1. 南京信息工程大学自动化学院
2. 南京航空航天大学仿生结构与材料防护研究所
3. 南京体育学院运动健康科学系
4. 南京体育学院奥林匹克学院
纸质出版:2019
移动端阅览
景元, 陈炜峰, 宋雅伟, 等. 基于多传感器的智能鞋设计[J]. 传感器与微系统, 2019,(4):100-103.
JING Yuan, CHEN Wei-feng, SONG Ya-wei, et al. Design of smart shoes based on multisensor[J]. 2019, (4): 100-103.
景元, 陈炜峰, 宋雅伟, 等. 基于多传感器的智能鞋设计[J]. 传感器与微系统, 2019,(4):100-103. DOI: 10.13873/J.1000-9787(2019)04-0100-04.
JING Yuan, CHEN Wei-feng, SONG Ya-wei, et al. Design of smart shoes based on multisensor[J]. 2019, (4): 100-103. DOI: 10.13873/J.1000-9787(2019)04-0100-04.
为了对人体足部的运动数据进行采集分析
研制了一种对足底压力及足部加速度和角速度数据进行采集的智能鞋系统。智能鞋除了鞋体本身外
包括压力鞋垫模块、无线传输模块和运动数据接收软件。智能鞋采集到足部运动数据后
通过蓝牙将数据发送到接收软件
并对运动数据进行显示和存储。通过多层长短期记忆(LSTM)网络对静坐、站立和行走三种基本的运动行为进行识别
实验验证了基于LSTM的运动行为识别模型的准确性
以及智能鞋所采集的运动数据的有效性
智能鞋可以用于进行人体运动行为识别的研究工作中。
In order to collect the data of human movements on foot and analyze
a smart shoe system is designed and implemented
which can collect plantar pressure
acceleration and angular velocity data. Besides the shoe body itself
the smart shoe system consists of pressure insole module
wireless transmission module and movement data receiving software. After movements data are collected
the data are transferred to receiving software through Bluetooth
then displayed on screen and stored. Through multi-layer long short-term memory( LSTM) network
the three kinds of actions can be identified
include sitting
standing and walking. The final experiment verifies that the LSTM recognition model is accuracy
the data collected through smart shoe is effective
and the smart shoes can be used in research of human action recognition.
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