The overall goal of the following experiment is to illustrate a generalized technique for synchronizing multiple data streams that are recorded during human biomechanical studies. This is achieved by using electromyographic and motion capture signals to generate an analog synchronization event that can be independently recorded by two or more systems. As a second step, simple circuit components can be designed, which transform this event into signals appropriate for each recording device.
Next, use analysis software to temporarily align the synchronization events across the independently recorded signals in order to synchronize all of the signals. The results show that several biomechanical signals can be temporarily aligned within the sampling frequencies of the respective data recording systems, which enable collection of a rich experimental data set of human naturalistic movement to study neuromuscular control. There are multiple complex questions in the fields of motor control and biomechanics that can best be answered by studying natural human movement in a laboratory setting.
Here we describe the method of using virtual reality to define behavioral tasks during which several physiological signals are recorded simultaneously. The advantage of a virtual reality based experimental setup over existing methods like hardware-based behavioral rigs is that it can be adapted very rapidly to different experiments as well as to the unique anatomy of individual participants. During behavioral experiments, it is common to simultaneously record several signals that quantify behavior such as electromyography and motion capture.
Our method provides a solution to the problem of temporal alignment of these signals by using a custom synchronization unit that is compatible across multiple manufacturers. Begin by making all necessary electrical connections between the EMG equipment, including amplifiers, pre amplifiers, sensor wires, and sensor pads according to the manufacturer's specifications. Clean each electrode site to ensure consistent and low electrode to skin impedance values.
Then instruct the subject to perform isometric contractions of the individual muscles of interest, affix the EMG electrodes over the palpated location of muscle contraction. Keeping in mind the orientation of the active sites along the muscle fibers. Attach the ground electrode to the skin over the C seven vertebra.
Next to test the signal quality, inspect the amplified EMG signals on the computer as the subject contracts each muscle of interest. Finally, decrease amplification gains if EMG signals saturate during muscle contractions that are required for the behavioral task. Begin by calibrating the motion tracking cameras according to the manufacturer's instructions.
Tape active LED sensors to bony landmarks near the arm joints, and other anatomical points of interest such as near the finger, wrist, shoulder and chest. Attach another LED sensor to the virtual reality or VR headset to set the viewpoint in the virtual environment. Then connect each LED to a wiring harness that is attached to the wireless driver unit.
Turn on the driver unit and ensure proper illumination of all LEDs. Finally, position the synchronization LED in a location away from the subject, but within a clear view of the motion capture cameras. First, calibrate the transcranial magnetic stimulation or TMS device and software to allow for accurate coil placement.
To do this, coregister the TMS coils with anatomical landmarks such as the NAS preauricular points and nose tip. Using a calibration pointer. Then perform hotspot techniques to locate TMS sensitive regions on the cortex that produce the greatest amplitude for motor evoked potentials or meps.
With the lowest amplitude of stimulation, record the location of the best stimulation site on the subject's scalp with the calibrated stereotaxic registration equipment and software. Finally, measure the subject's threshold by lowering the amplitude of stimulation at the selected location until meps of at least 50 microvolts are evoked 50%of the time. First, set up the VR environment for the behavioral task according to the manufacturer's protocol.
By using commercial VR software that is compatible with the headset and motion tracking system program. Digital outputs through the parallel port for synchronization and marking of specific events of interest. Connect the VR output to the synchronization circuit as well as other equipment to be synchronized by using cables with matching connectors.
Inform the about the requirements of the task he or she will be performing in vr. Ask the subject to point to spherical targets when they appear in his or her field of view. Once the subject understands the task and has a chance to practice it, start the recording of EMG motion capture data and synchronization signals during a single VR synchronization trial.
The software triggers the EMG equipment to record signals that illustrate neuromuscular activity that occurred during movements of the upper limb. It also triggers the motion capture equipment to record continuous movement data. This signal can be used to synchronize the EMG and motion capture data.Here.
The average angular kinematics and dynamics and the associated continuous and instantaneous neuromuscular activity across 24 trials are shown for a single task. These multi-dimensional data sets provided by the virtual reality will enable researchers to investigate specific human motor control mechanisms. After watching this video, you should have a general understanding of how to synchronize multiple data streams that can be recorded during human movement Experiments such as EMG and motion capture, This procedure can be expanded to include additional systems such as electroencephalography.
Moreover, electrical stimulation of peripheral nerves can also be used to evaluate the contribution of sensory feedback to motor control After its development. This technique paved the way for neuroscientists to explore changes in the neural controlled movement in individuals with movement disorders such as stroke or spinal cord injury.
