SensusFit reads your fitness data from Apple Health, analyses the data and presents if it to you in a visual way, helping you to monitor your fitness activity and track your progress over time and benchmark progress against peers
SensusFit Light
What is it about?
SensusFit reads your fitness data from Apple Health, analyses the data and presents if it to you in a visual way, helping you to monitor your fitness activity and track your progress over time and benchmark progress against peers.
App Screenshots
App Store Description
SensusFit reads your fitness data from Apple Health, analyses the data and presents if it to you in a visual way, helping you to monitor your fitness activity and track your progress over time and benchmark progress against peers.
SensusFit is a comprehensive, fitness dashboard, fitness diary and data analytics tool, enabling Apple Watch users. SensusFit provides Daily, Weekly, Monthly and Yearly fitness tracking at the touch of a bottom.
F-Score: SensusFit presents the F-Score system which aggregates your daily activity into a single number, easy to track and follow over time. F-Score utilizes an algorithm to allocate F Score Points for each of the 12 daily activities tracked by your Apple Watch, taking into account the intensity of the activities. The target is 100 points per day – reflecting the World Health Organisation (WHO) recommendations for daily physical activity for adults.
Analytics: SensusFit is a data analytics tool. SensusFit analyses your fitness and activity data over time and presents features such as: VO2max Cardio Test, Resting Heart Rate Analysis, Fitness Level Analysis and F-Score Analysis. Many more fitness data analytics features are coming soon.
Supported Features:
1. SensusFit Score
2. Steps
3. Distance
4. Number of Flights/Stairs
5. Stand Hours
6. Active Hours
7. Exercise Minutes
8. Moderate & Vigorous Intensity Minutes
9. Workouts
10. Active Energy
11. Resting Energy
12. Total Energy
13. Heart Rate Analysis
14. Sleep Analysis
15. Ranking System
16. Fitness Diary
17. Fitness Data Analytics
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