Health program data analysis
Time: 2015
Total working time: 3 months
Team members: me (responsible for data collection and analysis) and one app engineer
Method: Mobile ethnography, Statistics
Domain: Fitness
“The whole project team is not familiar with those defined health indexes by our partner.”
“We can’t wait development finished to collect data.”
“60 participants joined the program.”
“Not only discovered the health data trends, but common issues should be described in the user manual.”
It is the first time the company decided to launch a wrist wearable device and targeted it for improving health purpose. We worked with external partners, but the whole project team is not familiar with those defined health indexes by our partner. And how to link those indexes with the monitored daily activities is a question as well. Since we already have workable samples, it is time to collect some real data from users and get their feedback.
Purpose
The whole development is ongoing, but we cannot wait for it finished, or it will be too late to collect feedback and modify the design. The device needs to link with an app to gain the whole function. However, the Android app backend is not finished to collect data automatically. It is one example of the challenge hence we need to find a way to test it and collect monitored raw data as more as possible. Trial reviews were conducted several times with app engineer before delivery device to participants to reduce errors and understand the limitation.
Challenge
Mobile ethnography:
We collect data via users' mobile phone. By using the wearable device and smartphone app to collect data. The incomplete Android backend data was collected manually and logged by google form. Users were asked to take photos while encountering problems.

Statistics:
To understand the correlation between each health index (age, heart rate, energy, body stress).   And to check the defined health program hypothesis. 60 participants joined the program and divided into two groups: one only do steps and sleep recording with health index measuring, the other one with extra breath training and follow the health tasks.
Method
The program discovered how health indexes trend goes in a day. The health program is working such as doing breath training before sleep helps people to use less time to obtain the same sleep quality and reduce toss&turns during sleep. And the program allows people to stay physically younger especially for those who over 40. 3052 ECG and 699 raw sleep data were collected for future analysis and make the algorithm more accurately. According to the user feedback, steps, calories, and heart rate they would like to view directly without connecting the app. The measured heart rate reading was added to the device directly. Through this research, we also found some common issues a user may encounter while using the device and recommend to add them in the user manual.
Outcome
The research spent five weeks to collect data and spent another four weeks on analyzing data and finishing the report. It’s a long run while development is continuing and not wait. Although the analysis did assist the project team to the next level, some valuable findings cannot include in the final product. A feedback system to related project team stakeholders during the research could be set to catch up with the existing development schedule. Hence, any result can pass to related project team members instead of waiting for the final report.
Lesson & Learn
Contact Lydia
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The health program
The health program
Purpose
It is the first time the company decided to launch a wrist wearable device and targeted it for improving health purpose. We worked with external partners, but the whole project team is not familiar with those defined health indexes by our partner. And how to link those indexes with the monitored daily activities is a question as well. Since we already have workable samples, it is time to collect some real data from users and get their feedback.
Challenge
The whole development is ongoing, but we cannot wait for it finished, or it will be too late to collect feedback and modify the design. The device needs to link with an app to gain the whole function. However, the Android app backend is not finished to collect data automatically. It is one example of the challenge hence we need to find a way to test it and collect monitored raw data as more as possible. Trial reviews were conducted several times with app engineer before delivery device to participants to reduce errors and understand the limitation.
Method
Mobile ethnography:
We collect data via users' mobile phone. By using the wearable device and smartphone app to collect data. The incomplete Android backend data was collected manually and logged by google form. Users were asked to take photos while encountering problems.

Statistics:
To understand the correlation between each health index (age, heart rate, energy, body stress).   And to check the defined health program hypothesis. 60 participants joined the program and divided into two groups: one only do steps and sleep recording with health index measuring, the other one with extra breath training and follow the health tasks.
Outcome
The program discovered how health indexes trend goes in a day. The health program is working such as doing breath training before sleep helps people to use less time to obtain the same sleep quality and reduce toss&turns during sleep. And the program allows people to stay physically younger especially for those who over 40. 3052 ECG and 699 raw sleep data were collected for future analysis and make the algorithm more accurately. According to the user feedback, steps, calories, and heart rate they would like to view directly without connecting the app. The measured heart rate reading was added to the device directly. Through this research, we also found some common issues a user may encounter while using the device and recommend to add them in the user manual.
Lesson & Learn
The research spent five weeks to collect data and spent another four weeks on analyzing data and finishing the report. It’s a long run while development is continuing and not wait. Although the analysis did assist the project team to the next level, some valuable findings cannot include in the final product. A feedback system to related project team stakeholders during the research could be set to catch up with the existing development schedule. Hence, any result can pass to related project team members instead of waiting for the final report.
Contact Lydia
View next
More works
“The whole project team is not familiar with those defined health indexes by our partner.”
“We can’t wait development finished to collect data.”
“60 participants joined the program.”
“Not only discovered the health data trends, but common issues should be described in the user manual.”
Health program data analysis
Time: 2015
Total working time: 3 months
Team members: me (responsible for data collection and analysis) and one app engineer
Method: Mobile ethnography, Statistics
Domain: Fitness
Health program data analysis
Time: 2015
Total working time: 3 months
Team members: me (responsible for data collection and analysis) and one app engineer
Method: Mobile ethnography, Statistics
Domain: Fitness
The health program
Purpose
It is the first time the company decided to launch a wrist wearable device and targeted it for improving health purpose. We worked with external partners, but the whole project team is not familiar with those defined health indexes by our partner. And how to link those indexes with the monitored daily activities is a question as well. Since we already have workable samples, it is time to collect some real data from users and get their feedback.
Challenge
The whole development is ongoing, but we cannot wait for it finished, or it will be too late to collect feedback and modify the design. The device needs to link with an app to gain the whole function. However, the Android app backend is not finished to collect data automatically. It is one example of the challenge hence we need to find a way to test it and collect monitored raw data as more as possible. Trial reviews were conducted several times with app engineer before delivery device to participants to reduce errors and understand the limitation.
Method
Mobile ethnography:
We collect data via users' mobile phone. By using the wearable device and smartphone app to collect data. The incomplete Android backend data was collected manually and logged by google form. Users were asked to take photos while encountering problems.

Statistics:
To understand the correlation between each health index (age, heart rate, energy, body stress).   And to check the defined health program hypothesis. 60 participants joined the program and divided into two groups: one only do steps and sleep recording with health index measuring, the other one with extra breath training and follow the health tasks.
Outcome
The program discovered how health indexes trend goes in a day. The health program is working such as doing breath training before sleep helps people to use less time to obtain the same sleep quality and reduce toss&turns during sleep. And the program allows people to stay physically younger especially for those who over 40. 3052 ECG and 699 raw sleep data were collected for future analysis and make the algorithm more accurately. According to the user feedback, steps, calories, and heart rate they would like to view directly without connecting the app. The measured heart rate reading was added to the device directly. Through this research, we also found some common issues a user may encounter while using the device and recommend to add them in the user manual.
Lesson & Learn
The research spent five weeks to collect data and spent another four weeks on analyzing data and finishing the report. It’s a long run while development is continuing and not wait. Although the analysis did assist the project team to the next level, some valuable findings cannot include in the final product. A feedback system to related project team stakeholders during the research could be set to catch up with the existing development schedule. Hence, any result can pass to related project team members instead of waiting for the final report.
View next
More works
Contact Lydia
“The whole project team is not familiar with those defined health indexes by our partner.”
“We can’t wait development finished to collect data.”
“60 participants joined the program.”
“Not only discovered the health data trends, but common issues should be described in the user manual.”