Triboelectric vibration sensor for a human-machine interface built on ubiquitous surfaces

He, Qiang; Wu, Yulian; Feng, Zhiping; Sun, Chenchen; Fan, Wenjing; Zhou, Zhihao; Meng, Keyu; Fan, Endong; Yang, Jin

doi:10.1016/j.nanoen.2019.03.005

Cited by 111 publications

(60 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In terms of hand/finger gesture based self‐powered HMIs, sensors based on the piezoelectric 111,116,260,261 and triboelectric 262‐264 transducing mechanisms have been extensively developed for soft wearable glove‐based electronics. Moreover, because of the wide choices of flexible and stretchable triboelectric materials, for example, metal, oxide, wood, fabric, rubber, and polymer, 265 many triboelectric‐based finger sensors have been developed recently, proving its great potential as self‐powered wearable HMIs.…”

Section: Self‐sustainable Wearable Electronics Integrated With Energymentioning

confidence: 99%

Progress in wearable electronics/photonics—Moving toward the era of artificial intelligence and internet of things

Shi

Dong

et al. 2020

InfoMat

450

233

View full text Add to dashboard Cite

The past few years have witnessed the significant impacts of wearable electronics/photonics on various aspects of our daily life, for example, healthcare monitoring and treatment, ambient monitoring, soft robotics, prosthetics, flexible display, communication, human‐machine interactions, and so on. According to the development in recent years, the next‐generation wearable electronics and photonics are advancing rapidly toward the era of artificial intelligence (AI) and internet of things (IoT), to achieve a higher level of comfort, convenience, connection, and intelligence. Herein, this review provides an opportune overview of the recent progress in wearable electronics, photonics, and systems, in terms of emerging materials, transducing mechanisms, structural configurations, applications, and their further integration with other technologies. First, development of general wearable electronics and photonics is summarized for the applications of physical sensing, chemical sensing, human‐machine interaction, display, communication, and so on. Then self‐sustainable wearable electronics/photonics and systems are discussed based on system integration with energy harvesting and storage technologies. Next, technology fusion of wearable systems and AI is reviewed, showing the emergence and rapid development of intelligent/smart systems. In the last section of this review, perspectives about the future development trends of the next‐generation wearable electronics/photonics are provided, that is, toward multifunctional, self‐sustainable, and intelligent wearable systems in the AI/IoT era.

show abstract

Section: Self‐sustainable Wearable Electronics Integrated With Energymentioning

confidence: 99%

Progress in wearable electronics/photonics—Moving toward the era of artificial intelligence and internet of things

Shi

Dong

et al. 2020

InfoMat

450

233

View full text Add to dashboard Cite

show abstract

“…Previously, people have used different functional materials to sense or emulate a wide range of mechanical stimuli such as pressure and strain, like piezoelectric materials, triboelectric materials, etc. [ 2 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 ]. However, the soft stretching capability is one of remaining issues to be overcome that is rather preferred for practical HMI applications as rigid materials are incompatible to the skins, uncomfortable to wear, and lacking of adaptability to the dynamic motion of human body [ 128 , 129 ].…”

Section: Enabled Hmi Applicationsmentioning

confidence: 99%

Metamaterials-Enabled Sensing for Human-Machine Interfacing

2020

Sensors

View full text Add to dashboard Cite

Our modern lives have been radically revolutionized by mechanical or electric machines that redefine and recreate the way we work, communicate, entertain, and travel. Whether being perceived or not, human-machine interfacing (HMI) technologies have been extensively employed in our daily lives, and only when the machines can sense the ambient through various signals, they can respond to human commands for finishing desired tasks. Metamaterials have offered a great platform to develop the sensing materials and devices from different disciplines with very high accuracy, thus enabling the great potential for HMI applications. For this regard, significant progresses have been achieved in the recent decade, but haven’t been reviewed systematically yet. In the Review, we introduce the working principle, state-of-the-art sensing metamaterials, and the corresponding enabled HMI applications. For practical HMI applications, four kinds of signals are usually used, i.e., light, heat, sound, and force, and therefore the progresses in these four aspects are discussed in particular. Finally, the future directions for the metamaterials-based HMI applications are outlined and discussed.

show abstract

“…Artificial intelligence (AI) techniques will highly amplify the intelligence of wearable electronics, and provide more reliable yet simpler solutions to more problems and resonating tasks. The conventional method of analyzing sensory information was limited in the ability of handling natural data, which relies on the manual extraction of shallow features from the raw data [53][54][55][56] . For decades, as a subfield of machine learning, deep learning has shown its great potential in image processing, speech recognition, human activity recognition, and so on, which provides an efficient way to learn higher-level features of the raw input from various sensing signals [57][58][59][60] .…”

Section: Introductionmentioning

confidence: 99%

Deep learning-enabled triboelectric smart socks for IoT-based gait analysis and VR applications

et al. 2020

View full text Add to dashboard Cite

The era of artificial intelligence and internet of things is rapidly developed by recent advances in wearable electronics. Gait reveals sensory information in daily life containing personal information, regarding identification and healthcare. Current wearable electronics of gait analysis are mainly limited by high fabrication cost, operation energy consumption, or inferior analysis methods, which barely involve machine learning or implement nonoptimal models that require massive datasets for training. Herein, we developed low-cost triboelectric intelligent socks for harvesting waste energy from low-frequency body motions to transmit wireless sensory data. The sock equipped with self-powered functionality also can be used as wearable sensors to deliver information, regarding the identity, health status, and activity of the users. To further address the issue of ineffective analysis methods, an optimized deep learning model with an end-to-end structure on the socks signals for the gait analysis is proposed, which produces a 93.54% identification accuracy of 13 participants and detects five different human activities with 96.67% accuracy. Toward practical application, we map the physical signals collected through the socks in the virtual space to establish a digital human system for sports monitoring, healthcare, identification, and future smart home applications.

show abstract

Triboelectric vibration sensor for a human-machine interface built on ubiquitous surfaces

Cited by 111 publications

References 18 publications

Progress in wearable electronics/photonics—Moving toward the era of artificial intelligence and internet of things

Progress in wearable electronics/photonics—Moving toward the era of artificial intelligence and internet of things

Metamaterials-Enabled Sensing for Human-Machine Interfacing

Deep learning-enabled triboelectric smart socks for IoT-based gait analysis and VR applications

Contact Info

Product

Resources

About