# Detection of Arrhythmias Using Heart Rate Signals from Smartwatches
## 2 Related Works
### Arrhythmia Detection Using Artificial Intelligence and Smartwatches  
Smartwatches provide greater access to user data that may help in preventing and treating medical conditions. The evolution of watches in recent years has taken them from being timepiece accessories to computers that enable real-time signal recording, including ECGs [37]. With PPG, smartwatches can assess a patient's cardiac rhythms in about 30 s. Extensive application-based research employing the PPG technique has demonstrated its critical significance in arrhythmia detection [38]. Although smartwatches have been widely used to detect arrhythmias, these devices can detect other cardiac abnormalities based on other recordings, such as heart rate. Our work studies the most significant proposals for detecting arrhythmias using smartwatches. Although the techniques used are similar to those described in the previous section, data extracted from smartwatches are used in the training and validation data sets. Three review works are taken as references [2; 39; 40]. A total of 256 patients were investigated by [PERSON] et al. [32]. The standard 12-lead ECG was recorded first, and then the ECG from the smartwatch was recorded. All 40 cases \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Study** & **Year** & **Technique** & **Accuracy** \\ \hline [PERSON] et al. [35] & 2017 & Deep CNN & 0.945 \\ [PERSON] et al. [22] & 2020 & CNN + LSTM & 0.992 \\ [PERSON] and [PERSON]. [23] & 2020 & CNN & 0.975 \\ [PERSON] et al. [24] & 2020 & DNN + GA + KNN & 0.98 \\ [PERSON] et al. [25] & 2022 & ResNet + BiLSTM & 0.992 \\ [PERSON] et al. [26] & 2023 & Semi-supervised Transfer Learning & 0.98 \\ [PERSON] et al. [27] & 2023 & CNN with Attention Layer & 0.982 \\ [PERSON] and [PERSON] [28] & 2019 & CNN Sequence to Sequence & 0.995 \\ [PERSON] et al. [36] & 2024 & Transformers & 0.98 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of the most recent proposals for detecting arrhythmias using artificial intelligence. of bradyarrhythmia and all 64 cases of tachyarrhythmia were detected based on the data from the smartwatch. Nonetheless, the sensitivity and specificity of arrhythmia diagnosis remained poor, at 25% and 99%, respectively. After performing a normal 12-lead ECG, [PERSON] et al. [41] assessed 260 individuals whose ECG was captured using a smartwatch. In 57 out of 62 patients (92%), atrial arrhythmia was accurately diagnosed by their proposal. The diagnostic accuracy displayed a sensitivity of 25% and a specificity of 99%. [PERSON] et al. [42] assessed the Apple Watch's sensitivity and specificity in 110 children with 12-lead ECGs that were either normal (\(n=75\)) or aberrant (\(n=35\)) and ranged in age from one week to sixteen years. When it came to identifying aberrant ECGs, the smartwatch tracings had a sensitivity and specificity of 84% and 100%, respectively. The diagnostic capacity of commercially available smartwatches to detect atrial fibrillation (AF) was compared by [PERSON] et al. [43]. One hundred patients with a sinus rhythm and one hundred with AF were included in their study. They discovered that the sensitivity and specificity values of the Apple Watch Series 5 were 87% and 86%, respectively. Using a Samsung Simband 2 (Samsung, Suwon, Republic of Korea), [PERSON] et al. [14] created an algorithm to identify atrial fibrillation. Thirty-five people participated in their study. Subjects with atrial fibrillation were identified with a sensitivity, specificity, and accuracy of 92.10%, 96.40%, and 95.10%, respectively. The accuracy of the Apple Watch ECG in identifying atrial fibrillation (AF) was assessed by [PERSON] et al. [44] in a sample of 734 patients, of whom 21% had AF diagnoses and varied ECG abnormalities. The analysis's sensitivity was 88% and specificity was 98% when unclassified ECGs were removed. In comparison to a 12-lead ECG, [PERSON] et al. [45] assessed the diagnostic accuracy of atrial fibrillation (AF) using an Apple Watch (Apple, Cupertino, CA, USA) equipped with an AliveCor KardiaBand (KB).