Dual-Mode Flexible Capacitive Sensor for Proximity-Tactile Interface and Wireless Perception

Qin, Yuxin; Xu, Hongcheng; Li, Siyu; Xu, Dingbang; Zheng, Weihao; Wang, Weidong; Gao, Libo

doi:10.1109/jsen.2022.3171218

Cited by 19 publications

(9 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The capacitive sensing mechanism endows these flexible sensors with the advantage of low power consumption, good dynamic response, and low susceptibility to temperature and humidity change compared to piezoresistive sensors. Uniquely, some piezocapacitive sensors present excellent proximity sensing ability under non-contact situations [ 73 – 76 ]. However, they are vulnerable to electromagnetic noises and the parasitic coupling with the surroundings needs to be carefully investigated and addressed, making it difficult in measuring and processing the capacitance data, especially in an array configuration.…”

Section: Working Mechanismsmentioning

confidence: 99%

Machine Learning-Enhanced Flexible Mechanical Sensing

et al. 2023

Self Cite

View full text Add to dashboard Cite

To realize a hyperconnected smart society with high productivity, advances in flexible sensing technology are highly needed. Nowadays, flexible sensing technology has witnessed improvements in both the hardware performances of sensor devices and the data processing capabilities of the device’s software. Significant research efforts have been devoted to improving materials, sensing mechanism, and configurations of flexible sensing systems in a quest to fulfill the requirements of future technology. Meanwhile, advanced data analysis methods are being developed to extract useful information from increasingly complicated data collected by a single sensor or network of sensors. Machine learning (ML) as an important branch of artificial intelligence can efficiently handle such complex data, which can be multi-dimensional and multi-faceted, thus providing a powerful tool for easy interpretation of sensing data. In this review, the fundamental working mechanisms and common types of flexible mechanical sensors are firstly presented. Then how ML-assisted data interpretation improves the applications of flexible mechanical sensors and other closely-related sensors in various areas is elaborated, which includes health monitoring, human–machine interfaces, object/surface recognition, pressure prediction, and human posture/motion identification. Finally, the advantages, challenges, and future perspectives associated with the fusion of flexible mechanical sensing technology and ML algorithms are discussed. These will give significant insights to enable the advancement of next-generation artificial flexible mechanical sensing.

show abstract

Section: Working Mechanismsmentioning

confidence: 99%

Machine Learning-Enhanced Flexible Mechanical Sensing

et al. 2023

Self Cite

View full text Add to dashboard Cite

show abstract

“…The piezoresistive [31] and piezocapacitive [32] based pressure sensors have high sensitivity for low-pressure applications. This makes it an intriguing tool for use in a variety of robotics applications, including robotic hand for human-machine interface [33], gait analysis [34], estimating deformed surface displacement from contact pressure distribution [35], and dead reckoning in a dynamic quadruped robot [36]. Unfortunately, the sensor's nature makes it susceptible to damage if directly exposed, therefore, it cannot be utilized in demanding situations or for a long duration.…”

Section: Sensor Casing Designs For Conformable Packagingmentioning

confidence: 99%

Conformable packaging of a soft pressure sensor for tactile perception

Das

Bhattacharjee

Thiyagarajan

et al. 2023

Flex. Print. Electron.

View full text Add to dashboard Cite

Humans can perceive surface properties of an unfamiliar object without relying solely on vision. One way to achieve it is by physically touching the object. This human-inspired tactile perception is a complementary skill for robotic tactile perception. Robot perception depends on the informational quality of the tactile sensor; thus, packaging sensors and integrating them with robots plays a crucial role. In this work, we investigate the influence of conformable packaging designs on soft polydimethylsiloxane (PDMS)-based flexible pressure sensors that work in a variety of surface conditions and load levels. Four different 3D printed packaging designs capable of maintaining sensor trends have been developed. The low detection limits of 0.7 kPa and 0.1 kPa in the piezoresistive and piezocapacitive sensors, respectively, remain unaffacted and a performance variation as low as 30 % is observed. Coefficient of variation and sensitivity studies have also been performed. Limit tests show that the designs can handle large forces ranging from 500 N to more than a 1000 N. Lastly, qualitative study was performed which covered prospective use-case scenarios as well as the advantages and downsides of each sensor casing design. Overall, the findings indicate that each sensor casing is distinct and best suited for tactile perception when interacting with objects, depending on surface properties.

show abstract

“…As an important part of them, mechanical sensors have been widely used in electronic skin, motion monitoring, smart medical care, and human-computer interaction of intelligent robots by virtue of their ability to convert mechanical signals (such as pressure and friction) into electrical signals. − In order to adapt to different application scenarios, a variety of pressure sensors have been proposed and fabricated. Generally, according to different sensing mechanisms, pressure sensors can be classified as piezoresistive, − capacitive, − piezoelectric, , and triboelectric , types. Among them, the piezoresistive pressure sensor has the characteristics of formidable sensing ability, low power consumption, a wide detection range, and a simple manufacturing process .…”

Section: Introductionmentioning

confidence: 99%

Flexible Multimodal Sensors Based on Fibrous Porous Networks of Multiwalled Carbon Nanotubes and Polydimethylsiloxane for Sensing and Distinguishing Vertical and Shear Force

Qin

Gao

Chen

et al. 2023

ACS Appl. Nano Mater.

View full text Add to dashboard Cite

Wearable sensors are one of the key components in applications such as motion monitoring, smart medical care, and human-computer interaction systems. In the present work, we focus on the simultaneous improvements of flexible sensors in both performance and functionality. Here, with a porous fiber network of multi-walled carbon nanotubes (MWCNTs)−polydimethylsiloxane (PDMS) as an active layer, a flexible pressure sensor with ultra-high sensitivity and superior capability of identifying transverse shear force and temperature signals is designed and constructed. The fibral MWCNTs−PDMS piezoresistive layer was formed with a scouring pad (SP) fiber network as skeleton, and the PDMS thin layer formed by self-assembly can effectively increase the initial resistance. Attributing to the unique compressibility of the fibral porous network and the adjustable nanoscale contacts, the MWCNT-PDMS/SP sensor exhibits a wide detection range (0−360 kPa), and in particular, an ultra-high sensitivity (84,818.2 kPa −1 when <100 pa). Beyond the highly sensitive characteristics, the sensor also has a high shear-force sensitivity (GF = 6.15 under 0.05 N). The sensor can still maintain a relatively stable performance even after operating for more than 10,000 pressure cycles, showing as a potential candidate for the applications of electronic skin, intelligent robots, etc.

show abstract

Dual-Mode Flexible Capacitive Sensor for Proximity-Tactile Interface and Wireless Perception

Cited by 19 publications

References 33 publications

Machine Learning-Enhanced Flexible Mechanical Sensing

Machine Learning-Enhanced Flexible Mechanical Sensing

Conformable packaging of a soft pressure sensor for tactile perception

Flexible Multimodal Sensors Based on Fibrous Porous Networks of Multiwalled Carbon Nanotubes and Polydimethylsiloxane for Sensing and Distinguishing Vertical and Shear Force

Contact Info

Product

Resources

About