On-Body Edge Computing Through E-Textile Programmable Logic Array

Abstract

E-textiles have received tremendous attention in recent years due to the capability of integrating sensors into a garment, enabling high-precision sensing of the human body. Besides sensing, a number of solutions for e-textile garments have also integrated wireless interfaces, allowing sensing data to be transmitted, and also inbuilt capacitive touch sensors, allowing users to provide instructions. While this has provided a new level of sensing that can result in unprecedented applications, there has been little attention placed around on-body edge computing for e-textiles. This study focuses on the need for a noninvasive and remote health-monitoring solution with inbuilt on-body edge computing, and how enabling such sensing and computing capabilities in a fabric environment can act as a new method for healthcare monitoring through the use of embedded computing intelligence in smart garments. Facilitating computing in e-textiles can result in a new form of on-body edge computing, where sensor information is processed very close to the body before being transmitted to an external device or wireless access point. This form of computing can provide new security and data privacy capabilities and, at the same time, provide opportunities for new energy-harvesting mechanisms to process the data through the garment. This study proposes this concept through embroidered programmable logic arrays (PLAs) integrated into e-textiles. In the same way that PLAs have programmable logic circuits by interconnecting different AND, NOT, and OR gates, we propose e-textile–based gates that are sewn into a garment and connected through conductive thread stitching. Two designs are proposed, and this includes single- and multi-layered PLAs. Experimental validations have been conducted at the individual gates and the entire PLA circuits to determine the voltage utilization and logic computing reliability. The multilayered PLA garment superseded the single-layered garment with higher levels of accuracy in the yielded results due to the enhanced design layout, which reduces the potential for short circuits and errors occurring. Our proposed approach can usher in a new form of on-body edge computing for e-textile garments for future wearable technologies, and, in particular, with the current pandemic that requires noninvasive remote health-monitoring applications.