All-Fabric-Based Flexible Capacitive Sensors with Pressure Detection and Non-Contact Instruction Capability
Coatings
; 12(3):302, 2022.
Article
in English
| ProQuest Central | ID: covidwho-1760420
ABSTRACT
The flexible and wearable capacitive sensors have captured tremendous interest due to their enormous potential for healthcare monitoring, soft robotics, and human−computer interface. However, despite recent progress, there are still pressing challenges to develop a fully integrated textile sensor array with good comfort, high sensitivity, multisensing capabilities, and ultra-light detection. Here, we demonstrate a pressure and non-contact bimodal fabric-only capacitive sensor with highly sensitive and ultralight detection. The graphene nanoplatelets-decorated multidimensional honeycomb fabric and nickel-plated woven fabric serve as the dielectric layer and electrode, respectively. Our textile-only capacitive bimodal sensor exhibits an excellent pressure-sensing sensitivity of 0.38 kPa−1, an ultralow detection limit (1.23 Pa), and cycling stability. Moreover, the sensor exhibits superior non-contact detection performance with a detection distance of 15 cm and a maximum relative capacitance change of 10%. The sensor can successfully detect human motion, such as finger bending, saliva swallowing, etc. Furthermore, a 4 × 4 (16 units) textile-only capacitive bimodal sensor array was prepared and has excellent spatial resolution and response performance, showing great potential for the wearable applications.
Paints And Protective Coatings; wearable capacitive sensor; multifunctional; pressure; touchless; fabric; Robotics; Polymers; Graphene; Contact pressure; Electrodes; Nickel plating; Sensors; Sensitivity; Polyethylene terephthalate; Spatial resolution; Permeability; Flexibility; Wearable technology; Sensor arrays; Human motion; Needlework; Polyvinyl alcohol; Woven fabrics; COVID-19; China
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
Coatings
Year:
2022
Document Type:
Article
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