40,661 research outputs found

    A Simple Mono-Dimensional Approach for Lap Time Optimisation

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    Lap time minimisation methods have great relevance in the analysis of race tracks, and in the design and optimisation of race vehicles. Several lap time minimisation approaches have been proposed in the literature, which are computationally demanding because they need to either solve differential equations or to implement a forward−backward integration based on an apex-finding method. This paper proposes an alternative method, based on a mono-dimensional quasi-steady-state numerical approach. The proposed approach uses a simplified vehicle model accounting for combined tyre−road interactions, aerodynamic effects, and power limitations. The method exploits the knowledge of the curvature of the trajectory, which is worked out through a rigorous approach that allows for the use trajectories defined with respect to ageneric curve parameter and not necessarily the arc length. An iterative routine is implemented that exploits the vehicle dynamics, without solving differential equations or performing forward−backward integrations from the trajectory apexes. Simulations are carried out on three different tracks and are shown to be computationally efficient. Despite being intentionally simple, the proposed method allows to grasp key aspects of the problem, such as the effect of the combined tyre−road interactions on the acceleration profiles, and the effect of aerodynamic drag and downforce on the position of the braking point on the track and on the speed profile

    Changing ideas about others' intentions: updating prior expectations tunes activity in the human motor system

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    Predicting intentions from observing another agent’s behaviours is often thought to depend on motor resonance – i.e., the motor system’s response to a perceived movement by the activation of its stored motor counterpart, but observers might also rely on prior expectations, especially when actions take place in perceptually uncertain situations. Here we assessed motor resonance during an action prediction task using transcranial magnetic stimulation to probe corticospinal excitability (CSE) and report that experimentally-induced updates in observers’ prior expectations modulate CSE when predictions are made under situations of perceptual uncertainty. We show that prior expectations are updated on the basis of both biomechanical and probabilistic prior information and that the magnitude of the CSE modulation observed across participants is explained by the magnitude of change in their prior expectations. These findings provide the first evidence that when observers predict others’ intentions, motor resonance mechanisms adapt to changes in their prior expectations. We propose that this adaptive adjustment might reflect a regulatory control mechanism that shares some similarities with that observed during action selection. Such a mechanism could help arbitrate the competition between biomechanical and probabilistic prior information when appropriate for prediction

    Causative role of left aIPS in coding shared goals during human-avatar complementary joint actions

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    Successful motor interactions require agents to anticipate what a partner is doing in order to predictively adjust their own movements. Although the neural underpinnings of the ability to predict others' action goals have been well explored during passive action observation, no study has yet clarified any critical neural substrate supporting interpersonal coordination during active, non-imitative (complementary) interactions. Here, we combine non-invasive inhibitory brain stimulation (continuous Theta Burst Stimulation) with a novel human-avatar interaction task to investigate a causal role for higher-order motor cortical regions in supporting the ability to predict and adapt to others' actions. We demonstrate that inhibition of left anterior intraparietal sulcus (aIPS), but not ventral premotor cortex, selectively impaired individuals' performance during complementary interactions. Thus, in addition to coding observed and executed action goals, aIPS is crucial in coding 'shared goals', that is, integrating predictions about one's and others' complementary actions

    Testing rTMS-Induced Neuroplasticity: A Single Case Study of Focal Hand Dystonia

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    Focal hand dystonia in musicians is a neurological motor disorder in which aberrant plasticity is caused by excessive repetitive use. This work's purposes were to induce plasticity changes in a dystonic musician through five daily thirty-minute sessions of 1\u2009Hz repetitive transcranial magnetic stimulation (rTMS) applied to the left M1 by using neuronavigated stimulation and to reliably measure the effect of these changes. To this aim, the relationship between neuroplasticity changes and motor recovery was investigated using fine-grained kinematic analysis. Our results suggest a statistically significant improvement in motor coordination both in a task resembling the dystonic-inducing symptoms and in a reach-to-grasp task. This single case study supports the safe and effective use of noninvasive brain stimulation in neurologic patients and highlights the importance of evaluating outcomes in measurable ways. This issue is a key aspect to focus on to classify the clinical expression of dystonia. These preliminary results promote the adoption of kinematic analysis as a valuable diagnostic tool

    Facilitating the driver detection of road surface type by selective manipulation of the steering-wheel acceleration signal

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    Copyright @ 2012 by Institution of Mechanical Engineers.Previous research has investigated the possibility of facilitating the driver detection of road surface type by means of selective manipulation of the steering-wheel acceleration signal. In previous studies a selective increase in acceleration amplitude has been found to facilitate road-surface-type detection, as has selective manipulation of the individual transient events which are present in the signal. The previous research results have been collected into a first guideline for the optimization of the steering-wheel acceleration signal, and the guideline has been tested in the current study. The test stimuli used in the current study were ten steering-wheel acceleration-time histories which were selected from an extensive database of road test measurements performed by the research group. The time histories, which were all from midsized European automobiles and European roads, were selected such that the widest possible operating envelope could be achieved in terms of the r.m.s. value of the steering acceleration, the kurtosis, the power spectral density function, and the number of transient events present in the signal. The time histories were manipulated by means of the mildly non-stationary mission synthesis algorithm in order to increase, by a factor of 2, both the number and the size of the transient events contained within the frequency interval from 20 Hz to 60Hz. The ensemble, composed of both the unmanipulated and the manipulated time histories, was used to perform a laboratory-based detection task with 15 participants, who were presented the individual stimuli in random order. The participants were asked to state, by answering 'yes' or 'no', whether each stimulus was considered to be from the road surface that was displayed in front of them by means of a large photograph on a board. The results suggest that the selectively manipulated steering-wheel acceleration stimuli produced improved detection for eight of the ten road surface types which were tested, with a maximum improvement of 14 per cent in the case of the broken road surface. The selective manipulation did lead, however, to some degradation in detection for the motorway road stimulus and for the noise road stimulus, thus suggesting that the current guideline is not universally optimal for all road surfaces

    Non-linear dependency of the subjective perceived intensity of steering wheel rotational vibration

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    This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2009 ElsevierThe present study has established equal sensation curves for steering wheel hand-arm rotational vibration. Psychophysical response tests of 20 participants were performed in a steering wheel rotational vibration simulator using the category-ratio Borg CR10 scale procedure for direct estimation of perceived vibration intensity. The test stimuli used were sinusoidal vibrations at 22 third octave band centre frequencies in the range from 3 to 400 Hz, with acceleration amplitudes in the range from 0.06 to 30 m/s(2) r.m.s. A multivariate regression analysis was performed on the mean perceived intensity Borg CR10 values as a function of the two independent parameters of the vibration frequency and amplitude. The results suggested a non-linear dependency of the subjective perceived intensity on both the steering wheel rotational vibration frequency and amplitude. The equal sensation curves were found to be characterised by a decreased sensitivity to hand-arm vibration with increasing frequency from 10 to 400 Hz, but by an increased sensitivity with increasing frequency from 4 to 10 Hz. A 6th order polynomial model has been proposed as a best fit regression model from which the equal sensation curves for steering wheel rotational vibration are derived.Relevance to industry: For the manufactures of automobiles, steering systems and other automobile components this study provides a mathematical model from which one or more new frequency weightings for the use in evaluating the perceived intensity of steering wheel rotational vibration are derived. (C) 2008 Elsevier B.V. All rights reserved
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