Calculation of fascicle length and pennation angle

%% under construction!
Some paths do not seem to work properly. I will correct this in the next few days.

To calculates the length and angles you need the following:
- a set of 3d data of the muscles fascicles
- coordinates of the force axis
- coordinates of the anatomical landmarks from the calcaneus, the fibula and the main direction of the foot

- the coefficients of the polynomials got calculates with coeffvalues.m

code of the functions polynomtestlin, polynomtest22 and polynomtest33:

function [coefftest]=polynomtest33(AWert,CWert)

% %POLYNOMTEST33 Create plot of datasets and fits

% % POLYNOMTEST33(AWERT,CWERT)

% % Creates a plot, similar to the plot in the main curve fitting

% % window, using the data that you provide as input. You can

% % apply this function to the same data you used with cftool

% % or with different data. You may want to edit the function to

% % customize the code and this help message.

% %

% % Number of datasets: 1

% % Number of fits: 1

%
%

% % Data from dataset "CWert vs. AWert":

% % X = AWert:

% % Y = CWert:

% % Unweighted

% %

% % This function was automatically generated on 09-Feb-2011 13:59:28

%
%
% Set up figure to receive datasets and fits

% f_ = clf;

% figure(f_);

% set(f_,'Units','Pixels','Position',[943 394 680 484]);

% legh_ = []; legt_ = {};
% handles and text for legend

% xlim_ = [Inf -Inf];
% limits of x axis

% ax_ = axes;

% set(ax_,'Units','normalized','OuterPosition',[0 0 1 1]);

% set(ax_,'Box','on');

% axes(ax_); hold on;

%
%

% % --- Plot data originally in dataset "CWert vs. AWert"

% AWert = AWert(:);

% CWert = CWert(:);

% h_ = line(AWert,CWert,'Parent',ax_,'Color',[0.333333 0 0.666667],...

% 'LineStyle','none', 'LineWidth',1,...

% 'Marker','.', 'MarkerSize',12);

% xlim_(1) = min(xlim_(1),min(AWert));

% xlim_(2) = max(xlim_(2),max(AWert));

% legh_(end+1) = h_;

% legt_{end+1} = 'CWert vs. AWert';

%
%
% Nudge axis limits beyond data limits

% if all(isfinite(xlim_))

% xlim_ = xlim_ + [-1 1] * 0.01 * diff(xlim_);

% set(ax_,'XLim',xlim_)

% else

% set(ax_, 'XLim',[67.61313437675885, 89.315211296848659]);

% end

% --- Create fit "fit 30"
ok_ = isfinite(AWert) & isfinite(CWert);
if ~all( ok_ )
warning( 'GenerateMFile:IgnoringNansAndInfs', ...
'Ignoring NaNs and Infs in data' );
end
ft_ = fittype('poly3');

% Fit this model using new data
cf_ = fit(AWert(ok_),CWert(ok_),ft_);

% % Or use coefficients from the original fit:
% if 0
% cv_ = { 0.00017185714749200226, -0.046155284038860329, 4.1919924194089013, -127.69125063698891};
% cf_ = cfit(ft_,cv_{:});
% end
coefftest=cf_;
% % Plot this fit
% h_ = plot(cf_,'fit',0.95);
% legend off; % turn off legend from plot method call
% set(h_(1),'Color',[1 0 0],...
% 'LineStyle','-', 'LineWidth',2,...
% 'Marker','none', 'MarkerSize',6);
% legh_(end+1) = h_(1);
% legt_{end+1} = 'fit 30';
%
% % Done plotting data and fits. Now finish up loose ends.
% hold off;
% leginfo_ = {'Orientation', 'vertical', 'Location', 'NorthEast'};
% h_ = legend(ax_,legh_,legt_,leginfo_{:}); % create legend
% set(h_,'Interpreter','none');
% xlabel(ax_,''); % remove x label

% ylabel(ax_,'');
% remove y label

Additionally you can calculate the proximal and distal aponeurosis.