中文版 | English
题名

基于柔性压力传感器的人体动作识别研究

其他题名
RESEARCH ON HUMAN ACTION RECOGNITION BASED ON FLEXIBLE PRESSURE SENSOR
姓名
姓名拼音
SUN Ran
学号
12132567
学位类型
硕士
学位专业
0856 材料与化工
学科门类/专业学位类别
0856 材料与化工
导师
王磊
导师单位
中国科学院深圳先进技术研究院
论文答辩日期
2023-05-15
论文提交日期
2023-07-06
学位授予单位
南方科技大学
学位授予地点
深圳
摘要
人体动作识别技术可以应用于许多领域,如医疗保健、运动、娱乐和安全等。 当下的传感器技术和计算机技术正在快速发展和进步,推动了基于传感器的人体 动作识别的发展。基于计算机视觉的人体动作识别研究已经取得了不错的效果,但 是视觉信息容易受环境光线等外界因素影响,因此需要其他途径实现人体动作识 别。基于压力传感器的人体动作识别是其中一种方法,其原理是利用在身体各个 位置的压力传感器来检测和记录身体的变化和动作。对这些数据进行分析和识别, 可以了解人体的动作模式和习惯,从而实现对人体的监测和防护。但市面上目前 仍然较为缺乏一种高性能、低成本、制造简单的压力传感器,同时缺乏相应的深度学习算法来实现基于压力传感信号的人体动作识别。
基于上述需求,本文基于一种柔性苯基硅和碳纳米管组成的柔性压力传感器构建人体动作识别系统。该传感器通过采用简单的微针滚动和电泳工艺,实现了 特殊的裂纹-孔洞结构,具有稳定可靠、高灵敏、宽线性范围和响应范围等优点。使 用该传感器构建了一个人体动作识别数据集,该数据集包含 15 7482 个动作。在 该数据集的基础上,本文研究了四种常见的深度学习算法,并提出了一种适合短 信号分类的低秩注意力 Transformer 深度学习网络模型,该模型在该数据集上达到 了 87.81% 的精度。与 Transformer 相比,该网络有效降低了训练时间和显存占用, 适合在未来边缘设备上使用。实验验证了本方法的有效性。
关键词
语种
中文
培养类别
独立培养
入学年份
2021
学位授予年份
2023-06
参考文献列表

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材料与化工
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条目标识符http://sustech.caswiz.com/handle/2SGJ60CL/545128
专题中国科学院深圳理工大学(筹)联合培养
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孙然. 基于柔性压力传感器的人体动作识别研究[D]. 深圳. 南方科技大学,2023.
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