Flexible Strain Sensors for Wearable Hand Gesture Recognition: From Devices to Systems

Si, Yuying; Chen, Sujie; Li, Ming; Li, Siying; Pei, Yisen; Guo, Xiaojun

doi:10.1002/aisy.202100046

Cited by 59 publications

(31 citation statements)

References 113 publications

(172 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When all of the sensors are stretched, the relative resistance changes linearly. The drastically increasing slope as the number of layers increases implies improved sensing performance [ 45 ]. The gauge factor ( GF ) is an important indicator for sensors that can be calculated by:

where R 0 is the initial resistance of the sensor, and R is a resistance measured during stretching, ε is the rate of change in length, L 0 is the initial length of the sensor, and L is the length during stretching.…”

Section: Resultsmentioning

confidence: 99%

Droplets Patterning of Structurally Integrated 3D Conductive Networks-Based Flexible Strain Sensors for Healthcare Monitoring

et al. 2022

View full text Add to dashboard Cite

Flexible strain sensors with significant extensibility, stability, and durability are essential for public healthcare due to their ability to monitor vital health signals noninvasively. However, thus far, the conductive networks have been plagued by the inconsistent interface states of the conductive components, which hampered the ultimate sensitivity performance. Here, we demonstrate structurally integrated 3D conductive networks-based flexible strain sensors of hybrid Ag nanorods/nanoparticles(AgNRs/NPs) by combining a droplet-based aerosol jet printing(AJP) process and a feasible transfer process. Structurally integrated 3D conductive networks have been intentionally developed by tweaking droplets deposition behaviors at multi-scale for efficient hybridization and ordered assembly of AgNRs/NPs. The hybrid AgNRs/NPs enhance interfacial conduction and mechanical properties during stretching. In a strain range of 25%, the developed sensor demonstrates an ideal gauge factor of 23.18. When real-time monitoring of finger bending, arm bending, squatting, and vocalization, the fabricated sensors revealed effective responses to human movements. Our findings demonstrate the efficient droplet-based AJP process is particularly capable of developing advanced flexible devices for optoelectronics and wearable electronics applications.

show abstract

Section: Resultsmentioning

confidence: 99%

Droplets Patterning of Structurally Integrated 3D Conductive Networks-Based Flexible Strain Sensors for Healthcare Monitoring

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Another work [30] related to 3D separable convolutional neural network for dynamic hand gesture recognition is used for recognizing the hand gesture. Another work [31] applied flexible strain sensors for wearable hand gesture recognition, which is the latest in this field of research. Further to the latest work-related hand gesture, the authors here [32] have applied deformable convolution neural networks.…”

Section: Related Workmentioning

confidence: 99%

Sign Language Recognition for Arabic Alphabets Using Transfer Learning Technique

Zakariah

Alotaibi

Koundal

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Sign language is essential for deaf and mute people to communicate with normal people and themselves. As ordinary people tend to ignore the importance of sign language, which is the mere source of communication for the deaf and the mute communities. These people are facing significant downfalls in their lives because of these disabilities or impairments leading to unemployment, severe depression, and several other symptoms. One of the services they are using for communication is the sign language interpreters. But hiring these interpreters is very costly, and therefore, a cheap solution is required for resolving this issue. Therefore, a system has been developed that will use the visual hand dataset based on an Arabic Sign Language and interpret this visual data in textual information. The dataset used consists of 54049 images of Arabic sign language alphabets consisting of 1500\ images per class, and each class represents a different meaning by its hand gesture or sign. Various preprocessing and data augmentation techniques have been applied to the images. The experiments have been performed using various pretrained models on the given dataset. Most of them performed pretty normally and in the final stage, the EfficientNetB4 model has been considered the best fit for the case. Considering the complexity of the dataset, models other than EfficientNetB4 do not perform well due to their lightweight architecture. EfficientNetB4 is a heavy-weight architecture that possesses more complexities comparatively. The best model is exposed with a training accuracy of 98 percent and a testing accuracy of 95 percent.

show abstract

“…13–16 Therefore, flexible sensors have broad application prospects in human motion monitoring, health management, biomedicine, electronic robots, and other fields. 17,18…”

Section: Introductionmentioning

confidence: 99%

Research status of polysiloxane-based piezoresistive flexible human electronic sensors

Zhang,

Li,

Wang

et al. 2023

RSC Adv.

View full text Add to dashboard Cite

show abstract

Flexible Strain Sensors for Wearable Hand Gesture Recognition: From Devices to Systems

Cited by 59 publications

References 113 publications

Droplets Patterning of Structurally Integrated 3D Conductive Networks-Based Flexible Strain Sensors for Healthcare Monitoring

Droplets Patterning of Structurally Integrated 3D Conductive Networks-Based Flexible Strain Sensors for Healthcare Monitoring

Sign Language Recognition for Arabic Alphabets Using Transfer Learning Technique

Research status of polysiloxane-based piezoresistive flexible human electronic sensors

Contact Info

Product

Resources

About