WEARABLE GAIT DEVICE FOR LONG-TERM MONITORING

被引：1

作者：

Caciula, Ion ^{[1
]}

Ionita, Giorgian Marius ^{[1
]}

Coanda, Henri George ^{[1
]}

Coltuc, Dinu ^{[1
]}

Angelescu, Nicoleta ^{[1
]}

Albu, Felix ^{[1
]}

Hagiescu, Daniela ^{[2
]}

机构：

[1] Valahia Univ Targoviste, Dept Elect Telecommun & Energy Engn, Targoviste 130004, Romania

[2] Adv Slisys SRL, Bucharest 060104, Romania

来源：

JOURNAL OF SCIENCE AND ARTS | 2023年 / 03期

关键词：

Gait monitoring; data acquisition; ESP32; microcontroller; ICM-20948; module; power consumption; convolutional neural networks;

D O I：

10.46939/J.Sci.Arts-23.3-c01

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

This study describes a low-cost and easy to deploy gait monitoring system that uses an ESP32 microcontroller and an ICM-20948 module. The ESP32 microcontroller collects data from the ICM-20948 module and these data are used to train a convolutional neural network (CNN) to classify gait patterns into two categories: normal and pathological. The results show that the system can achieve a high accuracy for binary gait classification, being able to correctly classify 97.05% of the normal gait samples and 84.54% of the pathological gait samples. The power consumption of the devive was measured using a calibrated and dual-acquisition digital multimeter. The estimated operating time was around 12 hours, with a battery capacity of 1800 mAh LiPo type. Therefore, it could be used to track the gait of patients with neurological disorders or to assess the effectiveness of gait rehabilitation treatments.

引用

页码：791 / 802

页数：12

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