摘要
利用表面电极采集的下颌表面肌电信号比较微弱,又受周围其他生理电信号和外界电磁干扰的影响,信噪比很低,传统的信号处理方法已不能很好地解决。本文在现有电极数量、排布方式和肌电信号采集设备基础上,采用独立分量分析与经验模式分解相结合,对下颌表面肌电信号进行处理;并结合呼吸气流信号,提出针对下颌表面肌电信号处理的评价方法。我们同步采集了正常成年人和阻塞性睡眠呼吸暂停/低通气综合征患者在不同睡眠期的下颌表面肌电和呼吸气流信号。处理结果表明,下颌表面肌电信号的信噪比从处理前的-0.85±6.11 dB提高到4.55±6.67 dB;同时,呼吸与下颌表面肌电信号的均方根值之间的互相关也从0.39±0.13增加到0.52±0.19。说明,该方法能大幅提高信号质量,并提取出下颌表面肌电信号随呼吸变化的实相性成分。
It is difficult to process the mandibularis surface myoelectric signal by means of conventional methods,not only because the sig-nal is weak but also susceptible to the activity of other physiological electrical signal and the electromagnetic interference of environment.In this manuscript,the mandibular surface electromyogram （SEMG）was analyzed by independent component analysis followed by empirical mode decomposition based on current electrodes and electromyographic instrument.We also introduced a method to evaluate the effect of signal processing combining with the respiratory signal.We processed the SEMG signal of normal and obstructive sleep apnea/hypopnea syndrome subjects in different sleep stages.The results demonstrated the signal-noise-rate of SEMG was increased from -0.85 ±6.11dB to 4.55 ±6.67dB.At the same time,the cross-correlation between respiration and the root-mean-square of SEMG was increased from 0.39 ± 0.13 to 0.52 ±0.19.These results indicated that the method could increase the signal-noise-rate of SEMG and extract phasic component from mandibular SEMG.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2014年第8期1875-1882,共8页
Chinese Journal of Scientific Instrument
基金
国家科技支撑计划(2013BAI03B00)资助项目
关键词
颏舌肌
表面肌电
独立分量分析
经验模式分解
信噪比
genioglossus
surface myoelectricity
independent component analysis
empirical mode decomposition
signal noise rate
