ON THE ARM SWING MODEL DURING HUMAN WALKING FOR WRIST-WORN ROTATIONAL ELECTRET ENERGY HARVESTER

被引：1
|
作者：
Miyoshi, Tomoya [1 ]
Mei, Xutao [1 ]
Suzuki, Yuji [1 ]
机构：
[1] Univ Tokyo, Dept Mech Engn, Tokyo, Japan
来源：
2023 22ND INTERNATIONAL CONFERENCE ON MICRO AND NANOTECHNOLOGY FOR POWER GENERATION AND ENERGY CONVERSION APPLICATIONS, POWERMEMS 2023 | 2023年
关键词：
Energy harvesting; Human walking; Arm swing; Electret; Random forest regression;
D O I：
10.1109/POWERMEMS59329.2023.10417423
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
In this report, a machine-learning model for a wrist-worn rotational electret energy harvester (REEH) is presented. By using random forest regression (RFR) on a motion capture dataset, an arm swing model is developed to predict the output power during human walking. Compared to conventional linear regression, the present model shows better agreement with the experimental data of seven subjects wearing a REEH with a wireless output power measurement system.
引用
收藏
页码：56 / 59
页数：4
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