## 5 Devices
### Sensors and Metrics  
As mentioned before, our system provides a set of sensors able to measure a variety of metrics with a given degree of accuracy. These sensors are listed in Table 1, where--for each  
Figure 6: Structure of the command used to request real-time data. Figure 7: Sequence diagram illustrating the interactions between the Viatom Checkme O2 device and a connected BLE client during the retrieval of real-time data. one of them--we provide the metric which it measures (column Unit), its scale (column Scale) and its accuracy (column Accuracy). In Table 2, we compare the health and wellness monitoring features provided by HealthTracker with respect to other popular commercial devices, namely Apple Watch Series 9 [20], Garmin Venu 3 [21], Google Pixel Watch 2 [22] and Samsung Galaxy Watch6 [23], denoted as columns \"Apple\", \"Garmin\", \"Google\" and \"Samsung\" in the table, respectively. As we can note, some features are provided only by HealthTracker, such as \"Cough frequency and intensity\" and \"Tremors and hyperkinetic movements\". For these features, we are implementing specific algorithms in our firmware to monitor the relative parameters and send alerts in case a danger threshold is reached. In particular, there are acoustic techniques for cough detection [24] that can be used to diagnose over one hundred medical conditions like respiratory diseases (e.g., asthma, bronchiectasis, or chronic obstructive pulmonary disease), generic pathologies such as cold or allergies, or even lifestyle (smokers). Concerning sweating, in [25], a machine-learning model has been implemented to estimate sweat loss. Knowing how much individuals sweat during exercise allows the planning of fluid intake effectively before (prehydration), during, and after (rehydration) exercise. In [26], researchers propose a prediction model for sleep-disordered breathing (SDB) in relation to different malocclusions and oral habits with the purpose of aiding clinicians in early screening of patients at risk of developing SDB. Utilizing Python deep learning algorithms, a Multi-Layered Perceptron (MLP) was developed for SDB prediction. Finally, concerning tremors and hyperkinetic movements, in [27], the authors propose a novel algorithm to characterize tremors using inertial sensors. It uses a two-stage approach that (1) estimates the tremor frequency of a subject and only quantifies tremor near that range; (2) estimates the tremor amplitude as the portion of signal power above baseline activity during recording, allowing tremor estimation even in the presence of other activity; and (3) estimates tremor amplitude in physical units of translation (cm) and rotation (\"), consistent with current tremor rating scales. The authors declare that their algorithm can quantify tremor accurately even in the presence of other activities. \begin{table}
\begin{tabular}{c c c c} \hline
**Sensor** & **Unit** & **Scale** & **Accuracy** \\ \hline Accelerometer & Earth’s gravity (g) & \(\pm\)2/\(\pm\)4/\(\pm\)8/\(\pm\)16 & \(\pm\)0.04 \\ \hline Gyroscope & Degrees per Second (dps) & \(\pm\)125/\(\pm\)245/\(\pm\)500/\(\pm\)1000/\(\pm\)2000 & \(\pm\)3 \\ \hline Temperature & Celsius (\({}^{\circ}\)C) & 15 to 40 & \(\pm\)0.5 \\ \hline Humidity & Relative Humidity (rh) & 20 to +80\% & \(\pm\)3.5\% \\ \hline Heart rate & beats per minute (bpm) & 30 to 250 & \(\pm\)2 \\ \hline Oxygen saturation (SpO2) & Percentage (\%) & 70–100 & \(\pm\)3\% (for values 70–79) \\  & & & \(\pm\)2\% (for values 80–100) \\ \hline Microphones & sound pressure level (dBSPL) & 120 & Not provided \\  & decibels (dB) & 61 & by the \\  & decibels relative to full scale (dBFS) & \(-\)26 & component’s datasheet \\ \hline \end{tabular}
\end{table} 
Table 1: Unit, scale and accuracy of each sensor of our system. \begin{table}
\begin{tabular}{c c c c c c} \hline  & **HealthTracker** & **Apple** & **Garmin** & **Google** & **Samsung** \\ \hline Blood oxygen level & ✓ & ✓ & ✓ & ✓ & ✓ \\ \hline Breathing rate and depth & ✓ & ✓ & ✓ & ✓ & \\ \hline \end{tabular}
\end{table}