How to split my EMG signal into individual cycles?
Hi I have recorded an emg signal of 5 different muscles on someone performing manual wheelchair propulsion.
Sensor 1 = biceps
Sensor 2 = triceps
Sensor 3 = Anterioir Deltoid
Sensor 4 = Posterior Deltoid
Sensor 5 = Upper Trapezius
Each sensor also records the acceleration in the x, y and z directions.
I want to split the emg signal into seperate propulsion cycles (when the hand pushes and releases to when the hand hits the push rim again.) so that I can average each cycle, as well as convert time (s) to percentage of cycle.
I know there were 13-14 cycles during the recording as i videoed the subject while gathering data.
I have only looked at the bicep data as shown below and was wondeing if there is a way to do this with the information I have.
Please let me know if you need anymore information.
%% SEMG Signal Analysis – Row Test 1 Participant 1 28/06/2024
% *This is my practice code to figure out how to export the data into MATLAB and transfer the data into arrays that I can manipulate and do calculations with. *
clear all;
clc;
%% Importing raw data from csv. file
% *BOLD TEXT*
raw_data = readmatrix(‘P02_S09_T01.csv’);
%% SEMG Time Data
% *Storing the Sub-frame data in arrays*
fs = 1926; % sampling frequency in Hz
columnIndex = 2; % Specify the index of the column you want to extract (1 for the Frame column, 2 for the Sub Frame column, and so on)
Sub_Frame = []; % Creating an array to store all the sub-frames related to the EMG data
row = 4;
while ~isnan(raw_data(row, columnIndex))
number = raw_data(row, columnIndex);
Sub_Frame = [Sub_Frame, number];
row = row + 1;
end
Time = (1:length(Sub_Frame))/fs; % converting the sub frame array into time in seconds array
%% Acceleration Sensor 1 (bicep) ACCY1
%
% Find the maximum row number
maxRow = size(raw_data, 1);
acc_fs = 148; %sa/sec
%find sub frame for acceleration
columnIndex = 2; % Specify the index of the column you want to extract (1 for the Frame column, 2 for the Sub Frame column, and so on)
Acc_Sub_Frame = []; % Creating an array to store all the sub-frames related to the EMG data
acc_row = 77955;
while acc_row <= maxRow
number = raw_data(acc_row, columnIndex);
Acc_Sub_Frame = [Acc_Sub_Frame, number];
acc_row = acc_row + 1;
end
Acc_Time = (1:length(Acc_Sub_Frame))/acc_fs; % converting the sub frame array into time in seconds array
columnIndex4 = 4; % Corresponds to ACCY1 (acceleration in the y-direction of sensor 1).
ACCY1 = []; % Creating an array to store all the AccY1
row2 = 77955;
while row2 <= maxRow
num = raw_data(row2, columnIndex4);
ACCY1 = [ACCY1, num];
row2 = row2 + 1;
end
acc_rms_signal = [];
window = 50;
acc_rms_signal = sqrt(movmean((ACCY1.^2),window));
%% Muscle arrays
% Sensor #1 – Biceps Brachii
% Sensor #2 – Triceps Brachii
% Sensor #3 – Anterioir Deltoid
% Sensor #4 – Posterior Deltoid
% Sensor #5 – Upper Trapezius
% *Storing the muscle data in arrays*
columnIndex = 3; % Specify the index of the column you want to extract (1 for the Frame column, 2 for the Sub Frame column, and so on)
Biceps_Brachii = [];% Creating an array to store all the frames related to the EMG data
row = 4; % This is the starting position of the Frame data
% Create a for loop to run through every sensor and store in each array.
while ~isnan(raw_data(row, columnIndex))
number = raw_data(row, columnIndex);
Biceps_Brachii = [Biceps_Brachii, number];
row = row + 1;
end
%% BP filter
% filtering from 20 to Hz
fnyq = fs/2;
fcuthigh = 20;
fcutlow = 450;
%4th order Butterworth BP filter
[b,a]=butter(4,[fcuthigh,fcutlow]/fnyq,’bandpass’);
butterworth_filter_signal=filtfilt(b,a,Biceps_Brachii);
%% RMS
%
rms_signal = [];
window = 50;
rms_signal = sqrt(movmean((rec_signal.^2),window));
% Create a figure with two subplots
figure;
% Plot the first graph on the top
subplot(2, 1, 1);
plot(Time, rms_signal);
title(‘EMG’);
% Plot the second graph on the bottom
subplot(2, 1, 2);
plot(Acc_Time, acc_rms_signal);
title(‘Acceleration’);Hi I have recorded an emg signal of 5 different muscles on someone performing manual wheelchair propulsion.
Sensor 1 = biceps
Sensor 2 = triceps
Sensor 3 = Anterioir Deltoid
Sensor 4 = Posterior Deltoid
Sensor 5 = Upper Trapezius
Each sensor also records the acceleration in the x, y and z directions.
I want to split the emg signal into seperate propulsion cycles (when the hand pushes and releases to when the hand hits the push rim again.) so that I can average each cycle, as well as convert time (s) to percentage of cycle.
I know there were 13-14 cycles during the recording as i videoed the subject while gathering data.
I have only looked at the bicep data as shown below and was wondeing if there is a way to do this with the information I have.
Please let me know if you need anymore information.
%% SEMG Signal Analysis – Row Test 1 Participant 1 28/06/2024
% *This is my practice code to figure out how to export the data into MATLAB and transfer the data into arrays that I can manipulate and do calculations with. *
clear all;
clc;
%% Importing raw data from csv. file
% *BOLD TEXT*
raw_data = readmatrix(‘P02_S09_T01.csv’);
%% SEMG Time Data
% *Storing the Sub-frame data in arrays*
fs = 1926; % sampling frequency in Hz
columnIndex = 2; % Specify the index of the column you want to extract (1 for the Frame column, 2 for the Sub Frame column, and so on)
Sub_Frame = []; % Creating an array to store all the sub-frames related to the EMG data
row = 4;
while ~isnan(raw_data(row, columnIndex))
number = raw_data(row, columnIndex);
Sub_Frame = [Sub_Frame, number];
row = row + 1;
end
Time = (1:length(Sub_Frame))/fs; % converting the sub frame array into time in seconds array
%% Acceleration Sensor 1 (bicep) ACCY1
%
% Find the maximum row number
maxRow = size(raw_data, 1);
acc_fs = 148; %sa/sec
%find sub frame for acceleration
columnIndex = 2; % Specify the index of the column you want to extract (1 for the Frame column, 2 for the Sub Frame column, and so on)
Acc_Sub_Frame = []; % Creating an array to store all the sub-frames related to the EMG data
acc_row = 77955;
while acc_row <= maxRow
number = raw_data(acc_row, columnIndex);
Acc_Sub_Frame = [Acc_Sub_Frame, number];
acc_row = acc_row + 1;
end
Acc_Time = (1:length(Acc_Sub_Frame))/acc_fs; % converting the sub frame array into time in seconds array
columnIndex4 = 4; % Corresponds to ACCY1 (acceleration in the y-direction of sensor 1).
ACCY1 = []; % Creating an array to store all the AccY1
row2 = 77955;
while row2 <= maxRow
num = raw_data(row2, columnIndex4);
ACCY1 = [ACCY1, num];
row2 = row2 + 1;
end
acc_rms_signal = [];
window = 50;
acc_rms_signal = sqrt(movmean((ACCY1.^2),window));
%% Muscle arrays
% Sensor #1 – Biceps Brachii
% Sensor #2 – Triceps Brachii
% Sensor #3 – Anterioir Deltoid
% Sensor #4 – Posterior Deltoid
% Sensor #5 – Upper Trapezius
% *Storing the muscle data in arrays*
columnIndex = 3; % Specify the index of the column you want to extract (1 for the Frame column, 2 for the Sub Frame column, and so on)
Biceps_Brachii = [];% Creating an array to store all the frames related to the EMG data
row = 4; % This is the starting position of the Frame data
% Create a for loop to run through every sensor and store in each array.
while ~isnan(raw_data(row, columnIndex))
number = raw_data(row, columnIndex);
Biceps_Brachii = [Biceps_Brachii, number];
row = row + 1;
end
%% BP filter
% filtering from 20 to Hz
fnyq = fs/2;
fcuthigh = 20;
fcutlow = 450;
%4th order Butterworth BP filter
[b,a]=butter(4,[fcuthigh,fcutlow]/fnyq,’bandpass’);
butterworth_filter_signal=filtfilt(b,a,Biceps_Brachii);
%% RMS
%
rms_signal = [];
window = 50;
rms_signal = sqrt(movmean((rec_signal.^2),window));
% Create a figure with two subplots
figure;
% Plot the first graph on the top
subplot(2, 1, 1);
plot(Time, rms_signal);
title(‘EMG’);
% Plot the second graph on the bottom
subplot(2, 1, 2);
plot(Acc_Time, acc_rms_signal);
title(‘Acceleration’); Hi I have recorded an emg signal of 5 different muscles on someone performing manual wheelchair propulsion.
Sensor 1 = biceps
Sensor 2 = triceps
Sensor 3 = Anterioir Deltoid
Sensor 4 = Posterior Deltoid
Sensor 5 = Upper Trapezius
Each sensor also records the acceleration in the x, y and z directions.
I want to split the emg signal into seperate propulsion cycles (when the hand pushes and releases to when the hand hits the push rim again.) so that I can average each cycle, as well as convert time (s) to percentage of cycle.
I know there were 13-14 cycles during the recording as i videoed the subject while gathering data.
I have only looked at the bicep data as shown below and was wondeing if there is a way to do this with the information I have.
Please let me know if you need anymore information.
%% SEMG Signal Analysis – Row Test 1 Participant 1 28/06/2024
% *This is my practice code to figure out how to export the data into MATLAB and transfer the data into arrays that I can manipulate and do calculations with. *
clear all;
clc;
%% Importing raw data from csv. file
% *BOLD TEXT*
raw_data = readmatrix(‘P02_S09_T01.csv’);
%% SEMG Time Data
% *Storing the Sub-frame data in arrays*
fs = 1926; % sampling frequency in Hz
columnIndex = 2; % Specify the index of the column you want to extract (1 for the Frame column, 2 for the Sub Frame column, and so on)
Sub_Frame = []; % Creating an array to store all the sub-frames related to the EMG data
row = 4;
while ~isnan(raw_data(row, columnIndex))
number = raw_data(row, columnIndex);
Sub_Frame = [Sub_Frame, number];
row = row + 1;
end
Time = (1:length(Sub_Frame))/fs; % converting the sub frame array into time in seconds array
%% Acceleration Sensor 1 (bicep) ACCY1
%
% Find the maximum row number
maxRow = size(raw_data, 1);
acc_fs = 148; %sa/sec
%find sub frame for acceleration
columnIndex = 2; % Specify the index of the column you want to extract (1 for the Frame column, 2 for the Sub Frame column, and so on)
Acc_Sub_Frame = []; % Creating an array to store all the sub-frames related to the EMG data
acc_row = 77955;
while acc_row <= maxRow
number = raw_data(acc_row, columnIndex);
Acc_Sub_Frame = [Acc_Sub_Frame, number];
acc_row = acc_row + 1;
end
Acc_Time = (1:length(Acc_Sub_Frame))/acc_fs; % converting the sub frame array into time in seconds array
columnIndex4 = 4; % Corresponds to ACCY1 (acceleration in the y-direction of sensor 1).
ACCY1 = []; % Creating an array to store all the AccY1
row2 = 77955;
while row2 <= maxRow
num = raw_data(row2, columnIndex4);
ACCY1 = [ACCY1, num];
row2 = row2 + 1;
end
acc_rms_signal = [];
window = 50;
acc_rms_signal = sqrt(movmean((ACCY1.^2),window));
%% Muscle arrays
% Sensor #1 – Biceps Brachii
% Sensor #2 – Triceps Brachii
% Sensor #3 – Anterioir Deltoid
% Sensor #4 – Posterior Deltoid
% Sensor #5 – Upper Trapezius
% *Storing the muscle data in arrays*
columnIndex = 3; % Specify the index of the column you want to extract (1 for the Frame column, 2 for the Sub Frame column, and so on)
Biceps_Brachii = [];% Creating an array to store all the frames related to the EMG data
row = 4; % This is the starting position of the Frame data
% Create a for loop to run through every sensor and store in each array.
while ~isnan(raw_data(row, columnIndex))
number = raw_data(row, columnIndex);
Biceps_Brachii = [Biceps_Brachii, number];
row = row + 1;
end
%% BP filter
% filtering from 20 to Hz
fnyq = fs/2;
fcuthigh = 20;
fcutlow = 450;
%4th order Butterworth BP filter
[b,a]=butter(4,[fcuthigh,fcutlow]/fnyq,’bandpass’);
butterworth_filter_signal=filtfilt(b,a,Biceps_Brachii);
%% RMS
%
rms_signal = [];
window = 50;
rms_signal = sqrt(movmean((rec_signal.^2),window));
% Create a figure with two subplots
figure;
% Plot the first graph on the top
subplot(2, 1, 1);
plot(Time, rms_signal);
title(‘EMG’);
% Plot the second graph on the bottom
subplot(2, 1, 2);
plot(Acc_Time, acc_rms_signal);
title(‘Acceleration’); emg, cycle, signal processing MATLAB Answers — New Questions
