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"keyword","repo_name","file_path","file_extension","file_size","line_count","content","language"
"Biosensors","Cassey2016/PPG_Peak_Detection","main.m",".m","3040","58","% =========================================================================
% Below functions are the implementation for the comparison methods in
% paper:
% Han, Dong, Syed K. Bashar, Jesús Lázaro, Fahimeh Mohagheghian,
% Andrew Peitzsch, Nishat Nishita, Eric Ding, Emily L. Dickson,
% Danielle DiMezza, Jessica Scott, Cody Whitcomb, Timothy P. Fitzgibbons,
% David D. McManus, and Ki H. Chon. 2022.
% ""A Real-Time PPG Peak Detection Method for Accurate Determination of
% Heart Rate during Sinus Rhythm and Cardiac Arrhythmia""
% Biosensors 12, no. 2: 82. https://doi.org/10.3390/bios12020082
%
% Please cite our paper if you used our implementation code. Thank you.
% Author: Dong Han (dong.han@uconn.edu), 01/31/2022.
% =========================================================================
% -------------------------------------------------------------------------
% Input:
% PPG_raw_buffer: should be 30-sec segment.
% fs_PPG_raw: the sampling frequency of the PPG_raw_buffer.
% -------------------------------------------------------------------------
%% Preparation of PPG signal:
addpath('.\func')
[PPG_buffer,fs_PPG] = my_func_prep_PPG_buffer(PPG_raw_buffer,fs_PPG_raw);
%% Method 1: implemented method 1-a
V_max_flag = true; % true == upper peak detection.
addpath('.\method_01_and_02');
output_upper_Shin_2009 = my_peak_compare_Shin_2009(PPG_buffer,fs_PPG,V_max_flag); % Implementation of Shin 2009 paper.
%% Method 2: implemented method 1-b
V_max_flag = false; % false == lower peak detection.
output_lower_Shin_2009 = my_peak_compare_Shin_2009(PPG_buffer,fs_PPG,V_max_flag); % Implementation of Shin 2009 paper.
%% Method 3 & 4: implemented method 2, it has two output peaks in ""output_Elgendi_1_2013""
delta = 0.5; % it was 0.1 as mentioned in the paper. But I think 0.5 works better (0.5 is in the billauer's website).
addpath('.\method_03_and_04');
[output_Elgendi_1_2013] = my_Elgendi_2013_method_I_peakdet(PPG_buffer, delta, fs_PPG);
%% Method 5: first derivative and adaptive thresholding method in Li et al. [4] and Elgendi's paper [3]
abpsig = resample(PPG_buffer,fs_abpsig,fs_PPG_buffer); % upsampling it to 125 Hz.
addpath('.\method_05');
[output_Elgendi_2_2013] = my_func_ppg_peakdet_method_05_Elgendi_2013_method_II(abpsig,fs_abpsig);
%% Method 6: implemented method 4
fs_abp = 250; % Hz.
abp = resample(PPG_buffer,fs_abp,fs_PPG); % upsampling it to 125 Hz.
addpath('.\method_06');
[output_Elgendi_3_2013] = my_Elgendi_2013_method_III_peakdet(abp,fs_abp);
%% Method 7: event-related moving averages with dynamic threshold method in Elgendi et al.'s paper [3]
addpath('.\method_07');
[output_Elgendi_4_2013] = my_func_ppg_peakdet_method_07_Elgendi_2013_method_IV(-PPG_raw_buffer,fs_PPG_raw);
%% Method 8 & 9: peak detection on Stationary Wavelet Transform of PPG signal
fs_swt = 125; % Hz.
PPG_swt = resample(PPG_buffer,fs_swt,fs_PPG); % upsampling it to 125 Hz.
addpath('.\method_08_and_09');
[output_Vadrevu_1_2019,output_Vadrevu_2_2019] = my_Vadrevu_2019_peakdet(PPG_swt,fs_swt);","MATLAB"
"Biosensors","Cassey2016/PPG_Peak_Detection","method_07/my_func_ppg_peakdet_method_07_Elgendi_2013_method_IV.m",".m","6505","156","function output_Elgendi_4_2013 = my_func_ppg_peakdet_method_07_Elgendi_2013_method_IV(raw_PPG,fs_PPG)
% =========================================================================
% This is my implementation of the method IV in this paper:
% Elgendi, Mohamed, et al.
% ""Systolic peak detection in acceleration photoplethysmograms measured from
% emergency responders in tropical conditions."" PLoS One 8.10 (2013): e76585.
%
% Implemented by Dong Han on 03/02/2020.
%
% Please cite our paper if you used this code:
% Han, Dong, Syed K. Bashar, Jesús Lázaro, Fahimeh Mohagheghian,
% Andrew Peitzsch, Nishat Nishita, Eric Ding, Emily L. Dickson,
% Danielle DiMezza, Jessica Scott, Cody Whitcomb, Timothy P. Fitzgibbons,
% David D. McManus, and Ki H. Chon. 2022.
% ""A Real-Time PPG Peak Detection Method for Accurate Determination of
% Heart Rate during Sinus Rhythm and Cardiac Arrhythmia""
% Biosensors 12, no. 2: 82. https://doi.org/10.3390/bios12020082
%
% Please cite our paper if you used our code. Thank you.
% =========================================================================
%% pre-processing - bandpass filtering
[b, a] = butter(2,[0.5 8]/(fs_PPG/2)); % 2nd order bandpass filter 0.5-8Hz;
filtered_PPG = filtfilt(b, a, raw_PPG); % zero-phase filter.
filtered_PPG = filtered_PPG ./ std(filtered_PPG); % normalizing data is very important for my peak detection.
filtered_PPG = filtered_PPG - mean(filtered_PPG);
debugging_plot_flag = false; % only for plotting debugging figures.
% clip the signal by keeping the signal above zero.
% I do not want to do this, so i will move all signal above zero.
S_n = filtered_PPG;
% ---- Not following the paper to clip signal but move all signal above zero:
% if min(S_n) < 0
% Z_n = S_n - min(S_n); % elevate signal above zero.
% else
% % the minimum of S_n is still above zero, so do nothing.
% Z_n = S_n;
% end
% ---- Following the paper: only keep the positive value:
Z_n = S_n;
Z_n(Z_n < 0) = 0;
%% pre-processing - squaring
y_n = (Z_n).^2; % element-wise power.
%% feature extraction - generating potential blocks using two moving averages
W_1 = round(0.111 * fs_PPG); % mentioned as the paper by brute-force search.
% first moving average:
% MA_peak = y_n; % for the beginning and ending signal, use the original signal.
% for nn = 1+round(W_1/2):length(raw_PPG)-round(W_1/2)
% temp_range = (nn-round(W_1/2)):(nn+round(W_1/2));
% MA_peak(nn) = sum(y_n(temp_range))/W_1;
% end
MA_peak = movmean(y_n,W_1);
% second moving average:
W_2 = round(0.667 * fs_PPG);
% MA_beat = y_n;
% for nn = 1+round(W_2/2):length(raw_PPG)-round(W_2/2)
% temp_range = (nn-round(W_2/2)):(nn+round(W_2/2));
% MA_beat(nn) = sum(y_n(temp_range))/W_2;
% end
MA_beat = movmean(y_n,W_2);
%% classification - thresholding
beta = 0.02; % from the paper, by brute force search.
z_bar = mean(y_n);
alpha = beta * z_bar; % offset level.
THR_1 = MA_beat + alpha;
Blocks_Of_Interest = zeros(size(MA_peak)); % I initial it as zero.
for nn = 1:length(MA_peak)
if MA_peak(nn) > THR_1(nn) % I think it is THR_1(nn).
Blocks_Of_Interest(nn) = 0.1;
else
% since I inital block of interest as zero, so I do not need to
% assign zero again.
end
end
% searh for onset and offset of each block.
count_blocks = 0;
block_onset = NaN(size(MA_peak));
block_offset = NaN(size(MA_peak));
if any(Blocks_Of_Interest > 0) % there is a block exist.
for nn = 1:length(MA_peak)
if nn == 1 && Blocks_Of_Interest(nn) > 0
% the first point is a block;
count_blocks = count_blocks + 1; % since the block start from zero, I have to add the counter first.
block_onset(count_blocks,1) = nn;
elseif nn == length(MA_peak) && Blocks_Of_Interest(nn) > 0
% end with a block:
% no need to add count_blocks;
block_offset(count_blocks,1) = nn;
else
if nn > 1
if Blocks_Of_Interest(nn-1) == 0 && Blocks_Of_Interest(nn) > 0 % a jump means a new block.
count_blocks = count_blocks + 1;
block_onset(count_blocks,1) = nn;
elseif Blocks_Of_Interest(nn-1) > 0 && Blocks_Of_Interest(nn) == 0 % a drop means the end of previous block.
block_offset(count_blocks,1) = nn;
end
end
end
end
else
% there is no block existed. Check why.
% keyboard;
HR_Elgendi_4_2013 = 0; % there is no peak location.
S_peaks = 1;
output_Elgendi_4_2013 = struct('filtered_PPG_Elgendi_4_2013',S_n,...
'PPG_peak_loc_Elgendi_4_2013',S_peaks,...
'HR_Elgendi_4_2013',HR_Elgendi_4_2013);
return
end
block_onset(isnan(block_onset)) = []; % remove extra elements.
block_offset(isnan(block_offset)) = []; % remove extra elements.
if size(block_onset,1) ~= size(block_offset,1)
% not same number of onset and offset, check here.
keyboard;
end
if size(block_onset,1) ~= count_blocks
keyboard;
end
S_peaks = NaN(count_blocks,1);
THR_2 = W_1;
for jj = 1:count_blocks
block_idx = [block_onset(jj,1):block_offset(jj,1)];
[~,I] = max(y_n(block_idx));
S_peaks(jj,1) = block_onset(jj,1) + I - 1;
end
if debugging_plot_flag
figure;
plot(filtered_PPG);hold on;
plot(S_peaks,y_n(S_peaks),'r.','markersize',10);
plot(y_n);
plot(MA_peak,'k:');
plot(MA_beat,'r--');
plot(THR_1,'g.-');
plot(Blocks_Of_Interest*max(y_n)*10,'color',[0.5,0.5,0.5]); % grey color. I want to make block more obvious.
legend('filtered PPG','peaks', 'squared PPG with clip to zero', 'MA peak', 'MA beat','THR 1', 'Blocks of Interest');
end
if isempty(S_peaks)
HR_Elgendi_4_2013 = 0; % there is no peak location.
S_peaks = 1;
else
HR_Elgendi_4_2013 = 60 * fs_PPG ./ diff(S_peaks); % calculate the HR.
end
output_Elgendi_4_2013 = struct('filtered_PPG_Elgendi_4_2013',S_n,...
'PPG_peak_loc_Elgendi_4_2013',S_peaks,...
'HR_Elgendi_4_2013',HR_Elgendi_4_2013);
end","MATLAB"
"Biosensors","Cassey2016/PPG_Peak_Detection","method_01_and_02/my_peak_compare_Shin_2009.m",".m","21523","388","function [output_Shin_2009] = my_peak_compare_Shin_2009(raw_PPG,fs_PPG,V_max_flag)
% =========================================================================
% This function is the implementation of this paper:
% Shin, Hang Sik, Chungkeun Lee, and Myoungho Lee.
% ""Adaptive threshold method for the peak detection of
% photoplethysmographic waveform.""
% Computers in biology and medicine
% 39.12 (2009): 1145-1152.
%
% Implemented by: Dong Han, on 02/10/2020.
%
% Please cite our paper if you used this code:
% Han, Dong, Syed K. Bashar, Jesús Lázaro, Fahimeh Mohagheghian,
% Andrew Peitzsch, Nishat Nishita, Eric Ding, Emily L. Dickson,
% Danielle DiMezza, Jessica Scott, Cody Whitcomb, Timothy P. Fitzgibbons,
% David D. McManus, and Ki H. Chon. 2022.
% ""A Real-Time PPG Peak Detection Method for Accurate Determination of
% Heart Rate during Sinus Rhythm and Cardiac Arrhythmia""
% Biosensors 12, no. 2: 82. https://doi.org/10.3390/bios12020082
%
% Please cite our paper if you used our code. Thank you.
% =========================================================================
debugging_plot_flag = false; % debugging plot. Can be false if don't want to plot anything.
%% Section 2.4 PPG frequency analysis and filtering.
% (1): high pass >= 0.5 Hz.
[b, a] = butter(6,[0.5 20]/(fs_PPG/2)); % bandpass filter 0.5-10Hz, changed from 0.5-20 to 0.5-9 Hz at 11/21/2018
raw_PPG = filtfilt(b, a, raw_PPG); % -> AC component
raw_PPG = raw_PPG ./ std(raw_PPG); % normalizing data is very important for my peak detection.
raw_PPG = raw_PPG - mean(raw_PPG);
%% Section 2.5 & 2.6 Peak detection algorithm & Adaptive threshold detection
% (1): bandpass filtering, no moving average filter or wavelet
% decomposition.
filtered_PPG = raw_PPG;
Fs = fs_PPG;
% % ===== interpolation to 1kHz of PPG: =====
% x = 1:length(filtered_PPG);
% v = filtered_PPG;
%
% upsample_Fs = 250;
% xq = 1:Fs/upsample_Fs:length(filtered_PPG);
% vq1 = interp1(x,v,xq);
%
% filtered_PPG = vq1;
% Fs = upsample_Fs; % upsampled to 1000 Hz.
% figure
% plot(x,v,'o',xq,vq1,':.');
% xlim([0 max(xq)]);
% title('(Default) Linear Interpolation');
% (2): V_max
% slope_k: k-th slope amplitude;
% s_r: slope changing rate (empirically: V_max = -0.6);
% V_n_1: previous peak amplitude;
% std_PPG: standard deviation of entire PPG signal;
% Fs: sampling frequency.
filtered_PPG = filtered_PPG(:);
slope_k = NaN(size(filtered_PPG)); % should be a column vector.
peak_loc = NaN(size(filtered_PPG)); % the array to store PPG peak index.
pk_idx = 1; % the counter of peaks.
%% Section 2.7: Peak Correction
refractory_period = 0.6 * Fs; % sec * sampling frequency, initial refractory period is 0.6 sec.
temp_win_left = round(0.15 * Fs); % sec * sampling frequency. This is the search region for local minima or maxima detection. chose 0.15 sec because 0.3 sec == 200 BPM.
temp_win_right = round(0.15 * Fs);
if V_max_flag % doing upper peak detection.
s_r = -0.6;
else
s_r = 0.6;%0.6; % not positive because my signal is zero mean.
% I need to make all bottom signal positive, so I am moving them up.
% move_filter_amp = min(filtered_PPG) * (-1);
% filtered_PPG = filtered_PPG + move_filter_amp + std(raw_PPG); % move the lowest value more than zero.
end
slope_meet_PPG_flag = false; % mark if the slope meet PPG.
slope_lower_PPG_flag = false; % mark if slope is lower than PPG, once PPG amp is lower than slope, mark it back.
prev_slope = NaN; % First, I want to test not decreasing with PPG amplitude.
if debugging_plot_flag % debugging plot
figure;
plot(filtered_PPG);
hold on;
end
for kk = 1:length(filtered_PPG)
% this is for debugging:
if kk == 2
my_stop = 1;
end
if kk == 1 % initial the slope value
if V_max_flag
slope_k(1,1) = 0.2 * max(filtered_PPG);
std_PPG = std(filtered_PPG);
else
slope_k(1,1) = 0.2 * min(filtered_PPG); % since my signal is zero mean, I start from the negative amp. % I added what I moved.
std_PPG = -std(filtered_PPG);
end
% std_PPG = std(filtered_PPG);
V_n_1 = slope_k(1,1);
else
if slope_meet_PPG_flag % slope has met PPG before.
slope_k(kk,1) = filtered_PPG(kk,1);
if V_max_flag % upper peak detection.
if kk < 2 % in the second point of signal
turn_point_flag = (slope_k(kk,1) < slope_k(kk-1,1)); % we met local maximum.
else
turn_point_flag = (slope_k(kk,1) < slope_k(kk-1,1)) & (slope_k(kk - 1,1) > slope_k(kk-2,1)); % we met local maximum.
end
else
if kk < 2 % in the second point of signal
turn_point_flag = (slope_k(kk,1) > slope_k(kk-1,1)); % we met local minimum.
else
turn_point_flag = (slope_k(kk,1) > slope_k(kk-1,1)) & (slope_k(kk - 1,1) < slope_k(kk-2,1)); % we met local minimum.
end
end
if turn_point_flag % there is a turning point.
if pk_idx > 1 % not the first peak
% check local maxima or minima:
if (kk - temp_win_left) < 1
temp_left = 1;
else
temp_left = kk - temp_win_left;
end
if (kk + temp_win_right) > length(filtered_PPG)
temp_right = length(filtered_PPG);
else
temp_right = kk + temp_win_right;
end
temp_win = temp_left:temp_right;
local_m_check = filtered_PPG(temp_win);
if V_max_flag
temp_m_idx = find(local_m_check > slope_k(kk - 1,1)); % check if there is another maximum than detected, remember use k-1.
else
temp_m_idx = find(local_m_check < slope_k(kk - 1,1)); % check if there is another minimum than detected
end
if isempty(temp_m_idx) % there is no more max or min than this peak
if (kk - peak_loc(pk_idx-1,1) > refractory_period) % it is not the first peak, and the second peak is outside refractory period. It should be kk, because I have not assign the peak to the array.
peak_loc(pk_idx,1) = kk-1;
V_n_1 = filtered_PPG(peak_loc(pk_idx-1,1),1);% previous peak amplitude %slope_k(kk-1,1);
% update refractory period:
refractory_period = 0.6 * (kk - peak_loc(pk_idx-1,1)); % current index minus peak location. update the refractory peroid before updating the peak counting.
pk_idx = pk_idx + 1;
% reset slope meet flag:
slope_meet_PPG_flag = false;
slope_k(kk,1) = slope_k(kk - 1,1) + s_r * ((V_n_1 + std_PPG) / Fs);
% ---- for checking lower slope -------
temp_slope_check = s_r * ((V_n_1 + std_PPG) / Fs);
if V_max_flag
if temp_slope_check > 0 % upper peaks should be decreasing with negative slope.
temp_slope_check = -s_r * ((V_n_1 + std_PPG) / Fs);%-temp_slope_check;
slope_k(kk,1) = slope_k(kk - 1,1) + temp_slope_check;
end
else
if temp_slope_check < 0 % upper peaks should be decreasing with negative slope.
temp_slope_check = -s_r * ((V_n_1 + std_PPG) / Fs);%-temp_slope_check;
slope_k(kk,1) = slope_k(kk - 1,1) + temp_slope_check;
end
end
% -------------------------------------------
if V_max_flag
temp_slope_below_PPG_flag = slope_k(kk,1) < filtered_PPG(kk,1); % upper peak detection, so slope below signal.
else
temp_slope_below_PPG_flag = slope_k(kk,1) > filtered_PPG(kk,1); % lower peak detection, so slope above signal.
end
if temp_slope_below_PPG_flag % if slope is below PPG signal, we will reset slope value to PPG amplitude.
slope_lower_PPG_flag = true; % slope is lower than PPG signal.
prev_slope = slope_k(kk,1); % store the slope value now.
slope_k(kk,1) = filtered_PPG(kk,1);
end
if debugging_plot_flag % debugging plot
plot(kk,slope_k(kk,1),'r.');
end
else
if (kk - peak_loc(pk_idx-1,1) <= refractory_period) % it is because of the refractory period that cause the no peak. It should be kk, because I have not assign the peak to the array.
slope_k(kk,1) = filtered_PPG(kk,1);% from the fig.3(c) in the paper, I see they are using the signal amplitude, not slope.
% no need to reset slope meet flag, waiting for
% next turning point.
if debugging_plot_flag % debugging plot
plot(kk,slope_k(kk,1),'r.');
end
end
end
else % there are more peaks higher then current kk peak.
if debugging_plot_flag % debugging plot
plot(kk,slope_k(kk,1),'r.');
end
end
else % the first peak, no need to check refractory period.
% check local maxima or minima:
if (kk - temp_win_left) < 1
temp_left = 1;
else
temp_left = kk - temp_win_left;
end
if (kk + temp_win_right) > length(filtered_PPG)
temp_right = length(filtered_PPG);
else
temp_right = kk + temp_win_right;
end
temp_win = temp_left:temp_right;
local_m_check = filtered_PPG(temp_win);
if V_max_flag
temp_m_idx = find(local_m_check > slope_k(kk-1,1)); % check if there is another maximum than detected, always detect previous peak.
else
temp_m_idx = find(local_m_check < slope_k(kk-1,1)); % check if there is another minimum than detected
end
if isempty(temp_m_idx)
peak_loc(pk_idx,1) = kk-1;
if pk_idx > 1
V_n_1 = filtered_PPG(peak_loc(pk_idx-1,1),1);
else
V_n_1 = slope_k(kk-1,1);% previous peak amplitude %slope_k(kk-1,1);
end
pk_idx = pk_idx + 1;
% reset slope meet flag:
slope_meet_PPG_flag = false;
slope_k(kk,1) = slope_k(kk - 1,1) + s_r * ((V_n_1 + std_PPG) / Fs);
% ---- for checking lower slope -------
temp_slope_check = s_r * ((V_n_1 + std_PPG) / Fs);
if V_max_flag
if temp_slope_check > 0 % upper peaks should be decreasing with negative slope.
temp_slope_check = -s_r * ((V_n_1 + std_PPG) / Fs);%-temp_slope_check;
slope_k(kk,1) = slope_k(kk - 1,1) + temp_slope_check;
end
else
if temp_slope_check < 0 % upper peaks should be decreasing with negative slope.
temp_slope_check = -s_r * ((V_n_1 + std_PPG) / Fs);%-temp_slope_check;
slope_k(kk,1) = slope_k(kk - 1,1) + temp_slope_check;
end
end
% -------------------------------------------
if V_max_flag
temp_slope_below_PPG_flag = slope_k(kk,1) < filtered_PPG(kk,1); % upper peak detection, so slope below signal.
else
temp_slope_below_PPG_flag = slope_k(kk,1) > filtered_PPG(kk,1); % lower peak detection, so slope above signal.
end
if temp_slope_below_PPG_flag % if slope is below PPG signal, we will reset slope value to PPG amplitude.
slope_k(kk,1) = filtered_PPG(kk,1);
end
if debugging_plot_flag % debugging plot
plot(kk,slope_k(kk,1),'r.');
end
else % there are more peaks higher then current kk peak.
if debugging_plot_flag % debugging plot
plot(kk,slope_k(kk,1),'r.');
end
end
% no need to calculate refractory period, because there is only one peak, at least two peaks can give this correctly:
end
else
% turning point did not meet, so keep decreasing or
% increasing the slope.
% slope_k(kk,1) = slope_k(kk - 1,1) + s_r * ((V_n_1 + std_PPG) / Fs);
if debugging_plot_flag % debugging plot
plot(kk,slope_k(kk,1),'r.');
end
end
else % slope has not met PPG before. Keep decresing or increasing according to 'V_max_flag'.
% if slope_lower_PPG_flag % if there is a slope lower than PPG before:
% slope_k(kk,1) = prev_slope;
% else
slope_k(kk,1) = slope_k(kk - 1,1) + s_r * ((V_n_1 + std_PPG) / Fs);
% ---- for checking lower slope -------
temp_slope_check = s_r * ((V_n_1 + std_PPG) / Fs);
if V_max_flag
if temp_slope_check > 0 % upper peaks should be decreasing with negative slope.
temp_slope_check = -s_r * ((V_n_1 + std_PPG) / Fs);%-temp_slope_check;
slope_k(kk,1) = slope_k(kk - 1,1) + temp_slope_check;
end
else
if temp_slope_check < 0 % upper peaks should be decreasing with negative slope.
temp_slope_check = -s_r * ((V_n_1 + std_PPG) / Fs);%-temp_slope_check;
slope_k(kk,1) = slope_k(kk - 1,1) + temp_slope_check;
end
end
% -------------------------------------------
% end
% if slope_k(kk,1) < filtered_PPG(kk,1) % if slope is below PPG signal, we will reset slope value to PPG amplitude.
% slope_lower_PPG_flag = true; % slope is lower than PPG signal.
% prev_slope = slope_k(kk,1); % store the slope value now.
% slope_k(kk,1) = filtered_PPG(kk,1);
% elseif slope_k(kk,1) > filtered_PPG(kk,1) % slope is higher.
% slope_lower_PPG_flag = false;
% prev_slope = NaN; % reset the prev value.
% end
% if slope_lower_PPG_flag ~= 1 % if slope was not lower than PPG.
% % -------------- Check if two lines will meet -----------------
% PPG_x1 = kk - 1;
% PPG_x2 = kk;
% PPG_y1 = filtered_PPG(kk-1,1);
% PPG_y2 = filtered_PPG(kk,1);
% slope = s_r;
% slope_y2 = slope_k(kk,1);
% slope_y1 = slope_k(kk-1,1);
% [meet_x] = my_slope_meet_PPG(PPG_x1,PPG_x2,PPG_y1,PPG_y2,slope,slope_y2,slope_y1);
%
% slope_meet_PPG_flag = (ceil(meet_x) == kk);%(slope_k(kk,1) - filtered_PPG(kk,1)) < 0.1; % 0.3 is a testing value. %slope_k(kk,1) == filtered_PPG(kk,1) % slope meets the PPG signal.
% end
if V_max_flag
slope_meet_PPG_flag = ((slope_k(kk,1) < filtered_PPG(kk,1)) & slope_k(kk - 1,1) > filtered_PPG(kk - 1,1));
else
slope_meet_PPG_flag = ((slope_k(kk,1) > filtered_PPG(kk,1)) & slope_k(kk - 1,1) < filtered_PPG(kk - 1,1)); % lower peak use inverse amplitude.
end
% -------------------------------------------------------------
% I found I cannot use equal, because the PPG sampling
% frequency is not so high.
if slope_meet_PPG_flag
slope_k(kk,1) = filtered_PPG(kk,1); % starts from the next index, slope == PPG amplitude.
else
% don't need to do anything.
if slope_lower_PPG_flag ~= 1 % there was no slope lower than PPG before.
if V_max_flag
slope_lower_PPG_flag = ((slope_k(kk,1) < filtered_PPG(kk,1)) & slope_k(kk - 1,1) == filtered_PPG(kk - 1,1)); % beginning part has same amplitude, but the ending part slope is lower.
else
slope_lower_PPG_flag = ((slope_k(kk,1) > filtered_PPG(kk,1)) & slope_k(kk - 1,1) == filtered_PPG(kk - 1,1)); % lower peak use inverse amplitude.
end
if slope_lower_PPG_flag
prev_slope = slope_k(kk,1); % store the slope value now.
slope_k(kk,1) = filtered_PPG(kk,1); % starts from the next index, slope == PPG amplitude.
end
else % there was slope lower than PPG before.
if V_max_flag
temp_PPG_below_slope_flag = filtered_PPG(kk,1) < prev_slope; % upper peak detection, so PPG below slope.
else
temp_PPG_below_slope_flag = filtered_PPG(kk,1) > prev_slope; % lower peak detection, so PPG above slope.
end
if temp_PPG_below_slope_flag % PPG is lower than prev slope.
slope_k(kk,1) = prev_slope; % stop tracking PPG amp.
slope_lower_PPG_flag = false; % reset the lower PPG flag.
prev_slope = NaN;
else
slope_k(kk,1) = filtered_PPG(kk,1); % keep tracking PPG amp.
end
end
end
if debugging_plot_flag % debugging plot
plot(kk,slope_k(kk,1),'r.');
end
end
end
end
% ================== IMPORTANT: clean up NaN value ========================
peak_loc(isnan(peak_loc)) = []; % remove empty peak loc.
if V_max_flag % doing upper peak detection.
else
% moving signal back.
% filtered_PPG = filtered_PPG - move_filter_amp - std(raw_PPG); % move the lowest value more than zero.
% slope_k = slope_k - move_filter_amp - std(raw_PPG); % move the slope as well.
end
if debugging_plot_flag % debugging plot
plot(peak_loc,filtered_PPG(peak_loc),'ko');
end
if isempty(peak_loc)
HR_Shin_2009 = 0; % there is no peak location.
peak_loc = 1;
else
HR_Shin_2009 = 60 * Fs ./ diff(peak_loc); % calculate the HR.
end
output_Shin_2009 = struct('PPG_peak_loc_Shin_2009',peak_loc,...
'slope_Shin_2009',slope_k,...
'filtered_PPG_Shin_2009',filtered_PPG,...
'HR_Shin_2009',HR_Shin_2009);
end","MATLAB"
"Biosensors","Cassey2016/PPG_Peak_Detection","method_05/my_func_ppg_peakdet_method_05_Elgendi_2013_method_II.m",".m","11993","412","function [output_Elgendi_2_2013] = my_func_ppg_peakdet_method_05_Elgendi_2013_method_II(raw_PPG,fs_PPG)
% -------------------------------------------------------------------------
% This peak detection function was mentioned in this paper:
% Elgendi, Mohamed, et al.
% ""Systolic peak detection in acceleration photoplethysmograms measured from
% emergency responders in tropical conditions."" PLoS One 8.10 (2013): e76585.
%
[onsetp,peakp,dicron,abpsig] = delineator(raw_PPG,fs_PPG);
% -------------------------------------------------------------------------
if isempty(peakp) % there is no peak detected:
HR_Elgendi_2_2013 = 0; % there is no peak location.
peakp = 1;
else
HR_Elgendi_2_2013 = 60 * fs_PPG ./ diff(peakp); % calculate the HR.
end
output_Elgendi_2_2013 = struct('PPG_peak_loc_Elgendi_2_2013',peakp,...
'HR_Elgendi_2_2013',HR_Elgendi_2_2013,...
'filtered_PPG_Elgendi_2_2013',abpsig);
end
function [onsetp,peakp,dicron,abpsig] = delineator(abpsig,abpfreq)
% Below was copied from Mathwords File Exchange ""Pulse Waveform Delineator"":
% https://www.mathworks.com/matlabcentral/fileexchange/29484-pulse-waveform-delineator
% This program is intended to delineate the fiducial points of pulse waveforms
% Inputs:
% abpsig: input as original pulse wave signals;
% abpfreq: input as the sampling frequency;
% Outputs:
% onsetp: output fiducial points as the beginning of each beat;
% peakp: output fiducial points as systolic peaks;
% dicron: output fiducial points as dicrotic notches;
% Its delineation is based on the self-adaptation in pulse waveforms, but
% not in the differentials.
% Reference:
% BN Li, MC Dong & MI Vai (2010)
% On an automatic delineator for arterial blood pressure waveforms
% Biomedical Signal Processing and Control 5(1) 76-81.
% LI Bing Nan @ University of Macau, Feb 2007
% Revision 2.0.5, Apr 2009
%Initialization
peakIndex=0;
onsetIndex=0;
dicroIndex=0;
stepWin=2*abpfreq;
closeWin=floor(0.1*abpfreq); %invalide for pulse beat > 200BPM
sigLen=length(abpsig);
peakp=[];
onsetp=[];
dicron=[];
%lowpass filter at first
coh=25; %cutoff frequency is 25Hz
coh=coh*2/abpfreq;
od=3; %3rd order bessel filter
[B,A]=besself(od,coh);
abpsig=filter(B,A,abpsig);
abpsig=10*abpsig;
abpsig=smooth(abpsig);
%Compute differentials
ttp=diff(abpsig);
diff1(2:sigLen)=ttp;
diff1(1)=diff1(2);
diff1=100*diff1;
clear ttp;
diff1=smooth(diff1);
if sigLen>12*abpfreq
tk=10;
elseif sigLen>7*abpfreq
tk=5;
elseif sigLen>4*abpfreq
tk=2;
else
tk=1;
end
%Seek avaerage threshold in original signal
if tk>1 %self-learning threshold with interval sampling
tatom=floor(sigLen/(tk+2));
for ji=1:tk %search the slopes of abp waveforms
sigIndex=ji*tatom;
tempIndex=sigIndex+abpfreq;
[tempMin,jk,tempMax,jl]=seeklocales(abpsig,sigIndex,tempIndex);
tempTH(ji)=tempMax-tempMin;
end
abpMaxTH=mean(tempTH);
else
[tempMin,jk,tempMax,jl]=seeklocales(abpsig,closeWin,sigLen);
abpMaxTH=tempMax-tempMin;
end
clear j*;
clear t*;
abpMaxLT=0.4*abpMaxTH;
%Seek pulse beats by MinMax method
% diffIndex=1;
diffIndex=closeWin; %Avoid filter distortion
while diffIndex<sigLen
tempMin=abpsig(diffIndex); %Initialization
tempMax=abpsig(diffIndex);
tempIndex=diffIndex;
tpeakp=diffIndex; %Avoid initial error
tonsetp=diffIndex; %Avoid initial error
while tempIndex<sigLen
%If no pulses within 2s, then adjust threshold and retry
if (tempIndex-diffIndex)>stepWin
% tempIndex=diffIndex-closeWin;
tempIndex=diffIndex;
abpMaxTH=0.6*abpMaxTH;
if abpMaxTH<=abpMaxLT
abpMaxTH=2.5*abpMaxLT;
end
break;
end
if (diff1(tempIndex-1)*diff1(tempIndex+1))<=0 %Candidate fiducial points
if (tempIndex+5)<=sigLen
jk=tempIndex+5;
else
jk=sigLen;
end
if (tempIndex-5)>=1
jj=tempIndex-5;
else
jj=1;
end
%Artifacts of oversaturated or signal loss?
if (jk-tempIndex)>=5
for ttk=tempIndex:jk
if diff1(ttk)~=0
break;
end
end
if ttk==jk
break; %Confirm artifacts
end
end
if diff1(jj)<0 %Candidate onset
if diff1(jk)>0
[tempMini,tmin,ta,tb]=seeklocales(abpsig,jj,jk);
if abs(tmin-tempIndex)<=2
tempMin=tempMini;
tonsetp=tmin;
end
end
elseif diff1(jj)>0 %Candidate peak
if diff1(jk)<0
[tc,td,tempMaxi,tmax]=seeklocales(abpsig,jj,jk);
if abs(tmax-tempIndex)<=2
tempMax=tempMaxi;
tpeakp=tmax;
end
end
end
if ((tempMax-tempMin)>0.4*abpMaxTH) %evaluation
if ((tempMax-tempMin)<2*abpMaxTH)
if tpeakp>tonsetp
%If more zero-crossing points, further refine!
ttempMin=abpsig(tonsetp);
ttonsetp=tonsetp;
for ttk=tpeakp:-1:(tonsetp+1)
if abpsig(ttk)<ttempMin
ttempMin=abpsig(ttk);
ttonsetp=ttk;
end
end
tempMin=ttempMin;
tonsetp=ttonsetp;
if peakIndex>0
%If pulse period less than eyeclose, then artifact
if (tonsetp-peakp(peakIndex))<(3*closeWin)
%too many fiducial points, then reset
tempIndex=diffIndex;
abpMaxTH=2.5*abpMaxLT;
break;
end
%If pulse period bigger than 2s, then artifact
if (tpeakp-peakp(peakIndex))>stepWin
peakIndex=peakIndex-1;
onsetIndex=onsetIndex-1;
if dicroIndex>0
dicroIndex=dicroIndex-1;
end
end
if peakIndex>0
%new pulse beat
peakIndex=peakIndex+1;
peakp(peakIndex)=tpeakp;
onsetIndex=onsetIndex+1;
onsetp(onsetIndex)=tonsetp;
tf=onsetp(peakIndex)-onsetp(peakIndex-1);
to=floor(abpfreq./20); %50ms
tff=floor(0.1*tf);
if tff<to
to=tff;
end
to=peakp(peakIndex-1)+to;
te=floor(abpfreq./2); %500ms
tff=floor(0.5*tf);
if tff<te
te=tff;
end
te=peakp(peakIndex-1)+te;
% Dong added on 05/07/2020:
% For MIMIC III PACPVC 3_2, ii = 25.
if te > length(diff1)
te = length(diff1);
end
tff=seekdicrotic(diff1(to:te));
if tff==0
tff=te-peakp(peakIndex-1);
tff=floor(tff/3);
end
dicroIndex=dicroIndex+1;
dicron(dicroIndex)=to+tff;
tempIndex=tempIndex+closeWin;
break;
end
end
if peakIndex==0 %new pulse beat
peakIndex=peakIndex+1;
peakp(peakIndex)=tpeakp;
onsetIndex=onsetIndex+1;
onsetp(onsetIndex)=tonsetp;
tempIndex=tempIndex+closeWin;
break;
end
end
end
end
end
tempIndex=tempIndex+1; %step forward
end
% diffIndex=tempIndex+closeWin; %for a new beat
diffIndex=tempIndex+1;
end
if isempty(peakp),return;end
%Compensate the offsets of lowpass filter
sigLen=length(peakp);
for diffIndex=1:sigLen %avoid edge effect
tempp(diffIndex)=peakp(diffIndex)-od;
end
ttk=tempp(1);
if ttk<=0
tempp(1)=1;
end
clear peakp;
peakp=tempp;
clear tempp;
sigLen=length(onsetp);
for diffIndex=1:sigLen
tempp(diffIndex)=onsetp(diffIndex)-od;
end
ttk=tempp(1);
if ttk<=0
tempp(1)=1;
end
clear onsetp;
onsetp=tempp;
clear tempp;
if isempty(dicron),return;end
sigLen=length(dicron);
for diffIndex=1:sigLen
if dicron(diffIndex)~=0
tempp(diffIndex)=dicron(diffIndex)-od;
else
tempp(diffIndex)=0;
end
end
clear dicron;
dicron=tempp;
clear tempp;
end
function [mini,minip,maxi,maxip]=seeklocales(tempsig,tempbegin,tempend)
tempMin=tempsig(tempbegin);
tempMax=tempsig(tempbegin);
minip=tempbegin;
maxip=tempbegin;
for j=tempbegin:tempend
if tempsig(j)>tempMax
tempMax=tempsig(j);
maxip=j;
elseif tempsig(j)<tempMin
tempMin=tempsig(j);
minip=j;
end
end
mini=tempMin;
maxi=tempMax;
end
function [dicron]=seekdicrotic(tempdiff)
izcMin=0;
izcMax=0;
itemp=3;
tempLen=length(tempdiff)-3;
dicron=0;
tempdiff=smooth(tempdiff);
while itemp<=tempLen
if (tempdiff(itemp)*tempdiff(itemp+1))<=0
if tempdiff(itemp-2)<0
if tempdiff(itemp+2)>=0
izcMin=izcMin+1;
tzcMin(izcMin)=itemp;
end
end
% if tempdiff(itemp-2)>0
% if tempdiff(itemp+2)<=0
% izcMax=izcMax+1;
% tzcMax(izcMax)=itemp;
% end
% end
end
itemp=itemp+1;
end
if izcMin==0 %big inflection
itemp=3;
tempMin=tempdiff(itemp);
itempMin=itemp;
while itemp<tempLen
if tempdiff(itemp)<tempMin
tempMin=tempdiff(itemp);
itempMin=itemp;
end
itemp=itemp+1;
end
itemp=itempMin+1;
while itemp<tempLen
if tempdiff(itemp+1)<=tempdiff(itemp-1)
dicron=itemp;
return;
end
itemp=itemp+1;
end
elseif izcMin==1
dicron=tzcMin(izcMin);
return;
else
itemp=tzcMin(1);
tempMax=tempdiff(itemp);
itempMax=itemp;
while itemp<tempLen
if tempdiff(itemp)>tempMax
tempMax=tempdiff(itemp);
itempMax=itemp;
end
itemp=itemp+1;
end
for itemp=izcMin:-1:1
if tzcMin(itemp)<itempMax
dicron=tzcMin(itemp);
return;
end
end
end
end
function [diap]=seekdiap(tempabp)
diap=0;
[tt,ti]=max(tempabp);
if ti==0
diap=floor(length(tempabp)./2);
else
diap=ti;
end
end
","MATLAB"
"Biosensors","Cassey2016/PPG_Peak_Detection","func/my_func_standardizing_PPG.m",".m","422","11","function PPG_buffer = my_func_standardizing_PPG(PPG_buffer)
% Standardizing PPG into zero-mean and uni-variance.
var_sig_PPG = var(PPG_buffer);
if var_sig_PPG == 0
univar_sig_PPG = PPG_buffer;
else
univar_sig_PPG = sqrt(1/var_sig_PPG) * PPG_buffer;
end
zeromean_sig_PPG = univar_sig_PPG - mean(univar_sig_PPG);
PPG_buffer = zeromean_sig_PPG; % univariance for PPG 30 sec segment
end","MATLAB"
"Biosensors","Cassey2016/PPG_Peak_Detection","func/my_func_prep_PPG_buffer.m",".m","554","17","function [PPG_buffer,fs_PPG] = my_func_prep_PPG_buffer(PPG_raw_buffer,fs_PPG)
% Resample PPG to 50 Hz.
if fs_PPG ~= 50 % Hz
PPG_down = resample(PPG_raw_buffer,50,fs_PPG);
fs_PPG = 50;
else
PPG_down = PPG_raw_buffer;
end
PPG_buffer = PPG_down(:); % Make sure PPG is column vector
% Standardizing PPG in sub-function.
PPG_buffer = my_func_standardizing_PPG(PPG_buffer);
% Filter signal.
[b, a] = butter(6,[0.5 20]/(fs_PPG/2)); % Bandpass filter.
PPG_buffer = filtfilt(b, a, PPG_buffer);
end","MATLAB"
"Biosensors","Cassey2016/PPG_Peak_Detection","method_06/my_revise_run_wabp.m",".m","4330","109","function [r,ssf,my_avg0,A] = my_revise_run_wabp(abp,fs_abp)
% Below was copied from Erick Andres Perez Alday's Github repository
% "" physionetchallenges / matlab-classifier-2020 "":
% https://github.com/physionetchallenges/matlab-classifier-2020/blob/master/Tools/PhysioNet-Cardiovascular-Signal-Toolbox-master/Tools/BP_Tools/run_wabp.m
% WABP ABP waveform onset detector.
% r = run_wabp(abp) obtains the onset time (in samples)
% of each beat in the ABP waveform.
%
% In: ABP (125Hz sampled)
% Out: Onset sample time
%
% Usage:
% - ABP waveform must have units of mmHg
%
% Written by James Sun (xinsun@mit.edu) on Nov 19, 2005. This ABP onset
% detector is adapted from Dr. Wei Zong's wabp.c.
%
% LICENSE:
% This software is offered freely and without warranty under
% the GNU (v3 or later) public license. See license file for
% more information
% Dong changed: input should be 250 Hz for filtering.
%% Input checks
% if nargin ~=1
% error('exactly 1 argment needed');
% end
if size(abp,2)~=1
error('Input must be a <nx1> vector');
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% scale physiologic ABP
offset = 1600;
scale = 20;
Araw = abp*scale-offset;
% LPF
A = filter([1 0 0 0 0 -2 0 0 0 0 1],[1 -2 1],Araw)/24+30;
A = (A(4:end)+offset)/scale; % Takes care of 4 sample group delay
% ------- Dong changed this: -------
A = A ./ std(A); % normalizing data is very important for my peak detection.
A = A - mean(A);
% Slope-sum function
dypos = diff(A);
dypos(dypos<0) = 0;
% ssf = [0; 0; conv(ones(16,1),dypos)];
w = 16/125*fs_abp; % 125 Hz to 250 Hz.
ssf = [0; 0; conv(ones(w,1),dypos)];
% Decision rule
first_8sec = 8*fs_abp;
% avg0 = sum(ssf(1:1000))/1000; % average of 1st 8 seconds (1000 samples) of SSF
avg0 = sum(ssf(1:first_8sec))/first_8sec;
Threshold0 = 3*avg0; % initial decision threshold
% ignoring ""learning period"" for now
lockout = 0; % lockout >0 means we are in refractory
timer = 0;
% z = zeros(100000,1);
z = zeros(fs_abp*800,1);
counter = 0;
% Dong: copied from wabp.c, 02/27/2020. % Dong change here. 02/27/2020.
TmDEF = 0.25; %5;% Dong change here. 02/27/2020.
max_min_thres = 0.1; %10;% Dong change here. 02/27/2020.
my_avg0 = zeros(size(abp));% Dong change here. 02/27/2020.
step_adjust_thres = 0.025; % it was 0.1 % Dong change here. 02/27/2020.
% for t = 50:length(ssf)-17
for t = round(0.4*fs_abp):length(ssf)-w-1
lockout = lockout - 1;
timer = timer + 1; % Timer used for counting time after previous ABP pulse
if (lockout<1) & (ssf(t)>avg0+TmDEF) %(ssf(t)>avg0+5) % Not in refractory and SSF has exceeded threshold here % Dong change here. 02/27/2020.
timer = 0;
maxSSF = max(ssf(t:t+w)); % Find local max of SSF
minSSF = min(ssf(t-w:t)); % Find local min of SSF
if maxSSF > (minSSF + max_min_thres) %(minSSF + 10)% Dong change here. 02/27/2020.
onset = 0.01*maxSSF ; % Onset is at the time in which local SSF just exceeds 0.01*maxSSF
tt = t-w:t;
dssf = ssf(tt) - ssf(tt-1);
BeatTime = find(dssf<onset,1,'last')+t-w-1;
counter = counter+1;
if isempty(BeatTime)
counter = counter-1;
else
z(counter) = BeatTime;
end
Threshold0 = Threshold0 + step_adjust_thres*(maxSSF - Threshold0); % adjust threshold
avg0 = Threshold0 / 3; % adjust avg
lockout = round(32/125*fs_abp); % lock so prevent sensing right after detection (refractory period)
end
end
if timer > round(312/125*fs_abp) % Lower threshold if no pulse detection for a while
Threshold0 = Threshold0 - 0.1; %Threshold0 - 1; % Dong change here. 02/27/2020.
avg0 = Threshold0/3;
end
my_avg0(t,1) = avg0+TmDEF; % % Dong change here. 02/27/2020.
end
r = z(find(z))-2;
end","MATLAB"
"Biosensors","Cassey2016/PPG_Peak_Detection","method_06/my_Elgendi_2013_method_III_peakdet.m",".m","1028","22","function [output_Elgendi_3_2013] = my_Elgendi_2013_method_III_peakdet(raw_PPG,fs_PPG)
% -------------------------------------------------------------------------
% This peak detection function was mentioned in this paper:
% Elgendi, Mohamed, et al.
% ""Systolic peak detection in acceleration photoplethysmograms measured from
% emergency responders in tropical conditions."" PLoS One 8.10 (2013): e76585.
%
[r,ssf,my_avg0,A] = my_revise_run_wabp(raw_PPG,fs_PPG);
% -------------------------------------------------------------------------
if isempty(r)
HR_Elgendi_3_2013 = 0; % there is no peak location.
r = 1;
else
HR_Elgendi_3_2013 = 60 * fs_PPG ./ diff(r); % calculate the HR.
end
A = [A;0;0;0;]; % add zero
A(1:6) = A(7); % first six plots are all high amplitude.
output_Elgendi_3_2013 = struct('PPG_peak_loc_Elgendi_3_2013',r,...
'HR_Elgendi_3_2013',HR_Elgendi_3_2013,...
'filtered_PPG_Elgendi_3_2013',A,...
'thres_Elgendi_3_2013',my_avg0);
end","MATLAB"
"Biosensors","Cassey2016/PPG_Peak_Detection","method_03_and_04/my_Elgendi_2013_method_I_peakdet.m",".m","3762","111","function [output_Elgendi_1_2013] = my_Elgendi_2013_method_I_peakdet(raw_PPG, delta, fs_PPG)
% -------------------------------------------------------------------------
% Dong add this on 02/25/2020, based on this paper:
% Elgendi, Mohamed, et al.
% ""Systolic peak detection in acceleration photoplethysmograms measured from
% emergency responders in tropical conditions."" PLoS One 8.10 (2013): e76585.
%
% (1): bandpass filter (0.5-8Hz)
[b, a] = butter(6,[0.5 8]/(fs_PPG/2)); % bandpass filter 0.5-10Hz, changed from 0.5-20 to 0.5-9 Hz at 11/21/2018
raw_PPG = filtfilt(b, a, raw_PPG); % -> AC component
raw_PPG = raw_PPG ./ std(raw_PPG); % normalizing data is very important for my peak detection.
raw_PPG = raw_PPG - mean(raw_PPG);
debugging_plot_flag = false; % only for plotting debugging figures.
% -------------------------------------------------------------------------
% Below code is copied from: http://billauer.co.il/peakdet.html
% PEAKDET Detect peaks in a vector
% [MAXTAB, MINTAB] = PEAKDET(V, DELTA) finds the local
% maxima and minima (""peaks"") in the vector V.
% MAXTAB and MINTAB consists of two columns. Column 1
% contains indices in V, and column 2 the found values.
%
% With [MAXTAB, MINTAB] = PEAKDET(V, DELTA, X) the indices
% in MAXTAB and MINTAB are replaced with the corresponding
% X-values.
%
% A point is considered a maximum peak if it has the maximal
% value, and was preceded (to the left) by a value lower by
% DELTA.
% Eli Billauer, 3.4.05 (Explicitly not copyrighted).
% This function is released to the public domain; Any use is allowed.
maxtab = [];
mintab = [];
raw_PPG = raw_PPG(:); % Just in case this wasn't a proper vector
% if nargin < 3
x = (1:length(raw_PPG))';
% else
% x = x(:);
% if length(raw_PPG)~= length(x)
% error('Input vectors v and x must have same length');
% end
% end
if (length(delta(:)))>1
error('Input argument DELTA must be a scalar');
end
if delta <= 0
error('Input argument DELTA must be positive');
end
mn = Inf; mx = -Inf;
mnpos = NaN; mxpos = NaN;
lookformax = 1;
for i=1:length(raw_PPG)
this = raw_PPG(i);
if this > mx, mx = this; mxpos = x(i); end
if this < mn, mn = this; mnpos = x(i); end
if lookformax
if this < mx-delta
maxtab = [maxtab ; mxpos mx];
mn = this; mnpos = x(i);
lookformax = 0;
end
else
if this > mn+delta
mintab = [mintab ; mnpos mn];
mx = this; mxpos = x(i);
lookformax = 1;
end
end
end
if isempty(maxtab)
HR_Elgendi_1_max_2009 = 0; % there is no peak location.
peak_loc_max = 1;
else
peak_loc_max = maxtab(:,1);
HR_Elgendi_1_max_2009 = 60 * fs_PPG ./ diff(peak_loc_max); % calculate the HR.
end
if isempty(mintab)
HR_Elgendi_1_min_2009 = 0; % there is no peak location.
peak_loc_min = 1;
else
peak_loc_min = mintab(:,1);
HR_Elgendi_1_min_2009 = 60 * fs_PPG ./ diff(peak_loc_min); % calculate the HR.
end
output_Elgendi_1_2013 = struct('filtered_PPG_Elgendi_1_2013',raw_PPG,...
'PPG_peak_loc_Elgendi_1_max_2013',peak_loc_max,...
'PPG_peak_loc_Elgendi_1_min_2013',peak_loc_min,...
'HR_Elgendi_1_max_2013',HR_Elgendi_1_max_2009,...
'HR_Elgendi_1_min_2013',HR_Elgendi_1_min_2009);
if debugging_plot_flag % debugging plot
figure;
plot(x,raw_PPG);hold on;
plot(peak_loc_max,raw_PPG(peak_loc_max),'ro');
plot(peak_loc_min,raw_PPG(peak_loc_min),'go');
end
end","MATLAB"
"Biosensors","Cassey2016/PPG_Peak_Detection","method_08_and_09/my_Vadrevu_2019_peakdet.m",".m","10598","329","function [output_Vadrevu_1_2019,output_Vadrevu_2_2019] = my_Vadrevu_2019_peakdet(PPG_buffer,fs_PPG)
% =========================================================================
% This is my implementation of this paper:
%
% Vadrevu, Simhadri, and M. Sabarimalai Manikandan.
% ""A robust pulse onset and peak detection method for automated PPG signal
% analysis system."" IEEE Transactions on Instrumentation and Measurement
% 68.3 (2018): 807-817.
%
% Implemented by Dong Han on 05/03/2020.
%
% Please cite our paper if you used this code:
% Han, Dong, Syed K. Bashar, Jesús Lázaro, Fahimeh Mohagheghian,
% Andrew Peitzsch, Nishat Nishita, Eric Ding, Emily L. Dickson,
% Danielle DiMezza, Jessica Scott, Cody Whitcomb, Timothy P. Fitzgibbons,
% David D. McManus, and Ki H. Chon. 2022.
% ""A Real-Time PPG Peak Detection Method for Accurate Determination of
% Heart Rate during Sinus Rhythm and Cardiac Arrhythmia""
% Biosensors 12, no. 2: 82. https://doi.org/10.3390/bios12020082
%
% Please cite our paper if you used our code. Thank you.
% =========================================================================
debug_flag = false; % decide to plot the paper figure or not.
%% A. Stationary Wavelet Transform of PPG signal.
% first, for the input length, you can know the maximum wavelet
% decomposition level you can get:
TYPE = '1D'; % extension method.
MODE = 'zpd'; % zero extension.
X = PPG_buffer;
% based on your input signal length, you have to extend your input signal
% to MATLAB suggested length.
LEN = 45;%18; % 18 for fs_PPG 50, 45 for fs_PPG 125; for 30 sec input.
YEXT = wextend(TYPE,MODE,X,LEN); % required by swt.
sig = YEXT;
% s = PPG_buffer;
sLen = length(sig);
wname = 'bior1.5';
L = wmaxlev(sLen,wname);
% [swa,swd] = swt(s,3,'bior1.5'); % the author mentioned wavelet biorthogonal 1.5 (bior1.5)
[swa,swd] = swt(sig,L,wname); % the author mentioned wavelet biorthogonal 1.5 (bior1.5)
s1 = swd(3,:) + swd(4,:);
s1 = s1(:); % make sure it is column vector.
s2 = swd(5,:) + swd(6,:) + swd(7,:);
s2 = s2(:); % make sure it is column vector.
if debug_flag
% if you want to debug the result.
figure;
t_plot = [1:length(sig)]'./fs_PPG; %
subplot(5,1,1);
plot(t_plot,sig);
xlim([0 t_plot(end)])
ylabel('Orig');
title('Fig.3 in TIM 2019 paper');
subplot(5,1,2)
plot(t_plot,(swd(1,:) + swd(2,:)))
xlim([0 t_plot(end)])
ylabel('s_0');
subplot(5,1,3);
plot(t_plot,s1);
xlim([0 t_plot(end)])
ylabel('s_1');
subplot(5,1,4);
plot(t_plot,s2);
xlim([0 t_plot(end)])
ylabel('s_2');
subplot(5,1,5);
plot(t_plot,swa(7,:));
xlim([0 t_plot(end)])
ylabel('a_7');
end
%% B. Multiscale Sum and Products:
p = s1 .* s2;
p = p(:);
if debug_flag
% if you want to debug the result.
figure;
ax(1) = subplot(4,1,1);
plot(t_plot,sig);
xlim([0 t_plot(end)])
ylabel('Orig');
title('Fig.4 in TIM 2019 paper');
ax(2) = subplot(4,1,2);
p1 = swd(1,:) .* swd(2,:) .* swd(3,:) .* swd(4,:) .* swd(5,:) .* swd(6,:) .* swd(7,:);
plot(t_plot,p1);
xlim([0 t_plot(end)])
ylabel('p_1');
ax(3) = subplot(4,1,3);
p1 = swd(3,:) .* swd(4,:) .* swd(5,:) .* swd(6,:) .* swd(7,:);
plot(t_plot,p1);
xlim([0 t_plot(end)])
ylabel('p_2');
ax(4) = subplot(4,1,4);
plot(t_plot,p);
xlim([0 t_plot(end)])
ylabel('p');
linkaxes(ax,'x');
end
%% C. Shannon Entropy Envelope Extraction
eta = 0.01 + std(p);
p_tilda = abs(p);
p_tilda(p_tilda < eta) = 0;
p_tilda = p_tilda(:);
% normalize p_tilda:
norm_p_tilda = (p_tilda - min(p_tilda)) ./ (max(p_tilda) - min(p_tilda));
norm_p_tilda = norm_p_tilda(:);
se = NaN(size(norm_p_tilda));
for tttt = 1:size(norm_p_tilda,1)
if norm_p_tilda(tttt) == 0
% from MATLAB page: https://www.mathworks.com/help/wavelet/ref/wentropy.html
% log(0) = 0
% 0log(0) = 0.
se(tttt) = 0;
else
se(tttt) = -1 * norm_p_tilda(tttt) .* log(norm_p_tilda(tttt));
end
end
% % method 1: CONV twice:
filt_Len = floor(0.2 * fs_PPG); % 0.4 is better. 05/04/2020.
% h = ones(filt_Len,1)/filt_Len; % A third-order filter has length 4
% s = conv(se,h,'same'); % return the same size as se
% s = conv(s,h,'same'); % conv twice
% method 2: FILTFILT.
% for 4020, ii = 2, PPG is zero.
if any(isnan(se))
% any sample is NaN.
new_se = se;
new_se(isnan(new_se)) = [];
if isempty(new_se)
% nothing left after removing NaN.
HR_Vadrevu_1_2019 = 0; % there is no peak location.
onset_zx = 1;
HR_Vadrevu_2_2019 = 0; % there is no peak location.
peak_zx = 1;
filter_PPG = PPG_buffer;
output_Vadrevu_1_2019 = struct('filtered_PPG_Vadrevu_2019',filter_PPG,...
'PPG_peak_loc_Vadrevu_1_2019',onset_zx,...
'HR_Vadrevu_1_2019',HR_Vadrevu_1_2019);
output_Vadrevu_2_2019 = struct('filtered_PPG_Vadrevu_2019',filter_PPG,...
'PPG_peak_loc_Vadrevu_2_2019',peak_zx,...
'HR_Vadrevu_2_2019',HR_Vadrevu_2_2019);
return
else
% part of data is NaN, maybe I should fill zeros in it?
keyboard;
end
end
b = ones(filt_Len,1);
a = -1;
s = filtfilt(b, a, se); % -> AC component
%% D. Pulse Peak and Onset Determination.
% 1. Gaussian derivative kernel:
sigma_1 = floor(0.05 * fs_PPG); % 0.05 mentioned in the paper.
M = floor(2 * fs_PPG); % 2 mentioned in the paper.
g = gausswin(M,sigma_1); % size should be 250 if Fs = 125.
h_d = diff(g); % g(m+1) - g(m).
z = conv(s,h_d,'same');
% % My conv function did not work.
% temp_z = zeros(size(s,1),1);
% for nnnn = 1:size(s,1)
% for mmmm = 1:size(g,1)-1
% if (nnnn-mmmm+1 > 0)
% % h_d(mmmm) = g(mmmm+1) - g(mmmm);
% temp_z(nnnn) = temp_z(nnnn) + s(mmmm) * h_d(nnnn-mmmm+1);
% end
% end
% end
DownZCi = @(v) find(v(1:end-1) >= 0 & v(2:end) < 0); % Returns Down Zero-Crossing Indices. https://www.mathworks.com/matlabcentral/answers/267222-easy-way-of-finding-zero-crossing-of-a-function
zx = DownZCi(z); % negative zero crossing point.
% peak correction algorithm for onset:
search_intv = floor(0.1 * fs_PPG / 2); % w/2
onset_zx = NaN(size(zx));
for zz = 1:size(zx,1)
temp_zx = zx(zz);
if temp_zx - search_intv > 0 % not exceed signal limit.
if temp_zx + search_intv <= size(sig,1)
temp_PPG = sig(temp_zx - search_intv : temp_zx + search_intv);
[~,I] = min(temp_PPG);
if isempty(I) ~= 1
adj_loc = temp_zx - search_intv + I - 1;
else
% no local minimum.
adj_loc = temp_zx;
end
onset_zx(zz) = adj_loc;
else
% right interval exceed signal length.
onset_zx(zz) = zx(zz);
end
else
% left interval exceed index 1.
onset_zx(zz) = zx(zz);
end
end
% find peak:
peak_zx = NaN(size(onset_zx,1)-1,1); % one sample smaller.
for zz = 2:size(onset_zx,1)
temp_onset_1 = onset_zx(zz-1);
temp_onset_2 = onset_zx(zz);
temp_PPG = sig(temp_onset_1:temp_onset_2);
[~,I] = max(temp_PPG);
if isempty(I) ~= 1
peak_zx(zz-1) = temp_onset_1 + I - 1; % peak is one sample size smaller.
else
peak_zx(zz-1) = onset_zx(zz);
end
end
% prepare to output signal:
filter_PPG = z(LEN+1:end-LEN);
remove_left = find(onset_zx < LEN+1);
if isempty(remove_left) ~= 1
onset_zx(remove_left) = [];
end
remove_right = find(onset_zx > size(z,1) - LEN);
if isempty(remove_right) ~= 1
onset_zx(remove_right) = [];
end
onset_zx = onset_zx - LEN; % shifted.
remove_left = find(peak_zx < LEN+1);
if isempty(remove_left) ~= 1
peak_zx(remove_left) = [];
end
remove_right = find(peak_zx > size(z,1) - LEN);
if isempty(remove_right) ~= 1
peak_zx(remove_right) = [];
end
peak_zx = peak_zx - LEN;
if debug_flag
% if you want to debug the result.
figure;
ax(1) = subplot(7,1,1);
plot(t_plot,sig);
xlim([0 t_plot(end)])
ylabel('Orig');
title('Fig.5 in TIM 2019 paper');
ax(2) = subplot(7,1,2);
plot(t_plot,p);
xlim([0 t_plot(end)])
ylabel('p');
ax(3) = subplot(7,1,3);
plot(t_plot,norm_p_tilda);
xlim([0 t_plot(end)])
ylabel('p_th');
ax(4) = subplot(7,1,4);
plot(t_plot,se);
xlim([0 t_plot(end)])
ylabel('se');
ax(5) = subplot(7,1,5);
plot(t_plot,s);
xlim([0 t_plot(end)])
ylabel('s');
ax(6) = subplot(7,1,6);
plot(t_plot,z);
hold on;
plot(t_plot(zx),z(zx),'ro');
xlim([0 t_plot(end)]);
ylabel('z');
ax(7) = subplot(7,1,7);
plot(t_plot,sig);
hold on;
plot(t_plot(onset_zx),sig(onset_zx),'go');
plot(t_plot(peak_zx),sig(peak_zx),'ro');
xlim([0 t_plot(end)])
ylabel('orig with peak');
linkaxes(ax,'x');
end
if isempty(onset_zx)
HR_Vadrevu_1_2019 = 0; % there is no peak location.
onset_zx = 1;
else
HR_Vadrevu_1_2019 = 60 * fs_PPG ./ diff(onset_zx); % calculate the HR.
end
if isempty(peak_zx)
HR_Vadrevu_2_2019 = 0; % there is no peak location.
peak_zx = 1;
else
HR_Vadrevu_2_2019 = 60 * fs_PPG ./ diff(peak_zx); % calculate the HR.
end
output_Vadrevu_1_2019 = struct('filtered_PPG_Vadrevu_2019',filter_PPG,...
'PPG_peak_loc_Vadrevu_1_2019',onset_zx,...
'HR_Vadrevu_1_2019',HR_Vadrevu_1_2019);
output_Vadrevu_2_2019 = struct('filtered_PPG_Vadrevu_2019',filter_PPG,...
'PPG_peak_loc_Vadrevu_2_2019',peak_zx,...
'HR_Vadrevu_2_2019',HR_Vadrevu_2_2019);
end
","MATLAB"