feat: iterate on SsfStepDetector
* 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)
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@@ -6,6 +6,7 @@
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#include <limits>
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#include <cmath>
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#include <cassert>
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#include <iostream>
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static std::vector<double> make_ones(size_t sw) {
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std::vector<double> ones;
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@@ -33,21 +34,26 @@ SsfStepDetector::SsfStepDetector(size_t len_refr) :
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LEN_TH_WIN((size_t) (3.0 * FPS)), // subsequent window length for ssf_threshold
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num_samples(0),
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ssf_threshold(std::numeric_limits<double>::infinity()),
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ssf_threshold_nm1(std::numeric_limits<double>::infinity()),
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f_ssf_threshold_smoothing(6, 0, 0, make_ones(6)),
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len_refr(len_refr), n_refr(0), is_refr(false),
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nm1_ssf(0.0),
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ssf_nm1(0.0),
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f_ssf_mean(LEN_TH_WIN, 0, 0, make_ones(LEN_TH_WIN))
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{
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assert (LEN_INIT >= LEN_TH_WIN && "LEN_INIT < LEN_TH_WIN, check normalization of initial ssf_threshold");
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}
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double SsfStepDetector::filter(double val) {
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double ssf_mean = f_ssf_mean.filter(val) / ((double) LEN_TH_WIN);
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double SsfStepDetector::filter(double ssf) {
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double ssf_mean = f_ssf_mean.filter(ssf) / ((double) LEN_TH_WIN);
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double rv = 0.0;
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if (num_samples >= LEN_INIT) {
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// initial and subsequent threshold setting.
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ssf_threshold = 3.0 * ssf_mean * 0.99; // see Zong 2003 for the magic numbers
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}
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// threshold crossing detection
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bool is_txing = nm1_ssf < ssf_threshold && val >= ssf_threshold;
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// 'is_prev_lower' fixes a glitch where a falling threshold leads to undetected crossings
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bool is_prev_lower = ssf_nm1 < ssf_threshold || ssf_nm1 < ssf_threshold_nm1;
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bool is_cur_higher = ssf >= ssf_threshold;
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bool is_txing = is_prev_lower && is_cur_higher;
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// refractory period reset
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if (num_samples - n_refr >= len_refr) is_refr = false;
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// transition and not in refractory period? detected a step.
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@@ -56,7 +62,24 @@ double SsfStepDetector::filter(double val) {
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is_refr = true;
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n_refr = num_samples;
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}
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nm1_ssf = val;
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if (num_samples == LEN_INIT) {
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// initial threshold setting
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ssf_threshold = 3.0 * ssf_mean * 0.99; // see Zong 2003 for the magic numbers
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//std::cerr << "before prime()" << std::endl;
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f_ssf_threshold_smoothing.prime(ssf_threshold);
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} else if (num_samples > LEN_TH_WIN) {
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//std::cerr << "adaptive threshold setting" << std::endl;
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// adaptive threshold setting
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// +2 is half the window size
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// TODO: param upon SsfFilter.upslope_width/2 instead of hardcoding -- also f_ssf_threshold_smoothing(), nb. should be even number
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if (num_samples == n_refr + 2) {
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//std::cerr << "setting adaptive threshold setting" << std::endl;
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ssf_threshold_nm1 = ssf_threshold;
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// the ssf peak comes 3 samples (half-window + 1 sample) after the crossing
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ssf_threshold = f_ssf_threshold_smoothing.filter(ssf) / ((double) f_ssf_threshold_smoothing.size()) * 0.6;
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}
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}
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ssf_nm1 = ssf;
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num_samples++;
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return rv;
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}
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