Added some code to visualize 'Force' data (could be tweaked to visualize other data)

1-first-project/notes.md

@@ -0,0 +1,73 @@
+# Notes on 1st project
+
+The given data at [iui-datalrelease1-sose2021-readonly/\*](/opt/iui-datarelease1-sose2021) represents sensor data from a pen.
+
+|----------------------------------------------------------------------------|
+| Data   | MinVal | MaxVal | Description                                     |
+| Millis |   -    |   -    | Timestamp from tablet                           |
+| Acc1 X |   -    |   -    | Front/Tip accelerometer (Direction: Left/Right) |
+| Acc1 Y |   -    |   -    | Front/Tip accelerometer (Direction: Up/Down)    |
+| Acc1 Z |   -    |   -    | Front/Tip accelerometer (Direction: Back/Front) |
+| Acc2 X |   -    |   -    | Back accelerometer (Direction: Left/Right)      |
+| Acc2 Y |   -    |   -    | Back accelerometer (Direction: Up/Down)         |
+| Acc1 Z |   -    |   -    | Back accelerometer (Direction: Back/Front)      |
+| Gyro X |   -    |   -    | Gyroscope sensor                                |
+| Gyro Y |   -    |   -    | Gyroscope sensor                                |
+| Gyro Z |   -    |   -    | Gyroscope sensor                                |
+| Mag X  |   -    |   -    | Magnetometer                                    |
+| Mag Y  |   -    |   -    | Magnetometer                                    |
+| Mag Z  |   -    |   -    | Magnetometer                                    |
+| Force  |   -    |   -    | Force applied                                   |
+| Time   |   -    |   -    | Time from start of "recording"                  |
+|----------------------------------------------------------------------------|
+
+There were 100 participants.
+
+The folder-structure is as follows:
+`/opt/iui-datarelease1-sose2021/{P}/{N}{A}.csv`
+P = The ID of the participant
+N = The N-th letter the participant wrote
+A = The letter that was written
+
+Each participants folder contains a `calibration.txt`, which contains the calibration data of the pen for the participant.
+
+Sensor data was recorded at 100hz (100 recordings/s => 1 recording/ms).
+
+## Preprocessing
+
+### Millis
+
+- Could be used for identifying each data entry -> needs to be normalized to the first entry of the data set to see the comlete timeline of the data
+
+### Acc1
+
+todo
+
+### Acc2
+
+todo
+
+### Gyro 
+
+todo
+
+### Mag
+
+todo
+
+### Force
+
+- Sometimes sensor data was recorded even when there is no action -> we need to determine the area of interest 
+  - maybe sliding window, where window avg has to be certain threshold
+  - general threshold aproach (filter out data below threshold)
+  - more ideas welcome
+  
+- Data could be normalized by each users relative strength or data entry 
+
+### Time
+
+- Time is negative for some data, gotta find out why
+
+## Model selection
+
+todo