The security of vulnerable senior citizens through dynamically sensed signal acquisition,Transactions on Emerging Telecommunications Technologies

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The security of vulnerable senior citizens through dynamically sensed signal acquisition
Transactions on Emerging Telecommunications Technologies ( IF 2.5 ) Pub Date : 2020-07-14 , DOI: 10.1002/ett.4037
Xuanming Wang ₁ , Gautam Srivastava ₂

Affiliation

Traditional signal recognition methods generally use biosensors for signal acquisition. With senior citizens, sensor signal acquisition will be affected by their movements. These signal fluctuations are large, and if the signal area cannot be fixed, it may result in problems such as data loss. The most important issue caused by data loss is the safety for vulnerable seniors. Therefore, here we study abnormal behavior recognition based on dynamic sensing. In this paper, we look to improve the problems that exist in traditional methods. Using the SW-520D sensor, activity signals of the elderly are first collected. By comparing the received signal strength sets, dynamic sensor data flow of the abnormal behavior for senior citizens can be determined. A multiple linear regression estimation method is used to solve the problem of data loss in dynamic sensor data flow environments. We obtain system parameter thresholds in both area isolation and segmentation using the stochastic resonance method. From this, a direct notch is constructed that enters the dynamic sensor data stream, and the interference component filtering of abnormal behavior signals is processed. The amplitude-frequency response feature extraction method is used for high-precision isolation and segmentation of abnormal behavior signal areas such as falls, improving the accuracy of senior behavior signal recognition, and realizing safety monitoring for the elderly. The improved method was used to identify the signals of abnormal behaviors of young people. The minimum recognition error rate was only 2%, the recognition accuracy rate was as high as 98%, and the calculation time was only 19 ms.

中文翻译：

通过动态感知信号采集保护弱势老年人的安全

传统的信号识别方法一般使用生物传感器进行信号采集。对于老年人来说，传感器信号的采集会受到他们的运动的影响。这些信号波动较大，如果信号区域不能固定，可能会导致数据丢失等问题。数据丢失造成的最重要问题是弱势老年人的安全。因此，这里我们研究基于动态感知的异常行为识别。在本文中，我们希望改进传统方法中存在的问题。使用 SW-520D 传感器，首先收集老年人的活动信号。通过比较接收到的信号强度集，可以确定老年人异常行为的动态传感器数据流。采用多元线性回归估计方法解决动态传感器数据流环境中的数据丢失问题。我们使用随机共振方法在区域隔离和分割中获得系统参数阈值。由此构造一个直接陷波进入动态传感器数据流，并对异常行为信号进行干扰分量滤波处理。幅频响应特征提取方法用于对跌倒等异常行为信号区域进行高精度隔离和分割，提高老年人行为信号识别的准确性，实现对老年人的安全监测。改进后的方法用于识别青少年异常行为的信号。最小识别错误率仅为2%，

更新日期：2020-07-14

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