Department of Bioengineering, University of Texas at Arlington, Arlington, TX 76019, USA.
IEEE Trans Neural Syst Rehabil Eng. 2012 Jul;20(4):478-87. doi: 10.1109/TNSRE.2012.2197220. Epub 2012 Jun 5.
Clinical studies have shown that spinal or cerebral neurostimulation can significantly relieve pain. Current neurostimulators work in an open loop; hence, their efficacy depends on the patient's or physician's comprehension of pain. We have proposed and developed a real-time automatic recognition program with signal processing functions to detect action potentials. By using a wireless neurorecording module, spinal neuronal responses to mechanical stimuli (brush, pressure, and pinch) applied to rats' hind paws were recorded. Nociceptive spinal responses were detected and suppressed by our automated module through delivering electrical stimulation to the periaqueductal gray (PAG). The interspike intervals (ISIs) of the fired action potentials were used to distinguish among the three different mechanical stimuli. Our system was able to detect the neuronal activity intensities and deliver trigger signals to the neurostimulator according to a pre-set threshold in a closed-loop feedback configuration, thereby suppressing excessive activity in spinal cord dorsal horn neurons.
临床研究表明,脊髓或脑神经刺激可以显著缓解疼痛。目前的神经刺激器工作在开环模式下;因此,其疗效取决于患者或医生对疼痛的理解。我们提出并开发了一种具有信号处理功能的实时自动识别程序,以检测动作电位。通过使用无线神经记录模块,记录了大鼠后爪机械刺激(刷、压、捏)引起的脊髓神经元反应。我们的自动模块通过对中脑导水管周围灰质(periaqueductal gray,PAG)施加电刺激来检测和抑制伤害性脊髓反应。发射动作电位的尖峰间隔(interspike intervals,ISIs)可用于区分三种不同的机械刺激。我们的系统能够根据预设的阈值检测神经元活动强度,并根据闭环反馈配置向神经刺激器发送触发信号,从而抑制脊髓背角神经元的过度活动。