Wearable Piezoelectric Yarns with Inner Electrodes for Energy Harvesting and Signal Sensing. Issue 6 (2nd December 2021) - Ryu, Chul Hee; Cho, Jae Yong; Jeong, Se Yeong; Eom, Wonsik; Shin, Hwansoo; Hwang, Wonsoep; Jhun, Jeong Pil; Hong, Seong Do; Kim, Taeyun; Jeong, In Wha; Sung, Tae Hyun
Abstract: Wearable device‐based gait data analysis is being used in medical research to prevent and treat serious diseases such as dementia beyond modern health management strategies. For gait‐related data collection and analysis, it is advantageous to place the sensor on the sole of the foot as a foot‐pressure, it is advantageous to use a piezoelectric generator‐based electronic textile (E‐textile) that can supply its own power by converting mechanical energy from the foot into electrical energy. In order to apply E‐textile materials to the sole of the foot, excellent durability, flexibility, and high signal accuracy through noise minimization are required. In this study, a piezoelectric polymer was used to coat the surface of a conductive fiber using the reverse dip coating technique. This method is easily scalable, feasible for large‐scale processing with a continuous process. The electrodes of this process are placed inside a piezoelectric fiber to minimize noise from the electrodes. The inner‐electrode piezoelectric yarn (IEPY) used during the process has excellent tensile strength (maximum stress and strain value: 54.2 MPa, 54%) and strong durability, maintaining its performance over 10 5 cycles under pushing force of 60 kg and generating excellent piezoelectric output (292 mVmax, 16.2 µW). The IEPY can drive the sensor for gait data, with the sensors being capable of continuous and large‐scale operation and feasible for the manufacturing of custom sensors. Abstract : A wearable piezoelectric yarn with inner electrodes with strong durability, excellent tensile and electrical performance is achieved. For the yarns, a piezoelectric polymer is used to coat the surface of a conductive fiber via the reverse dip coating, scalable and feasible technology for large‐scale processing towards medical sensors.