An Instrumented Glove for Recognition of Brazilian Sign Language Alphabet

Dias, Thiago Simões; Mendes, José Jair Alves; Pichorim, Sérgio Francisco

doi:10.1109/jsen.2021.3136790

Cited by 18 publications

(3 citation statements)

References 30 publications

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“…The instrumented glove has five sensors, an inertial sensor, and two contact sensors and is designed with silver-coated fabric. Alpha-sign is intended to recognize the 26 letters of the alphabet [27].…”

Section: Introductionmentioning

confidence: 99%

IoT-based Flex Sensor Gloves for Immobility Patients: A Prototype

Azhari Zakri,

Yuliani Putri,

Romadoni

et al. 2024

Int. J. Adv. Sci. Eng. Inf. Technol.

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Immobility patients often experience difficulties in daily interactions, especially communicating with nurses or carers. This study designed a glove prototype installed with a tension sensor as a communication tool to help patients. The designed prototype, a cutting-edge innovation, is paired with five flexible sensors to make it easier for nurses to read the five-finger movement signals. This prototype is not just a tool but a lifeline, equipped with temperature and pulse sensors that provide real-time monitoring of the patient’s physical condition, enhancing patient safety. Testing of the flex sensor glove prototype is carried out by processing flex-sensor input data temperature sensors, and Pulse Oximeter sensors so that they can be displayed on the Blynk application. Every movement conveys the patient's emotions and is implemented with Arduino UNO; a wireless serial interface is used for data transmission between transmitter and receiver. In an emergency, communications will be transmitted using a GSM module. The flex sensor indentation is processed by Arduino-Nano and sent to the Blynk application. Every movement conveys the patient's emotions and is implemented with Arduino UNO; a wireless serial interface is used for data transmission between transmitter and receiver. In an emergency, communications will be transmitted using a GSM module. The results of the flex sensor test show that the prototype will send notifications in the form of requests to the Blynk application.

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Section: Introductionmentioning

confidence: 99%

IoT-based Flex Sensor Gloves for Immobility Patients: A Prototype

Azhari Zakri,

Yuliani Putri,

Romadoni

et al. 2024

Int. J. Adv. Sci. Eng. Inf. Technol.

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Section: Introductionmentioning

confidence: 99%

“…[30] Despite great achievement of sensing and recognition of gesture language, the reported smart gloves were still limited by the low recognition rate, poor biocompatible property, especially lack of the real-time feedback function. [31][32][33] Herein, we developed a smart glove system with sensingrecognition-feedback capabilities of gesture language, providing an effective new strategy for the hearing-impaired persons to commutate with the world. The silk-fibroin (SF)-based strain sensor showed excellent performance of high sensitivity, fast response time, good stability, and facile processing.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence–Enabled Gesture‐Language‐Recognition Feedback System Using Strain‐Sensor‐Arrays‐Based Smart Glove

Fang

Zhu

et al. 2023

Advanced Intelligent Systems

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Wearable smart glove of gesture language provides a novel strategy for the hearing‐impaired people to commutate with the world. Current commercialized solutions of gesture language are limited by the full extent of human interaction beyond operation dexterity, sensory feedback, and the huge cost of fabrication. Herein, a low‐cost, high‐efficient gesture‐language‐recognition feedback system combined with the strain‐sensor arrays and machine‐learning technology is proposed. The strain‐sensor arrays integrated with 3D‐printed glove can extract both spatial and temporal information about the finger's movement. The smart glove achieves gesture‐language recognition using machine learning with an accuracy of over 99%. Integrating with multidimensional manipulation, visual feedback and artificial intelligence (AI)‐based gesture‐language recognition, the smart system can accurately recognize complex gestures and provide real‐time feedback to users. The smart glove system can not only provide an efficient way for hearing‐impaired persons to communicate with the outside world, but also benefit industries in multiple fields such as entertainment, home healthcare, sports training, and the medical industry.

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