一个概率模型的人类活动识别与宽松的衣服
Tianchen Shen1, Irene Di Giulio2, Matthew Howard1
1Centre for Robotics Research, Department of Engineeing, King's College London, London WC2R 2LS, UK.
Sensors (Basel, Switzerland)
|July 11, 2023
概括
与刚性传感器相比,基于织品的传感器提供了更高的人类活动识别精度. 这是由于运动之间的统计距离增加,在短时间窗口中提高性能.
科学领域:
- 可穿戴式传感技术是可以穿戴的.
- 人类活动识别 人类活动识别
- 电子织品 电子织品
背景情况:
- 身体上可穿戴的传感器对于识别人类活动至关重要.
- 在服装中集成的基于织品的传感器提供了舒适的,长期的运动记录.
- 令人惊的是,连接到衣服上的传感器在准确性方面可以超过刚性传感器,特别是在短时间窗口.
研究的目的:
- 提出一个概率模型,解释织物附着传感器的增强精度.
- 调查织传感器响应性和准确性的提高背后的原因.
- 通过模拟和现实世界的实验来验证模型的预测.
主要方法:
- 开发用于织物传感的概率模型.
- 分析传感器记录的运动之间的统计距离.
- 模拟和真实的人类运动捕捉实验与多个参与者.
主要成果:
- 概率模型解释了通过织物传感提高的准确性.
- 织物连接的传感器在0.5秒的窗口大小下实现了比刚性连接的传感器高67%的准确性.
- 模型预测得到了实验数据的证实.
结论:
- 基于织品的传感器为人类活动识别提供了更准确,更快速的方法.
- 织物传感器准确度更高的反直觉效应是由增加的统计运动距离解释的.
- 舒适的,集成的织物传感器代表着可穿戴传感技术的有希望的进步.
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