I-Corps: Electronic Grip Gauge

这个I-Corps项目的更广泛的影响/商业潜力是开发一种评估和恢复手部精细感觉运动功能的设备。神经肌肉损伤后，由于手部的运动和感觉缺陷，患者经常难以处理和操纵易碎的物体。虽然现有的职业治疗和物理治疗设备主要关注上肢的整体功能，但该项目引入了一种能够监测手部精细感觉运动功能的设备，就像在轻轻地抓住易碎物体时一样。该设备简单、便携且价格低廉，可无缝集成到住院康复、门诊康复、熟练护理设施和家庭健康工作流程中。随着美国人口老龄化和神经肌肉损伤患病率的增加，职业和物理治疗市场预计将从2023年的530.8亿美元增长到2030年的923.8亿美元。中风是美国致残的主要原因，该项目提供了一种评估和恢复中风幸存者精细感觉运动功能的解决方案。这个I-Corps项目的基础是开发一种带有嵌入式传感器和人工智能的手持设备，以量化精细的手部感觉运动功能。病人可以用这个装置模拟轻轻地抓住一个易碎的物体而不打碎它。嵌入式传感器允许自动评估和康复疗程，从而减少对治疗师的需求。任务难度也可以自动实时更新，以最大限度地提高患者参与度和临床效果。实时计算和显示定量健康指标，以提高诊断准确性和互连器的可靠性。将这些功能集成到一个简单、廉价和微型的形状因子中，为评估和恢复手部精细感觉运动功能提供了一个实用的设备。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 a device to assess and rehabilitate fine sensorimotor hand function. After a neuromuscular injury, patients often struggle with handling and manipulating fragile objects due to motor and sensory deficits of the hand. While existing occupational-therapy and physical-therapy devices focus primarily on gross upper-limb function, this project introduces a device capable of monitoring fine sensorimotor function of the hand, as would be used when gently grabbing a fragile object. The device is simple, portable, and inexpensive, allowing it to be seamlessly integrated into inpatient rehabilitation, outpatient rehabilitation, skilled nursing facilities, and home-health workflows. The occupational and physical therapy market is expected to grow from $53.08 billion in 2023 to $92.38 billion by 2030 as the US population ages and the prevalence of neuromuscular injuries increases. Stroke is the leading cause of disability in the US, and this project offers a solution to assess and rehabilitate the fine sensorimotor function of stroke survivors.This I-Corps project is based on the development of a handheld device with embedded sensors and artificial intelligence to quantify fine sensorimotor hand function. Patients can use this device to simulate gently grasping a fragile object without breaking it. The embedded sensors allow for automated assessments and rehabilitation sessions, thereby reducing the demand on therapists. Task difficulty can also be automatically updated in real-time to maximize patient engagement and clinical outcomes. Quantitative health metrics are calculated and displayed in real-time to improve diagnostic accuracy and interrater reliability. The integration of these features into a simple, inexpensive and miniature formfactor offers a practical device for assessing and rehabilitating fine sensorimotor hand function.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.