PFI: BIC Wearable Smart Textiles Based on Programmable and Automated Knitting Technology for Biomedical and Sensor Actuation Applications

PFI：基于可编程和自动化针织技术的 BIC 可穿戴智能纺织品，适用于生物医学和传感器驱动应用

• 批准号: 1430212
• 负责人: Kapil Dandekar
• 金额: $ 79.96万
• 依托单位: Drexel University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1430212&HistoricalAwards=false
• 关键词: PFI; BIC; Wearable; Smart; Textiles

Many medical conditions would benefit from continuous patient monitoring and treatment, although this is currently impractical due to the cumbersome nature of current medical equipment. Recent advancements in specialized materials and fabrication technologies offer exciting opportunities to create seamless garments as sensors and actuators for biomedical applications. Knitting fabrication, known as the intermeshing of yarns into loops (resulting in fabrics), is an ancient form of textile production widely used in the fashion industry. Knitting technology has gained a great deal of attention in the field of wearable electronics and could become a widespread method of construction for smart textiles in the future. In this PFI:BIC project from Drexel University, the aim is to replace current bulky medical monitoring devices with a line of lightweight smart garments. The fiber content of these garments will be similar to those commonly used in active wear such as wicking polyester to insure breathability and comfort, while the actuators and sensors, made of smart materials, will be strategically placed in the clothing to comprise only a small percentage of the material used. The project will leverage intellectual property pertaining to fabric-based connectors, microwave antennas, super capacitors, and robotics, to integrate smart fabric sensors and actuators into comfortable clothing, providing unobtrusive sensing and treatment options that are not currently possible. For textile communication, active and passive transceivers will be fabricated through knitting of different microwave structures. These knit microwave structures will also be used along with processing of passive RFID signals to create mechanical strain sensors. Mechanical actuation will be realized through knit robot technology making use of shape memory alloys. The knit antennas will be combined with knit supercapacitors to create wireless power systems for body area sensor networks. Focus groups with patients and healthcare practitioners will determine market needs. Prototype garments will be beta tested with sample target users. Industrial partners will provide raw materials, manufacturing advice, and commercialization expertise. Key is Shima Seiki knitting technology at Drexel University, which enables customization and innovation in the design and fabrication of wearable and machine washable smart (with integrated power and circuitry) textiles capable of wireless sensing and actuated treatment applications. Target applications that are the focus of this project will include a "bellyband" for uterine contraction monitoring during pregnancy, medical sensor patches, and knit robots for therapeutic massage. Drexel University has formed an interdisciplinary academic team including expertise from industrial and fashion design, materials and electrical engineering, nursing and medicine, as well as management and entrepreneurship. To complement this academic team, a three-tier industry partnership representing all levels of production and commercialization has been formed. The Material Suppliers tier includes EY Technologies (small business, Fall River, MA), custom-engineering groups providing creative solutions for the development of specialized yarns allowing for the creation of raw materials with unique functionality for novel biomedical smart textiles. The Fabrication tier includes Shima Seiki USA (large business, Monroe Township, NJ), a leader in 3D knitting simulation software and computerized knitting machines to manufacture biomedical smart textiles at both laboratory and production scale. Finally, in the Commercialization tier, NetScientific America (small business, Harrison, NY) augmented by the industrial advisory board of the Drexel Coulter Translational Research program will help determine commercial viability of various biomedical smart textile solutions and carry promising technologies to the market. Ben Franklin Technology Partners/Southeastern PA (non-profit, Philadelphia, PA) will serve as a broader context partner building upon experience in launching university/industry partnerships that accelerate scientific discoveries to commercialization and seeding regional initiatives that strengthen the regional entrepreneurial community.

许多医疗状况将受益于持续的患者监测和治疗，尽管由于当前的医疗设备的性质繁琐，目前这是不切实际的。专业材料和制造技术的最新进展为创建无缝服装作为生物医学应用的传感器和执行器提供了令人兴奋的机会。编织的制造被称为纱线成循环（产生织物），是一种古老的纺织品生产形式，在时尚行业中广泛使用。编织技术在可穿戴电子产品领域引起了广泛关注，并可能在将来成为智能纺织品的一种广泛的建筑方法。在Drexel University的PFI：BIC项目中，其目的是用一系列轻巧的智能服装替换当前笨重的医疗监测设备。这些服装的纤维含量将类似于在活跃的磨损中常用的纤维含量，例如芯吸聚酯以确保透气性和舒适性，而由智能材料制成的执行器和传感器将策略性地放入服装中，仅包括一小部分所使用的材料。该项目将利用与基于织物的连接器，微波天线，超级电容器和机器人技术有关的知识产权，将智能面料传感器和执行器集成到舒适的服装中，从而提供了目前无法进行的不引人注目的传感和治疗选择。对于纺织通信，将通过编织不同的微波结构来制造主动和被动收发器。这些针织微波结构也将与被动RFID信号一起处理以创建机械应变传感器。机械致动将通过使用形状内存合金的针织机器人技术实现。针织天线将与针织超级电容器结合使用，以创建用于身体区域传感器网络的无线电源系统。与患者和医疗保健从业人员的焦点小组将确定市场需求。原型服装将与样本目标用户一起测试。工业合作伙伴将提供原材料，制造建议和商业化专业知识。 Key是Drexel University的Shima Seiki编织技术，该技术可以在设计和制造可穿戴和可机洗的智能（具有集成的功率和电路）纺织品的设计和制造方面进行定制和创新，该纺织品能够无线传感和驱动治疗应用。该项目重点的目标应用将包括一个“腹带”，用于怀孕期间的子宫收缩监测，医疗传感器贴片和针织机器人进行治疗按摩。德雷克塞尔大学（Drexel University）组成了一个跨学科的学术团队，包括工业和时装设计，材料和电气工程，护理和医学以及管理和企业家精神的专业知识。为了补充该学术团队，已经形成了代表所有级别生产和商业化的三层行业伙伴关系。材料供应商层包括EY Technologies（小型企业，马萨诸塞州福尔里弗），定制工程小组为开发专业纱线提供创造性解决方案，允许创建具有新型生物医学智能纺织品的独特功能的原材料。制造层包括美国Shima Seiki（大型企业，新泽西州门罗镇），这是3D编织仿真软件和计算机编织机的领导者，以在实验室和生产规模上生产生物医学智能纺织品。最后，在Drexel Coulter转化研究计划的工业顾问委员会增强了商业化层中，NetScientific America（小型企业，纽约州哈里森）将有助于确定各种生物医学智能纺织解决方案的商业可行性，并将有前途的技术携带到市场。 Ben Franklin Technology Partners/宾夕法尼亚州（非营利组织，宾夕法尼亚州非营利组织）将在建立大学/行业合作伙伴关系的经验的基础上成为更广泛的背景合作伙伴，该合作伙伴将科学发现加速到商业化和播种区域计划，从而加强该地区企业社区。

项目成果

Real-time detection of apnea via signal processing of time-series properties of RFID-based smart garments

• DOI: 10.1109/spmb.2016.7846871
• 发表时间: 2016-12
• 期刊: 2016 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)
• 作者: W. Mongan;I. Rasheed;K. Ved;Ariana Levitt;E. Anday;K. Dandekar;G. Dion;T. Kurzweg;A. Fontecchio

An improved design of wearable strain sensor based on knitted RFID technology

基于针织RFID技术的可穿戴应变传感器改进设计

• DOI: 10.1109/cama.2016.7815769
• 发表时间: 2016
• 期刊: 2016 IEEE Conference on Antenna Measurements & Applications (CAMA
• 作者: Liu, Yuqiao;Levitt, Ariana;Kara, Christina;Sahin, Cem;Dion, Genevieve;Dandekar, Kapil R.
• 通讯作者: Dandekar, Kapil R.

Data fusion of single-tag rfid measurements for respiratory rate monitoring

• DOI: 10.1109/spmb.2017.8257028
• 发表时间: 2017-12
• 期刊: 2017 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)
• 作者: W. Mongan;R. Ross;I. Rasheed;Y. Liu;K. Ved;E. Anday;K. Dandekar;G. Dion;T. Kurzweg;A. Fontecchio

On implementing an unconventional infant vital signs monitor with passive RFID tags

• DOI: 10.1109/rfid.2017.7945586
• 发表时间: 2017-01-01
• 期刊: 2017 IEEE International Conference on RFID (RFID)
• 作者: Vora, Shrenik A.;Mongan, William M.;Kurzweg, Timothy P.
• 通讯作者: Kurzweg, Timothy P.

On the Use of Radio Frequency Identification for Continuous Biomedical Monitoring

• DOI: 10.1145/3054977.3055002
• 发表时间: 2017-04
• 期刊: 2017 IEEE/ACM Second International Conference on Internet-of-Things Design and Implementation (IoTDI)
• 作者: W. Mongan;I. Rasheed;K. Ved;Shrenik A. Vora;K. Dandekar;G. Dion;T. Kurzweg;A. Fontecchio