eprintid: 4705
rev_number: 10
eprint_status: archive
userid: 364
dir: disk0/00/00/47/05
datestamp: 2022-03-21 00:29:24
lastmod: 2022-03-21 00:29:24
status_changed: 2022-03-21 00:29:24
type: conference_item
metadata_visibility: show
creators_name: Tran, Nhu Chi
creators_name: Nguyen, Dang Phu
creators_name: Nguyen, Thi Thanh Van
creators_name: Tran, Thi Thuy Ha
creators_name: Dau, Thanh Van
creators_name: Bui, Thanh Tung
creators_id: trannhuchi@vnu.edu.vn
creators_id: phund@vnu.edu.vn
creators_id: vanntt@vnu.edu.vn
creators_id: hatt@ptit.edu.vn
creators_id: v.dau@griffith.edu.au
creators_id: tungbt@vnu.edu.vn
title: A Sign Language Recognition System Using Ionic Liquid Strain Sensor
ispublished: pub
subjects: ECE
subjects: ElectronicsandComputerEngineering
divisions: cetr_uet
divisions: fac_fet
abstract: In this report, we develop a system converting sign language into voices and text. The system includes a glove attached self-developed ionic liquid-based strain sensors on each finger to detect the movement of them. When the hand move to express a letter lead to the resistance of the strain sensors on each finger change. Therefore, through the information from a set of sensors, the system can recognize the letter that user want to convey. A measuring and data acquisition circuit also are developed to receive and analyze data from the sensors. Furthermore, a data digitizing method is proposed as a solution for decoding purpose. The system is tested with 10 distinguished basic letters in American Sign Language table (ASL). The results show the accuracy of system is 98%. The system operates stably with the low power of 0.81W at rest state and 1.71W when working. Besides, applications on smartphone and PC are also built to translate the data into text and speech. These apps make it easier to communicate with deaf people. With achieved results, the system is fully extensible to detect more letters in ALS table in the future
date: 2021-12-10
date_type: completed
official_url: http://ismee.event.upi.edu/
full_text_status: public
pres_type: paper
event_title: 3 rd International Symposium on Materials and Electrical Engineering Virtual Conference
event_location: Bandung-Indonesia
event_dates: 10 – 11 November 2021
event_type: conference
refereed: TRUE
citation:   Tran, Nhu Chi and Nguyen, Dang Phu and Nguyen, Thi Thanh Van and Tran, Thi Thuy Ha and Dau, Thanh Van and Bui, Thanh Tung  (2021) A Sign Language Recognition System Using Ionic Liquid Strain Sensor.  In: 3 rd International Symposium on Materials and Electrical Engineering Virtual Conference, 10 – 11 November 2021, Bandung-Indonesia.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4705/1/1570765856_after%20review-4.pdf