The overall goal of the following experiment is to extend the concept of a mobile brain imaging framework to enable study of human brain body dynamics in a wide range of locomotive tasks. This is achieved by first placing E-E-G-E-M-G and motion capture sensors on a human subject as a second step. The three data collection systems are synchronized with custom software and a push button trigger device, which provides a timelock E-E-G-E-M-G and motion capture data set.
Next, the subject completes nine specific locomotive tasks within four different environments. In order to capture brain body dynamics during a variety of movements, the results show brain activity measured via EEG during the locomotive tasks. This method is can help to answer key questions in the field of neuroprosthetics and brain machine interfaces.
For example, is it possible to extract useful information about GA kinematics or surface EMG patterns from a scalp EEG? The main advantage of this technique over existing methods is that we can wirelessly collect E-E-G-E-M-G and motion capture data using a mobile setup, which allows us to explore more motor tasks and environments compared to traditional data collection techniques. The implications of these techniques also extend to the movement disorders and rehabilitation medicine because basically these protocols inform us about the changes in brain activity and the adaptation of the body.
My graduate students will now demonstrate the placement of the sensors or JI osir will show how to place the EMG sensors on our volunteer today. Kevin Nathan, with the assistance of John, he who will be placing the EEG sensors on his scalp To begin this protocol. First, record the subject's height, weight, and age.
Then adjust the treadmill speed to match the subject's preferred walking speed. Next, measure the distance between the nasion and Inion using a felt tip pen. Mark 10%of the distance as a reference for aligning the cap and mark the midpoint of the distance as the vertex of the head.
Now place the EEG cap on the subject and align it to the reference landmarks. Align the midpoint between the FP one and FP two electrodes with the 10%distance mark and align the CZ electrode with the marked vertex. Secure the cap by strapping below the chin.
Next, starting with ground and reference electrodes, use a small syringe to inject electrolyte gel in each electrode until the impedance of each measures below 25 kilo ohms as indicated by the electrode LED turning green. Finally, connect the electrodes to the wireless transmitter for the data acquisition system. Next, prepare for surface electromyography by first shaving the skin and then cleaning with an isopropyl alcohol pad.
Then place an electrode on each of eight prepared sites for per leg for the tali, anterior vastus, lateralis, biceps, fems, and gastroc. Finally, please EMG ground electrodes on the left or right wrist and connect all EMG electrodes to the EMG data logging unit. To set up for motion capture.
First place the mark sensors on the subject using Velcro straps or double-sided tape. Attach the sensors at the locations listed here. Then have the subject step onto the treadmill and attach a safety harness as seen here prior to data collection.
Examine the EEG and EMG signals to verify correct electrode placement, electrode connection, and data transmission. Then begin data collection by running the c plus plus console application. Press the manual trigger push button to initiate EMG recording and give an audio cue a beep.
To start the experiment, instruct the subject to remain in quiet stance for 30 seconds. Then after 30 seconds, push the trigger button to initiate walking. The treadmill should slowly accelerate to the subject's preselected speed.
Have the subject walk for five minutes. After five minutes, push the trigger button to initiate the walk to stand transition by slowly stopping the treadmill. After coming to a stop, the subject should remain standing for 30 seconds.
Now, press the queue button to stop the data collection trial and save the data. Repeat this experiment with three visual conditions, including a black. at a distance in front of the subject to focus on realtime observation of the legs on a video monitor and avoidance of a diagonal line on the treadmill.
Next, move on to the walking arena. The walking arena should be set up by placing five sets of infrared proximity sensors, cones, and television screens as seen. Here, position the subject at the start of the arena walking loop and begin data collection as previously described.
Now, push the trigger button to initiate the walking experiment. At the time the trigger is given. The first directional arrow is displayed on the screen opposite the subject.
If a right arrow or a left arrow is observed, the subject should exit the set of cones at the entrance, turn 90 degrees in that direction, complete the loop and return to the entrance cones. If an up arrow is observed, the subject should continue straight out of the entrance cones. A manual trigger and direction arrow should then be given When the subject reaches approximately two meters from the IR sensors.
The subject should then proceed through the first set of IR sensors and then make the corresponding 90 degree turn to complete the loop. Returning to the entrance cones during walking, the experimenter should follow the subject at a distance of approximately three to five meters with the host PC on a wheeled cart To assure wireless signal quality, the subject should continue walking when he or she reaches the entrance cones. After completing a single loop, the sequence should be repeated with random ordering of arrows until three loops have been completed for each initial arrow.
After completing the required number of loops, push the manual trigger button to signal transition to standing. The subject should stand quietly for 30 seconds. Then terminate data collection by pressing the cue button on the host pc.
Position a chair behind the subject and begin data collection. The subject should stand quietly for 15 seconds at the start of data collection. After 15 seconds, press the manual trigger button.
After hearing the cue, the subject should transition from standing to sitting, posture, holding, sitting position until the next audio queue. Wait a random interval of five to 15 seconds. Then press the manual trigger to give a cue for sit to stand transition.
Have the subject hold the standing posture until the next audio queue. Repeat this procedure until 10. Complete stand to sit and sit to stand.
Maneuvers are complete, after which the subject should stand quietly for 15 seconds. Then terminate data collection by pressing the cue button. Next, repeat the stand to sit protocol for self-initiated stand to sit and sit to stand transition.
This time rather than giving the subject a trigger to transition, have the subject initiate the transfer on their own until 10 of each maneuver is complete. For hallway walking position the subject and data collection cart in the middle of a one eighth mile straight hallway. Begin data collection as with the treadmill walking experiments.
After the initial 32nd resting period, give a manual trigger or beep to the subject to initiate walking. Have the subject walk continuously for five minutes. When the subject reaches within 10 meters of the hallway end, he or she should self-initiate a U-turn and continue walking in the opposite direction.
After five minutes, push the manual trigger button to stop walking. The subject should stand quietly for 30 seconds while looking straight ahead. Then terminate data collection election.
Next, begin a second hallway experiment. After a random time interval of walking between 20 to 40 seconds long, give a manual trigger and audio cue to have the subject stop walking. The subject should then remain standing for a short, random duration of five to 15 seconds.
Then push the manual trigger button to have the subject resume walking. Repeat these steps until 10 cycles of stop start are complete, and then terminate. Data collection representative results from 10 seconds of treadmill walking are shown here.
The top panel show 64 channel raw EEG data with channel name From the 10 20 International Convention, the middle panel shows acceleration in the vertical direction from 11 mark sensors. The bottom panel shows eight channel raw EMG. This figure shows representative data from one loop of walking during the arena.
One protocol vertical black bars indicate triggers. The first trigger is from the push button presenting the right arrow. The last four are from IR sensors, IR one through IR four as the subject traverses the loop, and here we see sample data from stand to Sit and sit to stand transition.
EEG acceleration and EMG data are presented as in the first figure. Vertical bars indicate manual triggers to initiate standing and sitting respectively. Finally, this figure shows sample data from the transition from standing to walking and walking to standing during the hallway.
Walking task. Vertical bars indicate manual triggers and audio cues to begin and stop walking respectively. It is important to remember that EEG sensors and the EMG sensors are sensitive to the motion artifacts, so we should assure that the sensors are secure and safely attached to this subject.
Following this procedure, you can apply other techniques such as independent component analysis or linear regression to isolate the electro cortical signals from the artifacts, allowing you to extract limb kinematics or EMG profiles from the EEG data. This technique will enable the neural interface community to answer questions about how the brain relates to movement and movement intent, and it will provide a means to extract information about gait from a scalp EEG.
