The interplay between machines and humans plays a pivotal role in advancing the new technologies of the metaverse, which aim to enhance the human experience through integrating cloud computing and extended reality (XR). Graphene, a two-dimensional carbon material, has emerged as a highly promising choice for wearable sensor technology and is poised to usher in a new era of seamless human-machine interaction (HMI).
Small, comfortable graphene sensors can measure a variety of bodily signals, including respirations, vocalizations, temperature, and gestures, through tests such as electroencephalograms (EEGs) that quantify brain waves and electrooculograms (EOCs) that measure eye movement. Image Credit: Carbon Future, Tsinghua University Press
A team of material scientists, led by Tian-Ling Ren from Tsinghua University in Beijing, China, has provided an overview of the current state of graphene-based human-machine interaction (HMI) sensor technology to advance research in this field. Advanced sensor technologies that are flexible, lightweight, and suitable for continuous wear are highly desirable for HMI applications.
They hold significant potential for use in both the immersive virtual world of the metaverse and wearable healthcare technologies. Present research efforts are directed at developing sensors capable of interfacing with nearly every body part, including the brain, eyes, and mouth. These sensors can then gather and characterize bodily information through interaction with machines.
The team's review was published in Carbon Future on August 13, 2023.
In this review, we present an overview of some of our research team’s efforts to create graphene-based sensors for human-machine interfaces. These sensors, designed for use on various parts of the human body, are introduced with a focus on their target signals, design, manufacturing process, and performance features. Additionally, we delve into potential future developments for graphene-based sensors, including multi-modality, improved comfort, and intelligence.
Tian-Ling Ren, Study Senior Author and Professor, School of Integrated Circuit
Tian-Ling Ren is also the Deputy Dean of the School of Information Science and Technology at Tsinghua University. Dr Ren is also the Yangtze River Scholar Professor of the Chinese Ministry of Education and Vice Director of the Center for Environmental and Health Sensing Technology at Tsinghua University.
Graphene comprises a single layer of carbon atoms arranged in a hexagonal lattice structure. Its distinctive characteristics, which encompass exceptional conductivity, minimal chemical reactivity, flexibility, and lightweight properties, position graphene as an optimal choice for developing sensors for human-machine interfaces.
The research team has delineated the advancements in developing graphene-based sensors designed to measure various signals originating from the human body.
Many parts of the human body, from head to toe, have the potential to be developed into human-machine interfaces. Brain, eyes, ears, nose, mouth, throat, fingertips, skin, joints, and feet can all be used as HMI interfaces based on electroencephalogram (EEG), electromyography (EMG), electrooculogram (EOG), eye movement, light, breathing, voice, touch, temperature, movement, gait, and other physiological information.
Tian-Ling Ren, Study Senior Author and Professor, School of Integrated Circuit
In human-machine interaction, individuals can also benefit from the output generated by machines. The advancement of multi-modal sensors that seamlessly transition between signal measurements, such as perceiving sound, and signal output, like generating sound, holds significant promise for HMIs.
Tian-Ling Ren's team previously researched to validate the capability of graphene for sound production.
Tian-Ling Ren says, “With the help of machine learning, this interface can achieve speech recognition, emotion analysis, content processing, and more, making it ideal for intelligent robotic communication.”
One of the primary objectives in developing graphene-based sensors is achieving a measurement range extensive enough to detect highly dynamic senses, such as the sense of touch. Researchers have addressed this challenge by creating graphene pressure sensors with a broad sensitivity range.
These sensors utilize loosely stacked laser-scribed graphene (LSG) films that become denser as pressure increases. This increased film density leads to a change in measured resistance, resulting in a wider range of sensitivity that meets the requirements for high-precision sensing.
The research team anticipates that their review will stimulate the creation of novel graphene-based sensors aimed at enhancing the naturalness of human-machine interfaces (HMIs) and enhancing real-time data collection and responses in healthcare applications.
“Graphene-based sensors for HMI are expected to become more diverse and practical in the coming years. In the same part of the body, the human and machine can interact with different signals… in many different ways,” said Tian-Ling Ren.
Other contributors include Tianrui Cui, Ding Li, Thomas Hirtz, Jiandong Xu, Yancong Qiao, Haokai Xu, He Tian, and Yi Yang from the School of Integrated Circuit and the Beijing National Research Center for Information Science and Technology (BNRist) at Tsinghua University in Beijing, China; and Houfang Liu from the BNRist at Tsinghua University.
This work was supported by the National Key R&D Program of China (2021YFC3002200 and 2022YFB3204100), the National Natural Science Foundation of China (U20A20168, 51861145202, 61874065, and 62022047).
Journal Reference:
Cui, T., et al. (2023). Graphene-based sensors for human-machine interaction. Carbon Future. doi.org/10.26599/CF.2023.9200005
Source: http://www.tup.tsinghua.edu.cn/en/index.html