Matlab_Codes_for_Processing/dataVisualizer.m

% dataVisualizer.m

% dataVisualizer visualizes joint angles and EMG signals for the Gait120 dataset.
% Kinematic data visualization uses the "kinematicsVisualizer" function, and EMG signal
% visualization uses the "EMGSignalVisualizer" function.
%
% Author: Junyo Boo (2025)  
% Data DOI: https://doi.org/10.6084/m9.figshare.27677016  
%
% The following script is provided under the Creative Commons Attribution 4.0
% International License (CC-BY 4.0).
%
% You are free to share and adapt this material for any purpose, even commercially,
% provided you give appropriate credit, provide a link to the license, and indicate
% if changes were made. The full license text can be found at:
%
% https://creativecommons.org/licenses/by/4.0/
%
% This file also includes the 'varycolor' function originally created by Daniel Helmick (2008),
% which is provided under a BSD-style license. See the function definition below for details.
%
%---------------------------------------------------------------------------------------

clear;
clc;
data_root = 'Gait120 Data';
kinematicsVisualizer(data_root);
EMGSignalVisualizer(data_root);

%%
function kinematicsVisualizer(data_root)
    target_task_name = {'LevelWalking', 'StairAscent', 'StairDescent',"SlopeAscent", 'SlopeDescent', 'SitToStand', 'StandToSit'};
    task_name_num = numel(target_task_name);
    target_mot_col_idx = [8, 9, 10, 11, 13];
    target_spline_normal_num = 101;
    
    total_data_cell = cell(1,task_name_num);
    total_data_subject_cell = cell(1,task_name_num);
    mot_data_struct = RealDir(data_root);
    task_data_num = zeros(1,task_name_num);
    
    for subject_idx = 1:numel(mot_data_struct)
        subject_trial = 0;
        subject_name = mot_data_struct(subject_idx).name;
        subject_folder = fullfile(mot_data_struct(subject_idx).folder, mot_data_struct(subject_idx).name, 'JointAngle');
        for task_idx = 1:task_name_num
            task_name = target_task_name{task_idx};
            task_directory = fullfile(subject_folder, task_name);
            task_struct = RealDir(task_directory);
            
            for trial_idx = 1:numel(task_struct)
                trial_name = task_struct(trial_idx).name;
                trial_directory = fullfile(task_directory, trial_name);
                trial_struct = RealDir(trial_directory);
                for step_idx = 1:numel(trial_struct)
                    task_data_num(task_idx) = task_data_num(task_idx)+1;
                    if task_idx == 6
                        subject_trial = subject_trial + 1;
                    end
                end
            end
        end
    end
    task_data_idx = ones(1,task_name_num);
    for i=1:task_name_num
        total_data_cell{i} = zeros(target_spline_normal_num,numel(target_mot_col_idx), task_data_num(i));
        total_data_subject_cell{i} = zeros(task_data_num(i),4);
    end
    
    for subject_idx = 1:numel(mot_data_struct)
        subject_name = mot_data_struct(subject_idx).name;
        subject_folder = fullfile(mot_data_struct(subject_idx).folder, mot_data_struct(subject_idx).name, 'JointAngle');
        for task_idx = 1:task_name_num
            task_name = target_task_name{task_idx};
            task_directory = fullfile(subject_folder, task_name);
            task_struct = RealDir(task_directory);
            
            for trial_idx = 1:numel(task_struct)
                trial_name = task_struct(trial_idx).name;
                trial_directory = fullfile(task_directory, trial_name);
                trial_struct = RealDir(trial_directory);
                for step_idx = 1:numel(trial_struct)
                    mot_file_directory = fullfile(trial_struct(step_idx).folder, trial_struct(step_idx).name);
                    splined_mot_data = SplineMotData(mot_file_directory, target_mot_col_idx, target_spline_normal_num);
                    total_data_cell{task_idx}(:,:,task_data_idx(task_idx)) = splined_mot_data;
                    total_data_subject_cell{task_idx}(task_data_idx(task_idx),:) = [task_data_idx(task_idx), subject_idx, trial_idx, step_idx];
                    task_data_idx(task_idx) = task_data_idx(task_idx) + 1;
                end
            end
        end
        fprintf("Loaded %s subject kinematics.\n", subject_name);
    end

    f=figure();
    for task_idx = 1:task_name_num
        temp_task_data = total_data_cell{task_idx};
        joint_num = size(temp_task_data,2);
        color_list = varycolor(joint_num);
        for joint_idx = 1:joint_num
            plot_idx = task_name_num*(joint_idx-1)+task_idx;
            subplot(joint_num,task_name_num,plot_idx);
            temp_joint_data = squeeze(temp_task_data(:,joint_idx,:));
            if joint_idx == 4
                temp_joint_data = -temp_joint_data;
            end
            plot_std_box(linspace(0,100,101), temp_joint_data',color_list(joint_idx,:));
    
        end
    end
    
    target_task_name = {"Level Walking", "Stair Ascent", "Stair Descent","Slope Ascent", "Slope Descent", "Sit-to-Stand", "Stand-to-Sit"};
    joint_name = {"Hip Flexion (Deg)", "Hip Adduction (Deg)", "Hip Int. Rot. (Deg)", "Knee Flexion (Deg)", "Ankle Dorsiflexion (Deg)"};
    figure(1);
    for i=1:7
        subplot(5,7,i);
        title(target_task_name{i}, 'FontSize',10, 'FontName','Times new roman');
    end
    for i=1:5
        subplot(5,7,7*(i-1)+1);
        ylabel(joint_name{i}, 'FontSize',10, 'FontName','Times new roman');
    end
    for i=1:7
        subplot(5,7,4*7+i);
        if (i<6)
            xlabel('Gait cycle (%)', 'FontSize',10, 'FontName','Times new roman');
        elseif (i==6)
            xlabel('Sit-to-stand (%)', 'FontSize',10, 'FontName','Times new roman');
        else
            xlabel('Stand-to-sit (%)', 'FontSize',10, 'FontName','Times new roman');
        end
    end
    f.Position = [422.500000000000	55.5000000000000	1147	835];
end
%%
function EMGSignalVisualizer(data_root)
    target_task_name = {'LevelWalking', 'StairAscent', 'StairDescent',"SlopeAscent", 'SlopeDescent', 'SitToStand', 'StandToSit'};
    task_name_num = numel(target_task_name);
    
    total_data_cell = cell(1,task_name_num);
    data_struct = RealDir(data_root);

    for subject_idx = 1:numel(data_struct)
        subject_trial = 0;
        subject_name = data_struct(subject_idx).name;
        subject_folder = fullfile(data_struct(subject_idx).folder, data_struct(subject_idx).name, 'EMG');
        emg_processed_data = load(fullfile(subject_folder, 'ProcessedData.mat'));
        
        for task_idx = 1:task_name_num
            task_name = target_task_name{task_idx};
            
            for trial_idx = emg_processed_data.(task_name).AvailableTrialIdx
                trial_name = sprintf('Trial%02d', trial_idx);
                for step_idx = 1:emg_processed_data.(task_name).(trial_name).nSteps
                    step_name = sprintf('Step%02d', step_idx);
                    emg_step_table = emg_processed_data.(task_name).(trial_name).(step_name).EMGs_interpolated;
                    if (subject_idx == 1 && task_idx == 1 && trial_idx == 1 && step_idx ==1)
                        muscle_names = emg_step_table.Properties.VariableNames;
                    end
                    emg_step_array = table2array(emg_step_table);
                    emg_step_array_reshaped = permute(emg_step_array, [1, 3, 2]);
                    total_data_cell{task_idx} = cat(2, total_data_cell{task_idx}, emg_step_array_reshaped);
                    if task_idx == 7
                        subject_trial = subject_trial + 1;
                    end
                end
            end
        end
        fprintf("Loaded %s subject EMG data.\n", subject_name);
    end
    
    f=figure();
    
    task_name_num = 7;
    plot_task_name = {'Level Walking', 'Stair Ascent', 'Stair Descent',"Slope Ascent", 'Slope Descent', 'Sit-to-Stand', 'Stand-to-Sit'};
    
    muscle_names_small = {'VL', 'RF', 'VM', 'TA', 'BF', 'ST', 'GM','GL','SM','SL','PL','PB'};
    muscle_num = numel(muscle_names);
    ymax_list = zeros(1,muscle_num);
    ymin_list = zeros(1,muscle_num);
    for task_idx = 1:task_name_num
        temp_task_data = total_data_cell{task_idx};
        color_list = varycolor(muscle_num);
        for muscle_idx = 1:muscle_num
            plot_idx = task_name_num*(muscle_idx-1)+task_idx;
            subplot(muscle_num,task_name_num,plot_idx);
            temp_joint_data = squeeze(temp_task_data(:,:,muscle_idx));
            plot_std_box(linspace(0,100,101), temp_joint_data',color_list(muscle_idx,:));
            ax = gca;
            yMax = ax.YLim(2);
            yMin = ax.YLim(1);
    
            if muscle_idx == 1
                title(plot_task_name{task_idx}, 'FontSize',10, 'FontName','Times new roman');
            end
            if muscle_idx == muscle_num
                if task_idx < 6
                    xlabel('Gait cycle (%)', 'FontSize',10, 'FontName','Times new roman');
                elseif task_idx == 6
                    xlabel('Sit-to-stand (%)', 'FontSize',10, 'FontName','Times new roman');
                else
                    xlabel('Stand-to-sit (%)', 'FontSize',10, 'FontName','Times new roman');
                end
            end
            if task_idx == 1
                ylabel(muscle_names_small{muscle_idx}, 'FontSize',10, 'FontName','Times new roman', 'Color','k');
            end
            if ymax_list(muscle_idx) < yMax
                ymax_list(muscle_idx) = yMax;
            end
            if ymin_list(muscle_idx) > yMin
                ymin_list(muscle_idx) = yMin;
            end
        end
    end
    f.Position = [376.500000000000	2	1088.50000000000	1002];
    for muscle_idx =1:muscle_num
        for task_idx = 1:task_name_num
            plot_idx = task_name_num*(muscle_idx-1)+task_idx;
            subplot(muscle_num,task_name_num,plot_idx);
            ylim([ymin_list(muscle_idx), ymax_list(muscle_idx)]);
        end
    end
    
    han = axes(figure(1), 'Visible', 'off');
    han.YLabel.Visible = 'on';
    ylabel(han, 'Muscle activation', 'FontSize',15, 'FontName','Times new roman');
    han.YLabel.Position(1) = han.YLabel.Position(1) - 0.01;
end
%%
function dir_struct = RealDir(directory)
    dir_struct = dir(directory);
    dir_struct = dir_struct(~ismember({dir_struct.name}, {'.', '..'}));
end
%%
function splined_mot_data = SplineMotData(mot_filename, target_idx, target_spline_normal_num)
    mot_data = readMOT(mot_filename);
    target_mot_data = mot_data.data(:,target_idx);
    x = linspace(0, 1, mot_data.nr);
    y = target_mot_data';
    xq = linspace(0,1,target_spline_normal_num);
    splined_mot_data = spline(x, y, xq)';
end
%%
function q = readMOT(fname)
    % q = readMOT(fname)
    % Input:    fname is the name of the ascii datafile to be read 
    % Output:   q returns a structure with the following format:
    %				q.labels 	= array of column labels
    %				q.data 		= matrix of data
    %				q.nr 		= number of matrix rows
    %				q.nc 		= number of matrix columns
    
    % Open ascii data file for reading.
    fid = fopen(fname, 'r');	
    if fid == -1								
	    error(['unable to open ', fname])		
    end
    % Process the file header;
    % store # data rows, # data columns.
    q.nr = 0; % Added to ensure that the q structures from reading a motion file
    q.nc = 0; % are always the same, even if nr and nc are different orders in file.
    nextline = fgetl(fid);	
    while ~strncmpi(nextline, 'endheader', length('endheader'))
	    if strncmpi(nextline, 'datacolumns', length('datacolumns'))
		    q.nc = str2num(nextline(findstr(nextline, ' ')+1 : length(nextline)));
	    elseif strncmpi(nextline, 'datarows', length('datarows'))
		    q.nr = str2num(nextline(findstr(nextline, ' ')+1 : length(nextline)));
	    elseif strncmpi(nextline, 'nColumns', length('nColumns'))
		    q.nc = str2num(nextline(findstr(nextline, '=')+1 : length(nextline)));
	    elseif strncmpi(nextline, 'nRows', length('nRows'))
		    q.nr = str2num(nextline(findstr(nextline, '=')+1 : length(nextline)));
        elseif strncmpi(nextline, 'inDegrees', length('inDegrees'))
		    q.inDeg = nextline(findstr(nextline, '=')+1 : length(nextline));
	    end
	    nextline = fgetl(fid);
    end
    % Process the column labels.
    nextline = fgetl(fid);
    if (all(isspace(nextline))) % Blank line, so the next one must be the one containing the column labels
	    nextline = fgetl(fid);
    end
    a=textscan(nextline,'%s','MultipleDelimsAsOne',1,'Delimiter',sprintf('\t'));
    q.labels = [a{:}]';
    % Process the data.
    % Note:  transpose is needed since fscanf fills columns before rows.
    % Text = fscanf(fid, '%c');fclose(fid);
    Data = fscanf(fid, '%f', [q.nc, q.nr])';fclose(fid);

    if any(size(Data)~=[q.nr, q.nc]) || (q.nr==0 && q.nc==1)
        fid = fopen(fname, 'r');
        Text = fscanf(fid,'%c');fclose(fid);
        if any(strfind(Text,'1.#QNAN0000000'))
            Text=strrep(Text,'1.#QNAN0000000','0.000000000000');
        end
        if any(strfind(Text,'-1.#IND00000000'))
            Text=strrep(Text,'-1.#IND00000000','0.000000000000');
        end
        if any(strfind(Text,'-1.#INF00000000'))
            Text=strrep(Text,'-1.#INF00000000','0.000000000000');
        end
        if any(strfind(Text,'242373565591244840000000000000000000000000000000000000000000000000000000000000000.000000000000'))
            Text=strrep(Text,'242373565591244840000000000000000000000000000000000000000000000000000000000000000.000000000000','0.000000000000');
        end    
        
        fid = fopen(fname, 'w');
        fprintf(fid,'%s',Text);fclose(fid);
        DataStart = strfind(Text,q.labels{end});
        DataStart=DataStart-1+min(strfind(Text(DataStart:end),char(13)))+1;
        DataText = Text(DataStart:end);
        LettersFound = intersect(regexp(DataText,'\w'),regexp(DataText,'\D'));
        if any(LettersFound)
            warning('letters found in data :')
            DataText(LettersFound)
        end
        DataText = strrep(DataText,DataText(LettersFound),'');
        Data = textscan(DataText, '%f');
        Data = Data{1};
        if length(Data) == q.nc*q.nr
            Data = reshape(Data,q.nc,q.nr)';
        else
            warning('not correct size of data specified in header, using size of Data vector and length of column labels')
            q.nc = length(q.labels);
            q.nr = length(Data)./q.nc;
            Data = reshape(Data,q.nc,q.nr)';
        end
        if any(size(Data)~=[q.nr q.nc])
            warning('File read error still'),beep
        end
    end
    q.data = Data;
end
%%
function ColorSet=varycolor(NumberOfPlots)
    % VARYCOLOR Produces colors with maximum variation on plots with multiple
    % lines.
    %
    %     VARYCOLOR(X) returns a matrix of dimension X by 3.  The matrix may be
    %     used in conjunction with the plot command option 'color' to vary the
    %     color of lines.  
    %
    %     Yellow and White colors were not used because of their poor
    %     translation to presentations.
    % 
    %     Example Usage:
    %         NumberOfPlots=50;
    %
    %         ColorSet=varycolor(NumberOfPlots);
    % 
    %         figure
    %         hold on;
    % 
    %         for m=1:NumberOfPlots
    %             plot(ones(20,1)*m,'Color',ColorSet(m,:))
    %         end
    %Created by Daniel Helmick 8/12/2008

    % Original source: MATLAB Central File Exchange
    % URL: https://kr.mathworks.com/matlabcentral/fileexchange/21050-varycolor
    %
    % The following BSD-style license applies to the 'varycolor' function:
    %
    % Copyright (c) 2008, Daniel Helmick
    % All rights reserved.
    %
    % Redistribution and use in source and binary forms, with or without
    % modification, are permitted provided that the following conditions are met:
    %
    %   * Redistributions of source code must retain the above copyright
    %     notice, this list of conditions and the following disclaimer.
    %   * Redistributions in binary form must reproduce the above copyright
    %     notice, this list of conditions and the following disclaimer in the
    %     documentation and/or other materials provided with the distribution.
    %
    % THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
    % AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
    % IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
    % ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
    % LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
    % CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
    % SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
    % INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
    % CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
    % ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
    % POSSIBILITY OF SUCH DAMAGE.
    %
    %------------------------------------------------------------------

    error(nargchk(1,1,nargin))%correct number of input arguements??
    error(nargoutchk(0, 1, nargout))%correct number of output arguements??
    %Take care of the anomolies
    if NumberOfPlots<1
        ColorSet=[];
    elseif NumberOfPlots==1
        ColorSet=[0 1 0];
    elseif NumberOfPlots==2
        ColorSet=[0 1 0; 0 1 1];
    elseif NumberOfPlots==3
        ColorSet=[0 1 0; 0 1 1; 0 0 1];
    elseif NumberOfPlots==4
        ColorSet=[0 1 0; 0 1 1; 0 0 1; 1 0 1];
    elseif NumberOfPlots==5
        ColorSet=[0 1 0; 0 1 1; 0 0 1; 1 0 1; 1 0 0];
    elseif NumberOfPlots==6
        ColorSet=[0 1 0; 0 1 1; 0 0 1; 1 0 1; 1 0 0; 0 0 0];
    else %default and where this function has an actual advantage
        %we have 5 segments to distribute the plots
        EachSec=floor(NumberOfPlots/5); 
        
        %how many extra lines are there? 
        ExtraPlots=mod(NumberOfPlots,5); 
        
        %initialize our vector
        ColorSet=zeros(NumberOfPlots,3);
        
        %This is to deal with the extra plots that don't fit nicely into the
        %segments
        Adjust=zeros(1,5);
        for m=1:ExtraPlots
            Adjust(m)=1;
        end
        
        SecOne   =EachSec+Adjust(1);
        SecTwo   =EachSec+Adjust(2);
        SecThree =EachSec+Adjust(3);
        SecFour  =EachSec+Adjust(4);
        SecFive  =EachSec;
        for m=1:SecOne
            ColorSet(m,:)=[0 1 (m-1)/(SecOne-1)];
        end
        for m=1:SecTwo
            ColorSet(m+SecOne,:)=[0 (SecTwo-m)/(SecTwo) 1];
        end
        
        for m=1:SecThree
            ColorSet(m+SecOne+SecTwo,:)=[(m)/(SecThree) 0 1];
        end
        
        for m=1:SecFour
            ColorSet(m+SecOne+SecTwo+SecThree,:)=[1 0 (SecFour-m)/(SecFour)];
        end
        for m=1:SecFive
            ColorSet(m+SecOne+SecTwo+SecThree+SecFour,:)=[(SecFive-m)/(SecFive) 0 0];
        end
        
    end
end
%%
function plot_std_box(x, data, color)
    data_mean = mean(data);
    data_std = std(data);
    
    xconf = [x x(end:-1:1)] ;         
    yconf = [data_mean+data_std data_mean(end:-1:1)-data_std(end:-1:1)];
    
    plot(x,data_mean,'Color', color);
    hold on;
    p = fill(xconf,yconf, 'k');
    p.FaceAlpha = 0.1;
    p.EdgeColor = 'none';

    hold on;
    plot(x,data_mean,'Color',color, "LineWidth", 2);
    hold off;
end