Context-Aware Delivery of Ecological Momentary Assessment

被引:16
作者
Aminikhanghahi, Samaneh [1 ]
Schmitter-Edgecombe, Maureen [2 ]
Cook, Diane J. [1 ]
机构
[1] Washington State Univ, Sch Elect Engn & Comp Sci, Pullman, WA 99163 USA
[2] Washington State Univ, Dept Psychol, Pullman, WA 99163 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
Activity recognition; activity transition; change detection algorithms; ecological momentary assessment (EMA); CHANGE-POINT DETECTION; PHYSICAL-ACTIVITY; NOTIFICATION; FRAMEWORK; HOME; EMA;
D O I
10.1109/JBHI.2019.2937116
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Ecological Momentary Assessment (EMA) is an in-the-moment data collection method which avoids retrospective biases and maximizes ecological validity. A challenge in designing EMA systems is finding a time to ask EMA questions that increases participant engagement and improves the quality of data collection. In this work, we introduce SEP-EMA, a machine learning-based method for providing transition-based context-aware EMA prompt timings. We compare our proposed technique with traditional time-based prompting for 19 individuals living in smart homes. Results reveal that SEP-EMA increased participant response rate by 7.19% compared to time-based prompting. Our findings suggest that prompting during activity transitions makes the EMA process more usable and effective by increasing EMA response rates and mitigating loss of data due to low response rates.
引用
收藏
页码:1206 / 1214
页数:9
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