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Sojung Lee
Department of Fashion Industry, Ewha Womans University, Seoul 03760, Korea

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Journal article
Published: 02 March 2021 in Sustainability
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According to recent trends, smart clothing products that can receive electromyography (EMG) signals during the wearer’s muscle activity are being developed and commercialized. On the other hand, there is a lack of knowledge on the way to specify the electrode locations on the clothing pattern. Accurately located EMG electrodes in the clothing support the reliability and usefulness of the products. Moreover, a systematic process to construct anatomically validated smart clothing digitally should be performed to facilitate the application of a mass-customized manufacturing system. The current study explored the EMG measurement locations of nine muscles and analyzed them in association with various anthropometric points and even postures based on the 3D body scan data. The results suggest that several line segments of the patterns can be substituted by size-dependent equations for the electrodes in place. As a final step, a customized pattern of a smart EMG suit was developed virtually. The current study proposes a methodology to develop body-size dependent equations and patterns of a smart EMG suit with well-located electrodes using 3D scan data. These results suggest ways to produce smart EMG suits in response to impending automation and mass customization of the clothing manufacturing system.

ACS Style

Sojung Lee; Siyeon Kim; Daeyoung Lim; Dong-Eun Kim; Wonyoung Jeong. Analysis of EMG Electrode Locations Using 3D Body Scanning for Digital Pattern Construction of a Smart EMG Suit. Sustainability 2021, 13, 2654 .

AMA Style

Sojung Lee, Siyeon Kim, Daeyoung Lim, Dong-Eun Kim, Wonyoung Jeong. Analysis of EMG Electrode Locations Using 3D Body Scanning for Digital Pattern Construction of a Smart EMG Suit. Sustainability. 2021; 13 (5):2654.

Chicago/Turabian Style

Sojung Lee; Siyeon Kim; Daeyoung Lim; Dong-Eun Kim; Wonyoung Jeong. 2021. "Analysis of EMG Electrode Locations Using 3D Body Scanning for Digital Pattern Construction of a Smart EMG Suit." Sustainability 13, no. 5: 2654.

Journal article
Published: 02 February 2021 in Processes
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The garment manufacturing industry is a labor-intensive industry, with one of the slowest transitions to automation. Hence, it is essential to build a smart factory based on automated systems to improve productivity and allow responsive production in the market. In this study, the manufacturing processes for a smart sports bra were established and optimized using various automated machines. For this system, computer-based 3D virtual design software, a technical embroidery machine, an automatic cutting machine, an industrial robot arm with gripper, and an industrial pattern sewing machine were used. The design and materials of the sports bra were selected considering embroidery, cutting, robot gripping, and sewing processes. In addition, conductive thread and light-emitting diode (LED) sequences were used to implement smart functions to the sports bra. Transport of intermediate materials, work orders, and process conditions were optimized to improve the flexible connection of each process and the quality of the final product. This study suggests the concept of the automated manufacturing system that minimizes human intervention by connecting the processes needed to produce a smart sports bra using various automation equipment and programs already used in the industry.

ACS Style

Suhyun Lee; Soo Rho; Sojung Lee; Jiwoong Lee; Sang Lee; Daeyoung Lim; Wonyoung Jeong. Implementation of an Automated Manufacturing Process for Smart Clothing: The Case Study of a Smart Sports Bra. Processes 2021, 9, 289 .

AMA Style

Suhyun Lee, Soo Rho, Sojung Lee, Jiwoong Lee, Sang Lee, Daeyoung Lim, Wonyoung Jeong. Implementation of an Automated Manufacturing Process for Smart Clothing: The Case Study of a Smart Sports Bra. Processes. 2021; 9 (2):289.

Chicago/Turabian Style

Suhyun Lee; Soo Rho; Sojung Lee; Jiwoong Lee; Sang Lee; Daeyoung Lim; Wonyoung Jeong. 2021. "Implementation of an Automated Manufacturing Process for Smart Clothing: The Case Study of a Smart Sports Bra." Processes 9, no. 2: 289.

Journal article
Published: 19 October 2020 in Polymers
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The surface electromyography (SEMG) is one of the most popular bio-signals that can be applied in health monitoring systems, fitness training, and rehabilitation devices. Commercial clothing embedded with textile electrodes has already been released onto the market, but there is insufficient information on the performance of textile SEMG electrodes because the required configuration may differ according to the electrode material. The current study analyzed the influence of electrode size and pattern reduction rate (PRR), and hence the clothing pressure (Pc) based on in vivo SEMG signal acquisition. Bipolar SEMG electrodes were made in different electrode diameters Ø 5–30 mm, and the clothing pressure ranged from 6.1 to 12.6 mmHg. The results supported the larger electrodes, and Pc showed better SEMG signal quality by showing lower baseline noise and a gradual increase in the signal to noise ratio (SNR). In particular, electrodes, Ø ≥ 20 mm, and Pc ≥ 10 mmHg showed comparable performance to Ag-Ag/Cl electrodes in current textile-based electrodes. The current study emphasizes and discusses design factors that are particularly required in the designing and manufacturing process of smart clothing with SEMG electrodes, especially as an aspect of clothing design.

ACS Style

Siyeon Kim; Sojung Lee; Wonyoung Jeong. EMG Measurement with Textile-Based Electrodes in Different Electrode Sizes and Clothing Pressures for Smart Clothing Design Optimization. Polymers 2020, 12, 2406 .

AMA Style

Siyeon Kim, Sojung Lee, Wonyoung Jeong. EMG Measurement with Textile-Based Electrodes in Different Electrode Sizes and Clothing Pressures for Smart Clothing Design Optimization. Polymers. 2020; 12 (10):2406.

Chicago/Turabian Style

Siyeon Kim; Sojung Lee; Wonyoung Jeong. 2020. "EMG Measurement with Textile-Based Electrodes in Different Electrode Sizes and Clothing Pressures for Smart Clothing Design Optimization." Polymers 12, no. 10: 2406.