic Ankle with Biomimetic Response

    SBC: ADA Technologies, Inc.            Topic: DHP16C007

    The Defense Health Program seeks to improve the lives of service members suffering below knee amputations through the development of a non-powered lower extremity prosthesis designed to restore range of motion and power generation to that of an uninjured anatomical ankle. Current passive systems are still in early stages of development and typically only address one aspect of what the Defense Heal ...

    STTR Phase I 2017 Department of DefenseDefense Health Agency
  5. Advanced Morphing Moulage for Medical Training (AMM-MT)

    SBC: Vcom3D, Inc.            Topic: DHA17A002

    For this Phase I SBIR proposal, Vcom3D proposes to design advanced medical moulage that accurately simulates the progression of an injury or pathology by morphing through a series of clinical states to enable learners to confirm the progression of the wound and to determine whether iatrogenic errors or pathologies occurred duing treatment. The physical morphing moulage may be applied to medical m ...

    STTR Phase I 2017 Department of DefenseDefense Health Agency
  6. Dynamic virtual moulage based on thin film adhesive displays

    SBC: ARCHIE MD INC.            Topic: DHA17A002

    Providing Army combat medics with meaningful experience in treatment of battlefield injuries is a particular challenge. Moulage has the potential to assist in acquiring what could otherwise be very hard-to-come-by preparatory experience for the distressing real-life emergencies medics and soldiers may encounter in the field. However, current approaches to moulage are limited in their ability to re ...

    STTR Phase I 2017 Department of DefenseDefense Health Agency
  7. Principled Design of an Augmented Reality Trainer for Medics

    SBC: Unveil LLC            Topic: DHA17A003

    Recent advances in augmented reality (AR) offer valuable opportunities for simulationbased training outside of a medical simulator facility. The potential benefits for combat casualty care training are particularly powerful, as over 100,000 U.S. military medical personnel must be prepared to quickly respond to a broad range of injuries at any point in time. We propose to develop and evaluate a hig ...

    STTR Phase I 2017 Department of DefenseDefense Health Agency
  8. Principled Design of an Augmented Reality Trainer for Medics

    SBC: Design Interactive, Inc            Topic: DHA17A003

    Design Interactive Inc. (DI) and Eastern Virginia Medical School (EVMS) propose to develop an Augmented reality Learning Environment for Refresher Training (ALERT) that provides realistic and relevant Tactical Combat Casualty Care (TC3) scenarios using AR technologies integrated with mannequins for pre-deployment training and humans for deployed training environments. ALERT will facilitate learnin ...

    STTR Phase I 2017 Department of DefenseDefense Health Agency
  9. Non-invasive Telemetric Assessment of Gut Microbiota Activity in Situ

    SBC: NANOHMICS INC            Topic: DHA17A004

    Physical, mental, and environmental stress, as well as diet and hydration have an impact on overall health, performance, and well-being of humans. These factors all affect the composition and metabolism of the microbiota in the gastrointestinal (GI) tract. The mix of microorganisms in the gut, and their metabolic transformation of food, can alter the overall health and physiology of the host. Me ...

    STTR Phase I 2017 Department of DefenseDefense Health Agency
  10. Medical Device to Assess the Viability of Tissue Prior to Skin Grafting

    SBC: Spectral Md, Inc.            Topic: DHA17A006

    The primary objective of this proposal is to design and demonstrate the SpectralMD DeepView imaging technology can allow surgeons to quickly and objectively assess the viability of tissue in a burn excision site prior to skin grafting. DeepView uses machine learning algorithms to analyze data acquired by multispectral imaging to generate quantitative prognostic images with a user-friendly output t ...

    STTR Phase I 2017 Department of DefenseDefense Health Agency
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