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Your search keyword '"Feng, Zhiquan"' showing total 2 results
Start Over Author "Feng, Zhiquan" Topic cognitive load
2 results on '"Feng, Zhiquan"'

1. A Massage Area Positioning Algorithm for Intelligent Massage System.

Author

Zhou, Liran, Feng, Zhiquan, Cai, Zeyuan, Yang, Xiaohui, Ai, Changsheng, and Shao, Haiyan

Subjects
*MASSAGE, *COGNITIVE load, *ONLINE education, *ONLINE algorithms, *ALGORITHMS, *USER experience
Abstract

A growing number of studies have been conducted over the past few years on the positioning of daily massage robots. However, most methods used for research have low interactivity, and a systematic method should be designed for accurate and intelligent positioning, thus compromising usability and user experience. In this study, a massage positioning algorithm with online learning capabilities is presented. The algorithm has the following main innovations: (1) autonomous massage localization can be achieved by gaining insights into natural human-machine interaction behavior and (2) online learning of user massage habits can be achieved by integrating recursive Bayesian ideas. As revealed by the experimental results, combining natural human-computer interaction and online learning with massage positioning is capable of helping people get rid of positioning aids, reducing their psychological and cognitive load, and achieving a more desirable positioning effect. Furthermore, the results of the analysis of user evaluations further verify the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Published
2022
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2. FM: Flexible mapping from one gesture to multiple semantics.

Author

Feng, Zhiquan, Yang, Bo, Xu, Tao, Yang, Xiaohui, Chen, Zhenxiang, Xie, We, and Ai, Changsheng

Subjects
*CARTOGRAPHY, *SEMANTICS, *COGNITIVE load, *INFORMATION science, *INTERFACES (Physical sciences)
Abstract

Abstract An algorithm for flexible mapping (FM) from one gesture to multiple semantics in the same situational context is presented for the first time to reduce the cognitive and operating loads of an operator by using gesture commands. First, the foundation of the FM is built with the semantic-oriented difference features of behavior model (SDFBM) of the operator as implicit inputs. Second, the gesture–semantics FM algorithm and its extended process, namely, attribute classification for FM are proposed and implemented. Third, five commonly used gestures are designed to demonstrate the way a gesture is mapped to multiple semantics. Finally, several comparative experimental results are provided to demonstrate the superiority of the proposed methods to the state of the art. The main innovation of this study is that the same gesture in the same context can be mapped to several different semantics through the SDFBM feature recognition. This study provides an intelligent and natural interaction interface model for 3D platforms and key support for gesture-based implicit interaction design. The proposed algorithms are also tested or used in several applications, such as smart teaching interface and onboard vehicular systems and intelligent TV. [ABSTRACT FROM AUTHOR]

Published
2018
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