使用嵌入式机器学习进行步行步伐长度估计
Joeri R Verbiest1,2, Bruno Bonnechère2,3, Wim Saeys4
1Department of Sciences and Technology, Karel de Grote (KdG) University of Applied Sciences and Arts, 2660 Antwerp, Belgium.
Sensors (Basel, Switzerland)
|August 26, 2023
概括
这项研究开发了嵌入式机器学习模型,用于估计微控制器上的步伐步伐长度. int8模型以最小的内存实现了高精度,从而实现了设备上的步态分析.
科学领域:
- 生物医学工程 生物医学工程
- 可穿戴技术可穿戴技术
- 机器学习 机器学习
背景情况:
- 传统的步态分析依赖于基于实验室的仪器仪表.
- 现有的可穿戴步态评估设备资源有限,限制了设备上的机器学习.
- 嵌入式机器学习 (tinyML) 为微控制器上的处理提供了一个解决方案.
研究的目的:
- 开发一个机器学习模型用于步行步伐长度估计.
- 创建一个可以在资源有限的微控制器上部署的模型.
- 通过可穿戴传感器实现直接在设备上进行步态分析.
主要方法:
- 使用了来自15名健康个体的4467步步的数据集.
- 开发了一个多层1D卷积神经网络 (CNN).
- 使用MLOps工具创建了float32和int8精度模型.
主要成果:
- int8模型实现了0.07±4.3厘米的平均准确度和精度.
- int8型号只需要91.6kB的闪存和13.6kB的RAM.
- 这两种模型都在Cortex-M4F微控制器上成功部署.
结论:
- 直接在微控制器上估计步伐步伐长度是可行的.
- 嵌入式机器学习 (tinyML) 对可穿戴步态分析设备具有重大潜力.
- 这种方法提高了资源有限的可穿戴传感器的能力.
相关概念视频
Machines: Problem Solving I
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
Machines: Problem Solving II
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.


