...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Computer Communications >Monitoring of human body running training with wireless sensor based wearable devices
【24h】

Monitoring of human body running training with wireless sensor based wearable devices

机译：基于无线传感器的可穿戴设备运行训练的人体监测

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

With the rapid pace of today's society, work pressure, less exercise time, people began to pay more attention to their health. Walking and running have become the first choice of moderate exercise for many young people. The recognition of human running state based on wireless acceleration sensor will play an increasingly important role in the fields of motion detection, energy consumption evaluation and health care. It is of great significance to develop and design a kind of wearable multi-functional wireless sensor which can monitor the running state of human body. In this paper, a wearable human body monitoring system based on wireless acceleration sensor technology is proposed for real-time monitoring of daily running volume of human body. Hardware and upper computer design: stm32f405 is used as the main control chip, and ma8451q is used to collect human motion data. In this paper, aiming at the problem that three kinds of motion states of human body are easy to be confused and difficult to distinguish, based on the in-depth study of the complex structure mode and self similarity characteristics of non-stationary acceleration signal, a method of human body motion state recognition based on single fractal and multi fractal is proposed. In this method, the fractal dimension and the generalized dimension are used as the feature variables, and the correlation judgment method is used to distinguish and recognize different motion states. Experiments show the validity and feasibility of single fractal and multifractal in walking and going up and down three kinds of motion state recognition. On the basis of multifractal motion state recognition, this paper combines fractal theory with wavelet multiresolution analysis, and proposes a matrix fractal human motion state recognition method based on wavelet transform. The fractal matrix based on wavelet transform quantifies the fractal characteristics of the component signals of walking and going up and down in different wavelet scales, and then describes the complexity and self similarity of the original acceleration signals. Experimental results show that the average recognition rate of walking, jogging and fast running can reach over 93% under the premise of less prior information.
机译：随着当今社会的快速速度，工作压力，较少的运动时间，人们开始更加关注他们的健康。走路和跑步已成为许多年轻人适度运动的首选。基于无线加速度传感器的人类运行状态的识别将在运动检测，能源消耗评估和医疗保健领域发挥越来越重要的作用。开发和设计一种可穿戴多功能无线传感器具有重要意义，可以监控人体的运行状态。本文提出了一种基于无线加速度传感器技术的可穿戴人体监测系统，用于实时监测人体日常运行量。硬件和上计算机设计：STM32F405用作主控制芯片，MA8451Q用于收集人类运动数据。在本文中，针对人体的三种运动状态易于混淆并且难以区分的问题，基于对非静止加速信号的复杂结构模式和自相似特性的深入研究，提出了一种基于单分形和多分形的人体运动状态识别方法。在该方法中，分形尺寸和广义尺寸用作特征变量，并且使用判断方法用于区分和识别不同的运动状态。实验表明，单一分形和多重术中的散步和上下三种运动状态识别的有效性和可行性。本文基于多重乳动作态识别，将分形理论与小波多分辨率分析结合，并提出了一种基于小波变换的基质分形人体运动状态识别方法。基于小波变换的分形矩阵量化了在不同小波尺度上行走和上下上下的分形信号的分形特征，然后描述了原始加速度信号的复杂性和自相似性。实验结果表明，在较少事先信息的前提下，步行，慢跑和快速运行的平均识别率可以达到93％以上。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号