Science of Emotion and Sensibility (감성과학)

Korean Society for Emotion and Sensibility (한국감성과학회)
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Development of Wrist Tunnel Syndrome Prevention Smart Gloves using CNT-based Tensile Fabric Sensor: Focusing on Mouse Use

CNT 기반의 인장 직물 센서를 사용한 손목터널증후군 예방 스마트장갑 개발: 마우스사용을 중심으로

  • 전세환 (숭실대학교 유기신소재파이버공학과) ;
  • 김상운 (숭실대학교 스마트웨어러블공학과) ;
  • 김주용 (숭실대학교 유기신소재파이버공학과)
  • Received : 2021.09.13
  • Accepted : 2021.11.07
  • Published : 2021.12.31
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Abstract

In this work, we study smart gloves that can prevent carpal tunnel syndrome when using a mouse. Because the left and right wrist movements are fine, a tensile fabric sensor with a large gauge factor and low hysteresis was required before the study. A universal testing machine was used to calculate each gauge rate on four different fabrics, and the fabric with the least hysteresis was selected. In addition, three attachment methods were analyzed using Arduino to select a method with a large sensor value change. For prototypes made by attaching to the selected fabric, data patterns were analyzed using Arduino. The first method identifies only one sensor (A sensor), and the second identifies two sensors (A and B sensors). When the wrist is bent to the right, tensile fabric sensors are attached to both the left (A sensor) and right (B sensor) sides of the wrist, the A sensor is strained, increasing the △sensor value, and the B sensor is relaxed, decreasing the △sensor value. However, when the wrist was bent to the left, the pattern was analyzed in the opposite direction. Through this study, we examined smart gloves to prevent carpal tunnel syndrome with an algorithm that turns on the LED when the wrist is bent, and based on the results of this study, we will directly use mice on 10 people to identify problems and solve problems when used.

본 연구의 목적은 마우스 사용 시 손목터널증후군을 예방할 수 있는 스마트장갑을 연구하는 것이다. 연구에 앞서 손목의 좌·우 움직임은 미세하므로 게이지율(Gauge Factor)이 크고, 이력현상(Hysteresis)이 적은 인장 직물 센서가 필요하다. 만능재료시험기(UTM)를 통해 4가지의 직물을 분석하여 각각의 게이지율을 계산하고, 이력현상도 가장 적은 직물을 선택하였다. 또한, 3가지 부착방법을 아두이노로 분석하여 센서값 변화(△Sensor Value) 값이 큰 방법을 선택하였다. 선택된 직물과 부착방법으로 제작한 프로토타입을 아두이노를 통해 데이터 패턴을 분석하였다. 첫 번째는 센서 1개(A 센서)로만 파악하는 방법이고, 두 번째로는 센서 2개(A, B 센서)로 파악하는 방법이다. 손목 왼쪽(A 센서), 손목 오른쪽(B 센서) 양쪽에 인장 직물 센서를 부착하고, 손목을 오른쪽으로 꺾을 때 A 센서는 늘어나서 △Sensor Value 값이 커지고, B 센서는 줄어들어서 △Sensor Value가 작아진다. 반면에 손목을 왼쪽으로 꺾을 때는 반대로 패턴이 분석되었다. 본 연구를 통해 손목이 꺾일 시 LED가 켜지는 알고리즘으로 손목터널증후군을 예방하는 스마트장갑을 연구하였고, 본 연구 결과를 기반으로 후속 연구에서는 10명을 대상으로 직접 마우스를 사용하면서 실제 사용 시 문제점을 파악하고 파악된 문제점을 해결하고자 한다.

Keywords

Acknowledgement

이 논문은 2021년도 산업통상자원부 및 산업기술평가관리원(KEIT) 연구비 지원에 의한 연구임('20016038'). 이 논문은 산업통상자원부 '산업혁신인재성장지원사업'의 재원으로 한국산업기술진흥원(KIAT)의 지원을 받아 수행된 연구임(P002397).

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