Understanding practices and needs of researchers in human state modeling by passive mobile sensing
Understanding practices and needs of researchers in human state modeling by passive mobile sensing
复制标题
DOI:
10.1007/s42486-021-00072-4
复制
发表时间:
2021-07-06
影响因子:
2.1
通讯作者:
Dey AK
中科院分区:
文献类型:
--
作者:
Xu X;Mankoff J;Dey AK
Passive mobile sensing for the purpose of human state modeling is a fast-growing area. It has been applied to solve a wide range of behavior-related problems, including physical and mental health monitoring, affective computing, activity recognition, routine modeling, etc. However, in spite of the emerging literature that has investigated a wide range of application scenarios, there is little work focusing on the lessons learned by researchers, and on guidance for researchers to this approach. How do researchers conduct these types of research studies? Is there any established common practice when applying mobile sensing across different application areas? What are the pain points and needs that they frequently encounter? Answering these questions is an important step in the maturing of this growing sub-field of ubiquitous computing, and can benefit a wide range of audiences. It can serve to educate researchers who have growing interests in this area but have little to no previous experience. Intermediate researchers may also find the results interesting and helpful for reference to improve their skills. Moreover, it can further shed light on the design guidelines for a future toolkit that could facilitate research processes being used. In this paper, we fill this gap and answer these questions by conducting semi-structured interviews with ten experienced researchers from four countries to understand their practices and pain points when conducting their research. Our results reveal a common pipeline that researchers have adopted, and identify major challenges that do not appear in published work but that researchers often encounter. Based on the results of our interviews, we discuss practical suggestions for novice researchers and high-level design principles for a toolkit that can accelerate passive mobile sensing research.
登录
查看更多内容
影响因子:
64.8
作者:
Althoff T;Sosič R;Hicks JL;King AC;Delp SL;Leskovec J
通讯作者:
Leskovec J
DOI:
10.1145/3090051
发表时间:
2017-06-01
影响因子:
--
作者:
Bae, Sangwon;Ferreira, Denzil;Dey, Anind K
通讯作者:
Dey, Anind K
影响因子:
4.6
作者:
Bogomolov, Andrey;Lepri, Bruno;Pentland, Alex
通讯作者:
Pentland, Alex
影响因子:
2.9
作者:
Carreiro, Stephanie;Wittbold, Kelley;Boyer, Edward W.
通讯作者:
Boyer, Edward W.
影响因子:
5
作者:
Doryab, Afsaneh;Villalba, Daniella K.;Dey, Anind K.
通讯作者:
Dey, Anind K.