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Validation of an Automatic Video Monitoring System for the Detection of Instrumental Activities of Daily Living in Dementia Patients

机译:用于痴呆症患者日常仪器活动检测的自动视频监控系统的验证

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Over the last few years, the use of new technologies for the support of elderly people and in particular dementia patients received increasing interest. We investigated the use of a video monitoring system for automatic event recognition for the assessment of instrumental activities of daily living (IADL) in dementia patients. Participants (19 healthy subjects (HC)and 19 mild cognitive impairment (MCI) patients) had to carry out a standardized scenario consisting of several IADLs such as making a phone call while they were recorded by 2D video cameras. After the recording session, data was processed by a platform of video signal analysis in order to extract kinematic parameters detecting activities undertaken by the participant. We compared our automated activity quality prediction as well as cognitive health prediction with direct observation annotation and neuropsychological assessment scores. With a sensitivity of 85.31% and a precision of 75.90%, the overall activities were correctly automatically detected. Activity frequency differed significantly between MCI and HC participants (p < 0.05). In all activities, differences in the execution time could be identified in the manually and automatically extracted data. We obtained statistically significant correlations between manually as automatically extracted parameters and neuropsychological test scores (p < 0.05). However, no significant differences were found between the groups according to the IADL scale. The results suggest that it is possible to assess IADL functioning with the help of an automatic video monitoring system and that even based on the extracted data, significant group differences can be obtained.
机译:在过去的几年中,使用新技术支持老年人尤其是痴呆症患者的兴趣日益浓厚。我们调查了视频监控系统用于自动事件识别的使用,以评估痴呆症患者的日常器械活动(IADL)。参与者(19位健康受试者(HC)和19位轻度认知障碍(MCI)患者)必须执行由几种IADL组成的标准化方案,例如在用2D摄像机记录时拨打电话。录制会话后,数据将通过视频信号分析平台进行处理,以提取检测参与者参加活动的运动学参数。我们将我们的自动活动质量预测以及认知健康预测与直接观察注释和神经心理学评估得分进行了比较。灵敏度为85.31%,精度为75.90%,可以正确地自动检测所有活动。 MCI和HC参与者之间的活动频率显着不同(p <0.05)。在所有活动中,可以在手动和自动提取的数据中识别执行时间的差异。我们获得了手动提取的自动参数与神经心理学测试成绩之间的统计显着相关性(p <0.05)。但是,根据IADL量表,两组之间没有发现显着差异。结果表明,可以借助自动视频监控系统评估IADL的功能,并且即使基于提取的数据,也可以获得明显的组差异。

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