README updates

Author: nitin710

README.md

@@ -1,5 +1,11 @@
 # Description
-This algorithm is derived from the Brainflow SpO2 algorithm, and uses PPG-R and PPG-IR data from the EmotiBit to calculate SPO2 level. As a starting point, `run.py` splits PPG-R and PPG-IR signals into buffers of length 64, which are then passed to the algorithm. It is recommended for the buffers to contain **at least** 64 samples for accurate results.
+This algorithm is derived from the Brainflow SpO2 algorithm, and uses PPG-R and PPG-IR data from the EmotiBit to calculate SPO2 level. 
+The repository has been setup to enable using the spO2 source code in both, Arduino and a standalone python script. We did this to enable testing source in pyhton, to fast track testing and enable us to improve algorithm performance with a shorter loop.
+
+- Arduino: To use this library in Arduino, just clone the git repo or download it using the Arduino Library manager into your `Arduino/libraries` directory.
+- Python:
+  - We use pybind11 to create bindgings for the c-source. The resulting `pyd` file is then used by the python script.
+  - To learn more about using pybind and pythin, check out the [pybind/README.md](./pybind/README.md).
 
 # Required Hardware
 - Emotibit

pybind/README.md

@@ -4,27 +4,32 @@
 - Python virtual environment (refer to the Emotibit Plugins [repo](https://github.com/EmotiBit/EmotiBit_Plugins/blob/main/README_py.md#Creating-python-env-with-pybind11) for specific instructions on how to setup)
 - CMake
 - [EmotiBit ArduinoFilters](https://github.com/EmotiBit/EmotiBit_ArduinoFilters)
+  - The EmotiBit ArduinoFilter directory should be on the same level as this repository.
   - **Option 1:** Library Manager 
     1. Open Arduino IDE, 
     1. open the Library Manager
     1. Download EmotiBit_ArduinoFilters `v1.0.1` (if not already installed)
-  - **Option 2:** `git clone`
+  - **Option 2:** `git clone` (*example showing cloning in Arduino Libraries directory, but user can clone in any other location, as long as ArduinoFilters is also cloned at the same directory level*)
     1. `cd` into Arduino libraries folder
        - **Windows:** `C:\Users\{username}\Documents\Arduino\libraries`
        - **Mac:** `/Users/{username}/Documents/Arduino/libraries`
        - **Linux:** `/home/{username}/Arduino/libraries`
     1. Run `git clone https://github.com/EmotiBit/EmotiBit_ArduinoFilters`
-    1. Run `git checkout 2a1d6cfa0b36ba8cf9e9a19b97d8fa261519a2d9`
 
 ## Build
 - Open a terminal window
 - `cd` into the `pybind` directory
-- Activate the Python virtual environment (instructions found in Emotibit Plugins [repo](https://github.com/EmotiBit/EmotiBit_Plugins/blob/main/README_py.md#setting-up-python-virtual-environment))
+- Before being able to run cmake, you will need to update the path to `pybind11` if required. `pybind11` is installed in the python virtual environment, as the link in the previous section explains.
+  - We tested this with cirtual environment created using python 3.12, and therefore the path to pybind in the current CMakeLists.txt file is `py-env/lib/python3.12/site-packages/pybind11/share/cmake/pybind11/`.
 - Run `cmake -B build` to generate the build files (the build files will be under a directory named `build`)
 - Run `cmake --build build --config Release` to generate the `.pyd` file
   - On Windows using MSVC, the `.pyd` file will be under `pybind/build/Release`
   - Otherwise, the `.pyd` file will be under `pybind/build`
+- Activate the Python virtual environment (instructions found in Emotibit Plugins [repo](https://github.com/EmotiBit/EmotiBit_Plugins/blob/main/README_py.md#setting-up-python-virtual-environment))
+
+### Running run.py
 - Open `run.py` and uncomment lines 6-7 (if on linux/macOS), or uncomment lines 10-11 (if on Windows)
+- `run.py` runs on emotibit data. We have checked in test data in thie repositoty. By default, the script looks for a `data` directory on the same level. Therefore, to test the script, you can extract the `tests/sit-stand-sit_v0.0.0/ip900ap/sit-stand-sit_v0.0.0_ip900ap.zip` file and place the EMotiBit.csv file in the `data` folder. You can then use the EmotiBit data parser to parse the files, since the script looks for files ending in `_PR` and `_PI`.
 
 ## Testing
 - Unzip the `.zip` file in `tests/simulated-unobstructed-airway_v0.0.0/ip900ap`