Vision of the body and the differentiation of perceived body side in touch

Although tactile representations of the two body sides are initially segregated into opposite hemispheres of the brain, behavioural interactions between body sides exist and can be revealed under conditions of tactile double simultaneous stimulation (DSS) at the hands. Here we examined to what extent vision can affect body side segregation in touch. To this aim, we changed hand-related visual input while participants performed a go/no-go task to detect a tactile stimulus delivered to one target finger (e.g., right index), stimulated alone or with a concurrent non-target finger either on the same hand (e.g., right middle finger) or on the other hand (e.g., left index finger = homologous; left middle finger = non-homologous). Across experiments, the two hands were visible or occluded from view (Experiment 1), images of the two hands were either merged using a morphing technique (Experiment 2), or were shown in a compatible vs incompatible position with respect to the actual posture (Experiment 3). Overall, the results showed reliable interference effects of DSS, as compared to target-only stimulation. This interference varied as a function of which non-target finger was stimulated, and emerged both within and between hands. These results imply that the competition between tactile events is not clearly segregated across body sides. Crucially, non-informative vision of the hand affected overall tactile performance only when a visual/proprioceptive conflict was present, while neither congruent nor morphed hand vision affected tactile DSS interference. This suggests that DSS operates at a tactile processing stage in which interactions between body sides can occur regardless of the available visual input from the body.

A vision for attaining food security

Food is fundamental to human wellbeing and development. Increased food production remains a cornerstone strategy in the effort to alleviate global food insecurity. But despite the fact that global food production over the past half century has kept ahead of demand, today around one billion people do not have enough to eat, and a further billion lack adequate nutrition. Food insecurity is facing mounting supply-side and demand-side pressures; key among these are climate change, urbanisation, globalisation, population increases, disease, as well as a number of other factors that are changing patterns of food consumption. Many of the challenges to equitable food access are concentrated in developing countries where environmental pressures including climate change, population growth and other socio-economic issues are concentrated. Together these factors impede people's access to sufficient, nutritious food; chiefly through affecting livelihoods, income and food prices. Food security and human development go hand in hand, and their outcomes are co-determined to a significant degree. The challenge of food security is multi-scalar and cross-sector in nature. Addressing it will require the work of diverse actors to bring sustained improvements inhuman development and to reduce pressure on the environment. Unless there is investment in future food systems that are similarly cross-level, cross-scale and cross-sector, sustained improvements in human wellbeing together with reduced environmental risks and scarcities will not be achieved. This paper reviews current thinking, and outlines these challenges. It suggests that essential elements in a successfully adaptive and proactive food system include: learning through connectivity between scales to local experience and technologies high levels of interaction between diverse actors and sectors ranging from primary producers to retailers and consumers, and use of frontier technologies.

Analysis of EEG signal to detect motor command generation towards stroke rehabilitation

Our aim is to reconstruct the brain-body loop of stroke patients via an EEG-driven robotic system. After the detection of motor command generation, the robotic arm should assist patient’s movement at the correct moment and in a natural way. In this study we performed EEG measurements from healthy subjects performing discrete spontaneous motion. An EEG analysis based on the temporal correlation of the brain activity was employed to determine the onset of single motion motor command generation.

A feasible study of EEG-driven assistive robotic system for stroke rehabilitation

Stroke is a medical emergency and can cause a neurological damage, affecting the motor and sensory systems. Harnessing brain plasticity should make it possible to reconstruct the closed loop between the brain and the body, i.e., association of the generation of the motor command with the somatic sensory feedback might enhance motor recovery. In order to aid reconstruction of this loop with a robotic device it is necessary to assist the paretic side of the body at the right moment to achieve simultaneity between motor command and feedback signal to somatic sensory area in brain. To this end, we propose an integrated EEG-driven assistive robotic system for stroke rehabilitation. Depending on the level of motor recovery, it is important to provide adequate stimulation for upper limb motion. Thus, we propose an assist arm incorporating a Magnetic Levitation Joint that can generate a compliant motion due to its levitation and mechanical redundancy. This paper reports on a feasibility study carried out to verify the validity of the robot sensing and on EEG measurements conducted with healthy volunteers while performing a spontaneous arm flexion/extension movement. A characteristic feature was found in the temporal evolution of EEG signal in the single motion prior to executed motion which can aid in coordinating timing of the robotic arm assistance onset.

Prescription software for recovery and rehabilitation using Microsoft Kinect

Brain injuries, including stroke, can be debilitating incidents with potential for severe long term effects; many people stop making significant progress once leaving in-patient medical care and are unable to fully restore their quality of life when returning home. The aim of this collaborative project, between the Royal Berkshire NHS Foundation Trust and the University of Reading, is to provide a low cost portable system that supports a patient's condition and their recovery in hospital or at home. This is done by providing engaging applications with targeted gameplay that is individually tailored to the rehabilitation of the patient's symptoms. The applications are capable of real-time data capture and analysis in order to provide information to therapists on patient progress and to further improve the personalized care that an individual can receive.

Disparity-driven vs blur-driven models of accommodation and convergence in binocular vision and intermittent strabismus

Background. Current models of concomitant, intermittent strabismus, heterophoria, convergence and accommodation anomalies are either theoretically complex or incomplete. We propose an alternative and more practical way to conceptualize clinical patterns. Methods. In each of three hypothetical scenarios (normal; high AC/A and low CA/C ratios; low AC/A and high CA/C ratios) there can be a disparity-biased or blur-biased “style”, despite identical ratios. We calculated a disparity bias index (DBI) to reflect these biases. We suggest how clinical patterns fit these scenarios and provide early objective data from small illustrative clinical groups. Results. Normal adults and children showed disparity bias (adult DBI 0.43 (95%CI 0.50-0.36), child DBI 0.20 (95%CI 0.31-0.07) (p=0.001). Accommodative esotropes showed less disparity-bias (DBI 0.03). In the high AC/A and low CA/C scenario, early presbyopes had mean DBI of 0.17 (95%CI 0.28-0.06), compared to DBI of -0.31 in convergence excess esotropes. In the low AC/A and high CA/C scenario near exotropes had mean DBI of 0.27, while we predict that non-strabismic, non-amblyopic hyperopes with good vision without spectacles will show lower DBIs. Disparity bias ranged between 1.25 and -1.67. Conclusions. Establishing disparity or blur bias, together with knowing whether convergence to target demand exceeds accommodation or vice versa explains clinical patterns more effectively than AC/A and CA/C ratios alone. Excessive bias or inflexibility in near-cue use increases risk of clinical problems. We suggest clinicians look carefully at details of accommodation and convergence changes induced by lenses, dissociation and prisms and use these to plan treatment in relation to the model.

Development of a wearable assistive soft robotic device for elbow rehabilitation

The loss of motor function at the elbow joint can result as a consequence of stroke. Stroke is a clinical illness resulting in long lasting neurological deficits often affecting somatosensory and motor cortices. More than half of those that recover from a stroke survive with disability in their upper arm and need rehabilitation therapy to help in regaining functions of daily living. In this paper, we demonstrated a prototype of a low-cost, ultra-light and wearable soft robotic assistive device that could aid administration of elbow motion therapies to stroke patients. In order to assist the rotation of the elbow joint, the soft modules which consist of soft wedge-like cellular units was inflated by air to produce torque at the elbow joint. Highly compliant rotation can be naturally realised by the elastic property of soft silicone and pneumatic control of air. Based on the direct visual-actuation control, a higher control loop utilised visual processing to apply positional control, the lower control loop was implemented by an electronic circuit to achieve the desired pressure of the soft modules by Pulse Width Modulation. To examine the functionality of the proposed soft modular system, we used an anatomical model of the upper limb and performed the experiments with healthy participants.

Feasibility study on EEG driven robotic system to realize efficient stroke rehabilitation

We aim to develop an efficient robotic system for stroke rehabilitation, in which a robotic arm moves the hemiplegic upper limb when the patient tries to move it. In order to achieve this goal we have considered a method to detect the patient's intended motion using EEG (Electroencephalogram), and have designed a rehabilitation robot based on a Redundant Drive Method. In this paper, we propose an EEG driven rehabilitation robot system and present initial results evaluating the feasibility of the proposed system.