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基于足部惯性传感器的可穿戴电子设备在游戏应用中的设计与实现。

Design and Implementation of Foot-Mounted Inertial Sensor Based Wearable Electronic Device for Game Play Application.

作者信息

Zhou Qifan, Zhang Hai, Lari Zahra, Liu Zhenbo, El-Sheimy Naser

机构信息

School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China.

Geomatics Engineering Department, University of Calgary, Calgary, AB T2N 1N4, Canada.

出版信息

Sensors (Basel). 2016 Oct 21;16(10):1752. doi: 10.3390/s16101752.

Abstract

Wearable electronic devices have experienced increasing development with the advances in the semiconductor industry and have received more attention during the last decades. This paper presents the development and implementation of a novel inertial sensor-based foot-mounted wearable electronic device for a brand new application: game playing. The main objective of the introduced system is to monitor and identify the human foot stepping direction in real time, and coordinate these motions to control the player operation in games. This proposed system extends the utilized field of currently available wearable devices and introduces a convenient and portable medium to perform exercise in a more compelling way in the near future. This paper provides an overview of the previously-developed system platforms, introduces the main idea behind this novel application, and describes the implemented human foot moving direction identification algorithm. Practical experiment results demonstrate that the proposed system is capable of recognizing five foot motions, jump, step left, step right, step forward, and step backward, and has achieved an over 97% accuracy performance for different users. The functionality of the system for real-time application has also been verified through the practical experiments.

摘要

随着半导体行业的发展,可穿戴电子设备得到了不断发展,并在过去几十年中受到了更多关注。本文介绍了一种基于新型惯性传感器的足部可穿戴电子设备的开发与实现,该设备用于一种全新的应用:游戏。所介绍系统的主要目标是实时监测和识别人类足部的踩踏方向,并协调这些动作以控制游戏中的玩家操作。该系统扩展了现有可穿戴设备的应用领域,并在不久的将来引入了一种方便便携的媒介,以更引人入胜的方式进行锻炼。本文概述了先前开发的系统平台,介绍了这种新颖应用背后的主要思想,并描述了所实现的人类足部移动方向识别算法。实际实验结果表明,该系统能够识别五种足部动作,即跳跃、向左迈步、向右迈步、向前迈步和向后迈步,并且在不同用户中实现了超过97%的准确率。通过实际实验也验证了该系统在实时应用中的功能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c7a/5087537/5faf6bd04d33/sensors-16-01752-g001.jpg

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