Abstract:

Objective Fabric-based pressure sensors have unrivaled advantages, but there are several problems that limit their application in wearable electronics. First, the preparation method of capacitive sensors with multilayer structure cannot achieve the effect of one-piece molding. Second, the dielectric layer in fabric capacitive sensors is difficult to meet the effect of textile air and moisture permeability. Third, a single fabric sensor is not enough to accurately detect the spatial pressure/touch/strain distribution of the human body. Therefore, the research on high-performance one-piece fabric-based array sensors is of particularly importance.

Method The dielectric layer of the fabric-based capacitive sensor adopts a unique three-dimensional(3-D) honeycomb weaving structure. The upper and lower layers are electrode layers, formed by interweaving conductive yarns as warp and weft to create a conductive network; the intermediate dielectric layer is woven with textile yarns and chemical fibers through a honeycomb-like organization to form a structure with interconnected pores, which can optimize the dielectric constant and enhance the response sensitivity. The three layers are connected using an integrated molding process: during weaving, interweaving yarns or special interweaving patterns are introduced to lock the three layers of yarns at the interweaving points, forming an overall structure without interface defects. This not only enhances the structural stability and durability but also avoids inter-layer slippage that interferes with the signal, meeting the precise monitoring requirements for flexible wearable scenarios.

Results The fabric incorporates the use of texturized yarns for a fluffier and softer performance, giving the fabric excellent resilience, softness, breathability and moisture permeability, while enhancing the "compression-recovery" cyclic stability of the fabric capacitance sensor output signal. In terms of mechanical properties, the tensile stress of the 3-D honeycomb fabric gradually decreased with 10 cyclic tensile loading, which was attributed to the stress relaxation of the fabric when subjected to cyclic stress. On the washing test, the capacitance value of the fabric-based capacitive sensor showed overall decreasing after five washing cycles because the effects of detergent and water temperature. In addition, the fabric-based sensor maintained good air permeability (average air permeability being about 464.98 mm/s), and its excellent air permeability was attributed to the fact that the multilayer honeycomb structure of the fabric has fewer interweaving points, longer floating lengths, and larger gaps between the yarns that are favorable for air circulation. Meanwhile, this fabric-based capacitive sensor exhibits excellent bidirectional sensing performance, and maintains good durability and stability even after 2 000 cycles of stretching and compressing tests. After 2 000 "stretch-recovery" cycles, the maximum error was 6.53%. Under 2 000 cycles of "loading-unloading", the maximum difference in relative capacitance change rate was only 1.44%. A high sensitivity of 0.086 kPa^-1 and a fast response time of <150 ms in the range of 0-10 kPa were achieved. The sensors were tested in three consecutive load/unload cycles at different loads (5, 10, 20 and 30 N) and showed good discrimination and stability at different load pressures.

Conclusion Fabric-based capacitive sensors can be used to sense different complex body motions and monitor sensing, such as posture capture, limb bending, pressure monitoring, and so on, which validates their potential application in the field of smart health monitoring. Under two regular states of the human body (walking state and sitting up state), the fabric can distinguish the changing pattern of movement by the obvious change of capacitance signal. The fabric-based capacitive sensor maintains excellent stability and responsiveness during continuous finger(elbow) flexion and relaxation with different amplitudes or durations under a variety of regular bending motions(finger flexion and elbow flexion). It was tested as a sensor array to achieve a normal distribution of pressure for monitoring loads, and its application to a smart cushion showed good sensing response performance under different site pressures.

Key words: fabric electronic, one-piece molding, three-dimentional honeycomb structure, array pressure sensor, fabric-based capacitive sensor, fabric-based pressure sensor, smart wearable textile