基于时间序列分析的独居老人活动量研究

为解决独居老人日常生活的监护问题, 提出一种基于时间序列分析与模糊模式识别的独居老人活动量研究方法。该方法将独居老人的日常活动量作为对独居老人生活状况监测的有效指标, 并利用时间序列分析对活动量时间序列建立预测模型, 利用模糊模式识别法鉴别活动量监测值与活动量预测值之间的差距, 当两者之间的差距超过正常范围时, 将预警信息反映给老人的监护人, 以便监护人对老人的生活状态是否异常予以关注。实验结果表明, 该方法对老人异常状态的识别准确率为96. 97%。从而为老人生活状况的研究提供了一种新的方法和途径。

Study of Activity Amount of Old People Living Alone Based on Time Series Analysis

To monitor the daily living of the old people living alone, a study of their activity amount based on time series analysis and fuzzy pattern recognition is proposed, in which the daily activity of the old people living alone is used as the effective index to monitor their living state. The predictive model for the activity amount time series is established by using random time series analysis. Using the fuzzy pattern recognition method, the difference between the amount of monitoring activity and the amount of forecast activity is identified. When the gap is more than the normal range, the warning information will be reflected to the guardian of the elderly. The result shows the accuracy rate of abnormal behavior recognition was 96. 97%. The study provides an alternative to activity amount monitoring of the old people.