\section{Introduction}

\subsection{Problem Setting}
\begin{frame}[c]{Introduction}
\framesubtitle{Problem Setting}
    \begin{center}
        \begin{large}
            \textbf{Classify single-lead ECG signals with variable length.}
        \end{large}
    \end{center}
    \vspace{0.5cm}
    \begin{figure}[!ht]
        \setlength{\figH}{3.75cm}
        \setlength{\figW}{0.95\textwidth}
        \centering
        \input{artwork/15_A}
        \caption{ECG signal of the 2017 PhysioNet/CinC Challenge dataset \cite{Clifford2017} labeled as AF.}
        \label{fig:ecg_signal_A}
    \end{figure}
\end{frame}

\subsection{Motivation}
\begin{frame}{Introduction}
\framesubtitle{Motivation}
    \begin{itemize}
        \item Atrial fibrillation (AF) dangerous and often undetected
        \item AF one of the most common heart arrhythmia's
        \item AF can lead to strokes, dementia, and heart failure
        \item Increasing amount of single-lead ECG edge devices available
        \begin{itemize}
            \item No expert knowledge typically available
            \item Need for automated classification of AF
        \end{itemize}
    \end{itemize}
    \begin{textblock*}{3cm}(11.8cm, 3cm)
        \raggedright
        \cite{Becker2006}
        \cite{Herold2019}
    \end{textblock*}
    \pause
    \begin{figure}[!ht] 
        \centering
        \input{artwork/beat_ecg}
        \vspace{-0.15cm}
        \caption{Regular heart beat left and atrial fibrillation on the right.}
        \label{fig:beat}
    \end{figure}
\end{frame}

\subsection{Related Work}
\begin{frame}{Introduction}
\framesubtitle{Related Work}
    \vspace{-0.5cm}
    \begin{columns}[T]
        \column{.48\textwidth}
            \begin{center}
                \textbf{Transitional ML approaches}
            \end{center}
            \onslide<2->{
            \begin{itemize}
                \item Preprocessing \& Feature extraction
                \begin{itemize}
                    \item Data augmentation
                    \item ECG timing features
                    \item Robust interval features
                    \item Waveform features
                \end{itemize}
                \item Learnable classifier
                \begin{itemize}
                    \item Random forest
                    \item Support vector machines
                    \item XGBoost
                \end{itemize}
                \item \cite{Antink2017, Smisek2017}
            \end{itemize}}
        \column{.01\textwidth}
        \vspace{0.25cm}\rule{.1mm}{.75\textheight}
        \column{.48\textwidth}
            \begin{center}
                \textbf{Deep learning approaches}
            \end{center}
            \onslide<3->{
            \begin{itemize}
                \item Preprocessing
                \begin{itemize}
                    \item Data augmentation
                    \item Data conversion (Spectrogram)
                \end{itemize}
                \item Deep learning classifier
                \item \cite{Zihlmann2017, Mousavi2019, Mashrur2019, Khriji2020, Nonaka2020}
            \end{itemize}}
    \end{columns}
\end{frame}