Nudging Behaviors for Better Sleep - STTR Topic DON26TZ01-NV016

Disclaimer:
This topic was temporarily posted by the Department of War SBIR Program on March 2nd 2026 and removed the following day.
We believe this topic is planned to be released once the SBIR program is reauthorized; however, this topic may ultimately be modified or withdrawn.

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Funding Amount:

Est. $240,000

Deadline to Apply:

Est. April 29th, 2026.

Objective:

Develop software for personalized and adaptive behavioral interventions (i.e., nudges) using commercial off-the-shelf (COTS) wearable hardware devices to promote and improve sleep outcomes and human performance in dynamic environments.

Description:

Despite extensive research on the mechanisms of sleep and behavioral modifications to improve sleep, relatively little is known about how context-sensitive behavioral nudging systems—those that dynamically suggest small, adaptive changes based on real-time data—can improve sleep quality and overall performance outcomes in complex, high-stakes settings. Fatigue caused by inadequate sleep negatively affects service members' performance and has contributed to accidents—resulting in deaths and hundreds of millions of dollars in damage to ships, vehicles, and aircraft [Ref 1]. “Nudging” refers to subtle interventions that steer behavior without restricting choices [Ref 2]. For example, non-obvious changes in how options are presented (e.g., ordering, timing, framing) have been shown to significantly affect sleep behaviors and dietary choices [Ref 3]. Recent advances in wearable sensor technology (e.g., smartwatches, rings, sleep trackers, etc.) allow for continuous collection of physiological and behavioral data. Many hardware devices are coupled with software that provide notifications, advice, and suggestions, but these are often canned, static statements that are simply pushed to the user (i.e., a one-way notification) and are not personalized to the user and/or their data.

Delivering adaptive behavioral nudges that learn and track the user’s state and responses, evolve over time, and promote sustained positive behavior change is also critical for mitigating the impact of sleep on operations. The objective of this STTR topic is to develop personalized and adaptive behavioral interventions (i.e., nudges) using COTS wearable devices to promote and improve sleep outcomes and human performance in dynamic environments. Achieving this objective requires: (1) research into integrated theoretical frameworks for personalized behavior change, grounded in cognitive, physiological, and contextual variables, and informed by mathematical tools such as dynamical systems modeling; (2) the development of adaptive algorithms that leverage Machine Learning (ML) and Artificial Intelligence (AI) to integrate with existing wearable and embedded sensors to identify optimal timing, modality, and content for real-time, minimally-intrusive, adherence-supporting behavioral nudges across diverse user states and operational contexts; (3) the exploration of human-centered communication strategies for delivering behavioral insights and recommendations, ensuring interventions are not only well-timed but also subtle and capable of supporting an ongoing user-system relationship built on trust and voluntary engagement; and (4) empirical testing in ecologically valid environments, including experiments that collect sleep and performance metrics to evaluate effectiveness, generalizability, and long-term behavioral impact.

Equal emphasis will be placed on (1) advancing theoretical models of behavior change, sleep regulation, and performance adaptation and (2) developing AI/ML systems and communication strategies for delivering behavioral nudges.

This topic focuses on sleep behavior due to its broad applicability to the general population, its foundational role in human performance, and the relative ease and reliability of measurement. Proposed efforts should aim to develop generalizable algorithms that integrate complex mathematical modeling and ML with cognitive-behavioral theory to drive adaptive behavioral interventions. These interventions must be compatible with existing wearable and embedded sensor ecosystems – this topic explicitly does not aim to develop new hardware, but instead to maximize the utility of currently available commercial sensors as inputs to a personalized, adaptive nudging system.

Who will win?

If you can achieve the objective above better than any other company on the market, you have a very high-likelihood of success and should apply.

Who is eligible to apply?

Any company that meets the following criteria:

• For-profit company

• U.S.-owned and controlled.

• 500 or fewer employees (including affiliates)

How Can BW&CO Help?

1) End-to-end support including, strategy, writing of the full proposal, and administrative & compliance support.

2) Proposal strategy and review.

3) Administrative & compliance support.

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