Abstract

This work reports the development of highly sensitive Piezoresistive flexible strain sensor for human motion detection and speech recognition. Initially, a conductive polymer composite (CPC) solution comprising of thermoplastic polyurethane and Carbon Nanoparticles was prepared using Dimethylformamide as solvent and Chloroform as dispersant with the composition of 50% v/v. The solution was heated to a temperature of 60°C for evaporation of the solvent until it contained 13.5% w/v solvent for steady electrospinning. In this way, the CPC solution was used to develop Electrospun Nanofibrous Yarns (ENFYs) by applying a potential difference of 40 KV between the electrospinning needle and Aluminum collector. A cotton fabric was wrapped on the Aluminum collector to allow twisting of the deposited electrospun nanofibers. This novel collector configuration resulted in the formation of nanofibrous yarns due to the whirling action of the advancing jet of CPC solution. The cotton fabric on the collector facilitated twisting of fibers by allowing them to roll over the fabric. The fabricated ENFY sensors showed remarkable stretchability up to 102% strain while achieving a gauge factor of 70 at 100% strain. Long-term usage necessitates repeatability, which was demonstrated by cyclic loading at a crosshead speed of 40 mm/min for up to 1000 cycles using a custom-developed linear actuator, with no signs of fracture. ENFY strain sensor was attached to different parts of human body such as finger, fist, elbow, knee and ankle and was found capable of measuring and observing angle, position and frequency of motion. Owing to its ultrasensitive behavior, the developed sensor was able to measure heart rate as well. When the developed sensor was attached to Adam’s apple for speech recognition it showed remarkable response towards different utterances and breathing and gulping actions with clearly distinguishable signals. These results demonstrate that the developed novel ENFY flexible strain sensor can be employed for proprioceptive sensing and speech recognition for human-machine interaction, soft robotics and wearable devices etc.

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