Motion Gesture Delimiters for Smartwatch Interaction

被引:2
|
作者
Zhao, Yiming [1 ]
Zhao, Yanchao [1 ]
Tu, Huawei [2 ]
Huang, Qihan [1 ]
Zhao, Wenlai [1 ]
Jiang, Wenhao [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Comp Sci & Technol, Nanjing 211100, Jiangsu, Peoples R China
[2] La Trobe Univ, Dept Comp Sci & Informat Technol, Melbourne, Vic 3086, Australia
基金
中国国家自然科学基金;
关键词
36;
D O I
10.1155/2022/6879206
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Smartwatches are increasingly popular in our daily lives. Motion gestures are a common way of interacting with smartwatches, e.g., users can make a movement in the air with their arm wearing the watch to trigger a specific command of the smartwatch. Motion gesture interaction can compensate for the small screen size of the smartwatch to some extent and enrich smartwatch-based interactions. An important aspect of motion gesture interaction lies in how to determine the start and end of a motion gesture. This paper is aimed at selecting gestures as suitable delimiters for motion gesture interaction with the smartwatch. We designed six gestures ( "shaking wrist left and right, " "shaking wrist up and down, " "holding fist and opening, " "turning wrist clockwise, " "turning wrist anticlockwise, " and "shaking wrist up ") and conducted two experiments to compare the performance of these six gestures. Firstly, we used dynamic time warping (DTW) and feature extraction with KNN (K-nearest neighbors) to recognize these six gestures. The average recognition rate of the latter algorithm for the six gestures was higher than that of the former. And with the latter algorithm, the recognition rate for the first three of the six gestures was greater than 98%. According to experiment one, gesture 1 (shaking wrist left and right), gesture 2 (shaking wrist up and down), and gesture 3 (holding fist and opening) were selected as the candidate delimiters. In addition, we conducted a questionnaire data analysis and obtained the same conclusion. Then, we conducted the second experiment to investigate the performance of these three candidate gestures in daily scenes to obtain their misoperation rates. The misoperation rates of two candidate gestures ( "shaking wrist left and right " and "shaking wrist up and down ") were approximately 0, which were significantly lower than that of the third candidate gesture. Based on the above experimental results, gestures "shaking wrist left and right " and "shaking wrist up and down " are suitable as motion gesture delimiters for smartwatch interaction.
引用
收藏
页数:11
相关论文
共 50 条
  • [41] Real Time Motion-Based Authentication for Smartwatch
    Lewis, Antwane
    Li, Yanyan
    Xie, Mengjun
    2016 IEEE CONFERENCE ON COMMUNICATIONS AND NETWORK SECURITY (CNS), 2016, : 380 - 381
  • [42] Tap 'n' Shake: Gesture-Based Smartwatch-Smartphone Communications System
    McGuckin, Steven
    Chowdhury, Soumyadeb
    Mackenzie, Lewis
    PROCEEDINGS OF THE 28TH AUSTRALIAN COMPUTER-HUMAN INTERACTION CONFERENCE (OZCHI 2016), 2016,
  • [43] On Gesture Combination: An Exploration of a Solution to Augment Gesture Interaction
    Delamare, William
    Silpasuwanchai, Chaklam
    Sarcar, Sayan
    Shiraki, Toshiaki
    Ren, Xiangshi
    PROCEEDINGS OF THE 2019 ACM INTERNATIONAL CONFERENCE ON INTERACTIVE SURFACES AND SPACES (ISS '19), 2019, : 135 - 146
  • [44] Control with Gestures: A Hand Gesture Recognition System Using Off-the-Shelf Smartwatch
    Zhu, Peide
    Zhou, Hao
    Cao, Shumin
    Yang, Panlong
    Xue, Shuangshuang
    2018 4TH INTERNATIONAL CONFERENCE ON BIG DATA COMPUTING AND COMMUNICATIONS (BIGCOM 2018), 2018, : 72 - 77
  • [45] Gesture-Based Interaction: Visual Gesture Mapping
    Rise, Kasper
    Alsos, Ole Andreas
    HUMAN-COMPUTER INTERACTION. MULTIMODAL AND NATURAL INTERACTION, HCI 2020, PT II, 2020, 12182 : 106 - 124
  • [46] Smartwatch User Interface Implementation Using CNN-Based Gesture Pattern Recognition
    Kwon, Min-Cheol
    Park, Geonuk
    Choi, Sunwoong
    SENSORS, 2018, 18 (09)
  • [47] Application of 3D Reconstruction and Leap Motion Gesture Interaction in Virtual Assembly System
    Wan, Youteng
    Wang, Dayong
    Zhao, Juan
    PROCEEDINGS OF THE WORLD CONFERENCE ON INTELLIGENT AND 3-D TECHNOLOGIES, WCI3DT 2022, 2023, 323 : 639 - 647
  • [48] Human hand gesture recognition using motion orientation histogram for interaction of handicapped persons with computer
    Vafadar, Maryam
    Behrad, Alireza
    IMAGE AND SIGNAL PROCESSING, 2008, 5099 : 378 - 385
  • [49] Beat gesture recognition and finger motion control of a piano playing robot for affective interaction of the elderly
    Park, Kwang-Hyun
    Jeong, Sung-Hoon
    Pelczar, Christopher
    Bien, Z. Zenn
    INTELLIGENT SERVICE ROBOTICS, 2008, 1 (03) : 185 - 193
  • [50] Beat gesture recognition and finger motion control of a piano playing robot for affective interaction of the elderly
    Kwang-Hyun Park
    Sung-Hoon Jeong
    Christopher Pelczar
    Z. Zenn. Bien
    Intelligent Service Robotics, 2008, 1 : 185 - 193