ms762wu/EMG_Biometrics_2021
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chore: add table of contents in README

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Skudalen 2021-07-08 18:08:46 +02:00
parent 060507bc78
commit 8de9efb0ac
2 changed files with 13 additions and 7 deletions
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3
Neural_Network_Analysis.py
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@ -11,7 +11,7 @@ import matplotlib.pyplot as plt
# path to json file that stores MFCCs and subject labels for each processed sample
DATA_PATH = str(Path.cwd()) + "/mfcc_data.json"
def load_data(data_path):
def load_data_from_json(data_path):
with open(data_path, "r") as fp:
data = json.load(fp)
@ -30,6 +30,7 @@ def load_data(data_path):
return X, y
def plot_history(history):
"""Plots accuracy/loss for training/validation set as a function of the epochs
:param history: Training history of model

17
README.md
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@ -23,10 +23,15 @@ Scripts to handle CSV files composed by 2 * 8 EMG sensors(left & right) devided
## Table of Contents
| File and classes | Description and help functions |
|-----------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Handle_emg_data.py: - Data_container - CSV_handler - NN_handler | Handles, manipulates, and stores data for analysis. - Data_container is a class that describes the data for each subject in the experiment. Use __init__. - CSV_handler takes data from CSV files and places it in Data_container for each subject. Use load_data() to load csv data into data containers and add the containers to the CSV_handler's 'data_container_dict', indexed by subject number. Use get_data() to retrieve specific data. - NN_handler prepares data for further analysis in Neural Networks. This class has storage for this data and/or can save it to a json file. |
| Signal_prep.py | |
| Present_data.py | |
| Neural_Network_Analysis.py | |
| File and classes | Description and help functions |
|---|---|
| Handle_emg_data.py:<br><br> * Data_container<br> * CSV_handler<br> * NN_handler | Handles, manipulates, and stores data for analysis. <br><br> * Data_container is a class that describes the data for each subject in the experiment.<br> * CSV_handler takes data from CSV files and places it in Data_container for each subject.<br> Use load_data() to load csv data into data containers and add the containers to the <br> CSV_handler's 'data_container_dict', indexed by subject number. Use get_data() to retrieve <br> specific data. <br> * NN_handler prepares data for further analysis in Neural Networks. This class has storage <br> for this data and/or can save it to a json file. |
| Signal_prep.py | Does mapping to data and contains various functions. Among others, this contains wavelet, <br>MFCC, cepstrum and normalization. |
| Present_data.py | Contains plot and case functions. Case functions combines many elements from the code and <br>presents some results described. |
| Neural_Network_Analysis.py | Contains functions to load, build and execute analysis with Neural Networks. Main functions are <br>load_data_from_json(), build_model(), and main() |