Low-back biomechanics and static stability during isometric pushing

Pushing and pulling tasks are increasingly prevalent in industrial workplaces. Few studies have investigated low-back biomechanical risk factors associated with pushing, and we are aware of none that has quantified spinal stability during pushing exertions. Data recorded from 11 healthy participants performing isometric pushing exertions demonstrated that trunk posture, vector force direction of the applied load, and trunk moment were influenced (p < .01) by exertion level, elevation of the handle for the pushing task, and foot position. A biomechanical model was used to analyze the posture and hand force data gathered from the pushing exertions. Model results indicate that pushing exertions provide significantly (p < .01) less stability than lifting when antagonistic cocontraction is ignored. However, stability can be augmented by recruitment of muscle cocontraction. Results suggest that cocontraction may be recruited to compensate for the fact that equilibrium mechanics provide little intrinsic trunk stiffness and stability during pushing exertions. If one maintains stability by means of cocontraction, additional spinal load is thereby created, increasing the risk of overload injury. Thus it is important to consider muscle cocontraction when evaluating the biomechanics of pushing exertions. Potential applications of this research include improved assessment of biomechanical risk factors for the design of industrial pushing tasks.     

Modeling reaching impairment after stroke using a population vector model of movement control that incorporates neural firing-rate variability

The directional control of reaching after stroke was simulated by including cell death and firing-rate noise in a population vector model of movement control. In this model, cortical activity was assumed to cause the hand to move in the direction of a population vector, defined by a summation of responses from neurons with cosine directional tuning. Two types of directional error were analyzed: the between-target variability, defined as the standard deviation of the directional error across a wide range of target directions, and the within-target variability, defined as the standard deviation of the directional error for many reaches to a single target. Both between- and within-target variability increased with increasing cell death. The increase in between-target variability arose because cell death caused a nonuniform distribution of preferred directions. The increase in within-target variability arose because the magnitude of the population vector decreased more quickly than its standard deviation for increasing cell death, provided appropriate levels of firing-rate noise were present. Comparisons to reaching data from 29 stroke subjects revealed similar increases in between- and within-target variability as clinical impairment severity increased. Relationships between simulated cell death and impairment severity were derived using the between- and within-target variability results. For both relationships, impairment severity increased similarly with decreasing percentage of surviving cells, consistent with results from previous imaging studies. These results demonstrate that a population vector model of movement control that incorporates cosine tuning, linear summation of unitary responses, firing-rate noise, and random cell death can account for some features of impaired arm movement after stroke.     

Computing with populations of monotonically tuned neurons

The parametric variation in neuronal discharge according to the values of sensory or motor variables strongly influences the collective behavior of neuronal populations. A multitude of studies on the populations of broadly tuned neurons (e.g., cosine tuning) have led to such well-known computational principles as population coding, noise suppression, and line attractors. Much less is known about the properties of populations of monotonically tuned neurons. In this letter, we show that there exists an efficient weakly biased linear estimator for monotonic populations and that neural processing based on linear collective computation and least-square error learning in populations of intensity-coded neurons has specific generalization capacities.     

Fuzzy force learning controller of flexible wiper system

Wiper blade of automobile is among those types of flexible system that is required to be operated in quite high velocity to be efficient in high load conditions. This causes some annoying noise and deteriorated vision for occupants. The modeling and control of vibration and low-frequency noise of an automobile wiper blade using soft computing techniques are focused in this study. The flexible vibration and noise model of wiper system are estimated using artificial intelligence system identification approach. A PD-type fuzzy logic controller and a PI-type fuzzy logic controller are combined in cascade with active force control (AFC)-based iterative learning (IL). A multi-objective genetic algorithm is also used to determine the scaling factors of the inputs and outputs of the PID-FLC as well as AFC-based IL gains. The results from the proposed controller namely fuzzy force learning (FFL) are compared with those of a conventional lead–lag-type controller and the wiper bang–bang input. Designing controllers based on classical methods could become tedious, especially for systems with high-order model. In contrast, FFL controller design requires only tuning of some scaling factors in the control loop and hence is much simpler and efficient than classical design methods.     

Robust Black-Box Modeling of Piezoelectric Actuators for Vibration Drilling Control

In this paper, we study a new modeling approach which is experimentally validated on piezoelectric actuators, in order to derive black-box pseudolinear models for the vibration drilling control. A common way is to use physical based approaches. However, sometimes, complex phenomena occur in the system due to atypical changes of the process behavior, output noise or some hard non-linearities. Therefore, identification methods to achieve the modeling task are adopted. The micro-displacements of the piezoelectric systems generate atypical data named observation outliers in the output signal, involving large errors named innovation outliers in the predicted output signal. Since the normal distribution of these estimation errors is disturbed, and present heavy tails, we choose here as model of contaminated distribution the gross error model (GEM) approach. In order to deal with the innovation outliers, we extend the noise interval range of the scaling factor, tuning the robust Huber’s ρ-function chosen. We propose from this function, a parameterized robust estimation criterion (PREC) and we give the asymptotic covariance matrix of the M-estimator for the Output Error (OE) model structure. A new decisional tool for the models quality, named L ₁-contribution function is proposed. Experimental results are presented and discussed.     

Mathematically modelling the effects of pacing,finger strategies and urgency on numerical typing performance with queuing network model human processor

Numerical typing is an important perceptual-motor task whose performance may vary with different pacing, finger strategies and urgency of situations. Queuing network-model human processor (QN-MHP), a computational architecture, allows performance of perceptual-motor tasks to be modelled mathematically. The current study enhanced QN-MHP with a top-down control mechanism, a close-loop movement control and a finger-related motor control mechanism to account for task interference, endpoint reduction, and force deficit, respectively. The model also incorporated neuromotor noise theory to quantify endpoint variability in typing. The model predictions of typing speed and accuracy were validated with Lin and Wu's (2011) experimental results. The resultant root-mean-squared errors were 3.68% with a correlation of 95.55% for response time, and 35.10% with a correlation of 96.52% for typing accuracy. The model can be applied to provide optimal speech rates for voice synthesis and keyboard designs in different numerical typing situations.

Practitioner Summary: An enhanced QN-MHP model was proposed in the study to mathematically account for the effects of pacing, finger strategies and internalised urgency on numerical typing performance. The model can be used to provide optimal pacing for voice synthesise systems and suggested optimal numerical keyboard designs under urgency.     

Power grip force is modulated in repeated elbow movement

The objective of this study was to quantitatively investigate the modulation of power grip force under repeated elbow movement and its relation to muscle cocontraction and potential risk of developing cumulative trauma disorders (CTD). Thirteen right-handed participants without any neuromuscular disorders were recruited. Participants were instructed to hold a digital dynamometer in the hand with three levels of grip forces (20%, 40% and 60% of the maximum grip force) and perform repeated arm movement in the sagittal plane at three speeds (slow, self-paced and fast) with the upper arm voluntarily held by side by the participant. With the increase of motion rate and target force level, the grip force fluctuation, finger flexor muscle activities, elbow muscles cocontraction and apparent stiffness were significantly increased (p < 0.01). This study suggests that the power grip coupled with fast arm movement be avoided as much as possible in the workplace. PRACTITIONER SUMMARY: Power grip is usually accompanied with arm movement in workplaces and the increased physical demand might result in higher muscle activities and potentially higher risk of repetitive musculoskeletal injuries.     

Performance Comparison of Gyro-Based and Gyroless Attitude Estimation for CubeSats

In this paper, a comparison study between gyro-based and gyroless approaches for spacecraft attitude estimation is presented. Due to its vulnerability to the model errors, the gyroless approach has not been widely focused on and there are only few comparison studies available. However, this conventional wisdom might not directly apply to CubeSat attitude estimation, where noisy MEMS gyro is usually implemented. Although the noise density can be improved by low-pass filtering, it sacrifices the bandwidth so that it can induce a discretization error when spacecraft rotates in high speed. This paper outlines expected pros and cons of gyroless attitude estimation with respect to cost and miniaturization, rotational agility, and model errors. Additionally, linearized system models for both of the attitude estimation methods are formulated and a simple guideline for tuning process noise against the model errors is proposed. Numerical results for a realistic earth observation scenario are presented to quantitatively compare the benefits and drawbacks of each attitude estimation method.

     

Trunk muscle activation and cocontraction while resisting applied moments in a twisted posture

Abstract

Previous studies of twisting have revealed substantial cocontraction of agonist and antagonist muscles within the torso when torsional moments are generated. The objective of the current study was to quantify the activations and cocontraction of eight trunk muscles as subjects maintained an axially rotated trunk posture and resisted external applied bending moments. Ten subjects twisted their torsos 25° to the right (clockwise) and resisted 20 and 40 Nm bending moments from 12 directions. The moment directions were in a transverse plane and labelled clockwise as viewed from above, ranging from 0° (mid-saggital, anterior) to 330°, in 30° increments. RMS EMG amplitude data were collected using surface electrodes and normalized to maximal voluntary contractions. Significant changes were observed in the muscle responses due to the interaction of the moment direction and moment magnitude for six of the eight muscles tested. Comparison of the present data with that collected previously in neutral postures indicated: (1) a large increase in the activation levels of the right erector spinae and the left external oblique muscles; and (2) a counter-clockwise shift in the moment direction at which the peak activation of these same muscles occurs. Analysis of the relative activation levels (RALs), constructed from the NEMG data to quantify the cocontraction, indicated that the changes in cocontraction were more robust in response to changes in the bending moment's direction as opposed to changes in bending moment's magnitude.     

Population computation of vectorial transformations

Many neurons of the central nervous system are broadly tuned to some sensory or motor variables. This property allows one to assign to each neuron a preferred attribute (PA). The width of tuning curves and the distribution of PAs in a population of neurons tuned to a given variable define the collective behavior of the population. In this article, we study the relationship of the nature of the tuning curves, the distribution of PAs, and computational properties of linear neuronal populations. We show that noise-resistant distributed linear algebraic processing and learning can be implemented by a population of cosine tuned neurons assuming a nonuniform but regular distribution of PAs. We extend these results analytically to the noncosine tuning and uniform distribution case and show with a numerical simulation that the results remain valid for a nonuniform regular distribution of PAs for broad noncosine tuning curves. These observations provide a theoretical basis for modeling general nonlinear sensorimotor transformations as sets of local linearized representations.     

Contact force and torque sensing for serial manipulator based on an adaptive Kalman filter with variable time period

Contact force and torque sensing approaches enable manipulators to cooperate with humans and to interact appropriately with unexpected collisions. In this paper, a mode-switching moving average with variable time period is proposed to reduce the effects of measured motor current noise and thus provide improved confidence in joint output torque estimation. The time period of the filter adapts continuously to achieve optimal tradeoff between response time and precision of estimation in real-time. An adaptive Kalman filter that consists of the proposed moving average and the classical Kalman filter is proposed. Calibration routines for the adaptive Kalman filter take the measured motor current noise and errors in the speed data from the individual joints into account. The combination of the proposed adaptive Kalman filter with variable time period and its calibration method facilitates force and torque estimation without force/torque sensors. Contact force/torque sensing and response time assessments from the proposed approach were performed on the Universal Robot 5 manipulator with differing unexpected end effector loads. The combined force and torque sensing method led to a reduction of the estimation errors and response time in comparison with the pioneering method, and the effect is further improved as the payload rises. The proposed method can be applied to any robotic manipulators as long as the motor information (current, joint position, and joint velocities) are available and consequently the cost will be reduced dramatically from methods that require load cells.     

Influence of fatigue in neuromuscular control of spinal stability

Lifting-induced fatigue may influence neuromuscular control of spinal stability. Stability is primarily controlled by muscle recruitment, active muscle stiffness, and reflex response. Fatigue has been observed to affect each of these neuromuscular parameters and may therefore affect spinal stability. A biomechanical model of spinal stability was implemented to evaluate the effects of fatigue on spinal stability. The model included a 6-degree-of-freedom representation of the spine controlled by 12 deformable muscles from which muscle recruitment was determined to simultaneously achieve equilibrium and stability. Fatigue-induced reduction in active muscle stiffness necessitated increased antagonistic cocontraction to maintain stability resulting in increased spinal compression with fatigue. Fatigue-induced reduction in force-generating capacity limited the feasible set of muscle recruitment patterns, thereby restricting the estimated stability of the spine. Electromyographic and trunk kinematics from 21 healthy participants were recorded during sudden-load trials in fatigued and unfatigued states. Empirical data supported the model predictions, demonstrating increased antagonistic cocontraction during fatigued exertions. Results suggest that biomechanical factors including spinal load and stability should be considered when performing ergonomic assessments of fatiguing lifting tasks. Potential applications of this research include a biomechanical tool for the design of administrative ergonomic controls in manual materials handling industries.     

Effects of stray magnetic forces on position error signals during a long seeking-and-settling process

This paper is to study how stray magnetic forces encountered in a long seeking process affect position errors of a hard disk drive after it finishes the seek and settles. The study consists of three parts: analysis of stray magnetic forces, numerical modeling, and analysis of numerical results. In the analysis of stray magnetic forces, we lump the stray magnetic forces into three components D1, D2 and D4. Specifically, D1 is a pair of stray magnetic forces in the plane of the voice coil. The two forces act on the two equal legs of the voice coil. In addition, the two forces point to and away from the pivot center, respectively. D2 is a pair of stray magnetic forces out of the plane of the voice coil. The two forces are equal in magnitudes but opposite in directions. The two force components also act on the two equal legs of the voice coil. D4 is identical to D2, except that the two force components in D4 act in the same direction. In the numerical study, we adopt a numerical model that includes a spinning spindle motor, a spinning disk pack with multiple disks, a stationary base plate with a top cover, and a slewing head-stack assembly. Moreover, multiple bearings are present in the model to connect the multiple components. In particular, fluid-dynamic bearings connect the rotating spindle and disk pack with the base plate, pivot bearings connect the base plate with the head-stack assembly, and air bearings connect the spinning disk pack with head sliders located at the tip of the slewing head-stack assembly. Also, the numerical model assumes that the head-stack assembly seeks according to a user-specified seeking profile. Numerical simulations show two major conclusions. First, stray magnetic force component D1 does not lead to significant position errors when the head-stack assembly settles. Stray magnetic force components D2 and D4, however, can affect the position errors by significantly exciting torsion and bending modes of the head-stack assembly. Second, a flex cable can significantly increase position errors below 1 kHz during settling.     

六相直线感应电机模糊间接矢量控制

针对直线电机运行于复杂环境条件下,系统建模准确度不高,参数难以整定的问题,提出了一种适用于六相直线感应电机的模糊间接矢量控制方法;在同步旋转坐标系下对六相直线电机建模,并阐述了间接矢量控制的原理;将模糊控制算法应用于间接矢量控制中的速度环,根据位移和速度的偏差直接模糊调节给定电磁力,使得参数的整定不再依赖准确的系统模型,且参数调节更为简单;通过对隶属函数分区和采用中心法清晰化,减小了模糊控制算法的计算量,从而能够满足实时计算的要求;将所提算法在数字信号处理器（DSP,digital signal processor） 中实现,并在半实物仿真平台上验证,结果表明所提算法投入后,位移和速度误差减小都超过了65%,能够实现电机速度和位移的准确控制,且通用性好。     

异步电动机电磁振动噪声自动抑制方法

针对电动机噪声抑制过程受到电动机部位、零件振频的影响,导致噪声抑制效果不均等问题,提出一种异步电动机电磁振动噪声自动抑制方法.根据电磁振动中基波磁场产生的倍频力波和定转子谐波磁场产生的径向力波,得出提高力波阶数能够一定程度对噪声进行抑制.由于电动机不同部位、不同零件的振频不同,可以针对其各自特征,采取特定的抑制方法,因...     

Level choice in truncated total least squares

The method of truncated total least squares (TTLS) is an alternative to the classical truncated singular value decomposition (TSVD) used for the regularization of ill-conditioned linear systems. Truncation methods aim at limiting the contribution of noise or rounding errors by cutting off a certain number of terms in an expansion such as the singular value decomposition. To this end a truncation level k must be carefully chosen. The TTLS solution becomes more significantly dominated by noise or errors when the truncation level k is overestimated than the TSVD solution does. Model selection methods that are often applied in the context of the TSVD are modified to be applied in the context of the TTLS. The proposed modified generalized cross validation (GCV) combined with the TTLS method performs better than the classical GCV combined with the TSVD, especially, when both the coefficient matrix and the right-hand side are contaminated by noise.     

矢量水听器目标定向融合算法仿真

针对矢量水听器定向算法在不同目标方向和噪声情况下精度各有优劣的特点,和定向结果普遍具有一致性较差的缺点,将多传感器和多源数据处理中先进的数据融合技术引入定向算法的研究当中.采用基于方差的加权数据融合技术,将平均声强法、反正弦法和反余弦法这三种矢量定向算法有效融合,取长补短,单一算法的执行过程中也有效沿用了重复检测的优化思想.仿真实验验证,融合算法不仅可以提高目标的定向精度,而且大大降低检测结果的均方差,从而提高了定向结果的准确性和可靠性,对水下目标检测工程具有重要意义.     

Individual muscle contributions to the swing phase of gait: An EMG-based forward dynamics modelling approach

Muscle activation patterns and kinematic conditions at the beginning of the swing phase of gait were used as input to a forward dynamics simulation of the swing leg. A neuromusculoskeletal model was used to account for the non-linearity between muscle excitation and muscle force outputs. Following model tuning a close agreement between simulated and measured swing phase kinematics was obtained. Simulation results suggest that swing leg muscles play an important role in controlling the motion of the swing leg during walking, and that the effect of individual muscles is not necessarily restricted to the joints they span or their basic anatomical classifications.     

Inward torque and high-friction handles can reduce required muscle efforts for torque generation

OBJECTIVE: The effects of handle friction and torque direction on muscle activity and torque are empirically investigated using cylindrical handles. BACKGROUND: A torque biomechanical model that considers contact force, friction, and torque direction was evaluated using different friction handles. METHODS: Twelve adults exerted hand torque in opposite directions about the long axis of a cylinder covered with aluminum or rubber while grip force, torque, and finger flexor electromyography (EMG) were recorded. In addition, participants performed grip exertions without torque, in which they matched the EMG level obtained during previous maximum torque exertions, to allow us to determine how grip force was affected by the absence of torque. RESULTS: (a) Maximum torque was 52% greater for the high-friction rubber handle than for the low-friction aluminum handle. (b) Total normal force increased 33% with inward torque (torque applied in the direction fingertips point) and decreased 14% with outward torque (torque in the direction the thumb points), compared with that with no torque. Consequently, maximum inward torque was 45% greater than maximum outward torque. (c) The effect of torque direction was greater for the high-friction rubber handle than for the low-friction aluminum handle. CONCLUSION: The results support the proposed model, which predicts a large effect of torque direction when high-friction handles are gripped. APPLICATION: Designing tasks with high friction and inward rotations can increase the torque capability of workers of a given strength, or reduce required muscle activities for given torque exertions, thus reducing the risk of fatigue and musculoskeletal disorders.