Self-Powered Intelligent Human-Machine Interaction for Handwriting Recognition

Guo, Hang; Wan, Ji; Wang, Haobin; Wu, Hao; Chen, Xu; Miao, Liming; Han, Mengdi; Zhang, Haixia

doi:10.34133/2021/4689869

Cited by 31 publications

(11 citation statements)

References 56 publications

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“…Triboelectric. The emerging TENG, which can readily convert mechanical energy into electrical energy by coupling triboelectrification and electrostatic induction, has been extensively explored to realize self-powered sensing and energy harvesting [129][130][131][132][133][134][135]. TENGs have four types of working modes, e.g., contact-separation mode, sliding mode, freestanding mode, and single electrode mode [136].…”

Section: Mechanoresistive Mechanoresistive Sensors Enable Conversion ...mentioning

confidence: 99%

Emerging Iontronic Sensing: Materials, Mechanisms, and Applications

et al. 2022

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Iontronic sensors represent a novel class of soft electronics which not only replicate the biomimetic structures and perception functions of human skin but also simulate the mechanical sensing mechanism. Relying on the similar mechanism with skin perception, the iontronic sensors can achieve ion migration/redistribution in response to external stimuli, promising iontronic sensing to establish more intelligent sensing interface for human-robotic interaction. Here, a comprehensive review on advanced technologies and diversified applications for the exploitation of iontronic sensors toward ionic skins and artificial intelligence is provided. By virtue of the excellent stretchability, high transparency, ultrahigh sensitivity, and mechanical conformality, numerous attempts have been made to explore various novel ionic materials to fabricate iontronic sensors with skin-like perceptive properties, such as self-healing and multimodal sensing. Moreover, to achieve multifunctional artificial skins and intelligent devices, various mechanisms based on iontronics have been investigated to satisfy multiple functions and human interactive experiences. Benefiting from the unique material property, diverse sensing mechanisms, and elaborate device structure, iontronic sensors have demonstrated a variety of applications toward ionic skins and artificial intelligence.

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Section: Mechanoresistive Mechanoresistive Sensors Enable Conversion ...mentioning

confidence: 99%

Emerging Iontronic Sensing: Materials, Mechanisms, and Applications

et al. 2022

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“…Ergonomic technology has penetrated into all aspects of life. Handwriting digital recognition technology belongs to the category of artificial intelligence, handwriting digit recognition is a traditional number recognition technology, and digital recognition technology is a typical pattern recognition [2] problem. Pattern recognition uses computer algorithms to automatically process and interpret images, and automatic pattern recognition is automatically pattern recognition by the machine without human intervention.…”

Section: Introductionmentioning

confidence: 99%

Research on handwriting recognition method based on machine learning

Yang

Kong

2023

Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022)

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Handwritten digit recognition is a process of identifying 0-9 ten digits handwritten by human hands, and its related research has always been a hot topic in the field of machine learning classification. In order to explore the accuracy of the classification recognition of handwriting bodies by K nearest neighbor classifier and MLP multilayer perceptron, this paper first introduces the relevant algorithm principle and its research progress, and then experiments on K nearest neighbor classifier and MLP multilayer perceptron, and summarizes the relevant experimental data. Experiments show that in the K nearest neighbor algorithm, the classification accuracy is the highest when the number of neighbors K=3; For the MLP multilayer perceptron algorithm, the classification rate is higher when the number of neurons is larger, the number of iterations is 1000, and the learning rate is smaller.

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“…Based on the coupling effect of triboelectric and electrostatic induction, the TENG can output external mechanical stimuli as electrical signals [11,12]. TENG-based sensors work without an external power supply or batteries [13][14][15][16][17][18]. The TENG provides a new prospect for motion monitoring based on its own advantages of portability and environmental protection [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

A Portable and Low-Cost Triboelectric Nanogenerator for Wheelchair Table Tennis Monitoring

et al. 2022

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With progress in fifth-generation techniques, more advanced techniques are available for disabled people. Disability table tennis has also benefited from the new technology. In this paper, a portable and low-cost triboelectric nanogenerator for wheelchair table tennis monitoring systems is proposed. It was applied for wheelchair table tennis athletes’ monitoring. The portable and low-cost triboelectric nanogenerator consists of Kapton, polyurethane triboelectric films, and a foam supporting layer. The materials have flexible and low-cost characteristics. Therefore, the device has no influence on exercise performance. Due to triboelectric and electrostatic induction, the portable and low-cost triboelectric nanogenerator can convert biomechanical signals into electric signals. The electric signal is used as a sensing signal and is transformed in a computer by an Analog-to-Digital acquisition module. The coach acquires motion information in real time from a terminal device regarding force, exercise amplitude, and stability of the athlete. Meanwhile, the electric signal provides also sustainable energy for the microelectronic device. It can light 20 LEDs easily and power a calculator and a watch. This portable and low-cost self-powered triboelectric nanogenerator offers a new approach to the field of motion monitoring for disabled people.

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Self-Powered Intelligent Human-Machine Interaction for Handwriting Recognition

Cited by 31 publications

References 56 publications

Emerging Iontronic Sensing: Materials, Mechanisms, and Applications

Emerging Iontronic Sensing: Materials, Mechanisms, and Applications

Research on handwriting recognition method based on machine learning

A Portable and Low-Cost Triboelectric Nanogenerator for Wheelchair Table Tennis Monitoring

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