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The Health & Physical Education Logger (HPE Logger) makes it convenient to acquire motion sensor signals for data analysis in your exercise and sport research/study

HPE Logger

by Kratos Digital Limited

What is it about?

The Health & Physical Education Logger (HPE Logger) makes it convenient to acquire motion sensor signals for data analysis in your exercise and sport research/study.

App Details

Version
1.0
Rating
NA
Size
4Mb
Genre
教育 運動
Last updated
February 6, 2018
Release date
February 6, 2018
More info

App Store Description

The Health & Physical Education Logger (HPE Logger) makes it convenient to acquire motion sensor signals for data analysis in your exercise and sport research/study.

The HPE Logger aims at facilitating data acquisition of sports science with the portability & convenience of smartphone form factor.

For example, the acceleration data allows you to analyse the performance of your running & jumping exercises. The rotation rate & attitude data allow you to evaluate the performance of activities like sit-up, sit-and-reach, etc.


The HPE Logger logs the following motion and activity data:
- Acceleration (X, Y, Z); Unit: g
- Rotation Rate (RX, RY, RZ); Unit: rad/s
- Attitude (Roll, Pitch, Yaw); Unit: radian
- GPS (longitude, latitude, altitude)
- Steps count (cumulative)

Added Features:
- Variable sampling freq. (1-30Hz) for different purposes
- Pre-filtered (moving average) data for quick data analysis purpose
- Also logs unfiltered data for validation
- Real time data sample display (at 1/4 second interval)
- “Slide to start/stop” operation to prevent unintentional trigger during application

Convenient Log File Access & Management:
- The latest log file can be sent instantly via email
- All log files can be accessed and managed via iTunes “File Sharing” function (Connect your iOS device to iTunes -> Select your device within iTunes -> Select “Apps” -> Select “HPE Logger” under “File Sharing”)


Remarks
^ Continued use of GPS can dramatically decrease battery life.
# This App is intended for physical education research studies. The App is expected to stay in foreground during data acquisition. Knowledge in the data representation in relation to the smartphone orientation is expected.

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