Development of low cost screen-printed piezoresistive strain sensor for facial expressions recognition systems

2020 ◽  
Vol 234 ◽  
pp. 111440
Author(s):  
Noor Amalina Ramli ◽  
Anis Nurashikin Nordin ◽  
Norsinnira Zainul Azlan
Keyword(s):  
Facial Expressions ◽  
Low Cost ◽  
Strain Sensor ◽  
Recognition Systems ◽  
Facial Expressions Recognition ◽  
Screen Printed

Deep Balanced Learning for Long-tailed Facial Expressions Recognition

2021 ◽  
Author(s):  
Hongxiang Gao ◽  
Shan An ◽  
Jianqing Li ◽  
Chengyu Liu
Keyword(s):  
Facial Expressions ◽  
Facial Expressions Recognition

scholarly journals Deep learning based facial expressions recognition system for assisting visually impaired persons

2020 ◽  
Vol 9 (3) ◽  
pp. 1208-1219
Author(s):  
Hendra Kusuma ◽  
Muhammad Attamimi ◽  
Hasby Fahrudin
Keyword(s):  
Deep Learning ◽  
Facial Expressions ◽  
Visually Impaired ◽  
Learning Algorithm ◽  
Recognition System ◽  
Verbal Information ◽  
Deep Learning Algorithm ◽  
Facial Recognition System ◽  
Visually Impaired Persons ◽  
Facial Expressions Recognition

In general, a good interaction including communication can be achieved when verbal and non-verbal information such as body movements, gestures, facial expressions, can be processed in two directions between the speaker and listener. Especially the facial expression is one of the indicators of the inner state of the speaker and/or the listener during the communication. Therefore, recognizing the facial expressions is necessary and becomes the important ability in communication. Such ability will be a challenge for the visually impaired persons. This fact motivated us to develop a facial recognition system. Our system is based on deep learning algorithm. We implemented the proposed system on a wearable device which enables the visually impaired persons to recognize facial expressions during the communication. We have conducted several experiments involving the visually impaired persons to validate our proposed system and the promising results were achieved.

scholarly journals Separable convolutional neural networks for facial expressions recognition

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Andry Chowanda
Keyword(s):  
Neural Networks ◽  
Social Interactions ◽  
Facial Expressions ◽  
Convolutional Neural Networks ◽  
The Other ◽  
Computational Power ◽  
Facial Cues ◽  
Emotional Recognition ◽  
Testing Accuracy ◽  
Facial Expressions Recognition

AbstractSocial interactions are important for us, humans, as social creatures. Emotions play an important part in social interactions. They usually express meanings along with the spoken utterances to the interlocutors. Automatic facial expressions recognition is one technique to automatically capture, recognise, and understand emotions from the interlocutor. Many techniques proposed to increase the accuracy of emotions recognition from facial cues. Architecture such as convolutional neural networks demonstrates promising results for emotions recognition. However, most of the current models of convolutional neural networks require an enormous computational power to train and process emotional recognition. This research aims to build compact networks with depthwise separable layers while also maintaining performance. Three datasets and three other similar architectures were used to be compared with the proposed architecture. The results show that the proposed architecture performed the best among the other architectures. It achieved up to 13% better accuracy and 6–71% smaller and more compact than the other architectures. The best testing accuracy achieved by the architecture was 99.4%.

Flexible and Degradable Paper-Based Strain Sensor with Low Cost

2017 ◽  
Vol 5 (11) ◽  
pp. 10538-10543 ◽  
Author(s):  
Hanbin liu ◽  
Huie Jiang ◽  
Fei Du ◽  
Danping Zhang ◽  
Zhijian Li ◽  
...  
Keyword(s):  
Low Cost ◽  
Strain Sensor

Evaluation of a low-cost optical-fiber-based strain sensor

1999 ◽  
Author(s):  
D. C. Inder ◽  
M. A. Buckley ◽  
Tonguy Liu ◽  
Gerard F. Fernando
Keyword(s):  
Optical Fiber ◽  
Low Cost ◽  
Strain Sensor

Highly responsive screen-printed asymmetric pressure sensor based on laser-induced graphene

2021 ◽  
Author(s):  
Jiang Zhao ◽  
Jiahao Gui ◽  
Jinsong Luo ◽  
Jing Gao ◽  
Caidong Zheng ◽  
...  
Keyword(s):  
Pressure Sensor ◽  
Screen Printing ◽  
Large Scale ◽  
Low Cost ◽  
Pressure Sensors ◽  
High Sensitivity ◽  
Wearable Electronics ◽  
Integrated Sensor ◽  
Patterned Electrodes ◽  
Screen Printed

Abstract Graphene-based pressure sensors have received extensive attention in wearable devices. However, reliable, low-cost, and large-scale preparation of structurally stable graphene electrodes for flexible pressure sensors is still a challenge. Herein, for the first time, laser-induced graphene (LIG) powder are prepared into screen printing ink, and shape-controllable LIG patterned electrodes can be obtained on various substrates using a facile screen printing process, and a novel asymmetric pressure sensor composed of the resulting screen-printed LIG electrodes has been developed. Benefit from the 3D porous structure of LIG, the as-prepared flexible LIG screen-printed asymmetric pressure sensor has super sensing properties with a high sensitivity of 1.86 kPa−1, low detection limit of about 3.4 Pa, short response time, and long cycle durability. Such excellent sensing performances give our flexible asymmetric LIG screen-printed pressure sensor the ability to realize real-time detection of tiny body physiological movements (such as wrist pulse and pronunciation action). Besides, the integrated sensor array has a multi-touch function. This work could stimulate an appropriate approach to designing shape-controllable LIG screen-printed patterned electrodes on various flexible substrates to adapt the specific needs of fulfilling compatibility and modular integration for potential application prospects in wearable electronics.

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