added figures

thesis/sections/background.tex

@@ -40,7 +40,7 @@ However, variations, particularly in the follicular phase length, are common and
 Figure~\ref{fig:background_menstrual_cycle_physiology} provides a detailed overview of the hormonal and physiological changes
 throughout the menstrual cycle.
 
-\begin{figure}
+\begin{figure}[htbp]
     \centering
     \includegraphics[width=0.6\textwidth]{background_menstrual_cycle_physiology}
     \caption{Physiological changes during the menstrual cycle~\cite{pedroso_menstrual_2022}.}
@@ -50,17 +50,66 @@ throughout the menstrual cycle.
 Not every cycle results in ovulation—a phenomenon known as anovulation—which leads to a monophasic temperature pattern.
 Anovulation can have various causes, including hormonal imbalances, stress, or underlying health conditions~\cite{rosenfield_adolescent_2013}.
 
+\begin{figure}[htbp]
+    \centering
+    \includegraphics[width=0.9\textwidth]{background_anovulatory_cycle}
+    \caption{Example of a cycle without an ovulation and the resulting temperature rise}
+    \label{fig:background_anovulation}
+\end{figure}
+
+
 Anovulation is reflected in temperature data as either an absence of a clear temperature rise or a rise
 that is insufficient in magnitude or duration to be considered a reliable indicator of ovulation.
 Distinguishing between ovulatory and anovulatory cycles is challenging, as the only definitive confirmation of
 successful ovulation in a clinical sense is a positive pregnancy test.
-Even ultrasound imaging can only confirm that an egg was released from its follicle—not whether it was fertilized or successfully implanted.
+Even ultrasound imaging can only confirm that an egg was released from its follicle—not whether it was successfully implanted or fertilized.
+Figure~\ref{fig:background_anovulation} shows a cycle that does not have an ovulation, and thus no resulting temperature rise.
 
-%TODO: find source for this
+
+To illustrate the diversity of real-world menstrual cycles, Figures~\ref{fig:background_long_cycle} and~\ref{fig:background_short_cycle}
+show examples of cycles that are significantly longer or shorter than a normative 28-day cycle.
+
+\begin{figure}[htbp]
+    \centering
+    \includegraphics[width=0.9\textwidth]{background_long_cycle}
+    \caption{Example of a long cycle with a length of 111 days}
+    \label{fig:background_long_cycle}
+\end{figure}
+
+\begin{figure}[htbp]
+    \centering
+    \includegraphics[width=0.9\textwidth]{background_short_cycle}
+    \caption{Example of a short cycle with a length of 22 days}
+    \label{fig:background_short_cycle}
+\end{figure}
+
+These irregularities appear not only on a per-cycle basis, but also across time within the same individual.
+Figures~\ref{fig:background_irregular_cycles} and~\ref{fig:background_regular_cycles}
+show examples of a woman with an irregular and a regular menstrual cycle pattern, respectively.
+Raw body core temperature readings are shown in light blue, with a red line indicating smoothing by local regression.
+Vertical dotted black lines mark the beginning of each cycle.
+The irregular example highlights how multiple parameters can vary between individuals:
+cycle length, timing of ovulation, temperature shift magnitude between phases, and intra-phase temperature variability.
+This multidimensional variability underscores the need for adaptive, data-driven models capable of learning personalized patterns---
+rather than relying on population-wide assumptions.
+
+\begin{figure}[htbp]
+    \centering
+    \includegraphics[width=0.9\textwidth]{background_irregular_cycle_example}
+    \caption{Example of a woman with irregular menstrual rhythm}
+    \label{fig:background_irregular_cycles}
+\end{figure}
+
+\begin{figure}[htbp]]
+    \centering
+    \includegraphics[width=0.9\textwidth]{background_regular_cycle_example}
+    \caption{Example of a woman with regular menstrual rhythm}
+    \label{fig:background_regular_cycles}
+\end{figure}
 
 %TODO: show plot of different cycle types
 
-\subsubsection{Fertility Prediction}\label{subsec:fertility_prediction}
+\subsubsection{Fertility Prediction}\label{subsubsec:fertility_prediction}
 Throughout the menstrual cycle, the chance of fertilization varies significantly.
 An egg cell released from the ovary during ovulation, can be fertilized for up to 24 hours.
 However, since male sperm cells can survive up to 6 days inside the female reproductive tract,
@@ -82,7 +131,7 @@ is constrained by the precision of ovulation detection.
 This relationship underscores the necessity of developing reliable ovulation prediction models,
 as even small inaccuracies can significantly impact fertility assessments.
 
-\subsubsection{Physiological Signs of Ovulation}\label{subsec:physiological_signs}
+\subsubsection{Physiological Signs of Ovulation}\label{subsubsec:physiological_signs}
 Several physiological signs correlate with ovulation and can be used for prediction.
 As shown in Figure~\ref{fig:background_menstrual_cycle_physiology}, these include hormonal fluctuations (LH and FSH surges) and
 changes in body temperature.
@@ -98,6 +147,8 @@ detecting the slight temperature rise that follows ovulation.
 Advances in wearable technology have further enabled continuous and automated temperature monitoring,
 improving accessibility and usability~\cite{alexander_fertilitatsmonitoring_2014, luo_detection_2020, yu_tracking_2022}.
 
+\subsection{Data and Measurement}\label{subsec:data_background}
+
 \subsection{Technical Background}\label{subsec:technological_background}
 
 \subsubsection{Time Series Analysis}\label{subsubsec:time_series_analysis}
@@ -145,7 +196,7 @@ outputs at each time step.
 
 \begin{figure}
     \centering
-    \includegraphics[width=0.7\textwidth]{recurrent_neural_network_unfold}
+    \includegraphics[width=0.8\textwidth]{recurrent_neural_network_unfold}
     \caption{Schematic diagram of the unfolded structure of a recurrent neural network~\cite{fdeloche_english_2017}}
     \label{fig:rnn_unfolded}
 \end{figure}