The potential of visual cues to overcome freezing of gait in Parkinson’s disease

Freezing of Gait (FOG) is arguably the most disabling motor dysfunction in Parkinson’s Disease (PD), being pharmacological an unfeasible approach in the long-run, which justifies the emergence of non-pharmacological solutions. In fact, patients easily overcome FOG when it is provided a rhythmical temporal information (external cues), favoring a goal-directed gait (biofeedback systems). In this paper, it was intended to assess the tolerability and acceptability of a healthy group towards an augmented reality interface which aims to apply visual cues in temporal synchrony with heel-strike event by an augmented reality glasses. It is intended to be later assessed, the visual cues ability to facilitate motor activity in PD patients. The experimental setup comprised a group of 15 healthy subjects, being those instructed to perform a 30 m straight-walking along an unobstructed walkway, both in the presence of external cues and without any feedback applied. Questionnaires proven visual feedback to be perceived by the users with ease. Users reported interest and curiosity towards the system and proved to be keen to integrate the system into their daily life if they would ever face this disease

Integrated design approach for responsive solar-shadings in double skin facades in hot arid climate

Ph. D. Thesis.To deliver climate adaptive architecture, current trends in architecture are directed towards dynamic and responsive building skins. ‘Responsive building skin’ is used to describe the ability of building envelopes to adapt in real time in response to external environmental conditions. Recent attention has focused on ‘soft robotics’ approach which uses soft and/or extensible materials to deform with muscle‐like actuation, mimicking biological systems. Material embedded actuation can autonomously alter shading systems’ morphology stimulated by external environmental conditions. Passively thermally‐activated shading systems offer responsive actuation by solar‐radiation and stratified hot air in a double skin façade (DSF) without recourse to energy consuming systems. This research identifies the intersection between bio‐inspiration, folding principles and smart materials to integrate the underlying mechanisms in responsive solar‐shading systems and assesses their environmental performance. The thesis proposes an interdisciplinary mixed methodology linking hands‐on experimentation with environmental performance simulation of responsive building skins. ‘Practice‐led approach’ is used to explore the design potential of responsive systems using smart materials. ‘Computational Fluid Dynamics’ (CFD) numerical methods are used to measure the impact of responsive solar‐shading systems on multiple environmental factors in a DSF cavity. This helps the design decisions, selection and customisation of smart materials. Hands‐on experimentation is used to explore various prototypes, leading to the selection of a folded prototype, to be simulated for environmental performance. Solar‐shading systems are tested within a DSF, in an hot arid climate. Flat and folded solar‐shading devices are installed in a DSF cavity with three aperture sizes (30%, 50% & 70%) to represent the responsive system states. Point‐in‐time simulations are carried at 9:00 am, 12:00 pm and 15:00 pm in peak summer and winter day. The developed analytical design framework presents different design parameters for responsive solar‐shading systems to guide decision‐making in research of climate actuated smart shading systems. Keywords: Responsive skins, Adaptive facades, Soft robotics, Bio‐inspiration, Origami, Deployable structures, Actuation, Smart materials, Shape memory alloys, Double skin facades, Energy efficiency, Digital simulation, CFD Modelling

Reactive direction control for a mobile robot: A locust-like control of escape direction emerges when a bilateral pair of model locust visual neurons are integrated

Locusts possess a bilateral pair of uniquely identifiable visual neurons that respond vigorously to the image of an approaching object. These neurons are called the lobula giant movement detectors (LGMDs). The locust LGMDs have been extensively studied and this has lead to the development of an LGMD model for use as an artificial collision detector in robotic applications. To date, robots have been equipped with only a single, central artificial LGMD sensor, and this triggers a non-directional stop or rotation when a potentially colliding object is detected. Clearly, for a robot to behave autonomously, it must react differently to stimuli approaching from different directions. In this study, we implement a bilateral pair of LGMD models in Khepera robots equipped with normal and panoramic cameras. We integrate the responses of these LGMD models using methodologies inspired by research on escape direction control in cockroaches. Using ‘randomised winner-take-all’ or ‘steering wheel’ algorithms for LGMD model integration, the khepera robots could escape an approaching threat in real time and with a similar distribution of escape directions as real locusts. We also found that by optimising these algorithms, we could use them to integrate the left and right DCMD responses of real jumping locusts offline and reproduce the actual escape directions that the locusts took in a particular trial. Our results significantly advance the development of an artificial collision detection and evasion system based on the locust LGMD by allowing it reactive control over robot behaviour. The success of this approach may also indicate some important areas to be pursued in future biological research

Modeling networks of spiking neurons as interacting processes with memory of variable length

We consider a new class of non Markovian processes with a countable number of interacting components, both in discrete and continuous time. Each component is represented by a point process indicating if it has a spike or not at a given time. The system evolves as follows. For each component, the rate (in continuous time) or the probability (in discrete time) of having a spike depends on the entire time evolution of the system since the last spike time of the component. In discrete time this class of systems extends in a non trivial way both Spitzer's interacting particle systems, which are Markovian, and Rissanen's stochastic chains with memory of variable length which have finite state space. In continuous time they can be seen as a kind of Rissanen's variable length memory version of the class of self-exciting point processes which are also called "Hawkes processes", however with infinitely many components. These features make this class a good candidate to describe the time evolution of networks of spiking neurons. In this article we present a critical reader's guide to recent papers dealing with this class of models, both in discrete and in continuous time. We briefly sketch results concerning perfect simulation and existence issues, de-correlation between successive interspike intervals, the longtime behavior of finite non-excited systems and propagation of chaos in mean field systems

Is defining life pointless? Operational definitions at the frontiers of Biology

Despite numerous and increasing attempts to define what life is, there is no consensus on necessary and sufficient conditions for life. Accordingly, some scholars have questioned the value of definitions of life and encouraged scientists and philosophers alike to discard the project. As an alternative to this pessimistic conclusion, we argue that critically rethinking the nature and uses of definitions can provide new insights into the epistemic roles of definitions of life for different research practices. This paper examines the possible contributions of definitions of life in scientific domains where such definitions are used most (e.g., Synthetic Biology, Origins of Life, Alife, and Astrobiology). Rather than as classificatory tools for demarcation of natural kinds, we highlight the pragmatic utility of what we call operational definitions that serve as theoretical and epistemic tools in scientific practice. In particular, we examine contexts where definitions integrate criteria for life into theoretical models that involve or enable observable operations. We show how these definitions of life play important roles in influencing research agendas and evaluating results, and we argue that to discard the project of defining life is neither sufficiently motivated, nor possible without dismissing important theoretical and practical research

Viral Hybrid Vectors for Somatic Integration - Are They the Better Solution?

The turbulent history of clinical trials in viral gene therapy has taught us important lessons about vector design and safety issues. Much effort was spent on analyzing genotoxicity after somatic integration of therapeutic DNA into the host genome. Based on these findings major improvements in vector design including the development of viral hybrid vectors for somatic integration have been achieved. This review provides a state-of-the-art overview of available hybrid vectors utilizing viruses for high transduction efficiencies in concert with various integration machineries for random and targeted integration patterns. It discusses advantages but also limitations of each vector system