Merge pull request #20 from stanfordnmbl/dev

Add info to metrics

gait_analysis/function/handler.py

@@ -111,6 +111,14 @@ def handler(event, context):
         gait_scalars[key]['multiplier'] = 1
 
     gait_scalars['step_width']['multiplier'] = 100 # cm
+
+    # %% Info about metrics.
+    gait_scalars['gait_speed']['info'] = "Gait speed is computed by dividing the displacement of the center of mass by the time it takes to move that distance. A speed larger than 1.12 m/s is considered good."
+    gait_scalars['step_width']['info'] = "Step width is computed as the average distance between the ankle joint centers in the mediolateral direction during 40-60% of the stance phase. A step width between 4.3 and 7.4 times the subject's height is considered good."
+    gait_scalars['stride_length']['info'] = "Stride length is computed as the distance between the calcaneus positions at the beginning and end of the gait cycle. A stride length larger than 0.45 times the subject's height is considered good."
+    gait_scalars['cadence']['info'] = "Cadence is computed as the number of gait cycles (left and right) per minute. A cadence larger than 100 is considered good."
+    gait_scalars['double_support_time']['info'] = "Double support time is computed as the duration when both feet are in contact with the ground. A double support time smaller than 35% of the gait cycle is considered good."
+    gait_scalars['step_length_symmetry']['info'] = "Step length symmetry is computed as the ratio between the right and left step lengths. A step length symmetry between 90 and 110 is considered good."
 
     # %% Thresholds.
     metadataPath = os.path.join(sessionDir, 'sessionMetadata.yaml')
@@ -155,6 +163,7 @@ def handler(event, context):
                                    gait_scalars[scalar_name]['decimal'])
         metrics_out[scalar_name]['label'] = scalar_labels[scalar_name]
         metrics_out[scalar_name]['value'] = vertical_values
+        metrics_out[scalar_name]['info'] = gait_scalars[scalar_name]['info']
         if scalar_name in scalar_reverse_colors:
             # Margin zone (orange) is 10% above threshold.
             metrics_out[scalar_name]['colors'] = ["green", "yellow", "red"]

treadmill_gait_analysis/function/handler.py

@@ -110,6 +110,14 @@ def handler(event, context):
         gait_scalars[key]['multiplier'] = 1
 
     gait_scalars['step_width']['multiplier'] = 100 # cm
+
+    # %% Info about metrics.
+    gait_scalars['gait_speed']['info'] = "Gait speed is computed by dividing the displacement of the center of mass by the time it takes to move that distance. A speed larger than 1.12 m/s is considered good."
+    gait_scalars['step_width']['info'] = "Step width is computed as the average distance between the ankle joint centers in the mediolateral direction during 40-60% of the stance phase. A step width between 4.3 and 7.4 times the subject's height is considered good."
+    gait_scalars['stride_length']['info'] = "Stride length is computed as the distance between the calcaneus positions at the beginning and end of the gait cycle. A stride length larger than 0.45 times the subject's height is considered good."
+    gait_scalars['cadence']['info'] = "Cadence is computed as the number of gait cycles (left and right) per minute. A cadence larger than 100 is considered good."
+    gait_scalars['double_support_time']['info'] = "Double support time is computed as the duration when both feet are in contact with the ground. A double support time smaller than 35% of the gait cycle is considered good."
+    gait_scalars['step_length_symmetry']['info'] = "Step length symmetry is computed as the ratio between the right and left step lengths. A step length symmetry between 90 and 110 is considered good."
 
     # %% Thresholds.
     metadataPath = os.path.join(sessionDir, 'sessionMetadata.yaml')
@@ -154,6 +162,7 @@ def handler(event, context):
                                    gait_scalars[scalar_name]['decimal'])
         metrics_out[scalar_name]['label'] = scalar_labels[scalar_name]
         metrics_out[scalar_name]['value'] = vertical_values
+        metrics_out[scalar_name]['info'] = gait_scalars[scalar_name]['info']
         if scalar_name in scalar_reverse_colors:
             # Margin zone (orange) is 10% above threshold.
             metrics_out[scalar_name]['colors'] = ["green", "yellow", "red"]