Feat: 增加新控制参数，增加数据记录，删除患者姓名

.vscode/launch.json

@@ -12,12 +12,13 @@
             "console": "integratedTerminal",
             "cwd": "${workspaceFolder}/backend",
             "justMyCode": true,
-            "args": ["--subj", "ylj", 
+            "args": ["--subj", "XW01", 
             "--n-trials", "15", 
             "--com", "COM3", 
             "-fm", "flex", 
             "-vfr", "1.0", 
-            "--model-path", "./static/models/ylj/baseline_rest+cylinder_11-16-2023-16-38-32.pkl"]
+            "-scth", "0.75",
+            "--model-path", "./static/models/XW01/baseline_rest+cylinder_11-16-2023-16-38-32.pkl"]
         },
         {
             "name": "Python: 当前文件",

backend/general_grasp_training.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 """
 This experiment was created using PsychoPy3 Experiment Builder (v2023.2.3),
-    on Mon Nov 20 16:11:17 2023
+    on Mon Nov 20 21:55:44 2023
 If you publish work using this script the most relevant publication is:
 
     Peirce J, Gray JR, Simpson S, MacAskill M, Höchenberger R, Sogo H, Kastman E, Lindeløv JK. (2019) 
@@ -88,6 +88,13 @@ def parse_args():
         type=float
     )
     parser.add_argument(
+        '--state-change-threshold',
+        '-scth',
+        dest='state_change_threshold',
+        help='Threshold for HMM state change',
+        type=float
+    )
+    parser.add_argument(
         '--model-path',
         dest='model_path',
         help='Path to model file',
@@ -111,7 +118,9 @@ trigger = TriggerNeuracle()
 hand_device = FuboPneumaticFingerClient({'port': args.com})
 
 # build bci controller
-controller = Controller(args.virtual_feedback_rate, args.model_path, state_change_threshold=0.8)
+controller = Controller(args.virtual_feedback_rate, 
+                        args.model_path, 
+                        state_change_threshold=args.state_change_threshold)
 # Run 'Before Experiment' code from decision
 
 
@@ -872,6 +881,11 @@ def run(expInfo, thisExp, win, inputs, globalClock=None, thisSession=None):
             data_from_buffer = receiver.get_trial_data(clear=False)
             decision = controller.step_decision(data_from_buffer, current_true_label)
             decision_buffer.append(decision)
+            
+            # write decision to data
+            thisExp.addData('decision.class', decision)
+            if controller.real_feedback_model is not None:
+                thisExp.addData('decision.prob', controller.real_feedback_model.probability)
             # using non-slip timing so subtract the expected duration of this Routine (unless ended on request)
             if routineForceEnded:
                 routineTimer.reset()

backend/training.py

@@ -107,7 +107,7 @@ def model_saver(model, model_path, model_type, subject_id, event_id):
 
 if __name__ == '__main__':
     # TODO: argparse
-    subj_name = 'ylj'
+    subj_name = 'XW01'
     model_type = 'baseline'
     # TODO: load subject config
 

backend/validation.py

@@ -101,7 +101,7 @@ def _event_to_stim_channel(events, time_length):
 
 if __name__ == '__main__':
     # TODO: argparse
-    subj_name = 'ylj'
+    subj_name = 'XW01'
     # TODO: load subject config
 
     data_dir = f'./data/{subj_name}/'