用matlab读取edf格式的脑电时，其数值是脑电的幅值吗？
用matlab读取edf格式的脑电时，matlab上的读数是脑电的幅值吗？ 个人水平专业有限, 不知edf格式是什么? :@L 冒昧问你一下你是怎么用matlab读取edf文件的？ 其实只要知道资料档案的格式, 使用fread就一定可以读!帮搜索下, 不过个人没edf的资料, 没试过
试过的人再说说是否可用
From http://www.mathworks.com/matlabcentral/fileexchange/31900-edfreadfunction = edfRead(fname, varargin)
% Read European Data Format file into MATLAB
%
% = edfRead(fname)
% Reads data from ALL RECORDS of file fname ('*.edf'). Header
% information is returned in structure hdr, and the signals
% (waveforms) are returned in structure record, with waveforms
% associated with the records returned as fields titled 'data' of
% structure record.
%
% [...] = edfRead(fname, 'assignToVariables', assignToVariables)
% Triggers writing of individual output variables, as defined by
% field 'labels', into the caller workspace.
%
% FORMAT SPEC: Source: http://www.edfplus.info/specs/edf.html SEE ALSO:
% http://www.dpmi.tu-graz.ac.at/~schloegl/matlab/eeg/edf_spec.htm
%
% The first 256 bytes of the header record specify the version number of
% this format, local patient and recording identification, time information
% about the recording, the number of data records and finally the number of
% signals (ns) in each data record. Then for each signal another 256 bytes
% follow in the header record, each specifying the type of signal (e.g.
% EEG, body temperature, etc.), amplitude calibration and the number of
% samples in each data record (from which the sampling frequency can be
% derived since the duration of a data record is also known). In this way,
% the format allows for different gains and sampling frequencies for each
% signal. The header record contains 256 + (ns * 256) bytes.
%
% Following the header record, each of the subsequent data records contains
% 'duration' seconds of 'ns' signals, with each signal being represented by
% the specified (in the header) number of samples. In order to reduce data
% size and adapt to commonly used software for acquisition, processing and
% graphical display of polygraphic signals, each sample value is
% represented as a 2-byte integer in 2's complement format. Figure 1 shows
% the detailed format of each data record.
%
% DATA SOURCE: Signals of various types (including the sample signal used
% below) are available from PHYSIONET: http://www.physionet.org/
%
%
% % EXAMPLE 1:
% % Read all waveforms/data associated with file 'ecgca998.edf':
%
% = edfRead('ecgca998.edf');
%
% % EXAMPLE 2:
% % Read records 3 and 5, associated with file 'ecgca998.edf':
%
% header = edfRead('ecgca998.edf','AssignToVariables',true);
% % Header file specifies data labels 'label_1'...'label_n'; these are
% % created as variables in the caller workspace.
%
% Coded 8/27/09 by Brett Shoelson, PhD
% brett.shoelson@mathworks.com
% Copyright 2009 - 2012 MathWorks, Inc.
% HEADER RECORD
% 8 ascii : version of this data format (0)
% 80 ascii : local patient identification
% 80 ascii : local recording identification
% 8 ascii : startdate of recording (dd.mm.yy)
% 8 ascii : starttime of recording (hh.mm.ss)
% 8 ascii : number of bytes in header record
% 44 ascii : reserved
% 8 ascii : number of data records (-1 if unknown)
% 8 ascii : duration of a data record, in seconds
% 4 ascii : number of signals (ns) in data record
% ns * 16 ascii : ns * label (e.g. EEG FpzCz or Body temp)
% ns * 80 ascii : ns * transducer type (e.g. AgAgCl electrode)
% ns * 8 ascii : ns * physical dimension (e.g. uV or degreeC)
% ns * 8 ascii : ns * physical minimum (e.g. -500 or 34)
% ns * 8 ascii : ns * physical maximum (e.g. 500 or 40)
% ns * 8 ascii : ns * digital minimum (e.g. -2048)
% ns * 8 ascii : ns * digital maximum (e.g. 2047)
% ns * 80 ascii : ns * prefiltering (e.g. HP:0.1Hz LP:75Hz)
% ns * 8 ascii : ns * nr of samples in each data record
% ns * 32 ascii : ns * reserved
% DATA RECORD
% nr of samples * integer : first signal in the data record
% nr of samples * integer : second signal
% ..
% ..
% nr of samples * integer : last signal
if nargin > 3
error('EDFREAD: Too many input arguments.');
end
if ~nargin
error('EDFREAD: Requires at least one input argument (filename to read).');
end
if nargin == 1
assignToVariables = false;
end
= fopen(fname,'r');
if fid == -1
error(msg)
end
assignToVariables = false; %Default
for ii = 1:2:numel(varargin)
switch lower(varargin{ii})
case 'assigntovariables'
assignToVariables = varargin{ii+1};
end
end
% HEADER
hdr.ver = str2double(char(fread(fid,8)'));
hdr.patientID= fread(fid,80,'*char')';
hdr.recordID = fread(fid,80,'*char')';
hdr.startdate= fread(fid,8,'*char')';% (dd.mm.yy)
% hdr.startdate= datestr(datenum(fread(fid,8,'*char')','dd.mm.yy'), 29); %'yyyy-mm-dd' (ISO 8601)
hdr.starttime= fread(fid,8,'*char')';% (hh.mm.ss)
% hdr.starttime= datestr(datenum(fread(fid,8,'*char')','hh.mm.ss'), 13); %'HH:MM:SS' (ISO 8601)
hdr.bytes = str2double(fread(fid,8,'*char')');
reserved = fread(fid,44);
hdr.records = str2double(fread(fid,8,'*char')');
hdr.duration = str2double(fread(fid,8,'*char')');
% Number of signals
hdr.ns = str2double(fread(fid,4,'*char')');
for ii = 1:hdr.ns
hdr.label{ii} = fread(fid,16,'*char')';
end
for ii = 1:hdr.ns
hdr.transducer{ii} = fread(fid,80,'*char')';
end
% Physical dimension
for ii = 1:hdr.ns
hdr.units{ii} = fread(fid,8,'*char')';
end
% Physical minimum
for ii = 1:hdr.ns
hdr.physicalMin(ii) = str2double(fread(fid,8,'*char')');
end
% Physical maximum
for ii = 1:hdr.ns
hdr.physicalMax(ii) = str2double(fread(fid,8,'*char')');
end
% Digital minimum
for ii = 1:hdr.ns
hdr.digitalMin(ii) = str2double(fread(fid,8,'*char')');
end
% Digital maximum
for ii = 1:hdr.ns
hdr.digitalMax(ii) = str2double(fread(fid,8,'*char')');
end
for ii = 1:hdr.ns
hdr.prefilter{ii} = fread(fid,80,'*char')';
end
for ii = 1:hdr.ns
hdr.samples(ii) = str2double(fread(fid,8,'*char')');
end
for ii = 1:hdr.ns
reserved = fread(fid,32,'*char')';
end
hdr.label = deblank(hdr.label);
hdr.units = deblank(hdr.units);
if nargout > 1 || assignToVariables
% Scale data (linear scaling)
scalefac = (hdr.physicalMax - hdr.physicalMin)./(hdr.digitalMax - hdr.digitalMin);
dc = hdr.physicalMax - scalefac .* hdr.digitalMax;
% RECORD DATA REQUESTED
tmpdata = struct;
for recnum = 1:hdr.records
for ii = 1:hdr.ns
% Use a cell array for DATA because number of samples may vary
% from sample to sample
tmpdata(recnum).data{ii} = fread(fid,hdr.samples(ii),'int16') * scalefac(ii) + dc(ii);
end
end
record = zeros(hdr.ns, hdr.samples(1)*hdr.records);
for ii = 1:numel(hdr.label)
ctr = 1;
for jj = 1:hdr.records
try
record(ii, ctr : ctr + hdr.samples - 1) = tmpdata(jj).data{ii};
end
ctr = ctr + hdr.samples;
end
end
if assignToVariables
for ii = 1:numel(hdr.label)
try
eval(['assignin(''caller'',''',hdr.label{ii},''',record(ii,:))'])
end
end
end
end
fclose(fid);
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