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http://dx.doi.org/10.14695/KJSOS.2022.25.1.67

Resistive E-band Textile Strain Sensor Signal Processing and Analysis Using Programming Noise Filtering Methods  

Kim, Seung-Jeon (숭실대학교 스마트웨어러블공학과)
Kim, Sang-Un (숭실대학교 스마트웨어러블공학과)
Kim, Joo-yong (숭실대학교 유기신소재파이버 공학과)
Publication Information
Science of Emotion and Sensibility / v.25, no.1, 2022 , pp. 67-78 More about this Journal
Abstract
Interest in bio-signal monitoring of wearable devices is increasing significantly as the next generation needs to develop new devices to dominate the global market of the information and communication technology industry. Accordingly, this research developed a resistive textile strain sensor through a wetting process in a single-wall carbon nanotube dispersion solution using an E-Band with low hysteresis. To measure the resistance signal in the E-Band to which electrical conductivity is applied, a universal material tester, an Arduino, and LCR meters that are microcontroller units were used to measure the resistance change according to the tensile change. To effectively handle various noises generated due to the characteristics of the fabric textile strain sensor, the filter performance of the sensor was evaluated using the moving average filter, Savitsky-Golay filter, and intermediate filters of signal processing. As a result, the reliability of the filtering result of the moving average filter was at least 89.82% with a maximum of 97.87%, and moving average filtering was suitable as the noise filtering method of the textile strain sensor.
Keywords
Textile Strain Sensor; Noise Filtering; Moving Average Filtering; Savitzky-Golay Flitering; Median Filtering;
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Times Cited By KSCI : 6  (Citation Analysis)
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