Suboptimal Exposure to Facial Expressions When Viewing Video Messages From a Small Screen: Effects on Emotion, Attention, and Memory.

The authors examined the effects of suboptimally presented facial expressions on emotional and attentional responses and memory among 39 young adults viewing video (business news) messages from a small screen. Facial electromyography (EMG) and respiratory sinus arrhythmia were used as physiological measures of emotion and attention, respectively. Several congruency priming effects were found. In particular, happy facial primes prompted increased (a) pleasure ratings, (b) orbicularis oculi EMG activity, (c) perceived trustworthiness, and (d) recognition memory for video messages with a positive emotional tone. Emotional and other responses to video messages presented on a small screen can be modified with suboptimal affective primes, but even small differences in the emotional tone of the messages should be allowed for. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The timing of appraisals.

The appraisal process consists of the subjective evaluation that occurs during an individual's encounter with significant events in the environment, determining the nature of the emotional reaction and experience. Placed in the context of appraisal theories of emotion-elicitation and differentiation, the aim of the present research was to test empirically the hypothesis that the intrinsic pleasantness evaluation occurs before the goal conduciveness evaluation. In two studies, intrinsically pleasant and unpleasant images were used to manipulate pleasantness, and a specific event in a Pacman-type videogame was used to manipulate goal conduciveness. Facial EMG was used to measure facial reactions to each evaluation. As predicted, facial reactions to the intrinsic pleasantness manipulation were faster than facial reactions to the goal conduciveness manipulation. These results provide good empirical support for the sequential nature of the appraisal process. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于谱插值与经验模态分解的表面肌电信号降噪处理*

根据表面肌电(surface electromyography, sEMG)信号的噪声特性来探讨其降噪方法的应用问题。采用谱插值法来削弱工频干扰以避免工频处的肌电信息成分丢失,再选取通过经验模态分解(empirical mode decomposition, EMD)方法获得的内在模态函数(intrinsic mode function, IMF)分量作小波软阈值分析,并将部分明显的低频IMF干扰分量及冗余分量去除,然后对相应IMF分量进行重构便可得到降噪处理后的sEMG信号。仿真和真实信号的降噪实验结果     

基于多核学习的下肢肌电信号动作识别

为了提高下肢肌电控制系统中多运动模式识别的准确性,提出一种基于多核学习(MKL)和小波变换尺度间相关性特征提取的多类识别方法.根据多核学习理论,采用二叉树组合策略构造基于多核学习的多类分类器.对下肢4路表面肌电信号进行离散平稳小波变换,用小波系数尺度间的相关性提取特征向量输入构造的多类分类器,对水平行走时划分的支撑前期、支撑中期、支撑末期、摆动前期、摆动末期这5个细分运动状态进行分类.实验结果表明,所提的多模式识别方法能够以较高识别率区分多个细分运动状态,得到比标准的单核支持向量机(SVM)分类器更好的准确性.     

在线半监督Kohonen网络的预抓取手势识别

为实现智能仿生手的抓取,提高模式识别的实时性和灵敏性,提出一种在线半监督Kohonen网络。该网络针对表面肌电信号(s EMG)的特性,在有监督Kohonen网络基础上,将有监督和无监督网络的优势进行结合,应用数据剪辑方法处理训练集更新识别网络,在线识别侧边抓取、球形抓取、三指精确抓取和圆柱形抓取4种预抓取手势。实验表明,与不同Kohonen网络相比,此识别方法具有很好的在线识别能力和正确率。     

基于熵和PSO优化SVM的肌电信号跌倒识别

跌倒对老年人的健康构成严重危害,设计了一种基于肌电信号的跌倒识别方法,可用于跌倒检测报警。该方法首先对表面肌电动作信号进行小波包分解,再依据信号特征选取信号的低频分量并重构,计算其排列组合熵,最后以4路肌电信号对应的排列组合熵组成的特征向量输入SVM进行模式识别并采用粒子群算法对SVM中惩罚参数c和核函数参数g进行优化,对8种动作进行识别实验,跌倒识别率88%,特异度98.3%,平均识别率97.0%,优于网格法和遗传算法支持向量机（GA-SVM）的参数优化,具有较强的鲁棒性和抗干扰能力。     

基于典型相关分析与低通滤波的肌电伪迹去除

提出了一种基于典型相关分析(CCA)和低通滤波的盲源分离方法去除脑电信号(EEG)中的肌电伪迹.该方法首先将混入了肌电伪迹的EEG信号分解为不相关的CCA分量,然后对与伪迹源相关的分量进行低通滤波处理,去除这些分量中的高频伪迹成分,最后利用与EEG相关的CCA分量和滤波处理后的新分量重构信号,消除肌电伪迹的影响.实验结果表明,采用CCA能够有效地分离出肌电伪迹,而结合低通滤波技术能够更有效地保留EEG信息.该方法取得了较好的去除肌电伪迹的效果.     

Differentiating types of muscle movements using a wavelet based fuzzy clustering neural network

Abstract: The electromyographic signals observed at the surface of the skin are the sum of many small action potentials generated in the muscle fibres. After the signals are processed, they can be used as a control source of multifunction prostheses. The myoelectric signals are represented by wavelet transform model parameters. For this purpose, four different arm movements (elbow extension, elbow flexion, wrist supination and wrist pronation) are considered in studying muscle contraction. Wavelet parameters of myoelectric signals received from the muscles for these different movements were used as features to classify the electromyographic signals in a fuzzy clustering neural network classifier model. After 1000 iterations, the average recognition percentage of the test was found to be 97.67% with clustering into 10 features. The fuzzy clustering neural network programming language was developed using Pascal under Delphi.     

Ergonomic design and evaluation of the handle for an endoscopic dissector

The purpose of this study was to design an endoscopic dissector handle and objectively assess its usability. The handles were designed with increased contact area between the fingers and thumb and the eye rings, and the eye rings were modified to have a more perpendicular insertion angle to the finger midline. Four different handle models were compared, including a conventional product. Subjects performed dissection, exclusion, grasping, precision manipulation and precision handling tasks. Electromyography and subjective evaluations were measured. Compared to conventional handles, the designated handle reduced the muscle load in the extensor and flexor muscles of the forearm and increased subjective stability. The activity of the first dorsal interosseous muscle was sometimes influenced by the shape of the other parts. The ergonomically designed endoscopic dissector handle used in this study achieved high usability. Medical instrument designs based on ergonomic concepts should be assessed with objective indices.

Practitioner Summary: The endoscopic dissector handles were designed with increased contact area and more suitable insertion angle between the fingers and thumb and the eye rings. Compared to conventional handles, the designated handle reduced the muscle load in the extensor and flexor muscles of the forearm and increased subjective stability.     

Influence of smartphone use styles on typing performance and biomechanical exposure

Twenty-seven subjects completed 2-min typing tasks using four typing styles: right-hand holding/typing (S-thumb) and two-hand typing at three heights (B-low, B-mid and B-high). The styles had significant effects on typing performance, neck and elbow flexion and muscle activities of the right trapezius and several muscles of the right upper limb (p < 0.0001 by repeated-measure analysis of variance). The subjects typed the fewest words (error-adjusted characters per minute: 78) with the S-thumb style. S-thumb style resulted in similar flexion angles of the neck, elbow and wrist, but significantly increased muscle activities in all tested muscles compared with the B-mid style. Holding the phone high or low reduced the flexion angles of the neck and right elbow compared with the B-mid style, but the former styles increased the muscle activity of the right trapezius. Right-hand holding/typing was not a preferable posture due to high muscle activities and slow typing speed.

Practitioner Summary: Right-hand holding/typing was not favoured, due to increased muscle activities and slower typing speed. Holding the phone high or low reduced the flexion angles of the neck and right elbow, but the former styles increased the muscle activity of the right trapezius compared with holding the phone at chest level.