updates overground gait analysis

stanfordnmbl · Feb 15, 2024 · 9a5a424 · 9a5a424
1 parent 778640e
commit 9a5a424
Show file tree

Hide file tree

Showing 2 changed files with 36 additions and 22 deletions.
diff --git a/gait_analysis/function/gait_analysis.py b/gait_analysis/function/gait_analysis.py
@@ -746,32 +746,46 @@ def detect_correct_order(rHS, rTO, lHS, lTO):
             return True
 
         # Subtract sacrum from foot.
-        # It looks like the position-based approach will be more robust.
-        r_calc_rel_x = (
+        # It looks like the position-based approach will be more robust.        
+        r_calc_rel = (
             self.markerDict['markers']['r_calc_study'] - 
-            self.markerDict['markers']['r.PSIS_study'])[:,0]
-        r_toe_rel_x = (
+            self.markerDict['markers']['r.PSIS_study'])
+
+        r_toe_rel = (
             self.markerDict['markers']['r_toe_study'] - 
-            self.markerDict['markers']['r.PSIS_study'])[:,0]
-
+            self.markerDict['markers']['r.PSIS_study'])
+        r_toe_rel_x = r_toe_rel[:,0]
         # Repeat for left.
-        l_calc_rel_x = (
+        l_calc_rel = (
             self.markerDict['markers']['L_calc_study'] - 
-            self.markerDict['markers']['L.PSIS_study'])[:,0]
-        l_toe_rel_x = (
+            self.markerDict['markers']['L.PSIS_study'])
+        l_toe_rel = (
             self.markerDict['markers']['L_toe_study'] - 
-            self.markerDict['markers']['L.PSIS_study'])[:,0]
+            self.markerDict['markers']['L.PSIS_study'])
 
         # Identify which direction the subject is walking.
-        r_psis_x = self.markerDict['markers']['r.PSIS_study'][:,0]
-        r_asis_x = self.markerDict['markers']['r.ASIS_study'][:,0]
-        r_dir_x = r_asis_x-r_psis_x
-        position_approach_scaling = np.where(r_dir_x > 0, 1, -1)
-        # Adjust relative positions accordingly.
-        r_calc_rel_x *= position_approach_scaling
-        r_toe_rel_x *= position_approach_scaling
-        l_calc_rel_x *= position_approach_scaling
-        l_toe_rel_x *= position_approach_scaling
+        mid_psis = (self.markerDict['markers']['r.PSIS_study'] + self.markerDict['markers']['L.PSIS_study'])/2
+        mid_asis = (self.markerDict['markers']['r.ASIS_study'] + self.markerDict['markers']['L.ASIS_study'])/2
+        mid_dir = mid_asis - mid_psis
+        mid_dir_floor = np.copy(mid_dir)
+        mid_dir_floor[:,1] = 0
+        mid_dir_floor = mid_dir_floor / np.linalg.norm(mid_dir_floor,axis=1,keepdims=True)
+
+        # Dot product projections   
+        r_calc_rel_x = np.einsum('ij,ij->i', mid_dir_floor,r_calc_rel)
+        l_calc_rel_x = np.einsum('ij,ij->i', mid_dir_floor,l_calc_rel)
+        r_toe_rel_x = np.einsum('ij,ij->i', mid_dir_floor,r_toe_rel)
+        l_toe_rel_x = np.einsum('ij,ij->i', mid_dir_floor,l_toe_rel)
+
+        # Old Approach that does not take the heading direction into account.
+        # r_psis_x = self.markerDict['markers']['r.PSIS_study'][:,0]
+        # r_asis_x = self.markerDict['markers']['r.ASIS_study'][:,0]
+        # r_dir_x = r_asis_x-r_psis_x
+        # position_approach_scaling = np.where(r_dir_x > 0, 1, -1)        
+        # r_calc_rel_x = r_calc_rel[:,0] * position_approach_scaling
+        # r_toe_rel_x = r_toe_rel[:,0] * position_approach_scaling
+        # l_calc_rel_x = l_calc_rel[:,0] * position_approach_scaling
+        # l_toe_rel_x = l_toe_rel[:,0] * position_approach_scaling
 
         # Detect peaks, check if they're in the right order, if not reduce prominence.
         # the peaks can be less prominent with pathological or slower gait patterns
@@ -901,5 +915,4 @@ def detect_correct_order(rHS, rTO, lHS, lTO):
                       'eventNamesContralateral':['TO','HS'],
                       'ipsilateralLeg':leg}
 
-        return gaitEvents
-
+        return gaitEvents
diff --git a/gait_analysis/function/handler.py b/gait_analysis/function/handler.py
@@ -88,7 +88,8 @@ def handler(event, context):
         gait[leg] = gait_analysis(
             sessionDir, trial_name, leg=leg,
             lowpass_cutoff_frequency_for_coordinate_values=filter_frequency,
-            n_gait_cycles=n_gait_cycles)
+            n_gait_cycles=n_gait_cycles, gait_style='overground',
+            trimming_start=0, trimming_end=0.5)
         gait_events[leg] = gait[leg].get_gait_events()
 
     # Select last leg.