Project Grant 2212935
- Lifespan Digital Health LLC was awarded a $255,409 Project Grant from the National Science Foundation under the NSF Technology, Innovation, and Partnerships program (CFDA 47.084) to develop bio-behavioral technology and provide mental health services. Specifically, the company will use predictive algorithms, wearable technology, and peripheral autonomic biofeedback to provide timely data and enable mental health professionals to treat students. This innovative approach aims to address the...
- This four-year $686,879 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support the development of novel closed-loop behavioral health interventions delivered through wearable and Internet of Things devices. Specifically, the researchers at Cornell University will create three types of wearable and IoT systems using different sensory modalities like vibration, airflow, and touch to provide just-in-time interventions...
- This $275,000 SBIR Phase I Project Grant awarded by the National Science Foundation (NSF) under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program supports the development of a wearable multimodal sensing device by Skywalk Inc., a for-profit Asian-Pacific American-owned manufacturer. The device aims to enable more intuitive interaction with augmented reality (AR) technologies by turning human hands into cursors, turning any surface into a touchscreen, and unlocking new...
- This $412,423 project grant from the National Science Foundation's Computer and Information Science and Engineering program will fund the development of novel closed-loop behavioral health interventions at the University of Chicago from September 2022 through July 2026. The university researchers will create three types of wearable and Internet of Things systems delivering sensory interventions for mental health issues like substance cravings, workplace stress, and social stress. The...
- This Cooperative Agreement, awarded by the National Science Foundation (NSF) under their Technology, Innovation, and Partnerships (CFDA 47.084) program, aims to develop a comprehensive, human-centered safety system using physiological and behavioral sensing to identify hazards and predict and prevent workplace accidents. The $1,003,730 Phase II SBIR project, awarded to Intellisafe Analytics LLC, will automate the collection of real-time physiological, emotional, and behavioral data from...
- The National Science Foundation (NSF) awarded a $305,000 STTR Phase I project grant to Sensvita Inc. under the NSF Technology, Innovation, and Partnerships (CFDA 47.084) program. The project aims to develop a non-invasive radio frequency sensing technology for home-based monitoring of heart and lung function. The proposed system uses advanced sensing methods to measure critical physiological parameters without the need for skin contact or maintenance, improving the convenience, scalability,...
- This federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $1,183,690.00 to The Regents of the University of California, San Francisco (UCSF) to develop personalized machine learning models that can predict adverse health events like substance use and stress-related blood pressure spikes using data from wearable devices like Fitbit and Apple Watch. The innovation of this project lies in...
- Cogwear LLC received a $256,000 Project Grant award from the National Science Foundation on May 15, 2021 to develop physiological brain measurement technologies for anxiety assessment and trend analysis. Funded under the NSF's Engineering program (CFDA 47.041), the six-month project will support Cogwear's efforts to improve tools that monitor brain activity to evaluate anxiety levels and patterns over time. The NSF Directorate for Engineering aims to advance innovation and excellence in...
- The National Science Foundation (NSF) awarded a $273,369 Project Grant to Intellisafe Analytics LLC for a Small Business Innovation Research (SBIR) Phase I project titled "Comprehensive, Human-Centered, Safety System Using Physiological and Behavioral Sensing to Predict and Prevent Workplace Accidents". The goal of this project is to develop a safety system that uses wearable technology to continuously collect real-time physiological and behavioral data from workers, and applies...
- This $254,369 federal Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) aims to develop a wearable device capable of continuously sensing physiological signals for biometric authentication and health monitoring. The key products and services to be delivered under this 3-year award include: The project will explore the use of multispectral photoplethysmography (PPG) signals collected through custom-designed wearable devices for continuous biometric...
SBIR PHASE I: WEARABLE SYSTEM FOR STRESS MANAGEMENT VIA REAL TIME STRESS TRACKING AND BIOFEEDBACK -THE BROADER IMPACT/COMMERCIAL POTENTIAL OF THIS SMALL BUSINESS INNOVATION RESEARCH (SBIR) PHASE I PROJECT IS CREATING A TOOL FOR POLICE OFFICERS AND OTHER SERVICE MEMBERS WHO ARE EXPECTED TO PERFORM THEIR JOB DUTIES UNDER HIGH STRESS. THIS PHASE 1 PROJECT SEEKS TO DEVELOP A TECHNOLOGY THAT CREATES STRESS SCORES AND ALERTS USERS WHEN THEY ARE IN ?RED ZONES? FOR DECISION MAKING BASED ON PHYSIOLOGICAL MONITORING VIA A WEARABLE SENSOR UNIT. THE INITIAL TARGET MARKET SEGMENT FOR THIS TECHNOLOGY IS THE ~$1 BILLION LAW ENFORCEMENT MARKET AS THERE IS A HIGH NEED FOR TOOLS THAT CAN HELP DE-ESCALATE SITUATIONS AND POTENTIALLY IMPROVE THE USE-OF-FORCE DECISIONS. THE PAIN POINTS OF ACUTE STRESS IMPACTING DECISION-MAKING HAVE BEEN VALIDATED IN MILITARY AND PROFESSIONAL ATHLETIC MARKETS AS WELL. THIS SMALL BUSINESS INNOVATION RESEARCH (SBIR) PHASE I PROJECT AIMS TO DEVELOP A WEARABLE TECHNOLOGY THAT USES SKIN CONDUCTIVITY TO MEASURE STRESS AND ALERT USERS VIA VIBRATIONAL FEEDBACK. THIS PHASE 1 PROJECT PROPOSES TO: (1) RUN A PILOT STUDY ON POLICE OFFICERS TO COLLECT SKIN CONDUCTANCE DATA DURING SCENARIO TRAINING, (2) BUILD MACHINE LEARNING ARTIFICIAL INTELLIGENCE (AI) MODELS WITH A HIGH PREDICTIVE ACCURACY OF POOR DECISION MAKING USING THIS DATA, (3) DETERMINE IDEAL SENSOR LOCATION AND BUILD A CUSTOM WEARABLE STRAP ATTACHMENT, (4) DEVELOP THE MOBILE APPLICATION TO BUILD A DATA VISUALIZATION INTERFACE FOR OFFICERS AND TRAINERS, AND (5) TEST THE EFFECTIVENESS OF DELIVERING VIBRATIONAL FEEDBACK DURING DECISION MAKING OF OFFICERS USING THE PROTOTYPE. THE SUCCESSFUL CONCLUSION OF PHASE 1 MAY LEAD TO A HARDWARE-SOFTWARE PROTOTYPE THAT MEASURES THE POLICE OFFICERS' EMOTIONAL STRESS USING A SKIN CONDUCTANCE SIGNAL, THEN ALERTS THE USER VIA VIBRATIONAL FEEDBACK WHEN THEY ARE IN A HEIGHTENED LEVEL OF STRESS. THIS AWARD REFLECTS NSF'S STATUTORY MISSION AND HAS BEEN DEEMED WORTHY OF SUPPORT THROUGH EVALUATION USING THE FOUNDATION'S INTELLECTUAL MERIT AND BROADER IMPACTS REVIEW CRITERIA.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $0 | 6/26/23 | ||
| Not listed | $20.0k | 3/27/23 | ||
| Not listed | $256.0k | 8/1/22 |