RESUMEN

The advancement of smart textiles has resulted in significant development in wearable textile sensors and offers novel interfaces to sense physical movements in daily life. Knitting, as a traditional textile fabrication method, is being used in promising ways to realize fully seamless fabrication and unobtrusive sensing in wearable textile applications. However, current flat-knitted sensors can sense strain only in the horizontal plane. This research presents a novel fully machine-knitted spacer piezoresistive sensor structure with a three-directional sensing ability that can detect both the pressure in the vertical direction and the strain in the warp/weft direction. Besides, it can sense the pressure under 1 kPa, which is critical in comfortable on-body interaction, one-piece integration, and wearable applications. Three sizes spacer-knitted sensors are evaluated in terms of their mechanical performance, stability cycles, and reaction to external factors such as sweat, laundering, etc. Then, the effect of material choice on sensor performance is evaluated and the rationale behind the use of different materials is summarized. Specifically, this research presents a detailed evaluation of the applications with both a single sensor and multiple sensor arrays for fine and gross motion sensing in several scenarios. The testing results demonstrate a fully machine-knitted piezoresistive sensor that can detect multidirectional motions (vertical, warp, and weft directions). In addition, this knitted sensor is scalable and can be facilely and seamlessly integrated into any garment piece. This universal knitted sensor structure could be made with a wide variety of materials for high sensitivity for multidirectional strain/pressure sensing, making it a high-compatibility sensor structure for wearable applications.

RESUMEN

The dynamic equivalent resistance is a major index that determines the sensing performance of knitted strain sensors, and has the characteristics of in-plane and three-dimensional curved strain sensing. Therefore, in addition to establishing the in-plane equivalent resistance, it is necessary to establish a three-dimensional equivalent resistance model to fully explain the surface sensing performance. This project establishes two equivalent resistance models of knitted strain sensors under in-plane deformation and one equivalent resistance model of three-dimensional curved surface strain. Based on the length of resistance and the geometric topological structure, an in-plane strain macro-micro equivalent resistance model and a topological equivalent resistance model are established, respectively. In addition, a three-dimensional curved surface equivalent resistance model is created based on the volume resistance. By comparing the theoretical model with the experimental data, the results prove that the proposed in-plane and three-dimensional models can be utilized to calculate the resistance change of knitted strain sensors. Length resistance, coil transfer, and curved surface deformation depth are the main factors that affect the equivalent resistance of knitted strain sensors.

RESUMEN

Electromyography (EMG) is the resulting electrical signal from muscle activity, commonly used as a proxy for users' intent in voluntary control of prosthetic devices. EMG signals are recorded with gold standard Ag/AgCl gel electrodes, though there are limitations in continuous use applications, with potential skin irritations and discomfort. Alternative dry solid metallic electrodes also face long-term usability and comfort challenges due to their inflexible and non-breathable structures. This is critical when the anatomy of the targeted body region is variable (e.g., residual limbs of individuals with amputation), and conformal contact is essential. In this study, textile electrodes were developed, and their performance in recording EMG signals was compared to gel electrodes. Additionally, to assess the reusability and robustness of the textile electrodes, the effect of 30 consumer washes was investigated. Comparisons were made between the signal-to-noise ratio (SNR), with no statistically significant difference, and with the power spectral density (PSD), showing a high correlation. Subsequently, a fully textile sleeve was fabricated covering the forearm, with 14 textile electrodes. For three individuals, an artificial neural network model was trained, capturing the EMG of 7 distinct finger movements. The personalized models were then used to successfully control a myoelectric prosthetic hand.

Asunto(s)

RESUMEN

In recent years, flexible sensors for data gloves have been developed that aim to achieve excellent wearability, but they are associated with difficulties due to the complicated manufacturing and embedding into the glove. This study proposes a knitted glove integrated with strain sensors for pattern recognition of hand postures. The proposed sensing glove is fabricated at all once by a knitting technique without sewing and bonding, which is composed of strain sensors knitted with conductive yarn and a glove body with non-conductive yarn. To verify the performance of the developed glove, electrical resistance variations were measured according to the flexed angle and speed. These data showed different values depending on the speed or angle of movements. We carried out experiments on hand postures pattern recognition for the practicability verification of the knitted sensing glove. For this purpose, 10 able-bodied subjects participated in the recognition experiments on 10 target hand postures. The average classification accuracy of 10 subjects reached 94.17% when their own data were used. The accuracy of up to 97.1% was achieved in the case of grasp posture among 10 target postures. When all mixed data from 10 subjects were utilized for pattern recognition, the average classification expressed by the confusion matrix arrived at 89.5%. Therefore, the comprehensive experimental results demonstrated the effectiveness of the knitted sensing gloves. In addition, it is expected to reduce the cost through a simple manufacturing process of the knitted sensing glove.

Asunto(s)

RESUMEN

By embedding conductive yarns in, or onto, knitted textile fabrics, simple but robust stretch sensor garments can be manufactured. In that way resistance based sensors can be fully integrated in textiles without compromising wearing comfort, stretchiness, washability, and ease of use in daily life. The many studies on such textile strain sensors that have been published in recent years show that these sensors work in principle, but closer inspection reveals that many of them still have severe practical limitations like a too narrow working range, lack of sensitivity, and undesired time-dependent and hysteresis effects. For those that intend to use this technology it is difficult to determine which manufacturing parameters, shape, stitch type, and materials to apply to realize a functional sensor for a given application. This paper therefore aims to serve as a guideline for the fashion designers, electronic engineers, textile researchers, movement scientists, and human-computer interaction specialists planning to create stretch sensor garments. The paper is limited to textile based sensors that can be constructed using commercially available conductive yarns and existing knitting and embroidery equipment. Within this subtopic, relevant literature is discussed, and a detailed quantitative comparison is provided focusing on sensor characteristics like the gauge factor, working range, and hysteresis.