CAJ | 학술논문

研究了肌肉静态及动态收缩过程中表面EMG信号演化模式的变化,发现了疲劳进程中肌电信号趋于规则性变化的规律,信号的所有规则性演化模式之和(以Dreg表示)的增加反映了该规律.与传统的疲劳指标相比,Dreg在刻画不同人体的肌肉疲劳时变异性更小.此外,基于时域的Dreg的计算可以避免传统频域指标的使用局限性.EMG信号规则度增加的发现,不仅为检测疲劳进程中EMG信号的变化提供了一种新的简易方法,更为以往工作中通过非线性指标(包括熵和复杂度等)来评估肌肉疲劳提供了有力的证据.介绍的信号规则度检测方法同样适用于其他生理电信号.
연구료기육정태급동태수축과정중표면EMG신호연화모식적변화,발현료피로진정중기전신호추우규칙성변화적규률,신호적소유규칙성연화모식지화(이Dreg표시)적증가반영료해규률.여전통적피로지표상비,Dreg재각화불동인체적기육피로시변이성경소.차외,기우시역적Dreg적계산가이피면전통빈역지표적사용국한성.EMG신호규칙도증가적발현,불부위검측피로진정중EMG신호적변화제공료일충신적간역방법,경위이왕공작중통과비선성지표(포괄적화복잡도등)래평고기육피로제공료유력적증거.개소적신호규칙도검측방법동양괄용우기타생리전신호.
The changes in the evolvement patterns of surface electromyography(EMG) signals during both static and dynamic fatiguing contractions are studied. The main finding is that the EMG signal tends to be more and more regular as muscle fatigues. An increase in the summation of all the regular evolvement patterns denoted by Dreg reflects such a tendency.Compared with traditional measurements, Dreg shows less variability among subjects when characterizing a fatigue process. In addition, the calculation of Dreg in the time domain is free from the restrictions disturbing those of spectral parameters. The detection of an increase in the EMG regularity not only proposes a new and easy way to inspect changes in EMG during the fatigue process, but also provides strong supports to estimate muscle fatigue by means of nonlinear analysis methods such as entropy and complexity measures. The detection method of signal regularity can also be applied to other physiological signals.