| Title |
Neural Interface Technology for Rehabilitation: Exploiting and Promoting Neuroplasticity
|
|---|---|
| Published in |
Physical medicine and rehabilitation clinics of North America, February 2010
|
| DOI | 10.1016/j.pmr.2009.07.003 |
| Pubmed ID | |
| Authors | |
| Abstract |
This article reviews neural interface technology and its relationship with neuroplasticity. Two types of neural interface technology are reviewed, highlighting specific technologies that the authors directly work with: (1) neural interface technology for neural recording, such as the micro-ECoG BCI system for hand prosthesis control, and the comprehensive rehabilitation paradigm combining MEG-BCI, action observation, and motor imagery training; (2) neural interface technology for functional neural stimulation, such as somatosensory neural stimulation for restoring somatosensation, and non-invasive cortical stimulation using rTMS and tDCS for modulating cortical excitability and stroke rehabilitation. The close interaction between neural interface devices and neuroplasticity leads to increased efficacy of neural interface devices and improved functional recovery of the nervous system. This symbiotic relationship between neural interface technology and the nervous system is expected to maximize functional gain for individuals with various sensory, motor, and cognitive impairments, eventually leading to better quality of life. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 18 | 3% |
| Germany | 5 | <1% |
| United Kingdom | 3 | <1% |
| Japan | 2 | <1% |
| Italy | 2 | <1% |
| India | 2 | <1% |
| Hong Kong | 2 | <1% |
| Switzerland | 2 | <1% |
| Austria | 2 | <1% |
| Other | 5 | <1% |
| Unknown | 491 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 99 | 19% |
| Student > Ph. D. Student | 89 | 17% |
| Student > Master | 69 | 13% |
| Student > Bachelor | 44 | 8% |
| Student > Doctoral Student | 31 | 6% |
| Other | 93 | 17% |
| Unknown | 109 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 96 | 18% |
| Medicine and Dentistry | 76 | 14% |
| Neuroscience | 67 | 13% |
| Agricultural and Biological Sciences | 43 | 8% |
| Psychology | 34 | 6% |
| Other | 74 | 14% |
| Unknown | 144 | 27% |