Development of knit band electrodes for multi-channel sEMG measurement

Lee, Seul Ah; Kim, Myoung Ok; Gang, Taeho; Choi, Youngjin

doi:10.1109/urai.2017.7992835

Cited by 4 publications

(4 citation statements)

References 4 publications

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“…The internal side of the wearable fabric sensor has sixteen-channels with 32 bipolar electrodes for sEMG signal acquisition. The shape of the electrode was a square of 12×12 mm, and the inter-electrode distance was designed to be 20 mm according to the surface electromyography for the non-invasive assessment of muscles (SENIAM) [45] and previous studies [16,24,25,46,47]. The external side of the wearable fabric sensor has 32 terminal snaps used as electric wire connectors as illustrated in figure 1.…”

Section: Design Of Wearable Fabric Sensormentioning

confidence: 99%

“…Among those studies of fabric sensors, many researchers have developed various types of textile electrodes with different structures, materials, sizes, and shapes. A fabric sensor was developed using non-woven fabric sheet or flat knitted electrodes for sEMG measurement [20][21][22][23][24][25][26][27][28][29][30][31][32]. However, it could not provide sufficient sEMG channels, and its fabrication processes were complicated and included cutting, sewing, and using various materials.…”

Section: Introductionmentioning

confidence: 99%

“…Most works on fabric electrodes and sensors for prostheses focused on wearing the electrodes on the upper limb for cases of wrist disarticulation and trans-radial amputation. We also developed a sEMG eight-channel knit sensor for wearing on the upper limb in our previous studies [24,25], but it was not suitable for high-level amputees, including trans-humeral amputation or shoulder disarticulation. Moreover, the number of channels was not sufficient, thus the number of the recognizable motion patterns was limited as well.…”

Section: Introductionmentioning

confidence: 99%

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Wearable fabric sensor for controlling myoelectric hand prosthesis via classification of foot postures

Lee¹,

Sung²,

Choi³

2020

Smart Mater. Struct.

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The degrees-of-freedom of robotic prosthetic hands have recently increased, but high-level amputees such as those with shoulder disarticulation and trans-humeral amputation do not have enough muscular areas on their upper limbs upon which to base surface electromyogram (sEMG) signals. In this paper, a wearable fabric sensor is proposed to measure the sEMG on the lower limb and to classify the foot postures by using the proposed convolutional neural network (CNN), ultimately, for the application to high-level upper limb amputees. First, we determined that sEMG signals of the lower limb can be classified into levels in a manner similar to those of the upper limb for eight postures. Second, a multilayer perceptron (MLP) and the proposed CNN was used to compare the pattern recognition accuracy for classifying eight postures. Finally, the wearable fabric sensor and the proposed CNN network were demonstrated by the trans-radial amputees. These results showed that the wearable fabric sensor verified different eight patterns based on similar motions of both limbs (p < 0.001). In addition, the classification accuracy (91.3%) of the proposed CNN was much higher than that (79%) of MLP (p < 0.05). The wearable fabric sensor allowed the measurement location to change from the upper limb to the lower limb and allowed the number of the classifiable patterns to increase thanks to the sixteenchannel sEMG signals acquired from 32 fabric electrodes. The high classification accuracy of the proposed CNN will be useful for various users who have to wear myoelectric prosthesis every day.

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Section: Design Of Wearable Fabric Sensormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Wearable fabric sensor for controlling myoelectric hand prosthesis via classification of foot postures

Lee¹,

Sung²,

Choi³

2020

Smart Mater. Struct.

Self Cite

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“…5 Wang 6 used polyester fabric (PETF) as the base material, introduced 3-mercaptopropytrimethoxysilane (MPTS) to modify the surface of the fabric, and performed electroless silver plating on the modified PETF (M-PETF) to fabricate electrocardiogram fabric electrodes with better conductivity and washable resistance. Lee 7 developed a multi-channel band electromyography(EMG) measuring instrument using the mosaic weaving method. The knitted electrodes developed used conductive silver and non-conductive Bio Max functional yarns.…”

Section: Introductionmentioning

confidence: 99%

Sensing performance of textile strain sensors with different weave structures

Fang,

Dong,

Zhang

et al. 2023

Journal of Industrial Textiles

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Many conductive fabrics have been widely used as fabric strain sensors in recent years due to their excellent flexibility. In this study, high-tenacity polyester warp yarn and silver-coated nylon weft yarn were used to produce six types of conductive fabrics with different structures. The surface morphology of silver-coated nylon yarn was observed under a microscope, and the yarn was placed in an airtight container to test the effect of different humidity on the resistance of the yarn. DM6500 digital multimeter was used to test the resistance sensitivity, fatigue resistance, repeatability, and antistatic properties of conductive fabric samples. The results showed that the change in yarn surface material, external humidity, and strain affected the change in yarn resistance. Different weave structures affected the sensing performance of the fabric. The tighter the structure, the better the sensitivity and antistatic properties, the looser the structure, the better the fatigue resistance and repeatability. Two types of fabric and nylon gloves with different structural tightness are used to make intelligent data gloves. The results showed that both fabrics had good application prospects in limb movement detection.

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