Generative topographic mapping applied to clustering and visualization of motor unit action potentials

The identification and visualization of clusters formed by motor unit action potentials (MUAPs) is an essential step in investigations seeking to explain the control of the neuromuscular system. This work introduces the generative topographic mapping (GTM), a novel machine learning tool, for clustering of MUAPs, and also it extends the GTM technique to provide a way of visualizing MUAPs. The performance of GTM was compared to that of three other clustering methods: the self-organizing map (SOM), a Gaussian mixture model (GMM), and the neural-gas network (NGN). The results, based on the study of experimental MUAPs, showed that the rate of success of both GTM and SOM outperformed that of GMM and NGN, and also that GTM may in practice be used as a principled alternative to the SOM in the study of MUAPs. A visualization tool, which we called GTM grid, was devised for visualization of MUAPs lying in a high-dimensional space. The visualization provided by the GTM grid was compared to that obtained from principal component analysis (PCA). (c) 2005 Elsevier Ireland Ltd. All rights reserved.

Application of neural network to hybrid systems with binary inputs

Boolean input systems are in common used in the electric industry. Power supplies include such systems and the power converter represents these. For instance, in power electronics, the control variable are the switching ON and OFF of components as thyristors or transistors. The purpose of this paper is to use neural network (NN) to control continuous systems with Boolean inputs. This method is based on classification of system variations associated with input configurations. The classical supervised backpropagation algorithm is used to train the networks. The training of the artificial neural network and the control of Boolean input systems are presented. The design procedure of control systems is implemented on a nonlinear system. We apply those results to control an electrical system composed of an induction machine and its power converter.

A Gentle/S approach to robot assisted neuro-rehabilitation

Movement disorders (MD) include a group of neurological disorders that involve neuromotor systems. MD can result in several abnormalities ranging from an inability to move, to severe constant and excessive movements. Strokes are a leading cause of disability affecting largely the older people worldwide. Traditional treatments rely on the use of physiotherapy that is partially based on theories and also heavily reliant on the therapists training and past experience. The lack of evidence to prove that one treatment is more effective than any other makes the rehabilitation of stroke patients a difficult task. UL motor re-learning and recovery levels tend to improve with intensive physiotherapy delivery. The need for conclusive evidence supporting one method over the other and the need to stimulate the stroke patient clearly suggest that traditional methods lack high motivational content, as well as objective standardised analytical methods for evaluating a patient's performance and assessment of therapy effectiveness. Despite all the advances in machine mediated therapies, there is still a need to improve therapy tools. This chapter describes a new approach to robot assisted neuro-rehabilitation for upper limb rehabilitation. Gentle/S introduces a new approach on the integration of appropriate haptic technologies to high quality virtual environments, so as to deliver challenging and meaningful therapies to people with upper limb impairment in consequence of a stroke. The described approach can enhance traditional therapy tools, provide therapy "on demand" and can present accurate objective measurements of a patient's progression. Our recent studies suggest the use of tele-presence and VR-based systems can potentially motivate patients to exercise for longer periods of time. Two identical prototypes have undergone extended clinical trials in the UK and Ireland with a cohort of 30 stroke subjects. From the lessons learnt with the Gentle/S approach, it is clear also that high quality therapy devices of this nature have a role in future delivery of stroke rehabilitation, and machine mediated therapies should be available to patient and his/her clinical team from initial hospital admission, through to long term placement in the patient's home following hospital discharge.

Authors' response to letter to the editor

Letter to the editor relates to article Warwick, K. and Nasuto, S.J (2006). 'Historical and Current Machine Intelligence.' IEEE Instrumentation and Measurement Magazine 9 (6):20-26.

Driving saccade to pursuit using image motion

Within the context of active vision, scant attention has been paid to the execution of motion saccades—rapid re-adjustments of the direction of gaze to attend to moving objects. In this paper we first develop a methodology for, and give real-time demonstrations of, the use of motion detection and segmentation processes to initiate capture saccades towards a moving object. The saccade is driven by both position and velocity of the moving target under the assumption of constant target velocity, using prediction to overcome the delay introduced by visual processing. We next demonstrate the use of a first order approximation to the segmented motion field to compute bounds on the time-to-contact in the presence of looming motion. If the bound falls below a safe limit, a panic saccade is fired, moving the camera away from the approaching object. We then describe the use of image motion to realize smooth pursuit, tracking using velocity information alone, where the camera is moved so as to null a single constant image motion fitted within a central image region. Finally, we glue together capture saccades with smooth pursuit, thus effecting changes in both what is being attended to and how it is being attended to. To couple the different visual activities of waiting, saccading, pursuing and panicking, we use a finite state machine which provides inherent robustness outside of visual processing and provides a means of making repeated exploration. We demonstrate in repeated trials that the transition from saccadic motion to tracking is more likely to succeed using position and velocity control, than when using position alone.

Generating virtual environments to allow increased access to the built environment

The problems encountered by individuals with disabilities when accessing large public buildings is described and a solution based on the generation of virtual models of the built environment is proposed. These models are superimposed on a control network infrastructure, currently utilised in intelligent building applications such as lighting, heating and access control. The use of control network architectures facilitates the creation of distributed models that closely mirror both the physical and control properties of the environment. The model of the environment is kept local to the installation which allows the virtual representation of a large building to be decomposed into an interconnecting series of smaller models. This paper describes two methods of interacting with the virtual model, firstly a two dimensional aural representation that can be used as the basis of a portable navigational device. Secondly an augmented reality called DAMOCLES that overlays additional information on a user’s normal field of view. The provision of virtual environments offers new possibilities in the man-machine interface so that intuitive access to network based services and control functions can be given to a user.