Problem finding "valleys" in signal

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Kcire L
Kcire L 2023-5-18
回答： Star Strider 2023-5-18
Hello,
I am using the findpeaks function to find the valleys in a signal, but it is not consistent and was wondering if there was a better way of doing this.
My code is below along with an image of a "missed" valley around the 8 second mark. Any help on this would be greatly appreciated.
[yfft_, freqvec_, yfft_dB_, freq_res] = calcFFT(temp_snip, 'hamming', Fs*100, Fs);
[fft_pks fft_locs] = findpeaks(yfft_, 'MinPeakHeight', 0.004);
BreathrateHz = freqvec_(fft_locs(2));
RespRate = (BreathrateHz * snippp)/2
%Get valleys
inverted_snip = max(temp_snip) - temp_snip;
snip_lo = max(inverted_snip);
[v1, vv] = findpeaks(inverted_snip, "MinPeakDistance", Fs*((RespRate)/2), "MinPeakHeight", snip_lo *.85); %-(Fs*BreathInstance_error))/5);

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回答（3 个）

Steven Lord
Steven Lord 2023-5-18
Have you tried using islocalmin on your original data rather than findpeaks on the "flipped" data?
Image Analyst
Image Analyst 2023-5-18
Ran in:
Is it possible your MinPeakDistance is too large?
You could also try to smooth your data with movmean or sgolayfilt before using findpeaks
help sgolayfilt
SGOLAYFILT Savitzky-Golay Filtering. SGOLAYFILT(X,ORDER,FRAMELEN) smooths the signal X using a Savitzky-Golay (polynomial) smoothing filter. The polynomial order, ORDER, must be less than the frame length, FRAMELEN, and FRAMELEN must be odd. The length of the input X must be >= FRAMELEN. If X is a matrix, the filtering is done on the columns of X. Note that if the polynomial order ORDER equals FRAMELEN-1, no smoothing will occur. SGOLAYFILT(X,ORDER,FRAMELEN,WEIGHTS) specifies a weighting vector WEIGHTS with length FRAMELEN containing real, positive valued weights employed during the least-squares minimization. If not specified, or if specified as empty, WEIGHTS defaults to an identity matrix. SGOLAYFILT(X,ORDER,FRAMELEN,[],DIM) and SGOLAYFILT(X,ORDER,FRAMELEN,WEIGHTS,DIM) operate along the dimension DIM. % Example: % Smooth the mtlb signal by applying a cubic Savitzky-Golay filter % to data frames of length 41. load mtlb % Load data smtlb = sgolayfilt(mtlb,3,41); % Apply 3rd-order filter plot([mtlb smtlb]); legend('Original Data','Filtered Data'); See also SGOLAY, MEDFILT1, FILTER Documentation for sgolayfilt doc sgolayfilt
Star Strider
Star Strider 2023-5-18
Ran in:
I prefer using 'MinPeakProminence' instead of 'MinPeakHeight' since that is usually more robust.
t = linspace(0, 10);
y = 0.03*sin(2*pi*t*0.7) + 0.06 + randn(size(t))/100;
[pks,locs] = findpeaks(-y, 'MinPeakDistance', 10, 'MinPeakProminence',0.025);
figure
plot(t, y)
hold on
plot(t(locs), -pks, 'xr')
hold off
Adjust the 'MinPeakProminence' value to get the desired result with your data.
.

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