Targeted regeneration of bone in the osteoporotic human femur

We have recently developed image processing techniques for measuring the cortical thicknesses of skeletal structures in vivo, with resolution surpassing that of the underlying computed tomography system. The resulting thickness maps can be analysed across cohorts by statistical parametric mapping. Applying these methods to the proximal femurs of osteoporotic women, we discover targeted and apparently synergistic effects of pharmaceutical osteoporosis therapy and habitual mechanical load in enhancing bone thickness. © 2011 Poole et al.

Human muscle spindles act as forward sensory models.

Modern theories of motor control incorporate forward models that combine sensory information and motor commands to predict future sensory states. Such models circumvent unavoidable neural delays associated with on-line feedback control. Here we show that signals in human muscle spindle afferents during unconstrained wrist and finger movements predict future kinematic states of their parent muscle. Specifically, we show that the discharges of type Ia afferents are best correlated with the velocity of length changes in their parent muscles approximately 100-160 ms in the future and that their discharges vary depending on motor sequences in a way that cannot be explained by the state of their parent muscle alone. We therefore conclude that muscle spindles can act as "forward sensory models": they are affected both by the current state of their parent muscle and by efferent (fusimotor) control, and their discharges represent future kinematic states. If this conjecture is correct, then sensorimotor learning implies learning how to control not only the skeletal muscles but also the fusimotor system.

Workspace comparisons of setup configurations for human-robot interaction

In virtual assembly verification or remote maintenance tasks, bimanual haptic interfaces play a crucial role in successful task completion. This paper proposes a method for objectively comparing how well a haptic interface covers the reachable workspace of human arms. Two system configurations are analyzed for a recently introduced haptic device that is based on two DLR-KUKA light weight robots: the standard configuration, where the device is opposite the human operator, and the ergonomic configuration, where the haptic device is mounted behind the human operator. The human operator directly controls the robotic arms using handles. The analysis is performed using a representation of the robot arm workspace. The merits of restricting the comparisons to the most significant regions of the human workspace are discussed. Using this method, a greater workspace correspondence for the ergonomic configuration was shown. ©2010 IEEE.

Bayesian dialogue system for the let's go spoken dialogue challenge

This paper describes how Bayesian updates of dialogue state can be used to build a bus information spoken dialogue system. The resulting system was deployed as part of the 2010 Spoken Dialogue Challenge. The purpose of this paper is to describe the system, and provide both simulated and human evaluations of its performance. In control tests by human users, the success rate of the system was 24.5% higher than the baseline Lets Go! system. ©2010 IEEE.

On-line policy optimisation of spoken dialogue systems via live interaction with human subjects

Statistical dialogue models have required a large number of dialogues to optimise the dialogue policy, relying on the use of a simulated user. This results in a mismatch between training and live conditions, and significant development costs for the simulator thereby mitigating many of the claimed benefits of such models. Recent work on Gaussian process reinforcement learning, has shown that learning can be substantially accelerated. This paper reports on an experiment to learn a policy for a real-world task directly from human interaction using rewards provided by users. It shows that a usable policy can be learnt in just a few hundred dialogues without needing a user simulator and, using a learning strategy that reduces the risk of taking bad actions. The paper also investigates adaptation behaviour when the system continues learning for several thousand dialogues and highlights the need for robustness to noisy rewards. © 2011 IEEE.

Deformation measurement of a human chest experiencing global motion

Current state-of-the-art techniques for determination of the change in volume of human chests, used in lung-function measurement, calculate the volume bounded by a reconstructed chest surface and its projection on to an approximately parallel static plane over a series of time instants. This method works well so long as the subject does not move globally relative to the reconstructed surface's co-ordinate system. In practice this means the subject has to be braced, which restricts the technique's use. We present here a method to compensate for global motion of the subject, allowing accurate measurement while free-standing, and also while undergoing intentional motion. © 2012 Springer-Verlag.

Human pavlovian-instrumental transfer.

The vigor with which a participant performs actions that produce valuable outcomes is subject to a complex set of motivational influences. Many of these are believed to involve the amygdala and the nucleus accumbens, which act as an interface between limbic and motor systems. One prominent class of influences is called pavlovian-instrumental transfer (PIT), in which the motivational characteristics of a predictor influence the vigor of an action with respect to which it is formally completely independent. We provide a demonstration of behavioral PIT in humans, with an audiovisual predictor of the noncontingent delivery of money inducing participants to perform more avidly an action involving squeezing a handgrip to earn money. Furthermore, using functional magnetic resonance imaging, we show that this enhanced motivation was associated with a trial-by-trial correlation with the blood oxygenation level-dependent (BOLD) signal in the nucleus accumbens and a subject-by-subject correlation with the BOLD signal in the amygdala. Our data dovetails well with the animal literature and sheds light on the neural control of vigor.

Frames, biases, and rational decision-making in the human brain.

Human choices are remarkably susceptible to the manner in which options are presented. This so-called "framing effect" represents a striking violation of standard economic accounts of human rationality, although its underlying neurobiology is not understood. We found that the framing effect was specifically associated with amygdala activity, suggesting a key role for an emotional system in mediating decision biases. Moreover, across individuals, orbital and medial prefrontal cortex activity predicted a reduced susceptibility to the framing effect. This finding highlights the importance of incorporating emotional processes within models of human choice and suggests how the brain may modulate the effect of these biasing influences to approximate rationality.

Healthcare human reliability analysis - By heart

As part of the investigations into a surgical incident involving the accidental retention inside a patient's venous system of a guide wire for central venous catheterisation (CVC), the Human Error Assessment and Reduction Technique (HEART) was used to examine the potential for further occurrences. It was found to be time-efficient and to yield plausible probabilities of human error, although its use in healthcare has challenges, suggesting adaptation would be beneficial.