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feat: iterate on SsfStepDetector

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* use SSF signal instead of accelerometer signal
* use higher BEAT_CORR_THR_{12} for SSF signal
* add absolute SSF_THRESHOLD to ignore small accelero bumps
* compute ssf_threshold according to detected SSF peaks, not the mean (more robust vs. noise)
This commit is contained in:
David Madl
2026-03-11 20:47:53 +01:00
parent 95d1fee44d
commit 90f8943930
8 changed files with 103 additions and 27 deletions
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10
google-tests/test2.cpp
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@@ -190,26 +190,36 @@ TEST(HelloTest, Zong_SSF_Stage3) {
std::vector a {1. , -4.83056552, 9.33652742, -9.02545247, 4.36360803, -0.8441171};
IirFilter filter(b, a);
//std::cerr << "before stage 1" << std::endl;
// Stage 1: high-pass
auto y = apply_filter(filter, signal);
Filt f_neg(1, 0, 0, std::vector {-1.0});
auto y_neg = apply_filter(f_neg, y);
//std::cerr << "before stage 2" << std::endl;
// Stage 2: sum slope function
const size_t upslope_width = 4;
SsfFilter f_ssf(upslope_width);
auto ssf = apply_filter(f_ssf, y_neg);
//std::cerr << "before stage 3" << std::endl;
// Stage 3: threshold detection
const size_t len_refr = (size_t) (FPS / (MAX_BPM / 60));
DebugSsfStepDetectorThreshold f_ssd_thr(len_refr);
auto ssf_threshold = apply_filter(f_ssd_thr, ssf);
//std::cerr << "before writing results 1 and doing step detection" << std::endl;
npy_save("test2/ssf_t2_ssf_threshold.npy", ssf_threshold);
SsfStepDetector f_ssd(len_refr);
auto steps = apply_filter(f_ssd, ssf);
//std::cerr << "before writing results 2" << std::endl;
npy_save("test2/ssf_t2_steps.npy", steps);
}