The Effect of dry Needling in Chronic Stroke with a complex Network Approach: A Case Study.

Background: Dry Needling (DN) has been demonstrated to be effective in improving sensorimotor function and spasticity in patients with chronic stroke. Electroencephalogram (EEG) has been used to analyze if DN has effects on the central nervous system of patients with stroke. There are no studies on how DN works in patients with chronic stroke based on EEG analysis using complex networks. Objective: The aim of this study was to assess how DN works when it is applied in a patient with stroke, using the graph theory. Methods: One session of DN was applied to the spastic brachialis muscle of a 62-year-old man with right hemiplegia after stroke. EEG was used to analyze the effects of DN following metrics that measure the topological configuration: 1) network density, 2) clustering coefficient, 3) average shortest path length, 4) betweenness centrality, and 5) small-worldness. Measurements were taken before and during DN. Results: An improvement of the brain activity was observed in this patient with stroke after the application of DN, which led to variations of local parameters of the brain network in the delta, theta and alpha bands, and inclined towards those of the healthy control bands. Conclusions: This case study showed the positive effects of DN on brain network of a patient with chronic stroke.

Providing Fault Detection from Sensor Data in Complex Machines That Build the Smart City.

Household appliances, climate control machines, vehicles, elevators, cash counting machines, etc., are complex machines with key contributions to the smart city. Those devices have limited memory and processing power, but they are not just actuators; they embed tens of sensors and actuators managed by several microcontrollers and microprocessors communicated by control buses. On the other hand, predictive maintenance and the capability of identifying failures to avoid greater damage of machines is becoming a topic of great relevance in Industry 4.0, and the large amount of data to be processed is a concern. This article proposes a layered methodology to enable complex machines with automatic fault detection or predictive maintenance. It presents a layered structure to perform the collection, filtering and extraction of indicators, along with their processing. The aim is to reduce the amount of data to work with, and to optimize them by generating indicators that concentrate the information provided by data. To test its applicability, a prototype of a cash counting machine has been used. With this prototype, different failure cases have been simulated by introducing defective elements. After the extraction of the indicators, using the Kullback-Liebler divergence, it has been possible to visualize the differences between the data associated with normal and failure operation. Subsequently, using a neural network, good results have been obtained, being able to correctly classify the failure in 90% of the cases. The result of this application demonstrates the proper functioning of the proposed approach in complex machines.

Dose dependent gene expression is dynamically modulated by the history, physiology and age of yeast cells.

Cells respond to external stimuli with transient gene expression changes in order to adapt to environmental alterations. However, the dose response profile of gene induction upon a given stress depends on many intrinsic and extrinsic factors. Here we show that the accurate quantification of dose dependent gene expression by live cell luciferase reporters reveals fundamental insights into stress signaling. We make the following discoveries applying this non-invasive reporter technology. (1) Signal transduction sensitivities can be compared and we apply this here to salt, oxidative and xenobiotic stress responsive transcription factors. (2) Stress signaling depends on where and how the damage is generated within the cell. Specifically we show that two ROS-generating agents, menadione and hydrogen peroxide, differ in their dependence on mitochondrial respiration. (3) Stress signaling is conditioned by the cells history. We demonstrate here that positive memory or an acquired resistance towards oxidative stress is induced dependent on the nature of the previous stress experience. (4) The metabolic state of the cell impinges on the sensitivity of stress signaling. This is shown here for the shift towards higher stress doses of the response profile for yeast cells moved from complex to synthetic medium. (5) The age of the cell conditions its transcriptional response capacity, which is demonstrated by the changes of the dose response to oxidative stress during both replicative and chronological aging. We conclude that capturing dose dependent gene expression in real time will be of invaluable help to understand stress signaling and its dynamic modulation.

Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring.

Marine environments are delicate ecosystems which directly influence local climates, flora, fauna, and human activities. Their monitorization plays a key role in their preservation, which is most commonly done through the use of environmental sensing buoy networks. These devices transmit data by means of satellite communications or close-range base stations, which present several limitations and elevated infrastructure costs. Unmanned Aerial Vehicles (UAV) are another alternative for remote environmental monitoring which provide new types of data and ease of use. These aircraft are mainly used in video capture related applications, in its various light spectrums, and do not provide the same data as sensing buoys, nor can they be used for such extended periods of time. The aim of this research is to provide a flexible, easy to deploy and cost-effective Wireless Sensor Network (WSN) for monitoring marine environments. This proposal uses a UAV as a mobile data collector, low-power long-range communications and sensing buoys as part of a single WSN. A complete description of the design, development, and implementation of the various parts of this system is presented, as well as its validation in a real-world scenario.

Managing Emergency Situations in the Smart City: The Smart Signal.

In a city there are numerous items, many of them unnoticed but essential; this is the case of the signals. Signals are considered objects with reduced technological interest, but in this paper we prove that making them smart and integrating in the IoT (Internet of Things) could be a relevant contribution to the Smart City. This paper presents the concept of Smart Signal, as a device conscious of its context, with communication skills, able to offer the best message to the user, and as a ubiquitous element that contributes with information to the city. We present the design considerations and a real implementation and validation of the system in one of the most challenging environments that may exist in a city: a tunnel. The main advantages of the Smart Signal are the improvement of the actual functionality of the signal providing new interaction capabilities with users and a new sensory mechanism of the Smart City.

A smart kitchen for ambient assisted living.

The kitchen environment is one of the scenarios in the home where users can benefit from Ambient Assisted Living (AAL) applications. Moreover, it is the place where old people suffer from most domestic injuries. This paper presents a novel design, implementation and assessment of a Smart Kitchen which provides Ambient Assisted Living services; a smart environment that increases elderly and disabled people's autonomy in their kitchen-related activities through context and user awareness, appropriate user interaction and artificial intelligence. It is based on a modular architecture which integrates a wide variety of home technology (household appliances, sensors, user interfaces, etc.) and associated communication standards and media (power line, radio frequency, infrared and cabled). Its software architecture is based on the Open Services Gateway initiative (OSGi), which allows building a complex system composed of small modules, each one providing the specific functionalities required, and can be easily scaled to meet our needs. The system has been evaluated by a large number of real users (63) and carers (31) in two living labs in Spain and UK. Results show a large potential of system functionalities combined with good usability and physical, sensory and cognitive accessibility.

Study of the therapeutic effects of an advanced hippotherapy simulator in children with cerebral palsy: a randomised controlled trial.

BACKGROUND: Although hippotherapy treatment has been demonstrated to have therapeutic effects on children with cerebral palsy, the samples used in research studies have been very small. In the case of hippotherapy simulators, there are no studies that either recommend or advise against their use in the treatment of children with cerebral palsy. The aim of this randomised clinical study is to analyse the therapeutic effects or the contraindications of the use of a commercial hippotherapy simulator on several important factors relating to children with cerebral palsy such as their motor development, balance control in the sitting posture, hip abduction range of motion and electromyographic activity of adductor musculature. METHODS/DESIGN: The study is a randomised controlled trial. It will be carried out with a sample of 37 children with cerebral palsy divided into two treatment groups. Eligible participants will be randomly allocated to receive either (a) Treatment Group with hippotherapy simulator, maintaining sitting posture, with legs in abduction and rhythmic movement of the simulator or (b) Treatment Group maintaining sitting posture, with legs in abduction and without rhythmic movement of the simulator. DATA COLLECTION AND ANALYSIS: all measurements will be carried out by a specially trained blind assessor. To ensure standardization quality of the assessors, an inter-examiner agreement will be worked out at the start of the study. The trial is funded by the Department of Research, Innovation and Development of the Regional Government of Aragon (Official Bulletin of Aragon 23 July 2007), project number PM059/2007. DISCUSSION: Interest in this project is due to the following factors: Clinical originality (there are no previous studies analysing the effect of simulators on the population group of children with CP, nor any studies using as many variables as this project); Clinical impact (infantile cerebral palsy is a chronic multisystemic condition that affects not only the patient but also the patient's family and their close circle of friends); Practical benefits (the development of an effective treatment is very important for introducing this element into the rehabilitation of these children). TRIAL REGISTRATION: Current Controlled Trials ISRCTN03663478.