I-Corps: Embedding fabric-based sensors into apparel

I-Corps项目的更广泛的影响/商业潜力是利用基于织物的技术来创造功能服装，这些服装可以跟踪身体运动，反过来分析运动技术，跟踪表现，并识别受伤的可能性。全球运动服装市场目前是一个价值2000亿美元的产业，但服装技术的重点一直是对材料性能的逐步改进和优化可制造性。因此，消费者依靠其他技术来告知他们的健康水平，这与智能手表销量的急剧增长相对应，自2015年以来每年翻一番。即便如此，运动员仍然依靠教练、私人教练和物理治疗来进行运动指导。鉴于不同的健身市场，消费者没有一个单一的平台可以访问他们的健康数据。I-Corps项目所追求的技术旨在利用新的缝纫技术，将这些价值主张直接结合到用户的服装中，以嵌入基于织物的运动传感电子设备。这个I-Corps项目旨在通过重新发明传统的缝纫方法来推进可穿戴技术的范围和应用。使用新型导电材料和纤维的组合，电活性线可以用传统的缝纫机缝制到服装中，而不会对服装的可制造性造成太大的影响。不同导电纤维的覆盖层和图案可以产生各种功能的基于织物的传感器，如压力、弯曲或拉伸响应传感器。然后利用这些传感机制直接测量穿衣服的关节或身体部位的运动。目前正在开发一种自定义算法来分析这些新数据集，以提取相关指标，如锻炼技术、努力程度，最终机器学习受伤的可能性或提供用户特定的反馈。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 to leverage fabric-based technologies to create functional apparel that can track body movements and in return analyze exercise technique, track performance, and identify likelihood of injuries. The global sports apparel market is currently a $200 billion dollar industry, yet the focus in apparel technologies have been on incremental improvements on material properties and optimizing manufacturability. Therefore, consumers rely on other technologies to inform them of their fitness levels which has corresponded to a dramatic rise in smart watch sales, doubling every year since 2015. Even so, athletes still rely on coaching, personal trainers, and physical therapy for exercise guidance. There is no single platform in which consumers can access data on their health given the disparate fitness markets. The technology pursued in this I-Corps project aims to combine these value propositions directly into users' clothing by leveraging new sewing technologies to embed fabric-based electronics for motion sensing.This I-Corps project aims to advance the scope and application of wearable technologies by re-inventing traditional sewing methodologies. Using a combination of new conductive materials and fibers, electrically active threads can be sewn into clothing using tradition sewing machines without much disturbance in apparel manufacturability. Over lays and patterning of different conductive fibers can produce various functional fabric-based sensors such as pressure, bend, or stretch responsive sensors. These sensing mechanisms can then be harnessed to directly measure the movement of the clothed joint or body part. Currently a custom algorithm is being developed to analyze these new datasets in order to extract relevant metrics such as exercise technique, effort level, and eventually machine learn likelihood of injuries or provide user-specific feedback.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.