Revert to window-mean gravity

src/phyphox_pipeline.py

@@ -495,23 +495,26 @@ def process_phyphox_files(
     if duration > 60:
         warnings.append(f"Long recording ({duration:.0f} s) — {n_windows} windows extracted.")
 
-    # Apply noise filters and gravity separation to the FULL signal before
-    # windowing — this is the UCI pipeline order. The 0.3 Hz LP filter needs
-    # the full continuous signal to settle; applying it per-window (128 samples)
-    # produces transient artefacts because 0.3 Hz requires ~167 samples to settle.
+    # Apply noise filters to the full signal before windowing.
     acc_50  = _butter_lp(_median_filt(acc_50), cutoff=20.0)
     gyro_50 = _butter_lp(_median_filt(gyro_50), cutoff=20.0)
-    grav_full = _butter_lp(acc_50, cutoff=0.3)
-    body_full = acc_50 - grav_full
 
     all_features = []
     dt = 1.0 / FS
 
     for start in range(0, n - WINDOW + 1, STEP):
         end = start + WINDOW
-        body = body_full[start:end]   # (128, 3)
-        grav = grav_full[start:end]   # (128, 3)
-        gw   = gyro_50[start:end]     # (128, 3)
+        aw = acc_50[start:end]   # (128, 3)
+        gw = gyro_50[start:end]  # (128, 3)
+
+        # Gravity separation: window mean as gravity estimate.
+        # The UCI pipeline used a 0.3 Hz LP on a full continuous recording.
+        # That filter needs ~167 samples to settle; a 10-second clip gives only
+        # ~500 samples total, so the filter corrupts all but the central window.
+        # The window mean is equivalent for symmetric activities (oscillations
+        # cancel over a stride cycle) and exact for static activities.
+        grav = np.tile(aw.mean(axis=0), (WINDOW, 1))
+        body = aw - grav
 
         # Jerk: finite difference → (127, 3)
         body_jerk = np.diff(body, axis=0) / dt