SIMI Motion, compared to GAITRite System Metrics
# Pre-Requisite:
# Written to run on Spyder IDE (Anaconda3 environment), Python 3.8.
# 1) "SIMIpy_m_main.py" to process all trials for all patricipants.
# Required: The folder structure should contain all 4 trial types collected for each and every participant.
# Each trial type should contain (3) files: one .txt file for SIMI data, and two .csv files for GS data ans GS sync:
# filepath = r"C:\...\X9001262 - Data\10010012\X9001262_A_10010012_01_SIMIMCS1_Normal_Walk_marker_processed_7_13_2021.txt"
# filepath_GS = r"C:\...\X9001262 - Data\10010012\X9001262_A_10010012_01_Normal_PKMAS.csv"
# filepath_GS_sync = r"C:\...\X9001262 - Data\10010012\X9001262_A_10010012_01_Normal_PKMAS_sync.csv"
# Calculates all SIMI vs. GS metrics and generates comparisons based on processed SIMI and GS data.
# Generates metrics for all trials and saves into a "Batch_Outputs" dictionary.
# 2) "SIMIpy_m_GUI.py" to select any one of the four trial types above, for further processing or visualization.
# 3) "SIMIpy_m_metric.py" to process the metrics for the selected individual trial.
# 4) "SIMIpy_m_plots.py" to plot the results such as GS events, and calculated metrics based on FVA, HMA, Heel to Heel Distance Algorithms.
# Scripts required:
# SIMIpy_m_Event_Metrics.py
# SIMIpy_m_filenames.py
# SIMIpy_m_GUI.py
# SIMIpy_m_main.py
# SIMIpy_m_metrics.py
# SIMIpy_m_metrics_SIMI_passes.py
# SIMIpy_m_PKMAS_sync.py
# SIMIpy_m_plots.py
# SIMIpy_m_processing_filepair.py