I-Corps: Remote wearable technology for mental health and treatment monitoring

I-Corps项目的更广泛影响/商业潜力是开发可穿戴技术，以监测患有抑郁症或应激障碍等精神健康状况的个人的症状和治疗反应。目前，通过定期问卷进行主观症状监测是诊断和监测心理健康状况的标准做法。然而，这些工具容易出现偏差和不准确，导致误诊和无效治疗。提出的技术是一种可穿戴传感器，通过监测物理、生物和数字标记提供替代方案。通过收集和分析多个生物特征数据点，该技术提供了对治疗反应的综合评估、监测和分析，这可能会改善心理健康监测和治疗。I-Corps项目的基础是开发一种传感器，利用生理和生物标记物收集各种生物特征数据，监测心理健康。该技术被设计为一种可穿戴技术，利用光谱和机器学习来收集心率、呼吸频率和体温等生理特征。该技术检测和量化特定的生物标志物，而不需要使用光学传感的额外标记剂或探针。光学检测系统在目标生物标记物存在的情况下测量光特性的变化，包括吸收、散射或荧光。通过收集和分析多个生物特征数据点，该技术能够全面评估、监测和分析治疗反应。目标是预测抑郁和压力水平，并推进个性化的、数据驱动的治疗方法。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。

The broader impact/commercial potential of this I-Corps project is the development of wearable technology to monitor symptoms and treatment responses in individuals with mental health conditions such as depression or stress disorders. Currently, subjective symptom monitoring through periodic questionnaires is the standard of practice in diagnosing and monitoring mental health conditions. However, these tools are prone to biases and inaccuracies, leading to misdiagnosis and ineffective treatment. The proposed technology is a wearable sensor that offers an alternative by monitoring physical, biological, and digital markers. By collecting and analyzing multiple biometric data points, the proposed technology provides a comprehensive assessment, monitoring, and analysis of treatment responses, which may improve mental health monitoring and treatment.This I-Corps project is based on the development of a sensor for gathering diverse biometric data using physiological and biological biomarkers to monitor mental health. The proposed technology is designed as a wearable technology that uses spectroscopy and machine learning to collect physiological characteristics such as heart rate, breathing rate, and body temperature. The technology detects and quantifies specific biomarkers without the need for additional labeling agents or probes using optical sensing. The optical detection system measures changes in light properties, including absorption, scattering, or fluorescence, in the presence of target biomarkers. By collecting and analyzing multiple biometric data points, the technology enables comprehensive assessment, monitoring, and analysis of treatment responses. The goal is to predict depression and stress levels and to advance personalized, data-driven approaches to treatment.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.