I-Corps: Developing a data analytics platform for pain management and alternative treatment

这个I-Corps项目的更广泛的影响是提供洞察力，以最小的干预支持疼痛管理。 所设想的系统使用现成的移动的和可穿戴设备，这些设备已经可用作消费者设备，以最小化消费者的成本，记录疼痛发作、睡眠模式和影响疼痛管理的相关生活方式因素。 此外，它将使患者和医疗保健提供者之间的沟通，使他们能够共同确定有效的治疗方案，以管理疼痛和降低医疗保健成本。 预计这将对肩部、背部和其他肌肉骨骼疼痛有特别的价值。这个I-Corps项目利用人工智能（AI）和深度学习算法来帮助患者记录他们的疼痛发作、睡眠和运动模式以及相关活动。该项目所基于的研究表明，移动的和可穿戴设备能够利用传感器，包括加速度计、高清摄像头、陀螺仪、温度计和其他环境传感器，来收集各种数据并生成智能深度学习算法。其他研究表明，健康的生活方式和替代治疗方法会减少处方药的使用。该项目中的技术为患者提供了一个安全收集自己数据的基础设施。患者和医疗服务提供者可以通过基于互联网的平台访问这些数据，以分析以下因素：1）患者的睡眠模式，运动和类似活动; 2）疼痛发作的频率和严重程度;以及3）治疗效果。该技术将作为患者智能管理慢性疼痛的技术基础设施。该奖项反映了NSF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 of this I-Corps project is to provide insight to support pain management with minimal intervention. The envisioned system uses off-the-shelf mobile and wearable devices already available as consumer devices to minimize costs to the consumer, recording pain episodes, sleep patterns, and associated lifestyle factors impacting pain management. Furthermore, it will enable communication between patients and health care providers so they can jointly identify effective treatment regimens to manage pain and reduce health care costs. It is anticipated that this will have particular value for shoulder, back and other musculoskeletal pains.This I-Corps project draws on artificial intelligence (AI) and deep learning algorithms to help patients record their pain episodes, sleep and exercise patterns, and related activities. The research on which this project is based has shown that mobile and wearable devices are able to utilize sensors, including accelerometers, high-definition cameras, gyroscopes, thermometers and other environmental sensors, to collect diverse data and produce intelligent deep learning algorithms. Additional studies suggest that healthy lifestyles and alternative treatments impact reduced use of prescription drugs. The technology in this project provides an infrastructure for patients to collect their own data securely. Patients and health providers can access these data through an internet-based platform to analyze factors such as: 1) patient sleep patterns, exercises and similar activities; 2) frequency and severity of pain episodes; and 3) treatment effectiveness. The technology will serve as a technological infrastructure for patients to manage chronic pain intelligently. It also will support the development of related smart and connected health applications.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.