Functions
function LRFB_3()%Version 3	delete (timerfindall)
interface with nidaq or	winsound (guessing) if~isempty(findstr('nidaq'
	addchannel (ai, options.ai)
	set (ai,'InputType','SingleEnded')
	set (ai,'LoggingMode','Memory') setverify(ai.Channel
elseif	~isempty (findstr('winsound', options.aidevice_name)) ai
	h_rms (i)
	h_filt (i)
	h_text (i)
	title (['Channel ', num2str(options.ai(i))])%legend('Raw data'
id	bkg_color ()
calculates threshold from average of best calibrations	load (sprintf('LRFBcalibration_%s%d_%d.mat', cohort, subject_id, calibration1))
	load (sprintf('LRFBcalibration_%s%d_%d.mat', cohort, subject_id, calibration2))
	Screen ('TextSize', wPtr, 72)
	DrawFormattedText (wPtr,'Start','center','center', wait_color)
	Screen (wPtr,'Flip')
end	Screen ('FillRect', wPtr, bkg_color)
Variables
clear	all
	options = paramSetupLRFB
pulls up GUI CHANGE EACH TIME	subject_id = options.subject_ID
	calibration1 = options.calibration1
	calibration2 = options.calibration2
	block = options.block
	cohort = 'CY'
timing definitions	sampleRate = 4000
Hz	dataRate = 12
Hz	filter_alpha = .95
interface with nidaq or options aidevice_name	ai = analoginput('nidaq','Dev1')
	actualRate = setverify(ai,'SampleRate',sampleRate)
ai	SamplesPerTrigger = Inf
	InputRange
else	return
end for loop to plot	data
end for loop to plot	RMF
end for loop to plot filter for each channel	h_fig = figure
for	i
hold	on
	RMS
Filtered end	commands = {'Left','Right','Forward','Backward'}
	nTrials = 12
should be divisible by	nListReps = ceil(nTrials/length(commands))
	command_list = repmat(commands',nListReps,1)
randomizes	reorder_idx = randperm(size(command_list,1))
	win = 1
is default	dims = [0 0 500 500]
	wait_color = 255
	go_color = [0 150 0]
	l_threshold = max(draw_rms(:,1))
	r_threshold = max(draw_rms(:,2))
	f_threshold = max(draw_rms(:,3))
	wink_threshold = max(draw_rms(:,4))
for bit calculations later	nChoices = length(commands)
	nCorrect = 0
	total_t = 0
	STARTING [wPtr, rect] = Screen('OpenWindow',win,bkg_color,dims)
	tic
while toc< 2endfor i=1:nTrials all_data=zeros(1, 4);all_t=[];draw_t=[];draw_rms=zeros(1, 4);draw_y=[];Screen('TextSize', wPtr, 72);DrawFormattedText(wPtr, char(command_list(i)),'center','center', wait_color);Screen(wPtr,'Flip');tic;while toc< 2 end Screen('TextSize', wPtr, 72);DrawFormattedText(wPtr, char(command_list(i)),'center','center', go_color);t_start=Screen(wPtr,'Flip');tic;start(ai);t=0;while isrunning(ai)&&max(draw_rms(:, 4))< wink_threshold[emg_data, emg_t]=getdata(ai, actualRate/dataRate);t=toc;%concatenate all data all_data=[all_data;emg_data];all_t=[all_t;emg_t];draw_t=[draw_t;t];if~exist('draw_rms','var') draw_rms=[];end draw_rms=[draw_rms;zeros(1, size(emg_data, 2))];for j=1:length(options.ai) draw_rms(end, j)=sqrt(mean(emg_data(:, j).^2));%draw_rms=[draw_rms;sqrt(mean(emg_data(:, 1).^2)) sqrt(mean(emg_data(:, 2).^2))];end if~isempty(draw_y) draw_y=[draw_y;filter_alpha draw_y(end,:)+(1-filter_alpha)(draw_rms(end,:))];else draw_y=draw_rms(end,:);end end given_command=command_list(i);stop(ai);nSamples=length(draw_rms);window_idx=floor(nSamples *.20);if window_idx==0 window_idx=1;end window=draw_rms(window_idx:end,:);%classifier if((max(window(:, 1)))> l_threshold)&&((max(window(:, 2)))< r_threshold)&&((max(window(:, 3)))< f_threshold) movement= 'Left';elseif(max(window(:, 1))< l_threshold)&&(max(window(:, 2))> r_threshold)&&(max(window(:, 3))< f_threshold) movement= 'Right';elseif(max(window(:, 1))> l_threshold)&&(max(window(:, 2))>r_threshold)&&(max(window(:, 3))> f_threshold) movement= 'Forward';elseif(max(window(:, 1))> l_threshold)&&(max(window(:, 2))> r_threshold &	max )(window(:, 3))< f_threshold) movement = 'Backward'
else	movement = 'Unknown'
	t_end = Screen(wPtr,'Flip')

Function Documentation

addchannel	(	ai	,
		options.	ai
	)

id bkg_color ( ) [virtual]

function LRFB_3 () % Version 3 delete ( timerfindall )

DrawFormattedText	(	wPtr	,
		'Start'	,
		'center'	,
		'center'	,
		wait_color
	)

h_filt ( i )

h_rms ( i )

h_text ( i )

load ( sprintf('LRFBcalibration_%s%d_%d.mat', cohort, subject_id, calibration2) )

calculates threshold from average of best calibrations load ( sprintf('LRFBcalibration_%s%d_%d.mat', cohort, subject_id, calibration1) )

Screen	(	wPtr	,
		'Flip'
	)

end Screen	(	'FillRect'	,
		wPtr	,
		bkg_color
	)

Screen	(	'TextSize'	,
		wPtr	,
		72
	)

set	(	ai	,
		'InputType'	,
		'SingleEnded'
	)

set	(	ai	,
		'LoggingMode'	,
		'Memory'
	)

title ( )

interface with nidaq or winsound ( guessing )

elseif ~isempty ( findstr('winsound', options.aidevice_name) )

Variable Documentation

actualRate = setverify(ai,'SampleRate',sampleRate)

interface with nidaq or options aidevice_name ai = analoginput('nidaq','Dev1')

close all

block = options.block

calibration1 = options.calibration1

calibration2 = options.calibration2

cohort = 'CY'

command_list = repmat(commands',nListReps,1)

Filtered end commands = {'Left','Right','Forward','Backward'}

end for loop to plot data

Hz dataRate = 12

is default dims = [0 0 500 500]

f_threshold = max(draw_rms(:,3))

Hz filter_alpha = .95

go_color = [0 150 0]

end for loop to plot filter for each channel h_fig = figure

for i

Initial value:

1:length(options.ai)
%     subplot(length(options.ai),1,i)
%     h_raw(i) = plot(0,0,'b')

InputRange

l_threshold = max(draw_rms(:,1))

while toc< 2endfor i = 1:nTrials all_data = zeros(1,4); all_t = []; draw_t = []; draw_rms = zeros(1,4); draw_y = []; Screen('TextSize',wPtr, 72); DrawFormattedText(wPtr,char(command_list(i)),'center','center',wait_color); Screen(wPtr,'Flip'); tic; while toc < 2 end Screen('TextSize',wPtr, 72); DrawFormattedText(wPtr,char(command_list(i)),'center','center',go_color); t_start = Screen(wPtr,'Flip'); tic; start(ai); t = 0; while isrunning(ai) && max(draw_rms(:,4)) < wink_threshold [emg_data,emg_t] = getdata(ai,actualRate/dataRate); t = toc; %concatenate all data all_data = [all_data; emg_data]; all_t = [all_t; emg_t]; draw_t = [draw_t; t]; if ~exist('draw_rms','var') draw_rms = []; end draw_rms = [draw_rms; zeros(1,size(emg_data,2))]; for j=1:length(options.ai) draw_rms(end,j) = sqrt(mean(emg_data(:,j).^2)); % draw_rms = [draw_rms; sqrt(mean(emg_data(:,1).^2)) sqrt(mean(emg_data(:,2).^2))]; end if ~isempty(draw_y) draw_y = [draw_y; filter_alpha*draw_y(end,:) + (1-filter_alpha)*(draw_rms(end,:))]; else draw_y = draw_rms(end,:); end end given_command = command_list(i); stop(ai); nSamples = length(draw_rms); window_idx = floor(nSamples*.20); if window_idx == 0 window_idx = 1; end window = draw_rms(window_idx:end,:); % classifier if ((max(window(:,1)))> l_threshold) && ((max(window(:,2)))< r_threshold) && ((max(window(:,3)))< f_threshold) movement = 'Left'; elseif (max(window(:,1))< l_threshold) && (max(window(:,2))> r_threshold)&&(max(window(:,3))< f_threshold) movement = 'Right'; elseif (max(window(:,1))> l_threshold) && (max(window(:,2))>r_threshold) && (max(window(:,3))> f_threshold) movement = 'Forward'; elseif (max(window(:,1))> l_threshold) && (max(window(:,2))> r_threshold& max)(window(:, 3))< f_threshold) movement = 'Backward'

else movement = 'Unknown'

for bit calculations later nChoices = length(commands)

nCorrect = 0

should be divisible by nListReps = ceil(nTrials/length(commands))

nTrials = 12

hold on

options = paramSetupLRFB

r_threshold = max(draw_rms(:,2))

randomizes reorder_idx = randperm(size(command_list,1))

else return

end for loop to plot RMF

RMS