为了实现矢量传感器在圆阵阵型下的应用,文中提出了一种适合于声矢量圆阵的目标方位估计算法。该算法首先将声矢量圆阵阵元域信号分解为一系列相互正交的相位模态,在相位模态域构造声压和质点振速的互协方差矩阵,然后进行MUSIC方位估计...为了实现矢量传感器在圆阵阵型下的应用,文中提出了一种适合于声矢量圆阵的目标方位估计算法。该算法首先将声矢量圆阵阵元域信号分解为一系列相互正交的相位模态,在相位模态域构造声压和质点振速的互协方差矩阵,然后进行MUSIC方位估计.理论分析和仿真结果表明,文中算法比相同阵型的声压阵MUSIC方位估计算法具有更好的噪声抑制能力、方位估计性能以及多目标分辨能力,试验结果也表明本文算法具有更好的噪声抑制能力以及更好的目标方位估计性能。该算法实现了声压和质点振速的相干处理,充分利用了声矢量传感器的平均声强抗噪原理,具有较强的抗各向同性噪声能力,并可以将子空间类DOA(Direction of Arrival)估计算法和相位模态域阵列信号处理技术有机结合起来,实现了声矢量传感器在圆阵阵型条件下的高分辨DOA估计。展开更多
目的探讨戴耳机听音乐对噪声作业工人高频噪声性听力损失(NIHL)的影响。方法采用判断抽样方法,以某汽车制造厂651名男性噪声作业工人为研究对象,对其进行个体噪声接触水平和纯音听阈测试;根据研究对象下班后戴耳机听音乐的频率分为低、...目的探讨戴耳机听音乐对噪声作业工人高频噪声性听力损失(NIHL)的影响。方法采用判断抽样方法,以某汽车制造厂651名男性噪声作业工人为研究对象,对其进行个体噪声接触水平和纯音听阈测试;根据研究对象下班后戴耳机听音乐的频率分为低、中和高频率使用耳机组,分别有60、436、155人。分析戴耳机听音乐联合职业性噪声接触对高频NIHL的影响。结果研究对象高频NIHL检出率为31.3%(204/651)。3组人群高频NIHL检出率由低到高依次为低、中和高频率使用耳机组(P<0.01);高频率使用耳机组人群高频NIHL检出率分别高于低和中频率使用耳机组(43.2% vs 25.0%,43.2% vs 28.0%,P<0.01)。多因素Logistic回归分析结果显示,在排除年龄、噪声作业工龄、噪声接触水平、佩戴防噪耳塞等混杂因素的影响后,戴耳机听音乐是噪声作业工人高频NIHL的危险因素(P<0.01);戴耳机听音乐的频率越高,发生高频NIHL的风险越大。结论噪声作业工人下班后戴耳机听音乐与职业性噪声接触对其发生高频NIHL具有协同作用。展开更多
传统DOA(direction of arrival)估计算法无法处理相干信号,因此提出一种基于重构噪声子空间的高精度DOA估计算法.该算法利用阵元接收数据的自协方差与互协方差信息构造成增广矩阵作为新的协方差矩阵,对该矩阵进行奇异值分解得到相应的...传统DOA(direction of arrival)估计算法无法处理相干信号,因此提出一种基于重构噪声子空间的高精度DOA估计算法.该算法利用阵元接收数据的自协方差与互协方差信息构造成增广矩阵作为新的协方差矩阵,对该矩阵进行奇异值分解得到相应的噪声子空间和特征值矩阵.为了获得更精确的信号向量,重构一个由新特征值矩阵对应的特征向量所组成的噪声子空间.最后通过谱峰搜索得到DOA估计值.算法不影响对非相干信号估计的效果,并且比IMMUSIC(improved multiple signal classification)算法具有更高的估计精度,在低信噪比及信号入射间隔较小的情况下也有良好的准确性.仿真结果表明,提出的改进算法在低信噪比及低采样快拍数的条件下,能有效估计出相干信号的波达方向.展开更多
Auditory stimuli are proposed as beneficial neurorehabilitation methods in patients with disorders of consciousness. However, precise and accurate quantitative indices to estimate their potential effect remain scarce....Auditory stimuli are proposed as beneficial neurorehabilitation methods in patients with disorders of consciousness. However, precise and accurate quantitative indices to estimate their potential effect remain scarce. Fourteen patients were recruited from the Neuro-Rehabilitation Unit of Hangzhou Hospital of Zhejiang Armed Police Corps of China. Altogether, there were seven cases of unresponsive wakefulness syndrome（five males and two females, aged 45.7 ± 16.8 years） and seven cases of minimally conscious state（six males and one female, aged 42.3 ± 20.8 years）. Simultaneously, fourteen healthy controls（10 males and 4 females, aged 51.7 ± 9.7 years） also participated in this case-control experiment. Brain response to music, subjects＇ own name, and noise was monitored by quantitative electroencephalography（QEEG） in the resting state and with acoustic stimulation. Predictive QEEG values in various brain regions were investigated. Our results show that cerebral activation was high in subjects stimulated by their own name, especially in the temporal lobe in patients with disorders of consciousness, and the frontal lobe in the control group. Further, during resting and stimulation, QEEG index（δ ＋ θ/α ＋ β ratio） negatively correlated with the Coma Recovery Scale-Revised score in traumatic disorders of consciousness patients. Hence, we speculate that a subject＇s own name might be an effective awakening therapy for patients with disorders of consciousness. Moreover, QEEG index in specific stimulation states may be used as a prognostic indicator for disorders of consciousness patients（sensitivity, 75%; specificity, 50%）.展开更多
文摘为了实现矢量传感器在圆阵阵型下的应用,文中提出了一种适合于声矢量圆阵的目标方位估计算法。该算法首先将声矢量圆阵阵元域信号分解为一系列相互正交的相位模态,在相位模态域构造声压和质点振速的互协方差矩阵,然后进行MUSIC方位估计.理论分析和仿真结果表明,文中算法比相同阵型的声压阵MUSIC方位估计算法具有更好的噪声抑制能力、方位估计性能以及多目标分辨能力,试验结果也表明本文算法具有更好的噪声抑制能力以及更好的目标方位估计性能。该算法实现了声压和质点振速的相干处理,充分利用了声矢量传感器的平均声强抗噪原理,具有较强的抗各向同性噪声能力,并可以将子空间类DOA(Direction of Arrival)估计算法和相位模态域阵列信号处理技术有机结合起来,实现了声矢量传感器在圆阵阵型条件下的高分辨DOA估计。
文摘目的探讨戴耳机听音乐对噪声作业工人高频噪声性听力损失(NIHL)的影响。方法采用判断抽样方法,以某汽车制造厂651名男性噪声作业工人为研究对象,对其进行个体噪声接触水平和纯音听阈测试;根据研究对象下班后戴耳机听音乐的频率分为低、中和高频率使用耳机组,分别有60、436、155人。分析戴耳机听音乐联合职业性噪声接触对高频NIHL的影响。结果研究对象高频NIHL检出率为31.3%(204/651)。3组人群高频NIHL检出率由低到高依次为低、中和高频率使用耳机组(P<0.01);高频率使用耳机组人群高频NIHL检出率分别高于低和中频率使用耳机组(43.2% vs 25.0%,43.2% vs 28.0%,P<0.01)。多因素Logistic回归分析结果显示,在排除年龄、噪声作业工龄、噪声接触水平、佩戴防噪耳塞等混杂因素的影响后,戴耳机听音乐是噪声作业工人高频NIHL的危险因素(P<0.01);戴耳机听音乐的频率越高,发生高频NIHL的风险越大。结论噪声作业工人下班后戴耳机听音乐与职业性噪声接触对其发生高频NIHL具有协同作用。
文摘传统DOA(direction of arrival)估计算法无法处理相干信号,因此提出一种基于重构噪声子空间的高精度DOA估计算法.该算法利用阵元接收数据的自协方差与互协方差信息构造成增广矩阵作为新的协方差矩阵,对该矩阵进行奇异值分解得到相应的噪声子空间和特征值矩阵.为了获得更精确的信号向量,重构一个由新特征值矩阵对应的特征向量所组成的噪声子空间.最后通过谱峰搜索得到DOA估计值.算法不影响对非相干信号估计的效果,并且比IMMUSIC(improved multiple signal classification)算法具有更高的估计精度,在低信噪比及信号入射间隔较小的情况下也有良好的准确性.仿真结果表明,提出的改进算法在低信噪比及低采样快拍数的条件下,能有效估计出相干信号的波达方向.
基金supported by grants from the General Project Plan of Zhejiang Medical Technology of China,No.2014RCA007the Medical Science and Technology Project Co-founded by Zhejiang Province and the Ministry of Health of China,No.2016152769
文摘Auditory stimuli are proposed as beneficial neurorehabilitation methods in patients with disorders of consciousness. However, precise and accurate quantitative indices to estimate their potential effect remain scarce. Fourteen patients were recruited from the Neuro-Rehabilitation Unit of Hangzhou Hospital of Zhejiang Armed Police Corps of China. Altogether, there were seven cases of unresponsive wakefulness syndrome（five males and two females, aged 45.7 ± 16.8 years） and seven cases of minimally conscious state（six males and one female, aged 42.3 ± 20.8 years）. Simultaneously, fourteen healthy controls（10 males and 4 females, aged 51.7 ± 9.7 years） also participated in this case-control experiment. Brain response to music, subjects＇ own name, and noise was monitored by quantitative electroencephalography（QEEG） in the resting state and with acoustic stimulation. Predictive QEEG values in various brain regions were investigated. Our results show that cerebral activation was high in subjects stimulated by their own name, especially in the temporal lobe in patients with disorders of consciousness, and the frontal lobe in the control group. Further, during resting and stimulation, QEEG index（δ ＋ θ/α ＋ β ratio） negatively correlated with the Coma Recovery Scale-Revised score in traumatic disorders of consciousness patients. Hence, we speculate that a subject＇s own name might be an effective awakening therapy for patients with disorders of consciousness. Moreover, QEEG index in specific stimulation states may be used as a prognostic indicator for disorders of consciousness patients（sensitivity, 75%; specificity, 50%）.
