Personal health management during COVID-19

  • Last Update:December,17,2020 Created:December,17,2020
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Title of the dataset Personal health management during COVID-19
Provenance of the dataset School of Engineering, The University of Tokyo
How were the data collected/created? What was the cost? Data can be collected through a smart phone app that can monitor heart rate etc.
Data sharing policy Shareable for research purpose
Data sharing policy

About data analysis and simulation

Type of data: Check all that apply. Use "Other" to specify other types so that we can include them in further updates. number series
Variable labels of dataset (the names of the variables) Resting heart rate/ Day walking steps/ Daily sleeping time/ Body temperature
Outline of data During the COVID-19, people quarantined at home and lived in the form of online courses and remote work. Due to the long-term stay at home and the inability to go out regularly every day, people's physical health condition may change. Therefore, this Datajacket was created to observe people's daily work, rest and energy consumption, then it is able to judge people's health level during long-term isolation.
Simulation process Theoretical support and collection mechanism: The smartphone app uses the phone camera to test the blood flow speed of the finger to determine the resting heart rate, and then uses a series of algorithms to determine the activity of the human sympathetic nerve at testing time, then analyzes whether the human energy is balanced. In addition, the health status of the human body is comprehensively judged through the questionnaire of alcohol drinking, body temperature and sleep time every day.
Expected outcome of the process (obtained knowledge, analysis results, output of tools) The collection of this data is a long-term process. It is necessary to compare the historical data before the COVID-19 with the data during the epidemic period to analyze whether the human health will deteriorate due to long-term home isolation.In addition, it is also possible to explore whether there are other factors affecting health by monitoring the comparison of personal data and group data.
Anticipation for analyses/simulations other than the typical ones provided above Through the collection of human health data and a questionnaire survey on living habits, we may be able to derive some of the impact or changes brought about by the COVID-19 on people's overall lifestyle from this research, then we are able to think about factors other than health data. For example, remote work and online learning could bring more irregular work and rest or daliy schedule, but avoiding long-distance commuting also reduces people’s mental stress and the risk of virus infection in crowded places. Which of these two factors has a greater impact on human health, it is an interesting issue for researching.


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