545.6K Views
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05:12 min
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September 18th, 2017
DOI :
September 18th, 2017
•0:05
Title
0:49
Virtual Reality Setup
2:00
Experiment and Analysis
3:26
Results: Left-hand Performance Gains Higher Relative to Observation or Right Hand Training
4:09
Conclusion
副本
The overall goal of this training set-up using virtual reality is to increase performance gains on a simple motor skill in a limb in the absence of its voluntary physical movement. This method can help answer key questions in the field of motor skill learning such as the role of sensory perception in skill acquisition. The main advantage of this technique is that it allows full control of visual and proprioceptive input during training.
The implications of this technique may extend towards therapy of upper limb hemiparesis because control of the healthy hand is used to train the affected hand. Demonstrating the procedure will be Shiri, a research assistant from my laboratory. Begin by escorting the subject to the testing chair.
And have them sit down with their hands forward and palms facing down. Place the virtual reality or VR headset with the head-mounted 3D camera on the subject to provide online visual feedback of the real environment. Ensure the video from the camera is presented in the VR headset.
Next, place motion-sensing MR-compatible gloves onto the subject's hands which allow online monitoring of individual finger flexure in each hand. Ensure that the subject only sees the virtual hands when looking down to the location of where their real hands would be. Then place the subject's hands in a specialized motion control device, and strap the right and left fingers individually to the pistons.
Make sure the subjects can move their right hand fingers separately. Finally, verify that voluntary movement of the left hand fingers is restricted by asking the subjects to move their left hand while it is located inside the device. Begin by unstrapping the subject's hands from the motion control device.
Then have the subjects perform a uni-manual five-digit finger sequence movement repeatedly as accurately and rapidly as possible with the non-training hand for 30 seconds. Next, strap the hands of the subject to the motion control device. Then cue the subject to the upcoming training stage to perform the sequence of finger movements with the active hand in a self-paced manner.
Following the evaluation, analyze the data in a customized software which records the hand configuration from the gloves during the experiment. Click Session Left File, and choose the files created in the left-hand capture folder under the relevant subject. Then click Session Right File, and choose the files created in the right-hand capture folder under the relevant subject.
Next click Play session to replay and visualize the virtual hand movements during each evaluation stage based on the data recorded from the sensors in the motion-tracking glove. Finally for each evaluation step and each subject separately, count the number of complete and correct finger sequences performed with the non-trained hand and then calculate the performance gains index. Left hand performance gains following training in the cross education or CE, and visual manipulation condition, were significantly higher relative to the gains obtained following training by left hand observation, or following right hand training with congruent visual feedback which is the traditional form of CE.In another set of healthy subjects where three training types were implemented, results indicated that the addition of passive left hand finger movement to the visual manipulation yielded the highest left hand performance gains that were significantly higher than performance gains following the visual manipulation alone.
Once mastered, this technique can be done in about 20 minutes if it is performed properly. While attempting this procedure, it's important to provide adequate breaks between training sessions. Since the gloves and the set-up are MRI compatible, this procedure can be performed inside an MRI scanner in order to answer additional questions about the underlying neuro mechanisms involved.
After its development, this technique paved the way for researchers in the field of motor skill learning to explore manipulations of sensory input, both visual and proprioceptive in the process of skill acquisition. After watching this video, you should have a good understanding of how to train a limb in the absence of its voluntary physical movement. Don't forget that working with a passive movement device can be tiring, therefore breaks during training should be provided.
We describe a novel virtual-reality based setup which exploits voluntary control of one hand to improve motor-skill performance in the other (non-trained) hand. This is achieved by providing real-time movement-based sensory feedback as if the non-trained hand is moving. This new approach may be used to enhance rehabilitation of patients with unilateral hemiparesis.
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