Name
Abstract | ||
|---|---|---|
Sensory information, such as the tactile or proprioceptive signals, helps motor brain-machine interface (mBMI) work more naturally. Before applying sensory feedback, we need to explore if the neural activities are discriminative to different stimuli during a BMI task. Previous studies on the cortical discrimination are mainly focused on the rat whisker system. In this paper, we design a BMI task, where the freely behaving rat needs to maintain its position by poking a hole to receive the vibration stimulation on forepaws. Neural signals are collected synchronously from the corresponding sensory cortex when the rat is performing the task. Support Vector Machine (SVM) algorithm is implemented to evaluate the single trial classification of natural stimulus by neural ensembles. We find that the average classification accuracy reaches 80% over 3 rats, which suggests the vibration with different frequencies can be used as tactile feedback to the mBMI system. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/BioCAS.2014.6981799 | BioCAS |
Keywords | Field | DocType |
bioelectric potentials,biomechanics,biomedical equipment,biomedical measurement,brain-computer interfaces,data acquisition,feature extraction,feedback,haptic interfaces,man-machine systems,medical signal processing,neurophysiology,signal classification,support vector machines,touch (physiological),vibrations,BMI task design,SVM algorithm,average classification accuracy,cortical discrimination,discriminative neural activity,forepaw vibration stimulation,freely behaving rat position,mBMI system feedback,motor brain-machine interface,natural stimulus,neural ensemble,proprioceptive signal,rat natural vibration stimulation,rat whisker system,sensory cortex,sensory feedback,sensory information,single trial classification,support vector machine algorithm,synchronous neural signal collection,tactile feedback,tactile signal,vibration frequency variation,BMI task,cortical discrimination,vibration stimulation | Computer vision,Computer science,Speech recognition,Artificial intelligence,Vibration,Stimulation | Conference |
ISSN | Citations | PageRank |
2163-4025 | 0 | 0.34 |
References | Authors | |
2 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yan Cao | 1 | 14 | 4.30 |
| Fang Wang | 2 | 106 | 14.59 |
| Qiaosheng Zhang | 3 | 24 | 7.54 |
| Kedi Xu | 4 | 9 | 5.63 |