arXiv cs.AI· Yanhua Zhao·· 14 小时前AI 评分18
基于环形膨胀CNN的智能鞋垫传感器数据活动识别
Activity Recognition from Smart Insole Sensor Data Using a Circular Dilated CNN
AI 导读
研究提出环形膨胀卷积神经网络（CDCNN），处理智能鞋垫压力、加速度计和陀螺仪的多模态时序数据，在四分类任务（站立、行走、坐、串联步态）的受试者独立评估中达到86.42%测试准确率。模型输入为160帧窗口、24通道（18路压力、3路加速度计、3路陀螺仪轴），并通过排列特征重要性揭示各传感器对分类的贡献分布。该方法可应用于智能鞋垫设计、健康监测与康复领域。
正文 · 原文
Abstract:Smart insoles equipped with pressure sensors, accelerometers, and gyroscopes offer a non-intrusive way of monitoring human gait and posture. We present an activity classification system based on a circular dilated convolutional neural network (CDCNN) that processes multi-modal time-series data from such insoles. The model operates on 160-frame windows with 24 channels (18 pressure, 3 accelerometer, 3 gyroscope axes), achieving 86.42% test accuracy in a subject-independent evaluation on a four-class task (Standing, Walking, Sitting, Tandem). Permutation feature importance reveals the distribution of contributions made by various sensors to the classification process. The proposed approach has potential applications in areas such as smart insole design, health monitoring, and rehabilitation.
| Comments: | Published in Current Directions in Biomedical Engineering |
| Subjects: | Machine Learning (cs.LG); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2603.04477 [cs.LG] |
| (or arXiv:2603.04477v2 [cs.LG] for this version) | |
| https://doi.org/10.48550/arXiv.2603.04477 arXiv-issued DOI via DataCite |
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| Journal reference: | Current Directions in Biomedical Engineering (2026) |
| Related DOI: | https://doi.org/10.1515/cdbme-2026-0267
DOI(s) linking to related resources |
Submission history
From: Yanhua Zhao [view email]
[v1]
Wed, 4 Mar 2026 15:27:14 UTC (1,281 KB)
[v2]
Sat, 24 Oct 2026 19:55:43 UTC (1,076 KB)
来源：arXiv cs.AI · arxiv.org