Graupe Daniel, Basu Ishita, Tuninetti Daniela, Vannemreddy Prasad, Slavin Konstantin V
University of Illinois at Chicago, Chicago, IL 60607-7053, USA.
Neurol Res. 2010 Nov;32(9):899-904. doi: 10.1179/016164110X12767786356354. Epub 2010 Aug 16.
We present patient test outcomes to show that on-off control of deep brain stimulation sequences in essential tremor patients is achievable in a self-adaptive manner via non-invasive surface-electromyography, to prevent tremors in these patients.
In our study, an essential tremor patient, who underwent bilateral deep brain stimulation implantation 8 years earlier, was subjected to deep brain stimulation at 130 pulses/second, with a 90-microsecond pulse-width, in packets of durations from 20 to 73 seconds and was monitored with surface-electromyography.
At the end of these stimulation packets, tremor-free intervals followed, averaging over 20 seconds, before tremor reappeared. Wavelet analysis of the eletromyographic signals allowed predicting onset of tremors at the end of the tremor-free intervals and was successful in all test cycles. Furthermore, once stimulation was restarted, the tremors disappeared within 0.5 seconds on average. When restarting stimulation approximately 2 seconds ahead of the end of tremor-free post-simulation intervals as predicted by visual inspection of unprocessed electromyograms, no tremors occurred during three successive cycles of stimulation-on and stimulation-off. Maximal ratio of tremor-free duration to stimulation duration was computed, to determine a best DBS (deep brain stimulation) duration range (20-35 seconds).
We show existence of a tremor-free interval averaging over 20 seconds that follows applying stimulation packets of 20-35 seconds and that surface electomyogram allows predicting onset of tremor to facilitate activation of a next stimulation packet before tremor reappears. This establishes the feasibility of electromyographic-based predictive on-off control of deep brain stimulation in certain essential tremor patients. Best tremor-free duration to stimulation duration ratio may differ over the progression of the disorder and from patient to patient.
我们展示患者的测试结果，以表明通过非侵入性表面肌电图以自适应方式实现特发性震颤患者深部脑刺激序列的开-关控制，从而预防这些患者的震颤。
在我们的研究中，一名8年前接受双侧深部脑刺激植入的特发性震颤患者，以130次脉冲/秒、90微秒脉冲宽度进行深部脑刺激，刺激包持续时间为20至73秒，并通过表面肌电图进行监测。
在这些刺激包结束时，出现了平均超过20秒的无震颤间隔，之后震颤再次出现。对肌电信号进行小波分析能够预测无震颤间隔结束时震颤的发作，并且在所有测试周期中均成功。此外，一旦重新开始刺激，震颤平均在0.5秒内消失。当按照未处理肌电图的视觉检查预测，在模拟后无震颤间隔结束前约2秒重新开始刺激时，在连续三个刺激开启和关闭周期中均未出现震颤。计算无震颤持续时间与刺激持续时间的最大比值，以确定最佳的深部脑刺激（DBS）持续时间范围（20 - 35秒）。
我们表明，在应用20 - 35秒的刺激包后，存在平均超过20秒的无震颤间隔，并且表面肌电图能够预测震颤发作，以便在震颤再次出现之前促进下一个刺激包的激活。这确立了在某些特发性震颤患者中基于肌电图的深部脑刺激预测性开-关控制的可行性。最佳的无震颤持续时间与刺激持续时间比值可能会因疾病进展以及患者个体差异而有所不同。
