From 287701af20940613d4d6b7f4189d0844e68136a7 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Oliver=20Sch=C3=BCtz?= Date: Sun, 27 Oct 2024 00:23:54 +0200 Subject: [PATCH 1/4] Analyse Paper Oliver und minor fixes --- README.md | 11 ++++++ ...s_introduction_data_science_assignment.pdf | Bin 207703 -> 293246 bytes term-paper/cds_data_science.bib | 34 ++++++++++++++++++ term-paper/data_oli.tex | 24 ++++++++++++- term-paper/discussion_oli.tex | 10 +++++- term-paper/results_gra.tex | 4 +-- term-paper/results_oli.tex | 19 +++++++++- term-paper/title.tex | 2 +- 8 files changed, 98 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index cf0095d..362556d 100644 --- a/README.md +++ b/README.md @@ -34,3 +34,14 @@ pip install setuptools pip install bs4 pip install requests ``` +## Hilfsmittel / Tools + +### Oliver +- Data Wrangler +- ChatGPT + - Grammatik + - https://chatgpt.com/share/671d541e-dfc0-8006-8df3-dcfcb0048214 +- Github Copilot + - Code Completion: Boilerplate und Comments +- 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z+l<1^*quK;p#=B?eC(}_={$RPcNy`G{I1P??Y8FKVKzSx6RUlT)z{#r^!4ACT$`T3 zhUwfD0P4o4LuJ~4YqplJXOIJI{x+eG3Gh4CEg?3k#%@Lf~EGEwXmidIC(xo4(dreY2JD-HQGuMSttR{R{N+gmHPWRcjO7fN-q zsm5U7eL4SDpkh2z3}nsgC~&itv9wT33=zWq1CJE8-pptP?(1cQXEYf|7rpb(q@+4x zOnL_!dZ}85Xnzsg5}h4UNL5GK2Wv!G+4`YzYO zEN0q*V>L9^Z`gmM%&9;f<~yE0%ETiK{<9ksQ;JV3E$yAQ8WDkUF0=1Vu3OKE8#$92 zA*J*!aWAQcbp)|=A6Sp9uLZr~fmF9wzU6rMAv43N!yYAr*et>;V4gF%O&)gDvW|>z^vpX^?)zLNlO`@O^q%Mecf zuFUyxk%x0R{)Q@-1@yC4+&wGJe+POQrs}m;uMPmDE`-zvYh)jyZ|M$^ElAsR+ zEWpD0|A7!%DrV;J%(C{TW}YOvEF_t|qO6>(qTCYf5}aa^V&b1=2a>#! zLL|)p|1qEI{BP*O#>w*EnFv5QBg-akgfVdaV-rC%pZp7|Agb>cy6;vHG)|ey0DSo% zkyc0yDgAJKm}vV)#_P%a(*@!B^Z58lfVLrgxHdT)+B8L7y$5(uHKcAe604=Z)UUou zhRmx5td+~AB4o=@bM3RCHVqju_}M=J4D}<{ZgE7`LVErN!?Mx9rW+ti)S3fJHw`D* z93*rUih$!U$`eY86T*%Ypv)7@O49=uA&whm1VOd)rO*%$*$Bpb2kgL*=-vn%%LqNu z5LY9=sFb*wuEWP$NA-{QZGGkT-Pl}6Z@%P5qF3~=p!D9i_i9*8M Date: Sun, 27 Oct 2024 01:06:20 +0200 Subject: [PATCH 2/4] Analyse Paper Oliver und minor fixes --- term-paper/data_oli.tex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/term-paper/data_oli.tex b/term-paper/data_oli.tex index 7f5b4fd..1d8fbc2 100644 --- a/term-paper/data_oli.tex +++ b/term-paper/data_oli.tex @@ -6,7 +6,7 @@ \subsection{Daten Oliver} \subsubsection{Beschaffung} -Zur Aufzeichnung meiner Daten habe ich eine "Withings Steel HR Sport"-Uhr verwendet. Damit habe ich von August bis Oktober Schlafdaten und den Tagespuls erfasst. Diese Daten werden in der App visualisiert und sind dort zugänglich. Für den Schlaf erhält man einen Sleep Score, die verschiedenen Schlafphasen, den Puls während des Schlafs, die Dauer, den Start- und Endzeitpunkt sowie Unterbrechungen. +Zur Aufzeichnung meiner Daten habe ich eine \texttt{'Withings Steel HR Sport'} Uhr verwendet. Damit habe ich von August bis Oktober Schlafdaten und den Tagespuls erfasst. Diese Daten werden in der App visualisiert und sind dort zugänglich. Für den Schlaf erhält man einen Sleep Score, die verschiedenen Schlafphasen, den Puls während des Schlafs, die Dauer, den Start- und Endzeitpunkt sowie Unterbrechungen. Für den Tagespuls sieht man für jeden Tag eine Kurve mit dem Verlauf, dem Minimum, Maximum und Durchschnitt. Um die Daten in einem verarbeitbaren Format zu erhalten, habe ich in der App eine E-Mail-Anfrage gestellt, um meine Daten herunterzuladen. Diese wurden mir als ZIP-Datei per E-Mail zugeschickt. Die ZIP-Datei enthält mehrere CSV-Dateien mit verschiedenen Daten, von denen die meisten Metadaten oder leere Tabellen sind. Die beiden Tabellen, die für meine Analyse relevant sind, enthalten die zuvor genannten Spalten. From 671230cbad157a92d06b5bdd7950d11ccfd1df57 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Oliver=20Sch=C3=BCtz?= Date: Sun, 27 Oct 2024 00:23:54 +0200 Subject: [PATCH 3/4] Analyse Paper Oliver und minor fixes --- README.md | 11 +++++++++++ term-paper/cds_data_science.bib | 34 +++++++++++++++++++++++++++++++++ term-paper/data_oli.tex | 24 ++++++++++++++++++++++- term-paper/discussion_oli.tex | 10 +++++++++- term-paper/results_oli.tex | 19 +++++++++++++++++- 5 files changed, 95 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index cf0095d..362556d 100644 --- a/README.md +++ b/README.md @@ -34,3 +34,14 @@ pip install setuptools pip install bs4 pip install requests ``` +## Hilfsmittel / Tools + +### Oliver +- Data Wrangler +- ChatGPT + - Grammatik + - https://chatgpt.com/share/671d541e-dfc0-8006-8df3-dcfcb0048214 +- Github Copilot + - Code Completion: Boilerplate und Comments +- DeepL + - Übersetzung von Fachbegriffen \ No newline at end of file diff --git a/term-paper/cds_data_science.bib b/term-paper/cds_data_science.bib index fdba74d..de4eca6 100644 --- a/term-paper/cds_data_science.bib +++ b/term-paper/cds_data_science.bib @@ -3,6 +3,24 @@ title = "Full Text PDF" } +@article{valentini_variables_2009, + series = {Heart {Rate} and {Cardiovascular} {Disease}}, + title = {Variables {Influencing} {Heart} {Rate}}, + volume = {52}, + issn = {0033-0620}, + url = {https://www.sciencedirect.com/science/article/pii/S0033062009000334}, + doi = {10.1016/j.pcad.2009.05.004}, + abstract = {In both physiologic and pathological conditions, instantaneous heart rate value is the result of a rather complex interplay. It constantly varies under the influence of a number of factors: nonmodifiable and modifiable ones. Pharmacologic blockade with β-adrenergic antagonists and/or with parasympathetic antagonists such as atropine have permitted the identification of the mechanisms of autonomic nervous regulation of heart rate in a variety of physiologic and pathological conditions. The analysis of heart rate and blood pressure variability has yielded additional information on the autonomic control of the circulation, which has proven to have diagnostic and prognostic implications in a number of clinically relevant conditions such as hypertension, acute myocardial infarction, heart failure, and predisposition to sudden cardiac death. This article will summarize, based on available epidemiologic and clinical studies, the key variables influencing heart rate and heart rate variability in view of the known association between heart rate and cardiovascular disease.}, + number = {1}, + urldate = {2024-10-26}, + journal = {Progress in Cardiovascular Diseases}, + author = {Valentini, Mariaconsuelo and Parati, Gianfranco}, + month = jul, + year = {2009}, + keywords = {Alcohol, Heart rate, Heart rate variability, Physiology, Smoking}, + pages = {11--19}, +} + @article{D8G7JHBA, author = "Sajjadieh, Amirreza and Shahsavari, Ali and Safae, Ali and Penzel, Thomas and Schoebel, Christoph and Fietze, Ingo and Mozafarian, Nafiseh and Amra, Babak and Kelishadi, Roya", volume = "19", @@ -11,3 +29,19 @@ pages = "135-143", year = "2020" } + +@article{wolk_sleep_2005, + title = {Sleep and {Cardiovascular} {Disease}}, + volume = {30}, + issn = {0146-2806}, + url = {https://www.sciencedirect.com/science/article/pii/S0146280605001003}, + doi = {10.1016/j.cpcardiol.2005.07.002}, + abstract = {Sleep is an important modulator of cardiovascular function, both in physiological conditions and in disease states. In individuals without a primary sleep disorder, sleep may exert significant effects on the autonomic nervous system, systemic hemodynamics, cardiac function, endothelial function, and coagulation. Some of these influences can be directly linked to specific modulatory effects of sleep stages per se; others result from the natural circadian rhythm of various physiological processes. There is a temporal association between physiological sleep and occurrence of vascular events, cardiac arrhythmias, and sudden death. Epidemiological and pathophysiological studies also indicate that there may be a causal link between primary sleep abnormalities (sleep curtailment, shift work, and sleep-disordered breathing) and cardiovascular and metabolic disease, such as hypertension, atherosclerosis, stroke, heart failure, cardiac arrhythmias, sudden death, obesity, and the metabolic syndrome. Finally, sleep disturbances may occur as a result of several medical conditions (including obesity, chronic heart failure, and menopause) and may therefore contribute to cardiovascular morbidity associated with these conditions. Further understanding of specific pathophysiological pathways linking sleep disorders to cardiovascular disease is important for developing therapeutic strategies and may have important implications for cardiovascular chronotherapeutics.}, + number = {12}, + urldate = {2024-10-26}, + journal = {Current Problems in Cardiology}, + author = {Wolk, Robert and Gami, Apoor S. and Garcia-Touchard, Arturo and Somers, Virend K.}, + month = dec, + year = {2005}, + pages = {625--662}, +} diff --git a/term-paper/data_oli.tex b/term-paper/data_oli.tex index 92ab019..7f5b4fd 100644 --- a/term-paper/data_oli.tex +++ b/term-paper/data_oli.tex @@ -1,4 +1,26 @@ -%! Author = gra +%! Author = Oliver Schütz %! Date = 24.10.24 % Preamble + +\subsection{Daten Oliver} + +\subsubsection{Beschaffung} +Zur Aufzeichnung meiner Daten habe ich eine "Withings Steel HR Sport"-Uhr verwendet. Damit habe ich von August bis Oktober Schlafdaten und den Tagespuls erfasst. Diese Daten werden in der App visualisiert und sind dort zugänglich. Für den Schlaf erhält man einen Sleep Score, die verschiedenen Schlafphasen, den Puls während des Schlafs, die Dauer, den Start- und Endzeitpunkt sowie Unterbrechungen. + +Für den Tagespuls sieht man für jeden Tag eine Kurve mit dem Verlauf, dem Minimum, Maximum und Durchschnitt. Um die Daten in einem verarbeitbaren Format zu erhalten, habe ich in der App eine E-Mail-Anfrage gestellt, um meine Daten herunterzuladen. Diese wurden mir als ZIP-Datei per E-Mail zugeschickt. Die ZIP-Datei enthält mehrere CSV-Dateien mit verschiedenen Daten, von denen die meisten Metadaten oder leere Tabellen sind. Die beiden Tabellen, die für meine Analyse relevant sind, enthalten die zuvor genannten Spalten. + +\subsubsection{Aufbereitung} +Zunächst werden beide Tabellen in ein Pandas DataFrame eingelesen. + +Beginnend mit den Schlafdaten: +Da der Zeitpunkt des Schlafs in keinem geeigneten Format vorlag, wurde der Endzeitpunkt als Datum des Schlafs verwendet. Die Dauer wurde aus der Summe aller Schlafphasen berechnet und von Sekunden in Stunden umgerechnet. Da der Einfluss auf den nächsten Tag untersucht werden soll, wurde das Folgedatum dem Tagespuls zugeordnet. + +Für den Tagespuls: +Die Werte für den Puls lagen nicht im Integer-Format vor, sondern als String mit einem Array. Dieses Array musste in einzelne Zahlenwerte aufgespalten werden, wobei für jedes Element des Arrays eine neue Zeile erzeugt wurde. Danach wurden alle Werte nach Datum gruppiert und daraus der Durchschnitt pro Tag berechnet. + +Abschließend wurden beide Tabellen anhand des Datums zusammengeführt und fehlerhafte Werte aus dem Datensatz entfernt. + + + + diff --git a/term-paper/discussion_oli.tex b/term-paper/discussion_oli.tex index 92ab019..ac2303f 100644 --- a/term-paper/discussion_oli.tex +++ b/term-paper/discussion_oli.tex @@ -1,4 +1,12 @@ -%! Author = gra +%! Author = Oliver Schütz %! Date = 24.10.24 % Preamble +\subsection{Oliver} +Trotz leichter Korrelation gibt es bei diesem Vorgehen viele Fehlerquellen. Die Datenmenge war recht klein, und da meine Schlafzeiten relativ konsistent waren und ich durchschnittlich einen sehr hohen Sleep Score (circa 90) hatte, fehlt größtenteils das untere Spektrum. + +Zudem beziehen sich die Daten nur auf eine Person, sodass es möglich ist, dass der Einfluss des Schlafs bei mir stärker ausgeprägt ist als bei anderen. + +Der Einfluss des Schlafs auf die Gesundheit ist bereits umfassend erforscht, und es wurde ein Zusammenhang zwischen Schlafmangel und Schlaganfällen festgestellt \cite{wolk_sleep_2005}. Dies bestätigt die Annahme, dass die Schlafqualität langfristig einen Einfluss auf den Puls haben kann. + +Es ist jedoch schwierig, den Puls des nächsten Tages genau vorherzusagen, da dieser auch durch andere Faktoren wie Koffein, Sport, Stress etc. beeinflusst werden kann \cite{valentini_variables_2009}. diff --git a/term-paper/results_oli.tex b/term-paper/results_oli.tex index 92ab019..7065735 100644 --- a/term-paper/results_oli.tex +++ b/term-paper/results_oli.tex @@ -1,4 +1,21 @@ -%! Author = gra +%! Author = Oliver Schütz %! Date = 24.10.24 + % Preamble + +\subsection{Oliver}\label{subsec:ergebnisse-oliver} +\begin{figure}[H] + \centering + \includegraphics[width=1\textwidth]{../media/chart-oliver}\label{fig:figure} +\end{figure} + + +\[ +r_{\text{Sleep duration, HR}} = -0.2244 \quad \text{and} \quad r_{\text{Sleep HR, Awake HR}} = 0.1707 +\] + + +Aus der Visualisierung und den berechneten Korrelationen lässt sich ein geringer Einfluss des Schlafs auf die Herzfrequenz feststellen. + + From 8f7d6529f005ef9e560a4084be28c6bb511d82f1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Oliver=20Sch=C3=BCtz?= Date: Sun, 27 Oct 2024 01:06:20 +0200 Subject: [PATCH 4/4] Analyse Paper Oliver und minor fixes --- term-paper/data_oli.tex | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/term-paper/data_oli.tex b/term-paper/data_oli.tex index 7f5b4fd..1d8fbc2 100644 --- a/term-paper/data_oli.tex +++ b/term-paper/data_oli.tex @@ -6,7 +6,7 @@ \subsection{Daten Oliver} \subsubsection{Beschaffung} -Zur Aufzeichnung meiner Daten habe ich eine "Withings Steel HR Sport"-Uhr verwendet. Damit habe ich von August bis Oktober Schlafdaten und den Tagespuls erfasst. Diese Daten werden in der App visualisiert und sind dort zugänglich. Für den Schlaf erhält man einen Sleep Score, die verschiedenen Schlafphasen, den Puls während des Schlafs, die Dauer, den Start- und Endzeitpunkt sowie Unterbrechungen. +Zur Aufzeichnung meiner Daten habe ich eine \texttt{'Withings Steel HR Sport'} Uhr verwendet. Damit habe ich von August bis Oktober Schlafdaten und den Tagespuls erfasst. Diese Daten werden in der App visualisiert und sind dort zugänglich. Für den Schlaf erhält man einen Sleep Score, die verschiedenen Schlafphasen, den Puls während des Schlafs, die Dauer, den Start- und Endzeitpunkt sowie Unterbrechungen. Für den Tagespuls sieht man für jeden Tag eine Kurve mit dem Verlauf, dem Minimum, Maximum und Durchschnitt. Um die Daten in einem verarbeitbaren Format zu erhalten, habe ich in der App eine E-Mail-Anfrage gestellt, um meine Daten herunterzuladen. Diese wurden mir als ZIP-Datei per E-Mail zugeschickt. Die ZIP-Datei enthält mehrere CSV-Dateien mit verschiedenen Daten, von denen die meisten Metadaten oder leere Tabellen sind. Die beiden Tabellen, die für meine Analyse relevant sind, enthalten die zuvor genannten Spalten.