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SBIR Phase I: Wearable System for Stress Management via Real Time Stress Tracking and Biofeedback

SBIR Phase I: Wearable System for Stress Management via Real Time Stress Tracking and Biofeedback
SBIR 第一阶段:通过实时压力跟踪和生物反馈进行压力管理的可穿戴系统
批准号:
2212935
负责人:
Melis Yilmaz Balban
金额:
$25.6万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-08-01 至 2023-08-31

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中文摘要
翻译
这项小企业创新研究(SBIR)第一阶段项目的广泛影响/商业潜力是为警察和其他在高压力下履行工作职责的服务人员创造一种工具。这个第一阶段的项目旨在开发一种技术,该技术可以创建压力分数,并在用户处于“红色区域”时提醒用户,从而根据可穿戴传感器单元的生理监测做出决策。这项技术最初的目标市场是价值约10亿美元的执法市场,因为这些市场非常需要能够帮助缓和局势并有可能改善使用武力决策的工具。急性压力影响决策的痛点在军事和专业运动市场中也得到了验证。这项小型企业创新研究(SBIR)第一阶段项目旨在开发一种可穿戴技术,该技术利用皮肤电导率来测量压力,并通过振动反馈提醒用户。第一期工程建议:(1)对警察进行试点研究,收集场景训练期间的皮肤电导数据;(2)利用这些数据构建机器学习人工智能(AI)模型,对不良决策具有较高的预测精度;(3)确定理想的传感器位置,并构建定制的可穿戴带配件;(4)开发移动应用程序,为警察和培训师构建数据可视化界面。(5)利用样机测试了在军官决策过程中传递振动反馈的有效性。第一阶段的成功结论可能会导致硬件软件原型,使用皮肤电导信号测量警察的情绪压力,然后在用户处于高度紧张状态时通过振动反馈提醒用户。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
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.
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