title: Recognition of sign language with an inertial sensor-based data glove.
abstract: Communication between people with normal hearing and hearing impairment is difficult. Recently, a variety of studies on sign language recognition have presented benefits from the development of information technology. This study presents a sign language recognition system using a data glove composed of 3-axis accelerometers, magnetometers, and gyroscopes. Each data obtained by the data glove is transmitted to a host application (implemented in a Window program on a PC). Next, the data is converted into angle data, and the angle information is displayed on the host application and verified by outputting three-dimensional models to the display. An experiment was performed with five subjects, three females and two males, and a performance set comprising numbers from one to nine was repeated five times. The system achieves a 99.26% movement detection rate, and approximately 98% recognition rate for each finger's state. The proposed system is expected to be a more portable and useful system when this algorithm is applied to smartphone applications for use in some situations such as in emergencies.
authors.affiliation: Department of Healthcare Engineering, Chonbuk National University, Deokjin-gu, Jeonju-si, Korea.
authors.forename: Kyung-Won
authors.initials: KW
authors.lastname: Kim
authors.affiliation: Department of Healthcare Engineering, Chonbuk National University, Deokjin-gu, Jeonju-si, Korea.
authors.forename: Mi-So
authors.initials: MS
authors.lastname: Lee
authors.affiliation: Division of Biomedical Engineering, Chonbuk National University, Korea.
authors.forename: Bo-Ram
authors.initials: BR
authors.lastname: Soon
authors.affiliation: Division of Biomedical Engineering, Chonbuk National University, Korea.|Research Center of Healthcare & Welfare Instrument for the Aged, Chonbuk National University, Korea.
authors.forename: Mun-Ho
authors.initials: MH
authors.lastname: Ryu
authors.affiliation: R&D Division, Chonbuk National University Automobile-parts & Mold Technology Innovation Center, Korea.
authors.forename: Je-Nam
authors.initials: JN
authors.lastname: Kim
mesh_terms: D000465:Algorithms; D006225:Hand; D006801:Humans; D009068:Movement; D010363:Pattern Recognition, Automated / Q000379:methods*; D056910:Republic of Korea; D012813:Sign Language; D014175:Translating
keywords: Data glove; accelerometer; inertial sensor; sign language recognition