SCH: INT: Novel Textile Based Sensors for Inner Prosthetic Socket Environment Monitoring

SCH:INT:用于内部假肢接受腔环境监测的新型纺织品传感器

基本信息

  • 批准号:
    1622451
  • 负责人:
  • 金额:
    $ 166.28万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-09-01 至 2022-08-31
  • 项目状态:
    已结题

项目摘要

Amputation is one of the major causes of disability. Sockets are the important prosthesis components and physical interface to integrate the prosthetic limbs mechanically with the amputee's residual limb to replace lost function. Objective monitoring of the inner socket environment (i.e. pressure, temperature, and humidity) and residual muscle activity during daily prosthesis use requires flexible, unobtrusive and multi-modal sensors that can be integrated into the socket structure without causing subject discomfort. The lack of such an inner-socket sensor technology has been a long-standing problem for evaluating the prosthesis socket, preventing the complications elicited by poor socket design and fit, and advancing the socket technologies. Therefore, advanced socket technologies are urgently needed and will be developed under this project to significantly reduce the number of clinic visits, lower the healthcare costs for amputees, and ultimately improve their quality of life. The impacts of this project will reach far beyond the immediate scientific and engineering contributions that result from it. The use of technologies to further understand the capability of textiles as sensing elements; to design novel systems to monitor the health; and to increase comfort and gait function of amputees in new ways, all provide priceless opportunities to motivate and educate younger generations, their educators and the public-at-large towards the future advancements in manufacturing and biomedical sensing innovation. This project aims to develop a novel Flexible InneR-socket Sensing Technology (FIRST) to be seamlessly, unobtrusively, and elegantly integrated into the lower-limb prosthesis socket. FIRST is based on an electronic-fabric structure where the fibers of the fabric act as sensory elements and could simultaneously track tactile forces, moisture/wetness, electromyography and body temperature at multiple sensing points around the residual limb. In particular, the focus of this project is to enable these soft textile-based sensors to address the relevant challenges in the context of wireless inner socket environment monitoring.The major challenge and overarching objective of this research is to develop a fundamental understanding of the coupling and interaction between multi-component fiber cross-sectional architecture, fabric structure, and its electro-mechanical response to achieve a multimodal sensor that can be unobtrusively integrated into 'textile-based' sensory devices in general. We will evaluate the multiple sensing capabilities of FIRST on patients with lower limb amputations inside and outside of a laboratory environment. The interpretation of FIRST data would identify locations of skin problems to enable patient-self management and allow for a more objective clinical evaluation to avoid the occurrence of potential skin breakdown and the resulting complications.
截肢是造成残疾的主要原因之一。接受腔是重要的假肢部件和物理接口,用于将假肢与截肢者的残肢进行机械整合,以替代失去的功能。在日常假肢使用过程中客观监测接受腔内部环境(即压力、温度和湿度)和残余肌肉活动需要灵活、不显眼的多模式传感器,这些传感器可以集成到接受腔结构中而不引起受试者不适。缺乏这种内部接受腔传感器技术一直是评估假肢接受腔、防止接受腔设计和配合不良引起的并发症以及推进接受腔技术的一个长期存在的问题。因此,迫切需要先进的插座技术,该项目将开发先进的插座技术,以显着减少就诊次数,降低截肢者的医疗费用,并最终提高他们的生活质量。该项目的影响将远远超出其所产生的直接科学和工程贡献。利用技术进一步了解纺织品作为传感元件的能力;设计新颖的系统来监测健康状况;并以新的方式提高截肢者的舒适度和步态功能,所有这些都提供了宝贵的机会来激励和教育年轻一代、他们的教育工作者和广大公众,以实现制造和生物医学传感创新的未来进步。该项目旨在开发一种新颖的柔性内插槽传感技术(FIRST),以无缝、不引人注目且优雅地集成到下肢假肢插槽中。 FIRST 基于电子织物结构,其中织物纤维充当传感元件,可以在残肢周围的多个传感点同时跟踪触觉力、湿度/湿度、肌电图和体温。特别是,该项目的重点是使这些基于软织物的传感器能​​够解决无线内插座环境监测背景下的相关挑战。这项研究的主要挑战和总体目标是对耦合有一个基本的了解以及多组分纤维横截面结构、织物结构及其机电响应之间的相互作用,以实现多模式传感器,该传感器通常可以不引人注目地集成到“基于纺织品的”传感设备中。 我们将在实验室环境内外评估 FIRST 对下肢截肢患者的多重传感能力。对 FIRST 数据的解释将确定皮肤问题的位置,以便患者进行自我管理,并进行更客观的临床评估,以避免发生潜在的皮肤破损和由此产生的并发症。

项目成果

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Alper Bozkurt其他文献

Quantifying Visual Differences in Drought-Stressed Maize through Reflectance and Data-Driven Analysis
通过反射率和数据驱动分析量化干旱胁迫玉米的视觉差异
  • DOI:
    10.3390/ai5020040
  • 发表时间:
    2024-06-04
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sanjana Banerjee;J. Reynolds;Matt Taggart;Michael Daniele;Alper Bozkurt;Edgar J. Lobaton
  • 通讯作者:
    Edgar J. Lobaton
EKO-ETİKETLERİN TURİZME VE YEREL EKONOMİYE ETKİLERİ
土耳其经济与经济研究所
The Effect of Auditory Stimulation upon Cerebral Blood Oxygenation in Infants: Measurements by Light Emitting Diode (LED) Near Infrared Spectroscopy
听觉刺激对婴儿脑血氧合的影响:通过发光二极管 (LED) 近红外光谱进行测量
Relationship of galectin-3 to left ventricular geometry and hypertrophy in chronic hemodialysis patients
半乳糖凝集素3与慢性血液透析患者左心室几何结构和肥厚的关系
  • DOI:
    10.1007/s00059-014-4111-4
  • 发表时间:
    2015-06-01
  • 期刊:
  • 影响因子:
    1.7
  • 作者:
    H. Yılmaz;O. M. Gurel;Huseyin Tugrul Celik;Alper Bozkurt;Mehmet Erol Yildirim;İsmail Bilgiç;M. A. Bilgiç;N. Bavbek;Ali Akcay
  • 通讯作者:
    Ali Akcay
Adolescent Asthma Monitoring: A Preliminary Study of Audio and Spirometry Modalities
青少年哮喘监测:音频和肺活量测定方式的初步研究

Alper Bozkurt的其他文献

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{{ truncateString('Alper Bozkurt', 18)}}的其他基金

UROL:ASC: AI-Supported Bionic Bivalves for Surface Water Monitoring based on Freshwater Mussel Response to Environmental Change
UROL:ASC:基于淡水贻贝对环境变化的响应,人工智能支持的仿生双壳类用于地表水监测
  • 批准号:
    2319389
  • 财政年份:
    2023
  • 资助金额:
    $ 166.28万
  • 项目类别:
    Standard Grant
SenSE: AI-Driven, Resilient and Adaptive Monitoring of Sleep (AI-DReAMS)
SenSE:人工智能驱动、弹性和自适应的睡眠监测 (AI-DReAMS)
  • 批准号:
    2037328
  • 财政年份:
    2021
  • 资助金额:
    $ 166.28万
  • 项目类别:
    Standard Grant
CAREER:Bio-electro-photonic Microsystem Interfaces for Small Animals
职业:小动物生物光电微系统接口
  • 批准号:
    1554367
  • 财政年份:
    2016
  • 资助金额:
    $ 166.28万
  • 项目类别:
    Standard Grant
Fiber based Fabric Sensors
基于光纤的织物传感器
  • 批准号:
    1509043
  • 财政年份:
    2015
  • 资助金额:
    $ 166.28万
  • 项目类别:
    Standard Grant
CPS: Synergy: Collaborative Research: Cyborg Insect Networks for Exploration and Mapping (CINEMa)
CPS:协同:协作研究:用于探索和绘图的机器人昆虫网络 (CINEMa)
  • 批准号:
    1239243
  • 财政年份:
    2012
  • 资助金额:
    $ 166.28万
  • 项目类别:
    Standard Grant

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