Kim, Jun Sik Kim, Byung Kook Jang, Minsu Kang, Kyumin Kim, Dae Eun Ju, Byeong-Kwon Kim, Jinseok 2024-01-19T18:00:32Z 2024-01-19T18:00:32Z 2021-09-05 2020-04 1424-8220 https://pubs.kist.re.kr/handle/201004/118790 This paper presents a wearable hand module which was made of five fiber Bragg grating (FBG) strain sensor and algorithms to achieve high accuracy even when worn on different hand sizes of users. For real-time calculation with high accuracy, FBG strain sensors move continuously according to the size of the hand and the bending of the joint. Representatively, four algorithms were proposed; point strain (PTS), area summation (AREA), proportional summation (PS), and PS/interference (PS/I or PS/I_alpha). For more accurate and efficient assessments, 3D printed hand replica with different finger sizes was adopted and quantitative evaluations were performed for index similar to little fingers (77 to 117 mm) and thumb (68 similar to 78 mm). For index similar to little fingers, the optimized algorithms were PS and PS/I_alpha. For thumb, the optimized algorithms were PS/I_alpha and AREA. The average error angle of the wearable hand module was observed to be 0.47 +/- 2.51 degrees and mean absolute error (MAE) was achieved at 1.63 +/- 1.97 degrees. These results showed that more accurate hand modules than other glove modules applied to different hand sizes can be manufactured using FBG strain sensors which move continuously and algorithms for tracking this movable FBG sensors. English MDPI MOTION MEASUREMENT SYSTEM FIBER ACCELEROMETER GLOVE Wearable Hand Module and Real-Time Tracking Algorithms for Measuring Finger Joint Angles of Different Hand Sizes with High Accuracy Using FBG Strain Sensor Article 10.3390/s20071921 1 SENSORS, v.20, no.7 SENSORS 20 7 scie scopus 000537110500117 2-s2.0-85082791132 Chemistry, Analytical Engineering, Electrical & Electronic Instruments & Instrumentation Chemistry Engineering Instruments & Instrumentation Article MOTION MEASUREMENT SYSTEM FIBER ACCELEROMETER GLOVE fiber Bragg grating strain sensor algorithm hand motion capture real-time tracking