Fitness Analytics

This page, which represents S4F’s report service, although it includes serious analyzes, using mathematical algorithms, is only a part of what our analytical data processing can do. Our data processing service provides analytical and statistical reports.

This report is based on Trainee X’s training data using the Smar4Fit Gym application.
S4F analytics data processing implemented advanced analytical methods with algorithms to make advanced analyzes on the basis of which a report is generated. The report reflects in detail and
qualitatively trainee’s performance.
The subjects of analysis are:
– the performance of the phases of one particular training (The Phase Analysis).
All phases have the same exercise structure. In this report, for each of the phases there are parameters:
Max HR, Average HR, HR Range, Resting Ability and Player Load.
– the performance of one particular exercise, with repetitions during that exercise (The Exercise Analysis)
The name of a specific exercise is “Alternative Toe Touches”.
The performance of exercise (The Exercise Performance) consists of repetitions (each repetition is a specific movement or action characteristic for that exercise. With our algorithm, we found that the performance of the exercise was with repetitions in continuity, but with small logical physiological pauses. These pauses separate the whole exercise performance into sections with repetitions (Repetitions Sections, Reps Sections). Every repetitions section has its own dynamics and parameters.
Parameters we track:
* Number of repetitions (no. of reps)
* length – time duration of repetition section
* Mean Acc – the average magnitude acceleration in repetition section
– the exercise performances comparison, comparing the performance of the same exercise but from 2 different exercise performances.

The Exercise Analysis

However, our system enables an X-RAY-like view of exercise performance. It means that we can see what is even beyond the data. We want to emphasize that already having the data created during exercising is a huge advantage, but we go a step beyond: We not only collect high-quality data, we enable also a high-quality and very advanced analysis of the data. But even so, the physiological need for short breaks is indispensable. The trainee performed every repetition one after the other, and after a certain time, She has to make a slight slowdown, only for a fraction of a second. Those fractions separate working flow into what we called Reps Sections.
With our algorithms, we have measuruments for:
– the length of each reps section
– the number of repetitions in each reps section
– Avg Acceleration (the average magnitude acceleration) in each reps section.

The Exercise Performances Comparison

To further improve the quality of the analyzes, we did a comparison of 2 performances of the same exercise, in the same training. For comparison purposes, we measured the same parameters as in the Exercise Analysis (Number of repetitions, length-duration, Avg acceleration).