Farajidavar Aydin, Hagains Christopher E, Peng Yuan B, Behbehani Khosrow, Chiao J-C
Department of Bioengineering, University of Texas at Arlington, TX 76019, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:1535-8. doi: 10.1109/IEMBS.2010.5626830.
We implemented an integrated system that can acquire neuronal signals from spinal cord dorsal horn neurons, wirelessly transmit the signals to a computer, and recognize the nociceptive signals from three different mechanical stimuli (brush, pressure and pinch). Positive peak detection method was chosen to distinguish between signal spikes. The inter spike intervals (ISIs) were calculated from the identified action potentials (APs) and fed into a numerical array called cluster. When the sum of the ISIs in the cluster reached a critical level, the program recognized the recorded signals as nociceptive inputs. The user has the flexibility to tune both the cluster size and critical threshold for individual's need to reach optimization in pain signal recognition. The program was integrated with a wireless neurostimulator to form a feedback loop to recognize and inhibit nociceptive signals.
我们实现了一个集成系统，该系统可以从脊髓背角神经元获取神经信号，将信号无线传输到计算机，并识别来自三种不同机械刺激（轻刷、按压和捏压）的伤害性信号。选择正峰值检测方法来区分信号尖峰。从识别出的动作电位（APs）计算出峰间间隔（ISIs），并将其输入到一个名为聚类的数值数组中。当聚类中ISIs的总和达到临界水平时，程序将记录的信号识别为伤害性输入。用户可以灵活调整聚类大小和临界阈值，以满足个人需求，从而在疼痛信号识别中达到优化。该程序与无线神经刺激器集成，形成一个反馈回路，以识别和抑制伤害性信号。
