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A fabric-based wearable band for hand gesture recognition based on filament strain sensors: A preliminary investigation

机译:基于纤维应变传感器的基于织物的可穿戴手带,用于手势识别:初步研究

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摘要

A wearable system based on a breathable cloth wristband equipped with stretchable strain gauge sensors were assembled and tested to detect a set of 16 different hand gestures. The sensors embedded on the wristband prototype do not require a direct contact with the skin, thus maximizing comfort. To evaluate the performance of the developed band, different gestures were labelled by using grasping information detected in real-time by commercial Force-Sensing Resistor (FSR) sensors. Signals recorded by the wristband were processed through two machine-learning algorithms, i.e. Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), reaching accuracies of 87% and 95% respectively.
机译:装配并测试了基于配备有可拉伸应变计传感器的透气布腕带的可穿戴系统,并进行了检测,以检测16种不同的手势。腕带原型上嵌入的传感器不需要直接与皮肤接触,从而最大程度地提高了舒适度。为了评估已开发频段的性能,通过使用商用力传感电阻(FSR)传感器实时检测到的抓握信息来标记不同的手势。腕带记录的信号通过两种机器学习算法进行处理,即线性判别分析(LDA)和支持向量机(SVM),其准确度分别达到87%和95%。

著录项

  • 来源
  • 会议地点 Cancun(MX)
  • 作者单位

    MENRVA Research Group, School of Engineering Science, Simon Fraser University, Burnaby, Canada;

    MENRVA Research Group, School of Engineering Science, Simon Fraser University, Burnaby, Canada;

    IMM - Istituto per la Microelettronica e i Microsistemi, CNR - Consiglio Nazionale delle Ricerche. Via del fosso del cavaliere n.100, 0133 Rome, Italy;

    IMM - Istituto per la Microelettronica e i Microsistemi, CNR - Consiglio Nazionale delle Ricerche. Via del fosso del cavaliere n.100, 0133 Rome, Italy;

    IMM - Istituto per la Microelettronica e i Microsistemi, CNR - Consiglio Nazionale delle Ricerche. Via del fosso del cavaliere n.100, 0133 Rome, Italy;

    MENRVA Research Group, School of Engineering Science, Simon Fraser University, Burnaby, Canada;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Sensors; Support vector machines; Taxonomy; Skin; Biomedical monitoring; Thumb; Gesture recognition;

    机译:传感器;支持向量机;分类学;皮肤;生物医学监测;拇指;手势识别;

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