Activity tracker systems are proposed to monitor physical activity during the day and the night. However, they might fail to retrieve specific information tailored for each user, especially from those that are still reluctant to use smart phones.
A classical, battery free, Old School activity Tracker system (OST) was evaluated for the period of one year from January to December 2017.
Daily sport activities performed by a motivated 37-year old male subject were manually documented after training through a keyboard into a database created in a 7-year old computer.
Daily training sessions were classified into 6 categories: 1) Legs, 2) Core (back, abdominals), 3) Arms/back contractions, 4) Arms/chest flexions, 5) whole body training, 6) others (including swimming, running, biking, etc).
A database with 137 exercises for the different categories was created based on personal experience and the recommendations of Marc Lauren (1). This database helped to spontaneously decide what to exercise every day.
An average of 16 exercises per week were performed uninterrupted in the year 2017, where the weeks with lowest performance were due to A) sickness B) relaxing days in a Spa, C) a summer family trip, D) laziness or E) the Christmas break; as shown in figure 1.
Number of exercises performed every week in 2017 classified by category.
Figure 1. A, B, C, D, E arrows point weeks where the normal training was interrupted. The Old School Activity Tracker OST was able to identify these periods
A total of 860 exercises were performed throughout the year. The in-house training period significantly improved performance on different physical challenges.
Attempt to break the world record of abdominal plank
New year resolution: The planche pushup
(9 month follow up, 7 attempts)
Of note, a considerable reduction in running activities compared to previous years was observed (285 minutes in 2017 vs approx. 2400 minutes per month from 1996 to 2003),
The correlation found between weeks with low activity (A to E, figure 1) and the periods of training restriction due to external or motivational reasons, validate OST as a strategy to monitor and evaluate physical performance.
These results revive and expose the potential benefits of writing down training achievements independently of invasive electronic devices such as smartphone-dependent activity trackers.
Material and methods
A bar fixed on a concrete wall, a very small child (4-8 Kg), a medium size child (9 to 14 Kg), a sponge mat and an ab wheel were spontaneously used depending on the mood of the operator. Statistical analysis was performed using Excel software (Microsoft Office). The majority of the exercises where performed according to Marc Lauren recommendation for each training category as shown in representative examples below.
Book: Marc Lauren. You are your own gym (Fit ohne Geräte). 2011