Suzuki Ryoji, Otake Sakuko, Izutsu Takeshi, Yoshida Masaki, Iwaya Tsutomu
Department of Biomedical Engineering, Osaka Electro-Communication University, 1130-70 Kiyotaki, Shijonawate, Osaka 575-0063, Japan.
Telemed J E Health. 2006 Apr;12(2):146-55. doi: 10.1089/tmj.2006.12.146.
We examined whether we could identify activity patterns of elderly people in a nursing home from sensor outputs of an infrared monitoring system. The subjects consisted of three elderly people. A single passive infrared sensor installed on the ceiling of each subject's usual dwelling room provided digital output whenever the subject moved. The subjects' actual daily activities were established from questionnaires with which patients documented their living patterns for each of 7 days. Activities were classed as sleeping, getting up/breakfast, indoor activities/going out, and dinner/going to bed. The mean +/- 2 standard deviations (SDs) of the sensor outputs on each day for each period of indoor activity was used to distinguish between normal and aberrant activities. Days on which sensor outputs exceeded the means +/- 2 SDs were regarded as atypical and were identified for each subject over a 28-day period. We were unable to determine the physical condition of the subjects on these atypical days. We were able to identify the pattern of daily indoor living activities and the duration of each class of activity using sensor outputs and a questionnaire. Days were assumed to be atypical when sensor outputs deviated from the normal pattern.
我们研究了能否从红外监测系统的传感器输出中识别养老院中老年人的活动模式。研究对象包括三名老年人。在每位受试者常用起居室的天花板上安装一个被动红外传感器,每当受试者移动时,该传感器就会提供数字输出。通过问卷调查确定受试者的实际日常活动,患者需用问卷记录他们7天中每一天的生活模式。活动分为睡觉、起床/吃早餐、室内活动/外出以及晚餐/上床睡觉。每个室内活动时间段每天传感器输出的均值±2标准差(SD)用于区分正常活动和异常活动。在28天的时间里,传感器输出超过均值±2 SD的日子被视为非典型日,并针对每个受试者进行识别。在这些非典型日,我们无法确定受试者的身体状况。我们能够利用传感器输出和问卷调查来识别日常室内生活活动模式以及每类活动的持续时间。当传感器输出偏离正常模式时,这些日子被假定为非典型日。