Creating and retargetting motion by the musculoskeletal human body model

Recently, optimization has been used in various ways to interpolate or retarget human body motions obtained by motion-capturing systems. However, in such cases, the inner structure of a human body has rarely been taken into account, and hence there have been difficulties in simulating physiological effects such as fatigue or injuries. In this paper, we propose a method to create/retarget human body motions using a musculoskeletal human body model. Using our method, it is possible to create dynamically and physiologically feasible motions. Since a muscle model based on Hill's model is included in our system, it is also possible to retarget the original motion by changing muscular parameters. For example, using the muscle fatigue model, a motion where a human body gradually gets tired can be simulated. By increasing the maximal force exertable by the muscles, or decreasing it to zero, training or displacement effects of muscles can also be simulated. Our method can be used for biomechanically correct inverse kinematics, interpolation of motions, and physiological retargetting of the human body motion.     

Enriching a motion database by analogous combination of partial human motions

We have synthesized new human body motions from existing motion data, by dividing the body of an animated character into several parts, such as upper and lower body, and partitioning the motion of the character into corresponding partial motions. By combining different partial motions, we can generate new motion sequences. We select the most natural-looking combinations by analyzing the similarity of partial motions, using techniques such as motion segmentation, dimensionality reduction, and clustering. These new combinations can dramatically increase the size of a motion database, allowing more score in selecting motions to meet constraints, such as collision avoidance. We verify the naturalness and physical plausibility of the new motions using an SVM learning model and by analysis of static and dynamic balance.     

Dexterous motion recognition for myoelectric control of multifunctional transradial prostheses

Attributed to its superior dexterity, the human’s thumb plays a significant role in the activities of daily living (ADLs). In order to promote the operational capability of the prosthetic hand, state-of-the-art designs tend to integrate multiple degrees of freedom (DOFs) in thumb’s trapeziometacarpal (TM) joint for achieving versatile movements. However, without proper control methods, this fine dexterity of multi-DOF prosthetic hand is hard to be demonstrated. This problem becomes more serious when the control signals, electromyography (EMG), are highly limited on the residual stump of the amputee. Through experiments, the paper examines the feasibility of recognizing 4 thumb motions (flexion/extension and abduction/adduction) together with the other 12 finger- and wrist-related motions under a general surface EMG configuration. After surveying the classification accuracy of several selective motion groups (thumb motions, thumb-involved finger motions, thumb-involved wrist motions, etc.), we report here the current limitations of the prevalent pattern recognition-based EMG control schemes. Considering the severely impaired neuromuscular systems of the amputees, controlling those thumb motions for achieving dexterous operations still faces many challenges. We finally discuss several alternative strategies, including switching, extended physiological proprioception (EPP) and postural synergy, for dealing with this problem.     

Single frame correction of motion artifacts in PMD-based time of flight cameras

One of the leading time of flight imaging technologies for depth sensing is based on Photonic Mixer Devices (PMD). In PMD sensors each pixel samples the correlation between emitted and received light signals. Current PMD cameras compute eight correlation samples per pixel in four sequential stages to obtain depth with invariance to signal amplitude and offset variations. With motion, PMD pixels capture different depths at each stage. As a result, correlation samples are not coherent with a single depth, producing artifacts. We propose to detect and remove motion artifacts from a single frame taken by a PMD camera. The algorithm we propose is very fast, simple and can be easily included in camera hardware. We recover depth of each pixel by exploiting consistency of the correlation samples and local neighbors of the pixel. In addition, our method obtains the motion flow of occluding contours in the image from a single frame. The system has been validated in real scenes using a commercial low-cost PMD camera and high speed dynamics. In all cases our method produces accurate results and it highly reduces motion artifacts.     

基于照片的人体尺寸信息自动提取技术

针对3D扫描仪成本高,传统手工软尺测量效率低的状况,在保证精度的前提下,尝试应用图像处理理论从满足一定条件的照片提取人体尺寸信息,为建立人体尺寸信息库提供一种信息采集的自动化方法.通过对实验结果的分析,本文验证了此方法的可行性,并提出未来的研究方向.     

The influence of perceptual grouping on motion detection

In this paper, we present a perceptual organization-based method for detecting moving objects from image sequences. To achieve the characteristics of real-time, efficiency, and robustness, a perceptual computation model of edge partitioning and grouping was proposed for the extraction of edge traces on the fly. Each edge trace is made up of generic edge tokens (GETs) which are perceptual features, and defined qualitatively based on the principles of Gestalt laws. Motion detection uses two basic computations: (1) segment motion GETs (MGETs) by computing the gradient differences between GET streams in consecutive frames; and (2) detect motion objects by perceptually grouping MGETs into object clusters. The MGETs in each cluster are constrained by the proximity of the features, and the motion continuation of the cluster measured by motion persistence, etc. Experimental results are provided.     

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.     

Computer-aided measurement plan for an impeller on a coordinate measurement machine with a rotating and tilting probe

This paper presents a computer-aided measurement plan (CAMP) for an impeller on a coordinate measurement machine (CMM) with a rotating/tilting probe. The blade surfaces of a machined impeller were measured exactly to secure the machining tolerance and surface finish of the impeller. CMM with a rotating and tilting probe is commonly used for this measurement. However, it is not easy to evaluate all the points on the impeller surfaces due to the time-consuming nature of the CMM measurement. In addition, many points cannot be easily accessed by the CMM probe due to the interference between the probe and the impeller blades. Furthermore, the inherent complexity of the existing teaching operation of a probe using a joystick suggests the necessity of developing a new method for the measurement planning of an impeller. Thus, this paper proposes a CAMP for effectively gauging the inspection points based on the ruled line information of the impeller blade surfaces. The proposed plan partitions the surfaces into several measurement regions based on the ruled lines of a blade surface and the approach vectors of the probe. Finally, a case example for an impeller is presented to demonstrate the effectiveness of the proposed strategy.     

Vertical vibration frequency and sitting posture effects on muscular loads and body balance

This study examined the effects of whole body vibration and sitting posture on muscular load, body balance and discomfort. An electric vibrator, a surface electromyography measurement system and a balance evaluation system were used in the experiment. Nine test conditions were studied consisting of three vertical frequencies (no vibration, 20 and 40 Hz) and three sitting postures (erect, bent-forward and twisted). Study results showed that whole body vibration had significant effects on the muscular loads in the torso muscles, body balance and perceived discomfort. Adverse effects generally increased with high-frequency vibration. No significant muscular load difference and balance difference were observed among sitting postures at any frequency. Significant discomfort differences between the erect and twisted postures were found with no vibration or at low frequency.Relevance to industryAttention should be paid to the negative effects of vibration transmission on the human body at worksites. The results from this study should be useful for whole body vibration risk assessment and control measures.     

Field measurement of hand forces of palm oil harvesters and evaluating the risk of work-related musculoskeletal disorders (WMSDs) through biomechanical analysis

Hand force data is critical in evaluating work-related musculoskeletal disorders (WMSDs). Nevertheless, earlier studies on oil palm workers relied on estimated or laboratory measurements, which may not accurately reflect the actual hand forces. This study is the first report on the field measurement of hand forces for palm oil harvesters using a chisel and sickle to harvest low and tall palm trees, respectively. The dynamic hand forces and ground reaction forces were measured using instrumented harvesting tools and force plates, while wearable motion (IMU) and electromyography (EMG) sensors were incorporated for quantifying postural angles and muscle activations, respectively. Additionally, the spinal loadings, continuous Rapid Entire Body Assessment (REBA) scores, and subjective pain scores were determined to evaluate the risk of WMSDs. A total of 10 harvesters were recruited to perform the palm pruning tasks using a chisel and sickle. Resultantly, the sickle and chisel recorded a maximum cutting force of 1601.23 ± 424.26 N and 420.80 ± 96.00 N, respectively. All pruning tasks were found to be highly risky to harvesters, with a peak REBA score of 12. Likewise, all investigated muscles were activated for over 40% MVC, thus inducing moderate pain in the muscles. The peak L5-S1 compression forces for all tasks exceeded the safety threshold (>3400 N), but the values were not significantly different. The shear force of the L5-S1 was extreme in pruning with a sickle (1446.10 ± 411.00 N) compared to using a chisel. In conclusion, palm harvesters were at a high risk of developing WMSDs following poor postures, high physical exertion and muscle activity, and excessive spinal loads.     

惯性传感器技术及发展

论述了惯性传感器的发展过程和其在惯性导航系统中的地位 ,对新型惯性传感器 :壳体谐振陀螺仪、微机械电子系统惯性传感器、光纤陀螺仪的原理、性能和研究现状作了分析 ,最后指出了惯性传感器的发展方向。     

基于LLE和SVM的手部动作识别方法

为了提高人体手部动作的识别性能,针对高维特征数据给模式识别带来的问题,提出了一种基于局部线性嵌入(LLE)算法和支持向量机(SVM)的模式识别方法.该方法从肱桡肌和尺侧腕屈肌上采集两路表面肌电信号(sEMG),通过对样本信号的时域分析和小波分析,提取原始信号的特征,构造特征矢量.再利用LLE算法对原始特征数据进行降维,挖掘出具有内在规律的低维特征.将降维后的特征数据输入SVM分类器进行4种动作的模式识别.实验表明:此方法可以有效、准确地对人体手部动作进行分类.     

度量行为信息基的可信认证

为了提高远程认证的灵活性和效率,提出将Merkle哈希树应用到基于可信平台的行为动态验证中,给出创建认证度量行为信息基AM_AIB的过程。通过度量当前行为,计算得到行为发生时根哈希值,然后远程认证。根哈希值由可信平台模块(TPM)签名,传递给服务器端验证,如果和服务器端的根哈希值一致,表明该行为是可信的。可根据行为特性设计不同粒度的行为信息基。实验结果表明,该模型能提高时间性能,验证方式灵活,保护平台隐私,克服了基于属性验证的静态特点,确保了平台应用软件运行时可信。     

基于表面肌电的下肢肌肉功能网络构建及其应用研究

在肌电控制下肢康复辅具研究中,合适的肌电采集位置是运动模式识别的前提与基础.针对目前肌电采集位置缺乏成熟理论依据和统一标准的问题,选取90个下肢肌电采集点作为节点,通过计算节点间的肌电相关性,构建下肢肌肉功能网络,证明其具有小世界特性.实验结果表明:不同运动模式的网络具有明显的拓扑结构差异,通过网络特性分析可以确定与模式关联度大的肌电采集位置,取得较好的运动模式识别结果.通过构建及分析下肢肌肉功能网络,深入了解下肢运动模式更替过程中的肌肉协同工作机制,为下肢康复辅具控制中肌电采集位置的确定提供了理论支持.     

下肢截肢者行走意图识别方法研究进展

直立行走是人类独立生活和正常参与社会活动的基本功能之一.人因遭受工伤、交通事故、战争、自然灾害（地震等）、疾病（糖尿病、癌症等）、先天出生缺陷等意外和不幸造成下肢截肢,从而部分或全部丧失行走能力,严重影响正常生活和参与社会活动.下肢假肢是下肢截肢者恢复行走功能的唯一手段,其技术发展吸引了众多研究者的关注.为使下肢假肢使用者能像正常腿一样或接近的步态行走,关键是实现截肢者行走意图的自动精确识别.本文首先探索了行走意图识别的内涵;然后从信号源的角度分析了不同截肢者行走意图识别方法的特点,尤其是神经功能重建作为补充的肌电信号（Electromyography,EMG）源的方法,并简述其研究进展,提出了一种融合生物力学信号和生物电信号的截肢者行走意图识别方法;最后对下肢截肢者行走意图识别方法发展趋势进行了总结和展望.     

面向无线传感器网络的无线携能通信研究

能量受限是无线传感器网络应用的瓶颈问题,为了使无线传感器网络获得稳定持续的能量来源,提出将无线携能通信（ SWIPT）技术应用到无线传感器网络中。基于时分多址（ TDMA）的通信方式建立了适应于无线传感器网络的无线携能通信系统新优化模型。通过凸优化问题的求解得到该优化模型的最优分配策略。利用仿真实验对无线携能通信在无线传感器网络中应用的可行性进行了分析,对方法的有效性进行了验证。     

基于运动矢量直方图不变的数字视频隐写算法

针对现有基于运动矢量(MV)的数字视频隐写算法对载体直方图统计特性带来较大改变这一问题,提出一种基于运动矢量直方图不变的数字视频隐写算法。利用保持直方图数据映射方法,把秘密信息隐藏在视频运动矢量中;同时,利用数据匹配编码对嵌入之前的秘密信息进行编码处理,得到了与视频运动矢量统计特征基本匹配的数据流,使算法接近于信息论下的完美安全。实验结果表明：算法有效控制了运动矢量直方图的改变,同时码率的增加也被有效地控制在1%以内,隐写分析检出率平均下降了30%~50%。     

构件化软件演化信息及演化相似性度量技术研究

对软件演化信息的度量能发现软件演化过程中的问题,预测其变化趋势。传统的软件演化信息度量技术主要是以文件、目录或者项目作为度量的基本单位,缺乏在较高抽象层次对软件系统进行度量的能力。在基于构件的软件配置管理模型的基础上,以构件作为软件演化度量的基本单位,提出了一组基于属性变化、适用于构件以及软件系统演化度量的公式（包括较近、较早演化度量,演化相似性度量等）,并开发了原型支撑系统。     

光纤光栅温度应力同时区分测量技术的新进展

从不同角度归纳了光纤光栅传感器区分测量温度及应力的最新技术方案,叙述其主要工作原理,给出图示说明,并对各种方案的适用场合及优缺点进行了比较分析,最后,指出了现有方案的不足。     

一个集成化软件过程度量系统的设计与实现*

为了使企业度量活动满足企业各层级角色的度量需求,提出了一个建立企业集成化软件过程度量体系的方法,给出了一个度量模型及其典型应用,描述了一个企业集成化软件过程度量系统的体系结构及功能。在系统支持下,企业度量活动的效率得到了有效提升。