Science of Emotion and Sensibility (감성과학)

Korean Society for Emotion and Sensibility (한국감성과학회)
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Development of an Angle Estimation System Using a Soft Textile Bending Angle Sensor

소프트 텍스타일 굽힘 각 센서를 이용한 각도 추정 시스템 개발

  • 양승아 (숭실대학교 신소재공학과) ;
  • 김상운 (숭실대학교 스마트웨어러블공학과 ) ;
  • 김주용 (숭실대학교 신소재공학과 )
  • Received : 2023.11.21
  • Accepted : 2024.03.12
  • Published : 2024.03.31
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Abstract

This study aimed to develop a soft fabric-based elbow-bending angle sensor that can replace conventional hard-type inertial sensors and a system for estimating bending angles using it. To enhance comfort during exercise, this study treated four fabrics (Bergamo, E-band, span cushion, and polyester) by single-walled carbon nanotube dip coating to create conductive textiles. Subsequently, one fabric was selected based on performance evaluations, and an elbow flexion angle sensor was fabricated. Gauge factor, hysteresis, and sensing range were employed as performance evaluation metrics. The data obtained using the fabricated sensor showed different trends in sensor values for the changes in the angle during bending and extending movements. Because of this divergence, the two movements were separated, and this constituted the one-step process. In the two-step process, multilayer perceptron (MLP) was employed to handle the complex nonlinear relationships and achieve high data accuracy. Based on the results of this study, we anticipate effective utilization in various smart wearable and healthcare domains. Consequently, a soft- fabric bending angle sensor was developed, and using MLP, nonlinear relationships can be addressed, enabling angle estimation. Based on the results of this study, we anticipate the effective utilization of the developed system in smart wearables and healthcare.

본 연구의 목적은 기존의 하드 타입의 관성 센서를 대체할 수 있는 소프트 원단 기반 팔꿈치 굽힘 각 센서를 개발하고, 이를 이용하여 굽힘 각도를 추정하는 시스템을 개발하는 것이다. 본 연구에서는 비교 선정을 위하여 Bergamo, E-band, Span cushion, Polyester의 서로 다른 역학적 특성을 가진 4종류 원단에 SWCNT (Single-Walled Carbon Nanotubes) 함침을 통해 전도성을 부여한 후 성능 평가를 통하여 하나의 원단을 선정하여 팔꿈치 굽힘 각 센서로 제작하였다. 성능을 평가하는 지표로 게이지율(Gauge factor), 이력현상(Hysteresis) 및 센싱 범위를 사용하였다. 제작된 센서를 통해 얻은 데이터는 bending 동작에서의 각도에 대한 센서 출력값의 변화와 extending 동작에서의 각도에 대한 센서 출력값의 변화가 다른 경향을 갖고 있기 때문에 두 가지 동작을 나누는 것을 1-step으로 하였다. 2-step으로, 데이터의 복잡한 비선형 관계를 처리하고 높은 데이터 정확도를 달성하기 위해 MLP (Multi-Layer Perceptron)를 활용하였다. 따라서 소프트 텍스타일 굽힘 센서를 제작하였고, MLP를 통해 비선형 관계를 처리하고 각도 추정이 가능해졌다. 본 연구 결과를 기반으로 다양한 스마트 웨어러블 및 헬스케어 분야에서 효과적으로 활용되기를 기대한다.

Keywords

References

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