.gitignore

@@ -21,6 +21,7 @@
 **/*.bcf
 **/*.blg
 **/*.gz
+**/*.loa
 **/*.log
 **/*.lof
 **/*.lot

app/withings/README.md

@@ -10,7 +10,7 @@ We use the following devices for vitals data measurement:
   * Heart Rate, SPO2
 * [Withings Thermo](https://www.withings.com/de/en/thermo) 
   * Body Surface Temperature
-* [WIthings BPM Core](https://www.withings.com/de/en/bpm-core) 
+* [Withings BPM Core](https://www.withings.com/de/en/bpm-core) 
   * Blood Pressure
 
 ## API Access

docs/analysis/.gitignore

@@ -0,0 +1 @@
+/.venv/

docs/analysis/charts.py

@@ -0,0 +1,217 @@
+import matplotlib.pyplot as plt
+import numpy as np
+
+plt.rcParams['font.family'] = 'serif'
+plt.rcParams['font.size'] = 12
+
+def generate_measurement_stats_pie_chart(show: bool, save: bool):
+    fig, ax = plt.subplots()
+
+    size_outer = 0.3
+    size_inner = 0.2
+
+    vals_outer = np.array([28., 7.])  # Measurements vs Measurement failures
+    vals_middle = np.array([17., 11., 7., 0.])  # MEWS calculations, Measurement only, P2 failures, P1 failures
+    vals_inner = np.array([16., 1., 8., 3., 2., 5., 0., 0.])  # Innermost ring values
+
+    cmap = plt.get_cmap("tab20b")
+    outer_colors = cmap(np.array([6, 13]))
+    middle_colors = cmap(np.array([5, 15, 14, 14]))
+    inner_colors = cmap(np.array([11, 10, 11, 10, 11, 10, 11, 10]))
+
+    # Outer ring
+    ax.pie(vals_outer, radius=1, colors=outer_colors,
+           wedgeprops=dict(width=size_outer, edgecolor='w'))
+
+    # Middle ring
+    ax.pie(vals_middle, radius=1-size_outer, colors=middle_colors,
+           wedgeprops=dict(width=size_inner, edgecolor='w'))
+
+    # Innermost ring
+    inner_pie = ax.pie(vals_inner, radius=1-size_outer-size_inner, colors=inner_colors,
+           wedgeprops=dict(width=size_inner, edgecolor='w'))
+    #labels_inner = ["home", "on the go"]
+    #ax.legend(inner_pie[0], labels_inner, loc="center right")
+
+    ax.set(aspect="equal")
+
+    if save:
+        plt.savefig(
+            "chart-measurement-stats.png",
+            dpi=900,
+            bbox_inches='tight',
+            transparent=True
+        )
+
+    if show:
+        plt.show()
+
+
+def generate_measurement_repeats_histogram(show: bool, save: bool):
+    device_names = ["Scanwatch", "BPM Core", "Thermo"]
+    labels_attempts = [f"{name} measurement attempts" for name in device_names]
+    labels_failures = ["S\u2081 failures", "B\u2081 failures", "T\u2081 failures"]
+    values_attempts = [43, 33, 28]
+    values_failures = [15, 5, 0]
+
+    # Define a list of colors for the bars
+    cmap = plt.get_cmap("tab20b")
+    colors_attempts = cmap(np.array([15, 11, 7]))
+    colors_failures = cmap(np.array([13, 9, 5]))
+
+    # Plot the bars with the specified colors and labels for the legend
+    bars_attempts = plt.bar(device_names, values_attempts, color=colors_attempts)
+    bars_failures = plt.bar(device_names, values_failures, color=colors_failures)
+
+    # Add individual labels for each bar in the legend
+    for i in range(3):
+        bars_attempts[i].set_label(labels_attempts[i])
+        bars_failures[i].set_label(labels_failures[i])
+
+    plt.ylabel("Count")
+
+    plt.ylim(0, 55)
+    plt.yticks(range(0, 56, 5))
+
+    plt.legend(loc="upper right", prop={"size":8})
+
+    if save:
+        plt.savefig(
+            "chart-measurement-repeats.png",
+            dpi=900,
+            bbox_inches="tight",
+            transparent=True
+        )
+
+    if show:
+        plt.show()
+
+
+def generate_connection_boxplots(show: bool, save: bool):
+    data_downlink = [
+        [50.42, 46.29, 39.94, 39.44, 50.21, 44.34, 41.03, 47.88, 50.34, 41.72, 43.93, 49.34, 50.49, 52.47, 47.04, 45.86, 51.17, 50.12, 52.16, 50.55, 50.69, 53.43, 42.21, 46.81],
+        [15.3, 25.47, 33.91, 12.27]
+    ]
+    data_uplink = [
+        [11.38, 11.24, 8.46, 9.33, 11.39, 9.33, 9.03, 10.65, 11.59, 8.81, 8.91, 10.56, 10.98, 10.04, 9.11, 8.62, 11.08, 10.62, 11.24, 11.29, 10.86, 10.46, 9.16, 9.15],
+        [5.33, 5.46, 3.38, 4.23]
+    ]
+    data_rtt = [
+        [14, 16, 15, 15, 15, 15, 16, 12, 15, 14, 18, 14, 19, 16, 23, 12, 16, 14, 12, 13, 13, 13, 17, 15],
+        [145, 127, 104, 108]
+    ]
+
+    fig, axes = plt.subplots(nrows=1, ncols=3, sharex=True, figsize=(15,5))
+    #plt.subplots_adjust(wspace=0.4)
+
+    cmap = plt.get_cmap("tab20b")
+
+    medianprops= {
+        "color": cmap(1),
+        "linewidth": 2,
+    }
+
+    # Downlink Boxplot
+    axes[1].boxplot(data_downlink, medianprops=medianprops)
+    axes[1].set_ylabel("Datarate [Mbps]")
+    axes[1].set_title("Downlink")
+    axes[1].set_xticks([1, 2])
+    axes[1].set_xticklabels(["At home", "On the go"])
+
+    # Uplink Boxplot
+    axes[0].boxplot(data_uplink, medianprops=medianprops)
+    axes[0].set_ylabel("Datarate [Mbps]")
+    axes[0].set_title("Uplink")
+    axes[0].set_xticks([1, 2])
+    axes[0].set_xticklabels(["At home", "On the go"])
+
+    # RTT Boxplot
+    axes[2].boxplot(data_rtt, medianprops=medianprops)
+    axes[2].set_ylabel("RTT [ms]")
+    axes[2].set_title("RTT")
+    axes[2].set_xticks([1, 2])
+    axes[2].set_xticklabels(["At home", "On the go"])
+
+    # Function to add jitter
+    def jitter(x, width=0.1):
+        """Return the given x coordinate plus a small random offset."""
+        np.random.seed = 0
+        return x + np.random.uniform(-width, width)
+
+    # Sample points to plot on the boxplots
+    points_uplink = [
+        (1, 11.38),
+        (2, 5.33),
+        (1, 9.33),
+        (2, 5.46),
+        (1, 11.59),
+        (1, 10.56),
+        (1, 10.98),
+        (1, 11.24),
+        (2, 4.23),
+        (1, 10.86),
+        (1, 10.46),
+    ]
+    points_downlink = [
+        (1, 50.42),
+        (2, 15.3),
+        (1, 39.44),
+        (2, 25.47),
+        (1, 50.34),
+        (1, 49.34),
+        (1, 50.49),
+        (1, 52.16),
+        (2, 12.27),
+        (1, 50.69),
+        (1, 53.43),
+    ]
+    points_rtt = [
+        (1, 14),
+        (2, 145),
+        (1, 15),
+        (2, 127),
+        (1, 15),
+        (1, 14),
+        (1, 19),
+        (1, 12),
+        (2, 108),
+        (1, 13),
+        (1, 13),
+    ]
+
+    # Plotting points on Uplink Boxplot
+    for x, y in points_uplink:
+        axes[0].scatter(jitter(x), y, marker='x', color=cmap(14), linewidth=0.5)
+
+    # Plotting points on Downlink Boxplot
+    for x, y in points_downlink:
+        axes[1].scatter(jitter(x), y, marker='x', color=cmap(14), linewidth=0.5)
+
+    # Plotting points on RTT Boxplot
+    for x, y in points_rtt:
+        axes[2].scatter(jitter(x), y, marker='x', color=cmap(14), linewidth=0.5)
+
+    # Plot a dummy point for the legend (outside the visible range)
+    #axes[0].scatter([-100], [-100], marker='x', color=cmap(14), linewidth=0.5, label='synchronization failure')
+    #fig.legend(loc='upper center', bbox_to_anchor=(0.5, 1.1))
+
+    if save:
+        plt.savefig(
+            "chart-connection-boxplot.png",
+            dpi=900,
+            bbox_inches="tight",
+            transparent=True
+        )
+
+    if show:
+        plt.show()
+
+
+def main():
+    #generate_measurement_stats_pie_chart(False, True)
+    #generate_measurement_repeats_histogram(False, True)
+    generate_connection_boxplots(False, True)
+
+
+if __name__ == "__main__":
+    main()

docs/analysis/main.py

@@ -0,0 +1,108 @@
+import json
+from datetime import datetime, timedelta
+
+import records as r
+
+def get_records() -> list[r.Collection]:
+    """Returns the trial data as a list of `records.Collection` objects."""
+
+    json_data = []
+    with open('data.json', 'r') as file:
+        json_data = json.load(file)
+
+    def incremented(time: datetime) -> datetime:
+        if time.hour == 22:
+            time += timedelta(hours=12)
+        else:
+            time += timedelta(hours=3)
+        return time
+
+    records: list[r.Collection] = []
+    time = datetime.fromisoformat("2023-08-14T10:00:00")
+
+    for item in json_data:
+        p1 = item['p1']
+        home_environment = item['home']
+
+        if p1:
+            mews = None
+            blood_pressure = None
+            body_temp = None
+            heart_rate = None
+            respiration_score = None
+            spo2 = None
+            s1 = None
+            b1 = None
+            t1 = None
+            p2 = None
+            s2 = None
+            b2 = None
+            t2 = None
+            uplink = None
+            downlink = None
+            rtt = None
+        else:
+            blood_pressure = r.BloodPressure(
+                time=datetime.fromisoformat(item['blood_pressure']['time']),
+                value_systolic=item['blood_pressure']['value_systolic'],
+                value_diastolic=item['blood_pressure']['value_systolic']
+            )
+            body_temp = r.BodyTemp(
+                time=datetime.fromisoformat(item['body_temp']['time']),
+                value=item['body_temp']['value']
+            )
+            heart_rate = r.HeartRate(
+                time=datetime.fromisoformat(item['heart_rate']['time']),
+                value=item['heart_rate']['value']
+            )
+            respiration_score = r.RespirationScore(
+                time=datetime.fromisoformat(item['respiration_score']['time']),
+                value=item['respiration_score']['value']
+            )
+            spo2 = r.Spo2(
+                time=datetime.fromisoformat(item['spo2']['time']),
+                value=item['spo2']['value']
+            )
+            s1 = item['s1']
+            b1 = item['b1']
+            t1 = item['t1']
+            p2 = item['p2']
+            s2 = item['s2']
+            b2 = item['b2']
+            t2 = item['t2']
+            uplink = item['uplink']
+            downlink = item['downlink']
+            rtt = item['rtt']
+            if s2 or b2 or t2:
+                mews = None
+            else:
+                mews = r.Mews(
+                    time=datetime.fromisoformat(item['mews']['time']),
+                    value=item['mews']['value']
+                )
+
+        records.append(r.Collection(
+            notification_time=time,
+            mews=mews,
+            blood_pressure=blood_pressure,
+            body_temp=body_temp,
+            heart_rate=heart_rate,
+            respiration_score=respiration_score,
+            spo2=spo2,
+            s1=s1,
+            b1=b1,
+            t1=t1,
+            s2=s2,
+            b2=b2,
+            t2=t2,
+            p1=p1,
+            p2=p2,
+            home_environment=home_environment,
+            uplink=uplink,
+            downlink=downlink,
+            rtt=rtt
+        ))
+
+        time = incremented(time)
+
+    return records

docs/analysis/records.py

@@ -0,0 +1,65 @@
+"""Type classes used during analysis."""
+
+from datetime import datetime
+from dataclasses import dataclass
+from typing import Optional
+
+
+@dataclass
+class BloodPressure:
+    time: datetime
+    value_diastolic: int
+    value_systolic: int
+
+
+@dataclass
+class BodyTemp:
+    time: datetime
+    value: float
+
+
+@dataclass
+class HeartRate:
+    time: datetime
+    value: int
+
+
+@dataclass
+class Mews:
+    time: datetime
+    value: int
+
+
+@dataclass
+class RespirationScore:
+    time: datetime
+    value: int
+
+
+@dataclass
+class Spo2:
+    time: datetime
+    value: int
+
+
+@dataclass
+class Collection:
+    notification_time: datetime
+    mews: Optional[Mews]
+    blood_pressure: Optional[BloodPressure]
+    body_temp: Optional[BodyTemp]
+    heart_rate: Optional[HeartRate]
+    respiration_score: Optional[RespirationScore]
+    spo2: Optional[Spo2]
+    s1: Optional[int]
+    b1: Optional[int]
+    t1: Optional[int]
+    s2: Optional[bool]
+    b2: Optional[bool]
+    t2: Optional[bool]
+    p1: bool
+    p2: Optional[bool]
+    home_environment: bool
+    uplink: Optional[float]
+    downlink: Optional[float]
+    rtt: Optional[int]

docs/analysis/shell.nix

@@ -0,0 +1,14 @@
+{ pkgs ? import <nixpkgs> {} }:
+  pkgs.mkShell {
+    nativeBuildInputs = with pkgs; [
+      python3Packages.numpy
+      python3Packages.matplotlib
+      python310Packages.pyqt6
+      python310Packages.pyside6
+      qt6.qtwayland
+    ];
+
+    shellHook = ''
+      export MPLBACKEND=QtAgg
+    '';
+}

docs/figures/components-micro.drawio

@@ -0,0 +1 @@
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docs/figures/datamodel.drawio

@@ -1 +1,210 @@
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+    "body_temp": {
+      "time": "2023-08-16T16:45:42",
+      "value": 37.64
+    },
+    "heart_rate": {
+      "time": "2023-08-16T16:47:26",
+      "value": 89
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": "2023-08-16T16:44:39",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-16T16:45:28",
+      "value": 98
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-16T20:12:49",
+      "value_diastolic": 81,
+      "value_systolic": 118
+    },
+    "body_temp": {
+      "time": "2023-08-16T20:11:58",
+      "value": 37.52
+    },
+    "heart_rate": {
+      "time": "2023-08-16T20:12:49",
+      "value": 97
+    },
+    "mews": {
+      "time": "2023-08-16T20:15:42",
+      "value": 0
+    },
+    "respiration_score": {
+      "time": "2023-08-16T20:10:52",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-16T20:11:35",
+      "value": 98
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-16T23:18:08",
+      "value_diastolic": 74,
+      "value_systolic": 125
+    },
+    "body_temp": {
+      "time": "2023-08-16T23:15:39",
+      "value": 37.65
+    },
+    "heart_rate": {
+      "time": "2023-08-16T23:18:08",
+      "value": 85
+    },
+    "mews": {
+      "time": "2023-08-16T23:18:50",
+      "value": 0
+    },
+    "respiration_score": {
+      "time": "2023-08-16T23:13:39",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-16T23:15:17",
+      "value": 99
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-17T11:01:05",
+      "value_diastolic": 79,
+      "value_systolic": 112
+    },
+    "body_temp": {
+      "time": "2023-08-17T11:00:04",
+      "value": 37.05
+    },
+    "heart_rate": {
+      "time": "2023-08-17T11:01:05",
+      "value": 87
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": "2023-08-17T10:58:59",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-17T10:59:48",
+      "value": 95
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-17T14:27:40",
+      "value_diastolic": 82,
+      "value_systolic": 118
+    },
+    "body_temp": {
+      "time": "2023-08-17T14:27:09",
+      "value": 37.43
+    },
+    "heart_rate": {
+      "time": "2023-08-17T14:27:40",
+      "value": 80
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": "2023-08-17T14:25:59",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-17T14:26:45",
+      "value": 98
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-17T16:53:03",
+      "value_diastolic": 71,
+      "value_systolic": 121
+    },
+    "body_temp": {
+      "time": "2023-08-17T16:52:21",
+      "value": 37.73
+    },
+    "heart_rate": {
+      "time": "2023-08-17T16:53:03",
+      "value": 83
+    },
+    "mews": {
+      "time": "2023-08-17T16:54:15",
+      "value": 0
+    },
+    "respiration_score": {
+      "time": "2023-08-17T16:50:34",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-17T16:51:58",
+      "value": 98
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-17T20:12:24",
+      "value_diastolic": 69,
+      "value_systolic": 129
+    },
+    "body_temp": {
+      "time": "2023-08-17T20:11:32",
+      "value": 37.46
+    },
+    "heart_rate": {
+      "time": "2023-08-17T20:12:24",
+      "value": 73
+    },
+    "mews": {
+      "time": "2023-08-17T20:13:09",
+      "value": 0
+    },
+    "respiration_score": {
+      "time": "2023-08-17T20:10:31",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-17T20:11:13",
+      "value": 96
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-17T22:47:55",
+      "value_diastolic": 81,
+      "value_systolic": 121
+    },
+    "body_temp": {
+      "time": "2023-08-17T22:47:18",
+      "value": 36.79
+    },
+    "heart_rate": {
+      "time": "2023-08-17T22:47:55",
+      "value": 95
+    },
+    "mews": {
+      "time": "2023-08-17T22:50:02",
+      "value": 0
+    },
+    "respiration_score": {
+      "time": "2023-08-17T22:46:04",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-17T22:46:54",
+      "value": 97
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-18T10:54:12",
+      "value_diastolic": 75,
+      "value_systolic": 124
+    },
+    "body_temp": {
+      "time": "2023-08-18T10:53:27",
+      "value": 37.34
+    },
+    "heart_rate": {
+      "time": "2023-08-18T10:54:12",
+      "value": 73
+    },
+    "mews": {
+      "time": "2023-08-18T10:55:50",
+      "value": 0
+    },
+    "respiration_score": {
+      "time": "2023-08-18T10:51:36",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-18T10:53:12",
+      "value": 96
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-18T13:32:51",
+      "value_diastolic": 86,
+      "value_systolic": 123
+    },
+    "body_temp": {
+      "time": "2023-08-18T13:32:16",
+      "value": 37.09
+    },
+    "heart_rate": {
+      "time": "2023-08-18T13:32:51",
+      "value": 61
+    },
+    "mews": {
+      "time": "2023-08-18T13:34:01",
+      "value": 0
+    },
+    "respiration_score": {
+      "time": "2023-08-18T13:29:25",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-18T13:31:55",
+      "value": 97
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-18T16:39:14",
+      "value_diastolic": 83,
+      "value_systolic": 122
+    },
+    "body_temp": {
+      "time": "2023-08-18T16:37:22",
+      "value": 37.13
+    },
+    "heart_rate": {
+      "time": "2023-08-18T16:39:14",
+      "value": 73
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": "2023-08-18T16:36:14",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-18T16:37:02",
+      "value": 96
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-18T19:38:58",
+      "value_diastolic": 75,
+      "value_systolic": 123
+    },
+    "body_temp": {
+      "time": "2023-08-18T19:36:37",
+      "value": 37.65
+    },
+    "heart_rate": {
+      "time": "2023-08-18T19:38:58",
+      "value": 114
+    },
+    "mews": {
+      "time": "2023-08-18T19:41:43",
+      "value": 2
+    },
+    "respiration_score": {
+      "time": "2023-08-18T19:35:24",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-18T19:36:14",
+      "value": 95
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": null,
+      "value_diastolic": null,
+      "value_systolic": null
+    },
+    "body_temp": {
+      "time": null,
+      "value": null
+    },
+    "heart_rate": {
+      "time": null,
+      "value": null
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": null,
+      "value": null
+    },
+    "spo2": {
+      "time": null,
+      "value": null
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-19T11:36:26",
+      "value_diastolic": 76,
+      "value_systolic": 121
+    },
+    "body_temp": {
+      "time": "2023-08-19T11:35:24",
+      "value": 37.5
+    },
+    "heart_rate": {
+      "time": "2023-08-19T11:36:26",
+      "value": 54
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": "2023-08-19T11:34:30",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-19T11:35:05",
+      "value": 98
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-19T13:24:56",
+      "value_diastolic": 73,
+      "value_systolic": 120
+    },
+    "body_temp": {
+      "time": "2023-08-19T13:24:02",
+      "value": 37.31
+    },
+    "heart_rate": {
+      "time": "2023-08-19T13:24:56",
+      "value": 106
+    },
+    "mews": {
+      "time": "2023-08-19T13:27:13",
+      "value": 1
+    },
+    "respiration_score": {
+      "time": "2023-08-19T13:21:46",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-19T13:23:43",
+      "value": 96
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": null,
+      "value_diastolic": null,
+      "value_systolic": null
+    },
+    "body_temp": {
+      "time": null,
+      "value": null
+    },
+    "heart_rate": {
+      "time": null,
+      "value": null
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": null,
+      "value": null
+    },
+    "spo2": {
+      "time": null,
+      "value": null
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": null,
+      "value_diastolic": null,
+      "value_systolic": null
+    },
+    "body_temp": {
+      "time": null,
+      "value": null
+    },
+    "heart_rate": {
+      "time": null,
+      "value": null
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": null,
+      "value": null
+    },
+    "spo2": {
+      "time": null,
+      "value": null
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": null,
+      "value_diastolic": null,
+      "value_systolic": null
+    },
+    "body_temp": {
+      "time": null,
+      "value": null
+    },
+    "heart_rate": {
+      "time": null,
+      "value": null
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": null,
+      "value": null
+    },
+    "spo2": {
+      "time": null,
+      "value": null
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": null,
+      "value_diastolic": null,
+      "value_systolic": null
+    },
+    "body_temp": {
+      "time": null,
+      "value": null
+    },
+    "heart_rate": {
+      "time": null,
+      "value": null
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": null,
+      "value": null
+    },
+    "spo2": {
+      "time": null,
+      "value": null
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-20T13:21:35",
+      "value_diastolic": 82,
+      "value_systolic": 119
+    },
+    "body_temp": {
+      "time": "2023-08-20T13:20:44",
+      "value": 37.29
+    },
+    "heart_rate": {
+      "time": "2023-08-20T13:21:35",
+      "value": 83
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": "2023-08-20T13:18:46",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-20T13:20:20",
+      "value": 98
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-20T16:13:04",
+      "value_diastolic": 79,
+      "value_systolic": 118
+    },
+    "body_temp": {
+      "time": "2023-08-20T16:12:05",
+      "value": 37.38
+    },
+    "heart_rate": {
+      "time": "2023-08-20T16:13:04",
+      "value": 95
+    },
+    "mews": {
+      "time": null,
+      "value": null
+    },
+    "respiration_score": {
+      "time": "2023-08-20T16:10:40",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-20T16:11:52",
+      "value": 97
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-20T19:06:47",
+      "value_diastolic": 82,
+      "value_systolic": 120
+    },
+    "body_temp": {
+      "time": "2023-08-20T19:05:37",
+      "value": 37.25
+    },
+    "heart_rate": {
+      "time": "2023-08-20T19:06:47",
+      "value": 93
+    },
+    "mews": {
+      "time": "2023-08-20T19:12:52",
+      "value": 0
+    },
+    "respiration_score": {
+      "time": "2023-08-20T19:04:47",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-20T19:05:24",
+      "value": 97
+    }
+  },
+  {
+    "blood_pressure": {
+      "time": "2023-08-20T22:25:47",
+      "value_diastolic": 73,
+      "value_systolic": 115
+    },
+    "body_temp": {
+      "time": "2023-08-20T22:25:06",
+      "value": 37.45
+    },
+    "heart_rate": {
+      "time": "2023-08-20T22:25:47",
+      "value": 83
+    },
+    "mews": {
+      "time": "2023-08-20T22:29:09",
+      "value": 0
+    },
+    "respiration_score": {
+      "time": "2023-08-20T22:23:27",
+      "value": 0
+    },
+    "spo2": {
+      "time": "2023-08-20T22:24:51",
+      "value": 97
+    }
+  }
+]

docs/thesis/cover.tex

@@ -1,28 +1,34 @@
 \begin{titlepage}
     \begin{center}
-        {\normalsize\textbf{Early detection of patient deterioration at home using smart medical sensors}} \\
+        {\Large\textbf{Early detection of patient deterioration at home using smart medical sensors}} \\
-        \vspace{1cm}
+        \vspace{2cm}
         \includegraphics[width=0.5\textwidth]{figures/tubs-logo.png} \\
+        \vspace{2cm}
+        {\large\textbf{Bachelor Thesis}} \\
         \vspace{1cm}
-        {\large{Bachelor Thesis}} \\
+        {\small{
-        \vspace{1cm}
-        {\small\textbf{
             submitted to \\
-            Peter L. Reichertz Institut für Medizinische Informatik \\
+            \vspace{1cm}
-            der Technischen Universität Braunschweig \\
+            \textbf{
-            und der Medizinischen Hochschule Hannover \\
+                Peter L. Reichertz Institut für Medizinische Informatik \\
+                der Technischen Universität Braunschweig \\
+                und der Medizinischen Hochschule Hannover \\
+            }
             \vspace{0.5cm}
-            in September 2023 \\
+            in \\
+            \vspace{0.5cm}
+            \textbf{September 2023} \\
             \vspace{0.5cm}
             by \\
-            Julian Lobbes \\
+            \vspace{0.5cm}
-            from Hannover
+            \textbf{Julian Lobbes} \\
+            born in Hannover
         }} \\
     \end{center}
     \vfill
     {\footnotesize{
-        Supervisor: Prof. Dr. Thomas M. Deserno \\
+        Supervisor: \textbf{Prof. Dr. Thomas M. Deserno} \\
-        Supervising assistant: Prof. Dr. Sharareh R. Niakan Kalhori \\
+        Supervising assistant: \textbf{Prof. Dr. Sharareh R. Niakan Kalhori} \\
     }}
 \end{titlepage}
 %\newpage

docs/thesis/glossary.tex

@@ -1,15 +1,211 @@
 \makenoidxglossaries
 \newglossaryentry{dbms}{
     type=\acronymtype,
-        name={DBMS},
+    name={DBMS},
-        description={Database Management System},
+    description={Database Management System},
-        first={\Gls{dbms_full} (DBMS)}
+    first={\Gls{dbms_full} (DBMS)}
 }
 \newglossaryentry{dbms_full}{
     name={Database Management System},
-        description={
+    description={
-            A Database Management System is a software system which enables the creation, organization, and management of databases.
+        A Database Management System is a software system which enables the creation, organization, and management of databases.
-            It generally acts as an interface between the database and client applications, ensuring that data is consistently
+        It generally acts as an interface between the database and client applications, ensuring that data is consistently
-            stored and readily accessible in a secure and efficient manner, while maintaining data integrity.
+        stored and readily accessible in a secure and efficient manner, while maintaining data integrity.
-        }
+        They can manage various forms of data, including text, numbers, multimedia, and more.
+        The DBMS plays a crucial role in maintaining the integrity, consistency, and security of the data it handles.
+    }
+}
+\newglossaryentry{gui}{
+    type=\acronymtype,
+    name={GUI},
+    description={Graphical User Interface},
+    first={Graphical User Interface (GUI)}
+}
+\newglossaryentry{ui}{
+    type=\acronymtype,
+    name={UI},
+    description={User Interface},
+    first={User Interface (UI)}
+}
+\newglossaryentry{iot}{
+    type=\acronymtype,
+    name={IoT},
+    description={Internet of Things},
+    first={Internet of Things (IoT)}
+}
+\newglossaryentry{spo2}{
+    type=\acronymtype,
+    name={SPO\textsubscript{2}},
+    description={\Gls{spo2_full}},
+    first={\Gls{spo2_full} (SPO\textsubscript{2})}
+}
+\newglossaryentry{spo2_full}{
+    name={Blood Oxygen Saturation},
+    description={
+        A percentage measure indicating the level of oxygen saturation in the blood.
+        The blood oxygen saturation represents the proportion of hemoglobin molecules in the bloodstream that are saturated with oxygen\cite{hafen_oxygen_2023}.
+    }
+}
+\newglossaryentry{uplink-datarate}{
+    name={uplink datarate},
+    description={
+        The speed at which data is transmitted from a client device, such as a computer or smartphone, to a server or central network.
+        Typically measured in Mbps (megabits per second), it represents the efficiency of data sending capabilities of a network connection.
+    }
+}
+\newglossaryentry{downlink-datarate}{
+    name={downlink datarate},
+    description={
+        The rate at which data is received by a client device from a central server or network.
+        Expressed often in Mbps, it reflects the downloading or data reception efficiency of a network connection.
+    }
+}
+\newglossaryentry{rtt}{
+    type=\acronymtype,
+    name={RTT},
+    description={\Gls{rtt_full}},
+    first={\Gls{rtt_full} (RTT)}
+}
+\newglossaryentry{rtt_full}{
+    name={Round trip time},
+    description={
+        The time taken for a data packet to travel from a source to a destination and back again.
+        It provides an indication of the latency or delay inherent in a network connection and is usually measured in milliseconds (ms).
+    }
+}
+\newglossaryentry{icu}{
+    type=\acronymtype,
+    name={ICU},
+    description={intensive care unit},
+    first={intensive care unit (ICU)},
+}
+\newglossaryentry{mews}{
+    type=\acronymtype,
+    name={MEWS},
+    plural={MEWSs},
+    description={\Gls{mews_full}},
+    first={\Gls{mews_full} (MEWS)},
+}
+\newglossaryentry{mews_full}{
+    name={Modified Early Warning Score},
+    description={
+        An adaptation of the \Gls{ews_full}, which provides a simplified scoring system based on fewer physiological parameters to predict medical deterioration.
+    }
+}
+\newglossaryentry{news2}{
+    type=\acronymtype,
+    name={NEWS2},
+    description={\Gls{news2_full}},
+    first={\Gls{news2_full} (NEWS2)},
+}
+\newglossaryentry{news2_full}{
+    name={National Early Warning Score 2},
+    description={
+        The second iteration of a standardized scoring system used in the UK to detect and respond to clinical deterioration in adult patients.
+        It builds upon and refines the original NEWS score.
+    }
+}
+\newglossaryentry{ews}{
+    type=\acronymtype,
+        name={EWS},
+        plural={EWSs},
+        description={\Gls{ews_full}},
+        first={\Gls{ews_full} (EWS)}
+}
+\newglossaryentry{ews_full}{
+    name={Early Warning Score},
+    plural={Early Warning Scores},
+    description={
+        A clinical tool used to assess the severity and likelihood of patient deterioration by scoring multiple vital signs.
+    }
+}
+\newglossaryentry{deterioration}{
+    name={deterioration},
+    description={
+        A decline in a patient's health status marked by worsening of clinical signs and symptoms, often necessitating escalated medical intervention.
+    }
+}
+\newglossaryentry{rpm}{
+    type=\acronymtype,
+    name={RPM},
+    description={\Gls{rpm_full}},
+    first={\Gls{rpm_full} (RPM)}
+}
+\newglossaryentry{rpm_full}{
+    name={remote patient monitoring},
+    description={
+        A technology to enable monitoring of patients outside of conventional clinical settings, such as in the home or in a remote area,
+        which may increase access to care and decrease healthcare delivery costs.
+    }
+}
+\newglossaryentry{rwsm}{
+    type=\acronymtype,
+    name={RWSM},
+    description={\Gls{rwm_full}},
+    first={\Gls{rwm_full} (RWSM)}
+}
+\newglossaryentry{rwm_full}{
+    name={Remote Warning Score Monitoring},
+    description={
+        An approach that integrates \gls{rpm} of mobile patients with the automated calculation of an \gls{ews}.
+        It enables real-time assessment of patient deterioration risk based on data gathered remotely.
+    }
+}
+\newglossaryentry{api}{
+    type=\acronymtype,
+    name={API},
+    description={\Gls{api_full}},
+    first={\Gls{api_full} (API)}
+}
+\newglossaryentry{api_full}{
+    name={Application Programming Interface},
+    description={
+        A set of rules and protocols that allow different software entities to communicate with each other. 
+        It defines the methods and data formats that applications can use to request and exchange information. 
+        APIs are utilized to enable the integration between different systems and devices, streamlining their functionalities and expanding capabilities.
+    }
+}
+\newglossaryentry{pews}{
+    type=\acronymtype,
+    name={PEWS},
+    description={\Gls{pews_full}},
+    first={\Gls{pews_full} (PEWS)}
+}
+\newglossaryentry{pews_full}{
+    name={Pediatric Early Warning Score},
+    description={
+        An early warning score used to identify early signs of \gls{deterioration} in pediatric patients.
+    }
+}
+\newglossaryentry{avpu}{
+    type=\acronymtype,
+    name={AVPU},
+    description={\Gls{avpu_full}},
+    first={\Gls{avpu_full} (AVPU)}
+}
+\newglossaryentry{avpu_full}{
+    name={AVPU Score},
+    description={
+        A rapid assessment method to determine a patient's level of consciousness.
+        The AVPU scale is used to quickly identify potential neurological impairment or altered mental status in emergency settings.
+        The four possible findings are:
+        \begin{itemize}
+            \item \textbf{Alert}: Patient is fully alert and oriented.
+            \item \textbf{Voice}: Patient responds to verbal stimuli but is not fully alert.
+            \item \textbf{Pain}: Patient responds only to painful stimuli.
+            \item \textbf{Unresponsive}: Patient does not respond to any external stimuli.
+        \end{itemize}
+    }
+}
+\newglossaryentry{ecg}{
+    type=\acronymtype,
+    name={ECG},
+    description={\Gls{ecg_full}},
+    first={\Gls{ecg_full} (ECG)}
+}
+\newglossaryentry{ecg_full}{
+    name={Electrocardiogram},
+    description={
+        A medical test that measures the electrical activity of the heartbeat to diagnose various heart conditions.
+    }
 }