Study on Human Motion Recognition Based on Random  Forest Algorithm and Multifunctional Triboelectric Sensor

doi:10.16046/j.cnki.issn2096-5680.2022.02.005

Journal of Hebei University of Water Resources and Electric Engineering ›› 2022, Vol. 32 ›› Issue (2): 29-34.DOI: 10.16046/j.cnki.issn2096-5680.2022.02.005

• Electrical Engineering Column • Previous Articles Next Articles

Study on Human Motion Recognition Based on Random Forest Algorithm and Multifunctional Triboelectric Sensor

LENG Han-song^1,2, ZHANG Feng-duo³, REN Li-jie⁴, YANG Da-wei⁴, WANG Zhi-hua^1,2

1. School of Electrical Engineering, Hebei University of Technology, 300401, Tianjin, China;
2. State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, 300401, Tianjin, China;
3. State Grid Shandong Electric Power Company Jinan Licheng District Power Supply Company, 250000, Jinan, Shandong, China;
4. Bohai Equipment Chengde Petroleum Machinery Co., Ltd., 067000, Chengde, Hebei, China

Received:2021-12-14 Revised:2022-01-16 Online:2022-06-30 Published:2023-10-27

基于随机森林算法和摩擦起电传感器的人体运动识别研究

冷寒松^1,2, 张丰铎³, 任立杰⁴, 杨大伟⁴, 王志华^1,2

1.河北工业大学电气工程学院,天津市北辰区西平道5340号 300401;
2.河北工业大学省部共建电工装备可靠性与智能化国家重点实验室,天津市北辰区西平道5340号 300401;
3.国网山东省电力公司济南市历城区供电公司,山东省济南市历下区华龙路31号 250000;
4.渤海石油装备承德石油机械有限公司,河北省承德市双桥区开发区西区四号 067000

通讯作者: 王志华(1982-),男,河南安阳人,副教授,从事新能源发电技术、柔性传感器技术研究。E-mail:wangzhihua@hebut.edu.cn
作者简介:冷寒松(1997-),男,河北隆化人,河北工业大学硕士研究生在读,从事柔性传感器技术研究。E-mail:hansongleng@163.com
基金资助:
国家自然科学基金项目(51775166);河北省引进留学人员优秀项目(CL201708)

Abstract

Abstract: Human motion sensors are key sensors in wearable devices, Internet of Things and other fields. Low-cost polymer multifunctional motion sensors have broad application prospects.Based on the principle of triboelectricity, polymer sensors can realize a variety of motion sensing. The analysis of the sensor structure and charge transfer law shows that it can effectively sense three-dimensional linear motion. The output voltage under different motion states such as running and walking is measured by fixing the sensor at the ankle of the testers. The range and standard deviation of the output voltage of some electrodes are selected as the characteristic quantities, and the random forest algorithm is used to analyze the characteristic quantities. The research results show that the accuracy of this method for walking and running recognition can reaches 98.3%, laying the foundation for the application of this type of sensor on wearable devices.

Key words: triboelectricity, multifunctional motion sensor, motion recognition, characteristic mass, random forest algorithm

摘要： 人体运动传感器是可穿戴设备、物联网等领域的关键传感器,低成本的聚合物多功能运动传感器有广阔的应用前景。基于摩擦起电原理,聚合物传感器可实现多种运动的感知。通过对传感器结构和电荷转移规律的分析,表明其可有效感知三维直线运动。将传感器固定在测试人员脚踝处,测得跑步和走路等不同运动状态下的输出电压。选择部分电极输出电压的极差和标准差作为特征量,采用随机森林算法对特征量进行分析,研究结果表明该方法对走路和跑步的识别准确率可达98.3%,为该型传感器在可穿戴设备上的应用奠定了基础。

关键词: 摩擦起电, 多功能运动传感器, 运动识别, 特征量, 随机森林算法

CLC Number:

TP212

LENG Han-song, ZHANG Feng-duo, REN Li-jie, YANG Da-wei, WANG Zhi-hua. Study on Human Motion Recognition Based on Random Forest Algorithm and Multifunctional Triboelectric Sensor[J]. Journal of Hebei University of Water Resources and Electric Engineering, 2022, 32(2): 29-34.

冷寒松, 张丰铎, 任立杰, 杨大伟, 王志华. 基于随机森林算法和摩擦起电传感器的人体运动识别研究[J]. 河北水利电力学院学报, 2022, 32(2): 29-34.

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Study on Human Motion Recognition Based on Random Forest Algorithm and Multifunctional Triboelectric Sensor

基于随机森林算法和摩擦起电传感器的人体运动识别研究

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