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RMS_percentile_250.m
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function RMS_percentile_250
%%%%%%%%%%%%%%%%%%%% 滤波器参数 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Fs = 250; % Sampling Frequency
%%% filter_design(Fs,Fstop1,Fpass1,Fpass2,Fstop2) % 滤波器系数的计算，并存储系数 B
Hd = kasier_filter;
% load('B.mat');
B = Hd.Numerator;
prefile = spm_select(1, 'dir', 'Select imported EEG file','' ...
,pwd,'.*');
%%%%%%%%%%%%%%%%%%%% 参数 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
unit_num = 125; %多少个点算一次rms
N2_dir_path = prefile; % （N2_dir_path：所有被试的数据文件夹的路径）
N2_dir = dir(N2_dir_path); %（ N2_dir：N2数据文件夹的信息的结构体）
m = length(N2_dir); % m-2 为被试个数
percentile = 95;
%%%%%%%%%%%%%%%%%%% rms, threshold %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
h=waitbar(0,'Please waiting...');
number_segment = zeros(1,m-2);
for subj_i = 3:m
subj_name = N2_dir(subj_i).name; % （subj_name：当前被试的名字）
subj_dir_path = [N2_dir_path,subj_name]; % （subj_dir_path：当前被试文件夹的路径）
subj_dir = dir(subj_dir_path);
number_segment(subj_i-2) = length(subj_dir)-2;
end
total_step = sum(number_segment)*10;
n = 0;
for subj_i = 3:m % 对被试的循环 (因为N2_dir的前两个是当前文件夹和上层文件夹，所以要从3开始)
subj_name = N2_dir(subj_i).name; % （subj_name：当前被试的名字）
subj_dir_path = [N2_dir_path,subj_name]; % （subj_dir_path：当前被试文件夹的路径）
subj_dir = dir(subj_dir_path);
for segment = 3:length(subj_dir)
subj_dir_name = subj_dir(segment).name;
load([subj_dir_path,'\',subj_dir_name]);
mat_orgn_length = size(b,2); % （mat_length：mat_orgn_data的长度）
mat_length = mat_orgn_length-mod(mat_orgn_length,unit_num); % (mat_length:计算数据长度中能被unit_num整除的部分)
data = b(:,1:mat_length); % 将当前数据不能被unit_num整除的部分从最后去掉
left_data = [data(1:2:11,:);data(18:2:20,:)];
right_data = [data(2:2:12,:);data(19:2:21,:)];
middle_data = data(13:15,:);
left_data = left_data-ones(size(left_data,1),1)*data(17,:);
right_data = right_data-ones(size(right_data,1),1)*data(16,:);
middle_data = middle_data-ones(size(middle_data,1),1)*mean(data(16:17,:),1);
data_all = [left_data;right_data;middle_data];
data_all_medi = zeros(size(data_all,1),size(data_all,2));
data_all_medi(1:2:11,:) = left_data(1:6,:);
data_all_medi(2:2:12,:) = right_data(1:6,:);
data_all_medi(13:15,:) = middle_data;
data_all_medi(16:2:18,:) = left_data(7:8,:);
data_all_medi(17:2:19,:) = right_data(7:8,:);
data_all = data_all_medi;
mat_data_2 = data_all';
clear data_all_medi;
mat_data_3 = filtfilt(B,1,mat_data_2); % 对mat_data_2进行滤波，得到10列数据；需要较长时间，所以save mat_data_3。
mat_data_4 = reshape(mat_data_3,unit_num,[],size(data_all,1)); % 对数据进行维度转换，便于一次性rms计算。
each_mat_rms= rms(mat_data_4);
each_mat_rms = reshape(each_mat_rms,[],size(data_all,1));
detection = zeros(size(mat_data_3,1),size(mat_data_3,2));
for channel = 1:size(each_mat_rms,2)
n = n+1;
Spd_amplitude = [];
Spd_frequency = [];
Spd_duration = [];
thres = prctile(each_mat_rms(:,channel),percentile);
rms_data_1 = (each_mat_rms(:,channel)>thres);
res = lianxu_1(rms_data_1,unit_num,Fs); % 计算连续1的位置和个数
if isempty(res)
continue;
else
[spd_num,~] = size(res);%纺锤波个数
spindle_position=zeros(spd_num,2);%纺锤波的开始时间和结束时间
for spd_i = 1:spd_num
st = res(spd_i,1); % 计算rms纺锤波的起点index
ed =res(spd_i,1)+res(spd_i,2)-1; % 计算rms纺锤波的结束index
st = (st-1)*unit_num+1; % 换算纺锤波的起点index
ed = ed*unit_num; % 换算纺锤波的结束index
detection(st:ed,channel)=1;
spindle_position(spd_i,:)=[st ed];
spd_data = mat_data_3(st:ed,channel); %得到纺锤波数据
[pks_p,locs_p] = findpeaks(spd_data); % 得到极大值
[pks_n,locs_n] = findpeaks(-spd_data); %得到极小值
locs_p = st-1+locs_p; %得到极大值在mat_data_3 的绝对index
locs_n = st-1+locs_n; %得到极小值在mat_data_3 的绝对index
%%%%%%%%%%%%%%% 计算幅值 %%%%%%%%%%%%%%%%%%%%%%%%%
length_p = length(locs_p);
length_n = length(locs_n);
length_union = length_p+length_n;
pks_union = zeros(1,length_union);
if (locs_p(1)<locs_n(1)) % 极大值在前面
pks_union(1:2:end) = pks_p;
pks_union(2:2:end) = pks_n; % 进行峰值的插缝拼接，便于计算pks-to-pks
pks_union_1 = [pks_union(2:end),0]; % 从第二个开始取
pks_union_2 = pks_union+pks_union_1; % 计算 pks-to-pks
pks_union = pks_union_2(1:end-1); % 取的实际的pks-to-pks
[amplitude,index_1] = max(pks_union); % 得到最大的peak-to-peak
else
pks_union(1:2:end) = pks_n;
pks_union(2:2:end) = pks_p;
pks_union_1 = [pks_union(2:end),0];
pks_union_2 = pks_union+pks_union_1; % 计算 pks-to-pks
pks_union = pks_union_2(1:end-1);
[amplitude,index_1] = max(pks_union); % 得到最大的peak-to-peak
end
Spd_amplitude = [Spd_amplitude,amplitude];
%%%%%%%%%%%%%%%%%% 计算频率 %%%%%%%%%%%%%%%%%
N=2*Fs;
FFT_data=abs(fft(spd_data,N));
freqs=(1:N/2)*Fs/N;
index_freq1 = find(freqs <= 11);
index_freq2 = find(freqs <= 16);
[pks,locs]=findpeaks(FFT_data(index_freq1(end):index_freq2(end)));
[~,pks_pos] = max(pks);
frequency = freqs(locs(pks_pos)+index_freq1(end)-1);
Spd_frequency = [Spd_frequency,frequency];
%%%%%%%%%%%%%%%%% 计算持续时间 %%%%%%%%%%%%%%%%%%%%%%%%%
duration = res(spd_i,2)*(unit_num/Fs); %
Spd_duration = [Spd_duration,duration];
end
end
Spd(channel).number = spd_num;
Spd(channel).amplitude = Spd_amplitude;
Spd(channel).posiiton = spindle_position;
Spd(channel).frequency = Spd_frequency;
Spd(channel).duration = Spd_duration;
i = n/total_step;
waitbar(i,h,['已完成' num2str(i*100) '%']);
end
Spindle_segment(segment).detection = detection;
Spindle_segment(segment).length = mat_length;
Spindle_segment(segment).spindle = Spd;
end
mkdir([subj_dir_path,'\',subj_name]);
subject_result_path = [subj_dir_path,'\',subj_name];
save([subject_result_path,'\','spindle_result_',num2str(subj_i-2)],'Spindle_segment');
end
close(h);
end
%%%%%%%%%%%%%%%%%%%% filter_design %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function Hd = kasier_filter
%UNTITLED Returns a discrete-time filter object.
%
% MATLAB Code
% Generated by MATLAB(R) 7.14 and the Signal Processing Toolbox 6.17.
%
% Generated on: 08-Sep-2015 18:31:40
%
% FIR Window Bandpass filter designed using the FIR1 function.
% All frequency values are in Hz.
Fs = 250; % Sampling Frequency
N = 2400; % Order
Fc1 = 11; % First Cutoff Frequency
Fc2 = 15; % Second Cutoff Frequency
flag = 'scale'; % Sampling Flag
Beta = 5; % Window Parameter
% Create the window vector for the design algorithm.
win = kaiser(N+1, Beta);
% Calculate the coefficients using the FIR1 function.
b = fir1(N, [Fc1 Fc2]/(Fs/2), 'bandpass', win, flag);
Hd = dfilt.dffir(b);
% [EOF]
end
%%%%%%%%%%%%%%%%%%%%%%% lianxu_1 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function res = lianxu_1(a,Num,Fs)
%a = [0 ones(1,5) 0 0 1 0 ones(1,10) 0] ;
b = find(a) ; %找出rms计算结果中大于阈值被赋值为1的位置
res = [] ;
n = 1 ;
i = 1 ;
while i < length(b)
j = i+1 ;
while j <= length(b) && b(j)==b(j-1)+1 %如果出现连续为1
n = n + 1 ;%连续为1的个数
j = j + 1 ;
end
if n >= ((0.5*Fs)/Num) && n <= ((2*Fs)/Num) % 连续为1的个数范围在此之内，则满足纺锤波的持续时间，就将这个值记录下来
res = [res ; b(i),n] ;
end
n = 1 ;
i = j ;
end
end