SBIR Phase II: New Wearable for Body Focused Repetitive Behavior Detection

这个小型企业创新研究(SBIR)第二阶段项目的更广泛的影响/商业潜力将帮助患有以身体为中心的重复行为(BFRb)的人。超过4%的美国人遭受摘皮、拔头发和咬指甲的痛苦，由于治疗成本障碍和缺乏有效的工具来促进行为改变，大多数人求助于用化妆品、手套、假发甚至纹身来掩盖问题。虽然行为疗法，特别是习惯逆转训练已经显示出效果，但这种方法传统上受到不可靠的日记记录、缺乏治疗途径以及患者由于缺乏意识而难以实时执行的负担。虽然实时感知设备确实存在，但在检测精度方面仍有改进的空间。该项目将把一种新型的传感器系统集成到一种可穿戴设备中，以实现对BFRB相关行为的最先进的检测精度。这种可穿戴传感器解决方案是此类解决方案中的第一个，使用新型传感器来提取有意义的生物力学信息。这个小型企业创新研究(SBIR)第二阶段项目将产生新的行为识别算法、新的远程监控系统和现场实验产生的新数据。该项目将：1)开发新的传感器校准系统，并表征可能影响检测精度的信号伪影；2)使用实验室捕获的数据开发新的行为检测算法；3)使用提出的远程监控系统在现场进行自我引导实验；4)改进识别算法。这种灵敏的测量要求理想的信号完整性，充分不受信号伪影的影响，并在可穿戴设计限制内紧密集成电子产品。这种可穿戴系统可以深刻影响认知行为疗法中习惯逆转训练的有效性，认知行为疗法是减少这些行为负面影响的领先方法。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will help people who suffer from body-focused repetitive behaviors (BFRBs). Over 4% of Americans suffer from skin picking, hair pulling, and nail biting, the majority of whom resort to covering up the problem with makeup, gloves, wigs, and even tattoos due to treatment cost barriers and lack of effective tools to facilitate behavior change. While behavior therapy, and in particular habit reversal training, has shown efficacy, this method is traditionally burdened by unreliable journaling, a lack of access to treatment, and difficulty for patients to perform in real-time because of a lack of awareness. While real-time awareness devices do exist, there is room for improvement in detection accuracy. This project will integrate a novel sensor system into a wearable device that can lead to state-of-the-art detection accuracy of BFRB-related behaviors. This wearable sensor solution is the first of its kind, using the novel sensor to extract meaningful biomechanical information. This Small Business Innovation Research (SBIR) Phase II project will result in new behavior recognition algorithms, a new remote monitoring system, and new data generated from in-field experiments. The project will: 1) develop a new sensor calibration system and characterize signal artifacts that may influence detection accuracy; 2) develop new behavior detection algorithms using data captured in the lab; 3) conduct self-guided experiments in the field using the remote monitoring system proposed; and 4) refine recognition algorithms. Such sensitive measurements require ideal signal integrity, be sufficiently immune to signal artifacts, and tight electronics integration within wearable design constraints. This wearable system can profoundly impact the efficacy of habit reversal training during cognitive behavioral therapy, the leading method for reducing the negative effect of these behaviors.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.