How active gaze informs the hand in sequential pointing movements

Visual information is vital for fast and accurate hand movements. It has been demonstrated that allowing free eye movements results in greater accuracy than when the eyes maintain centrally fixed. Three explanations as to why free gaze improves accuracy are: shifting gaze to a target allows visual feedback in guiding the hand to the target (feedback loop), shifting gaze generates ocular-proprioception which can be used to update a movement (feedback-feedforward), or efference copy could be used to direct hand movements (feedforward). In this experiment we used a double-step task and manipulated the utility of ocular-proprioceptive feedback from eye to head position by removing the second target during the saccade. We confirm the advantage of free gaze for sequential movements with a double-step pointing task and document eye-hand lead times of approximately 200 ms for both initial movements and secondary movements. The observation that participants move gaze well ahead of the current hand target dismisses foveal feedback as a major contribution. We argue for a feedforward model based on eye movement efference as the major factor in enabling accurate hand movements. The results with the double-step target task also suggest the need for some buffering of efference and ocular-proprioceptive signals to cope with the situation where the eye has moved to a location ahead of the current target for the hand movement. We estimate that this buffer period may range between 120 and 200 ms without significant impact on hand movement accuracy.

The role of visual and nonvisual information in the control of locomotion

During locomotion, retinal flow, gaze angle, and vestibular information can contribute to one's perception of self-motion. Their respective roles were investigated during active steering: Retinal flow and gaze angle were biased by altering the visual information during computer-simulated locomotion, and vestibular information was controlled through use of a motorized chair that rotated the participant around his or her vertical axis. Chair rotation was made appropriate for the steering response of the participant or made inappropriate by rotating a proportion of the veridical amount. Large steering errors resulted from selective manipulation of retinal flow and gaze angle, and the pattern of errors provided strong evidence for an additive model of combination. Vestibular information had little or no effect on steering performance, suggesting that vestibular signals are not integrated with visual information for the control of steering at these speeds.

Eye-movements aid the control of locomotion

Eye-movements have long been considered a problem when trying to understand the visual control of locomotion. They transform the retinal image from a simple expanding pattern of moving texture elements (pure optic flow), into a complex combination of translation and rotation components (retinal flow). In this article we investigate whether there are measurable advantages to having an active free gaze, over a static gaze or tracking gaze, when steering along a winding path. We also examine patterns of free gaze behavior to determine preferred gaze strategies during active locomotion. Participants were asked to steer along a computer-simulated textured roadway with free gaze, fixed gaze, or gaze tracking the center of the roadway. Deviation of position from the center of the road was recorded along with their point of gaze. It was found that visually tracking the middle of the road produced smaller steering errors than for fixed gaze. Participants performed best at the steering task when allowed to sample naturally from the road ahead with free gaze. There was some variation in the gaze strategies used, but sampling was predominantly of areas proximal to the center of the road. These results diverge from traditional models of flow analysis.

Application of constrained predictive control on a 3D crane system

This paper describes the SIMULINK implementation of a constrained predictive control algorithm based on quadratic programming and linear state space models, and its application to a laboratory-scale 3D crane system. The algorithm is compatible with Real Time. Windows Target and, in the case of the crane system, it can be executed with a sampling period of 0.01 s and a prediction horizon of up to 300 samples, using a linear state space model with 3 inputs, 5 outputs and 13 states.

Robust identification for linear-in-the-parameters models

In this paper new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness, including three algorithms using combined A- or D-optimality or PRESS statistic (Predicted REsidual Sum of Squares) with regularised orthogonal least squares algorithm respectively. A common characteristic of these algorithms is that the inherent computation efficiency associated with the orthogonalisation scheme in orthogonal least squares or regularised orthogonal least squares has been extended such that the new algorithms are computationally efficient. A numerical example is included to demonstrate effectiveness of the algorithms. Copyright (C) 2003 IFAC.

Reach & grasp therapy: Design and control of a 9-DOF robotic neuro-rehabilitation system

This paper presents the Gentle/G integrated system for reach & grasp therapy retraining following brain injury. The design, control and integration of an experimental grasp assistance unit is described for use in robot assisted stroke rehabilitation. The grasp assist unit is intended to work with the hardware and software of the Gentle/S robot although the hardware could be adapted to other rehabilitation applications. When used with the Gentle/S robot a total of 6 active and 3 passive degrees of freedom are available to provide active, active assist or passive grasp retraining in combination with reaching movements in a reach-grasp-transfer-release sequence.

Combining Human and Machine Brains - Practical systems in information & control

In this paper a look is taken at how the use of implant technology can be used to either increase the range of the abilities of a human and/or diminish the effects of a neural illness, such as Parkinson's Disease. The key element is the need for a clear interface linking the human brain directly with a computer. The area of interest here is the use of implant technology, particularly where a connection is made between technology and the human brain and/or nervous system. Pilot tests and experimentation are invariably carried out apriori to investigate the eventual possibilities before human subjects are themselves involved. Some of the more pertinent animal studies are discussed here. The paper goes on to describe human experimentation, in particular that carried out by the author himself, which led to him receiving a neural implant which linked his nervous system bi-directionally with the internet. With this in place neural signals were transmitted to various technological devices to directly control them. In particular, feedback to the brain was obtained from the fingertips of a robot hand and ultrasonic (extra) sensory input. A view is taken as to the prospects for the future, both in the near term as a therapeutic device and in the long term as a form of enhancement.

Generic control interface for networked haptic virtual environments

As Virtual Reality pushes the boundaries of the human computer interface new ways of interaction are emerging. One such technology is the integration of haptic interfaces (force-feedback devices) into virtual environments. This modality offers an improved sense of immersion to that achieved when relying only on audio and visual modalities. The paper introduces some of the technical obstacles such as latency and network traffic that need to be overcome for maintaining a high degree of immersion during haptic tasks. The paper describes the advantages of integrating haptic feedback into systems, and presents some of the technical issues inherent in a networked haptic virtual environment. A generic control interface has been developed to seamlessly mesh with existing networked VR development libraries.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Simplifying Bode's maximum available feedback design

Bode's method for obtaining 'maximum obtainable feedback' is a good example of a nontrivial feedback system design technique, but it is largely overlooked. This paper shows how the associated mathematics can be simplified and linear elements used in its implementation, so as to make it accessible for teaching to undergraduates.

Effects of biologically active tumour-promoting and non-promoting phorbol esters on in vivo growth of melanocytic cells

Sapintoxin A (SAP A), a naturally occurring biologically active but non-promoting phorbol ester, acts as an effective in vitro mitogen for freshly derived human melanocytes. Seven days after addition of 50 nM SAP A there was a four to fivefold increase in melanocyte number over that observed in untreated control cultures comparable to that achieved with a 50 nM concentration of 12-0-tetradecanoylphorbol 13-acetate (TPA). The fluorescent stage 2 promoter sapintoxin D (SAP D) also supported the growth of these cells, with a 50 nM dose producing an increase in cell number comparable to that observed with 200 nM TPA. Similar results were obtained with an established, but non-tumorigenic, line of murine melanocytes. The same compounds exerted a potent anti-proliferative effect against transformed melanocyte lines of murine and human origin associated with morphological alterations and an increase in melanin production consistent with induced cytodifferentiation.

Extracts of tropical African spices are active against Plutella xylostella

Extracts from Piper guineense, Aframomum melegueta, Aframomum citratum and Afrostyrax kamerunensis were investigated for their antifeedant, lethal and developmental effects against Plutella xylostella larvae through laboratory dual-choice tests and topical application. Water and ethanol extracts of P. guineense were dose-dependent antifeedants at concentrations ≥300 and 500 ppm, respectively, whilst methanol extracts required ≥1,000 ppm. Methanol and hexane extracts of A. melegueta acted at ≥100 ppm and water extracts at ≥300 ppm, but ethanol extracts were deterring feeding only slightly at ≥1,000 ppm. Hexane and methanol extracts of A. citratum inhibited feeding at ≥300 ppm and water extracts did so at ≥500 ppm. None of the Afrostyrax kamerunensis extracts deterred feeding at any of the concentrations tested. No mortality was observed at any of the concentrations after topical application of the extracts on the larvae. However, the effects on larval development varied with extract concentration and larval age. Ingestion of the water and ethanol extracts of P. guineense caused 100% mortality of second instars at ≥100 ppm two to three days after infestation (DAI). Methanol and water extracts of A. melegueta and A. citratum, respectively, achieved ≥80% mortality of larvae at concentrations of ≥500 ppm and ≥1,000 ppm, respectively. With third instars, the mortalities were significantly lower; however, the P. guineense water or ethanol extracts caused 100% mortality two to four DAI. Larvae that survived till pupation had significantly longer larval periods compared with the control after application of A. melegueta extracts. We concluded that potent extracts from Aframomum melegueta, Aframomum citratum and especially P. guineense could be used as complementary measures in the management of P. xylostella by subsistence farmers.

Self-tuning regulators—a state space approach

This paper employs a state space system description to provide a pole placement scheme via state feedback. It is shown that when a recursive least squares estimation scheme is used, the feedback employed can be expressed simply in terms of the estimated system parameters. To complement the state feedback approach, a method employing both state feedback and linear output feedback is discussed. Both methods arc then compared with the previous output polynomial type feedback schemes.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.