# Real-Time Feedback in Swimming Exercises Using Embedded Devices in Water
## 3 Results
The results obtained when the training phase was conducted on dryland and the voting routine performed in water showed improved performance compared to the scenario in which both training and voting were conducted in water. Specifically, Nodes 1 and 2 exhibited a 30-40% increase in similarity scores for the same stroke type as used in the initial experiment. To enhance clarity and allow for easier comparison, in Table 2 outline the key differences between land-based training and in-water training. Analysis of multiple test iterations, as illustrated in the corresponding figures, reveals that accelerometer data tends to deviate more significantly from the reference pattern during the in-water voting phase. This discrepancy is attributed to the propulsion of the swimmer's body during the stroke, which introduces additional linear acceleration. In contrast, the gyroscope data remain largely unaffected, as forward movement does not induce significant changes in angular rotation. Figure 13: Data read from Node_1 (wrist) with a total of 59% similarity. Figure 14: Data read from Node_2 (elbow) with a total of 73% similarity. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Aspect** & **Land-Based Training** & **In-Water Training** \\ \hline Environment & Dry, stable & Dynamic water conditions \\ Movement Specificity & Isolated swimming & Full swimming stroke in \\  & movements & aquatic conditions \\ Feedback Type & Immediate feedback for & Immediate feedback for \\  & movement correction & movement correction \\ Training Focus & Easy to train, no external & Hard to train, multitude of \\  & impediments & external movements \\ Data Accuracy & High & Moderate \\ Accessibility & Lower cost, more accessible & Requires waterproofing, \\  & & additional cost \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison between land-based training and in-water training. Testing was carried out in two different swimming pool environments:  
* a smaller pool measuring 25 m in length, 10 m in width, and 1.7 m in depth, as shown in Figure 16;  
Figure 16: Small swimming pool testing data transmission. Figure 15: Data read from Node_3 (shoulder) with a total of 83% similarity. * a larger pool measuring 50 m in length, 18 m in width, with depths ranging from 2 to 4 m, as shown in Figure 17.  
In the small pool, at least 10 laps of approximately 15 m were performed within range of the master device. In the larger pool, 20 laps covering distances between 15 and 20 m were executed, also within communication range of the master device. In both setups, the master device was connected to a laptop and placed on a chair at the edge of the pool. Data transmission from the slave nodes to the master device was consistently reliable. No significant data loss was observed during the experiments. Successful data transfer occurred whenever the slave devices were above the water surface. However, transmission attempts made while the devices were submerged were unsuccessful due to the attenuation of Wi-Fi signals in water. The direct feedback mechanism implemented through the vibration motors on each node functioned reliably; the vibrations were consistently perceptible upon activation and could be clearly associated with deviations from the expected movement pattern at the corresponding sensor location during swimming.