In this paper, a textile-based strain sensor has been developed to create a respiration belt. The constituent materials and the knitted structure of the textile sensor have been specifically selected and tailored for this application. Electromechanical modeling has been developed by exploiting Peirce's loop model in order to describe the fabric geometry under static and dynamic conditions. Kirchhoff's node and loop equations have been employed to create a generalized solution for the equivalent electrical resistance of the textile sensor for a given knitted loop geometry and for a specified number of loops. A laboratory test setup was built to characterize the prototype sensor and the resulting equivalent resistance under strain levels up to 40%, and consistent resistance response levels have been obtained from the sensor which correlate well with the modelled data. Production of the respiration belt was realized by bringing together knitted sensor and a relatively inelastic textile strap. Both machine simulations and real-time measurements on a human subject have been performed in order to calculate average breathing frequencies under different static and dynamic conditions. Also, different scenarios have been performed, such as slow breathing and rapid breathing. The sensory belt was located in either the chest area or in the abdominal area during the experimental measurements and the sensor yielded a good response under both static and dynamic conditions. However, body motion artefacts affected the signal quality under dynamic conditions and an additional signal-processing step was added to eliminate unwanted interference from the breathing signal.

The design and development of textile-based strain sensors has been a focus of research and many investigators have studied this subject. This paper presents a new textile-based strain sensor design and shows the effect of base fabric parameters on its sensing properties. Sensing fabric could be used to measure articulations of the human body in the real environment. The strain sensing fabric was produced by using electronic flat-bed knitting technology; the base fabric was produced with elastomeric yarns in an interlock arrangement and a conductive yarn was embedded in this substrate to create a series of single loop structures. Experimental results show that there is a strong relationship between base fabric parameters and sensor properties.

This paper presents a study of the sensing properties exhibited by textile-based knitted strain sensors. Knitted sensors were manufactured using flat-bed knitting technology, and electro-mechanical tests were subsequently performed on the specimens using a tensile testing machine to apply strain whilst the sensor was incorporated into a Wheatstone bridge arrangement to allow electrical monitoring. The sensing fabrics were manufactured from silver-plated nylon and elastomeric yarns. The component yarns offered similar diameters, bending characteristics and surface friction, but their production parameters differed in respect of the required yarn input tension, the number of conductive courses in the sensing structure and the elastomeric yarn extension characteristics. Experimental results showed that these manufacturing controls significantly affected the sensing properties of the knitted structures such that the gauge factor values, the working range and the linearity of the sensors varied according to the knitted structure. These results confirm that production parameters play a fundamental role in determining the physical behavior and the sensing properties of knitted sensors. It is thus possible to manipulate the sensing properties of knitted sensors and the sensor response may be engineered by varying the production parameters applied to specific designs.

The electronic textile area has gained considerable attention due to its implementation of wearable devices, and soft sensors are the main components of these systems. In this paper, a new sensor design is presented to create stretchable, capacitance-based strain sensors for human motion tracking. This involves the use of stretchable, conductive-knit fabric within the silicone elastomer matrix, as interdigitated electrodes. While conductive fabric creates a secure conductive network for electrodes, a silicone-based matrix provides encapsulation and dimensional-stability to the structure. During the benchtop characterization, sensors show linear output, i.e., R² = 0.997, with high response time, i.e., 50 ms, and high resolution, i.e., 1.36%. Finally, movement of the knee joint during the different scenarios was successfully recorded.