【信号处理】心电信号PQRST峰值检测matlab工具箱
【信号处理】心电信号PQRST峰值检测matlab工具箱
TT_Matlab
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1 简介
一种基于PQRST波位置识别的心电信号峰值检测方法，通过使用一种基于PQRST波位置识别的 心电 信号 峰值检测方法，进一步挖掘出心电波形的特征，利用一种基于PQRST波位置识别的 心电 信号检测方法，可以有效检测出包含RonT波的心电波形数据，使用F1值，可以定量分析检测 心电 信号 的识别效果，对 心电 信号 识别研究有促进作用。缓解 心电 信号 波的检测尚缺乏医学上的金标准且检测准确性不高的问题。
2 部分代码
function [RR_mean,QRS_mean,mean_QT,mean_PR,RR_std,RR_skew,RR_kurt,QRS_std,QRS_skew,QRS_kurt,std_PR,skew_PR,kurt_PR,std_QT,skew_QT,kurt_QT]= compute_mean_interval_c(locs_P,locs_Q,locs_R2,locs_S,locs_T,fs)
%% WHAT DOES THIS FUNCTION
DO
?
% THIS
FUNCTION
COMPUTES THE MEAN RR, MEAN QRS, MEAN QT
AND
MEAN PR
%
INTERVAL
BASED
ON
THE LOCATIONS
OF
THE PEAKS.
% OTHER STATISTICAL
DATA
ALSO COMPUTED.
%
COMPILED
AND
MAINTAINED
BY
-
% ROHAN SANGHAVI
%% CODE LOGIC - RR
INTERVAL
RR_period = diff((locs_R2))./fs;
RR_mean = mean(RR_period); % we consider the unwindowed mean for accuracy
RR_std = std(RR_period);
RR_skew = skewness(RR_period);
RR_kurt = kurtosis(RR_period);
if isnan(RR_mean)
RR_mean = 0;
end
if
isnan(RR_std)
RR_std =
0
;
end
if
isnan(RR_skew)
RR_skew =
0
;
end
if
isnan(RR_kurt)
RR_kurt =
0
;
end
%% QRS COMPLEX PERIOD.
if
(
length
(
unique
(locs_Q))>
2
&&
length
(
unique
(locs_S))>
2
)
if
length
(locs_Q)~=
length
(locs_S)
locs_S = locs_S(~isnan(interp1(
unique
(locs_Q),
unique
(locs_Q),
unique
(locs_S),
’nearest’
))); % if lengths are unequal
end
end
if
(
length
(
unique
(locs_Q))>
2
&&
length
(
unique
(locs_S))>
2
)
if
length
(locs_Q)~=
length
(locs_S)
locs_Q = locs_Q(~isnan(interp1(
unique
(locs_S),
unique
(locs_S),
unique
(locs_Q),
’nearest’
))); % interpolation to find closest values.
end
end
%
double
check
and
then
finally subtract.
if
length
(locs_Q) >
length
(locs_S)
locs_Q1 = locs_Q(
1
:
length
(locs_S));
locs_S1 = locs_S;
else
locs_S1 = locs_S(1:length(locs_Q));
locs_Q1 = locs_Q;
end
QRS_period = ((locs_S1 - locs_Q1)./fs);
QRS_mean = mean(QRS_period);
QRS_std = std(QRS_period);
QRS_kurt = kurtosis(QRS_period);
QRS_skew = skewness(QRS_period);
if isnan(QRS_mean)
QRS_mean = 0;
end
if
isnan(QRS_std)
QRS_std =
0
;
end
if
isnan(QRS_skew)
QRS_skew =
0
;
end
if
isnan(QRS_kurt)
QRS_kurt =
0
;
end
%% PR
INTERVAL
if
(
length
(
unique
(locs_P))>
2
&&
length
(
unique
(locs_R2))>
2
)
if
length
(locs_P)~=
length
(locs_R2)
locs_R2 = locs_R2(~isnan(interp1(
unique
(locs_P),
unique
(locs_P),
unique
(locs_R2),
’nearest’
))); % if lengths are unequal
end
end
if
(
length
(
unique
(locs_P))>
2
&&
length
(
unique
(locs_R2))>
2
)
if
length
(locs_P)~=
length
(locs_R2)
locs_P = locs_P(~isnan(interp1(
unique
(locs_R2),
unique
(locs_R2),
unique
(locs_P),
’nearest’
))); % interpolation to find closest values.
end
end
if
length
(locs_R2) >
length
(locs_P)
locs_R3 = locs_R2(
1
:
length
(locs_P));
locs_P2 = locs_P;
temp = 1;
else
locs_P2 = locs_P(1:length(locs_R2));
locs_R3 = locs_R2;
temp = 1;
end
PR_interval = ((locs_R3 - locs_P2)./fs);
if temp == 0
mean_PR = mean(PR_interval);
else
mean_PR = abs(mean(PR_interval));
end
std_PR =
std
(PR_interval);
skew_PR = skewness(PR_interval);
kurt_PR = kurtosis(PR_interval);
if isnan(mean_PR)
mean_PR = 0;
end
if
isnan(std_PR)
std_PR =
0
;
end
if
isnan(kurt_PR)
kurt_PR =
0
;
end
if
isnan(skew_PR)
skew_PR =
0
;
end
%% QT
INTERVAL
if
(
length
(
unique
(locs_Q))>
2
&&
length
(
unique
(locs_T))>
2
)
if
length
(locs_Q)~=
length
(locs_T)
locs_T = locs_T(~isnan(interp1(
unique
(locs_Q),
unique
(locs_Q),
unique
(locs_T),
’nearest’
))); % if lengths are unequal
end
end
if
(
length
(
unique
(locs_Q))>
2
&&
length
(
unique
(locs_T))>
2
)
if
length
(locs_Q)~=
length
(locs_T)
locs_Q = locs_Q(~isnan(interp1(
unique
(locs_T),
unique
(locs_T),
unique
(locs_Q),
’nearest’
))); % interpolation to find closest values.
end
end
if
length
(locs_Q) >
length
(locs_T)
locs_Q2 = locs_Q(
1
:
length
(locs_T));
locs_T2 = locs_T;
flag =1;
else
locs_T2 = locs_T(1:length(locs_Q));
locs_Q2 = locs_Q;
flag =1; % equal here
end
QT_interval = ((locs_T2 - locs_Q2)./fs);
if flag ==0
mean_QT = mean(QT_interval);
elseif flag == 1
mean_QT = abs(mean(QT_interval));
else
mean_QT = abs(mean(QT_interval));
end
std_QT =
std
(QT_interval);
skew_QT = skewness(QT_interval);
kurt_QT = kurtosis(QT_interval);
if isnan(mean_QT)
mean_QT = 0;
end
if
isnan(std_QT)
std_QT =
0
;
end
if
isnan(skew_QT)
skew_QT =
0
;
end
if
isnan(kurt_QT)
kurt_QT =
0
;
end
end
3 仿真结果
4 参考文献
[1]胡广书, 郑良和. 体表心电Mapping系统中心电信号的处理与峰值定位检测[J]. 北京生物医学工程, 1995, 14(2):5.
博主简介：擅长智能优化算法、神经网络预测、信号处理、元胞自动机、图像处理、路径规划、无人机等多种领域的Matlab仿真，相关matlab代码问题可私信交流。
部分理论引用网络文献，若有侵权联系博主删除。