Service robot system with integration of wearable Myo armband for specialized hand gesture human–computer interfaces for people with disabilities with mobility problems. (July 2018)

• Record Type: Journal Article
• Authors: Ding, Ing-Jr; Lin, Rui-Zhi; Lin, Zong-Yi
• Is Part Of: Computers & electrical engineering. Volume 69(2018)
• Page Start: 815
• Page End: 827
• Publication Date: 2018-07
• Subjects: Myo armband -- Service robot vehicle -- Hand gesture HCIs -- Disabled people with mobility problems -- Identity recognition -- Support vector machine; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.02.041
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Hand gestures will become a mainstream method of manipulating human computer interfaces (HCIs). For disabled people with mobility problems, hand gesture-based HCIs should be specifically designed. To achieve effective hand gesture HCIs, this study integrated a mobile service robot platform, three-dimensional (3D) imaging sensors, and wearable Myo armband device. Four kernel techniques are presented: (1) Myo armband software development kit hand gesture recognition using a two-layer hierarchy scheme to significantly increase hand gesture command numbers, (2) identity recognition of users using clustering-based support vector machine classifiers with a designed root mean square surface electromyography (RMS-sEMG) feature, (3) robot vehicle navigation with effective obstacle avoidance using a conceptually simple and computationally fast approach, and (4) efficient vehicle positioning based on the face-detection information of the user provided from the 3D imaging sensor to receive the hand gestures commands of the user with disabilities.