## 2 Review Methodology
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**S/No** & **Author** & **Year** & **Objective** & **Methodology** \\ \hline \multirow{2}{*}{1} & [PERSON], [PERSON] [30] & \multirow{2}{*}{2010} & To develop a system that estimates the severity of a health episode of patients by collecting and analyzing patient information for disease using wearable sensors. & \multirow{2}{*}{Fiducial features and ANN} \\ \hline \multirow{2}{*}{2} & [PERSON] [31] & \multirow{2}{*}{2010} & To design an approach to interpret the ECG recording of patients based on ECG Rule Markup Language (ecgRuleML) to externalize decision rules. & XML knowledge-based \\ \hline \multirow{2}{*}{3} & [PERSON], [PERSON] [28] & \multirow{2}{*}{2010} & To develop a mobile mHealth system to attend to abnormal or emergency for patients suffering from heart problem & Ontology \\ \hline \multirow{2}{*}{4} & [PERSON], [PERSON] [36] & \multirow{2}{*}{2010} & To develop a framework that can be used for supporting complex real-time ECG analysis based on clinical rules translation models & Data streaming \\ \hline \multirow{2}{*}{5} & [PERSON], [PERSON] [37] & \multirow{2}{*}{2010} & To design an expert system for ECG heart arrhythmia detection & Fiducial and Discrete Wavelet Transform \\ \hline \multirow{2}{*}{6} & [PERSON], [PERSON] [38] & \multirow{2}{*}{2011} & To develop the Specialist’s Decision Support System (SDSS) for disease diagnosis & SensorArt platform based ECG data analysis and knowledge extraction \\ \hline \multirow{2}{*}{7} & [PERSON] and [PERSON] [39] & \multirow{2}{*}{2011} & To use the SVM Machine Learning algorithm for ECG classification and detection of QRS-complexes, P- and T-waves in the 12-lead ECG signal. & SVD, Haar wavelet, Discrete Fourier Transform and SVM \\ \hline \multirow{2}{*}{8} & [PERSON], [PERSON] [40] & \multirow{2}{*}{2011} & To predict the hypertension risk of patients using Fuzzy Expert System & Fuzzy-based approach \\ \hline \multirow{2}{*}{9} & [PERSON], [PERSON] [27] & \multirow{2}{*}{2011} & To design procedures for diagnosing and monitoring chronic heart disease patients remotely & Machine learning using SVM, Random Forests, Artificial Neural Networks, Decision Trees and Naive Bayes \\ \hline \multirow{2}{*}{10} & [PERSON], [PERSON] [41] & \multirow{2}{*}{2011} & To design a machine learning based statistical model for the detection of cardiac arrhythmias & Bayesian Network \\ \hline \multirow{2}{*}{11} & [PERSON], [PERSON] [42] & \multirow{2}{*}{2012} & To design an ECG-based decision support system for predicting cardiac quality level & Ontology and Fuzzy-based approach \\ \hline \multirow{2}{*}{12} & [PERSON], [PERSON] [43] & \multirow{2}{*}{2012} & The develop a mobile system for telecardiology investigations & Remote Radio-Consultation (RRC) system framework \\ \hline \multirow{2}{*}{13} & [PERSON], [PERSON] [44] & \multirow{2}{*}{2012} & To analyze various hybrid expert system approaches and their applications & Review paper \\ \hline \multirow{2}{*}{14} & [PERSON] and [PERSON] [45] & \multirow{2}{*}{2013} & To identify similarities and variabilities among existing MPMs & Body Area Network (BAN) and Back-End Systems (BESys). \\ \hline \multirow{2}{*}{15} & [PERSON], [PERSON] [46] & \multirow{2}{*}{2013} & To survey applications and methodologies for designing computer-aided Decision Support System in biomedical informatics & Review paper \\ \hline \multirow{2}{*}{16} & [PERSON], [PERSON] [47] & \multirow{2}{*}{2013} & a design of a telecommunication and computer-based system for monitoring patients in comorbid condition & Logical model-based algorithms \\ \hline \multirow{2}{*}{17} & [PERSON], [PERSON] [48] & \multirow{2}{*}{2014} & To develop a mobile android application prototype that is compatible with existing ECG acquisition device for ECG analysis & Fiducial \\ \hline \multirow{2}{*}{18} & [PERSON], [PERSON] [9] & \multirow{2}{*}{2014} & To develop a smart and adaptive synchronization model for m-Health applications & Cost-oriented algorithms \\ \hline \hline \end{tabular}
\end{table}