Development and validation of a miniature programmable tDCS device

Research is being conducted on the use of transcranial direct current stimulation (tDCS) for therapeutic effects, and also on the mechanisms through which such therapeutic effects are mediated. A bottleneck in the progress of the research has been the large size of the existing tDCS systems which prevents subjects from performing their daily activities. To help research into the principles, mechanisms, and benefits of tDCS, reduction of size and weight, improvement in simplicity and user friendliness, portability, and programmability of tDCS systems are vital. This paper presents a design for a low-cost, light-weight, programmable, and portable tDCS device. The device is head-mountable and can be concealed in a hat and worn on the head by the subject while receiving the stimulation. The strength of the direct current stimulation can be selected through a simple user interface. The device is constructed and its performance evaluated through bench and in vivo tests. The tests validated the operation of the device in inducing neuromodulatory changes in primary motor cortex, M1, through measuring excitability of dominant M1 of resting right first dorsal interosseus muscle by transcranial magnetic stimulation induced motor evoked potentials. It was observed that the tDCS device induced comparable neuromodulatory effects in M1 as the existing bulky tDCS systems.

Enabling industrial scale simulation / emulation models

OLE Process Control (OPC) is an industry standard that facilitates the communication between PCs and Programmable Logic Controllers (PLC). This communication allows for the testing of control systems with an emulation model. When models require faster and higher volume communications, limitations within OPC prevent this. In this paper an interface is developed to allow high speed and high volume communications between a PC and PLC enabling the emulation of larger and more complex control systems and their models. By switching control of elements within the model between the model engine and the control system it is possible to use the model to validate the system design, test the real world control systems and visualise real world operation.

Highly programmable surface

A highly programmable electro-mechanical surface is developed using an effective array of individual pins arranged in a gridform. Each pin can be independently raised or lowered to create a wide range of contoured surfaces. It was found that as the number of elements increased. high levels of accuracy could still be achieved. however the required processing power increased logarithmically. This finding was attributed to the large amounts of data being passed. and subsequently led to a second focus; various methods of data management and flow control techniques within large-scale multi elemental systems. Results indicated a large potential for highly programmable surfaces within industry to provide a computer controlled surface for rapid prototyping. The research also revealed the potential for such a device to be used as a HID within Haptic applications.

A systematic grounded approach to the development of complex interventions : The Australian WorkHealth Program – Arthritis as a case study

Despite demands for evidence-based research and practice, little attention has been given to systematic approaches to the development of complex interventions to tackle workplace health problems. This paper outlines an approach to the initial stages of a workplace program development which integrates health promotion and disease management. The approach commences with systematic and genuine processes of obtaining information from key stakeholders with broad experience of these interventions. This information is constructed into a program framework in which practice-based and research-informed elements are both valued. We used this approach to develop a workplace education program to reduce the onset and impact of a common chronic disease – osteoarthritis.

To gain information systematically at a national level, a structured concept mapping workshop with 47 participants from across Australia was undertaken. Participants were selected to maximise the whole-of-workplace perspective and included health education providers, academics, clinicians and policymakers. Participants generated statements in response to a seeding statement: Thinking as broadly as possible, what changes in education and support should occur in the workplace to help in the prevention and management of arthritis? Participants grouped the resulting statements into conceptually coherent groups and a computer program was used to generate a ‘cluster map’ along with a list of statements sorted according to cluster membership.

In combination with research-based evidence, the concept map informed the development of a program logic model incorporating the program's guiding principles, possible service providers, services, training modes, program elements and the causal processes by which participants might benefit. The program logic model components were further validated through research findings from diverse fields, including health education, coaching, organisational learning, workplace interventions, workforce development and osteoarthritis disability prevention.

In summary, wide and genuine consultation, concept mapping, and evidence-based program logic development were integrated to develop a whole-of-system complex intervention in which potential effectiveness and assimilation into the workplace for which optimised.

Agent-based hybrid framework for decision making on complex problems

Electronic commerce and the Internet have created demand for automated systems that can make complex decisions utilizing information from multiple sources. Because the information is uncertain, dynamic, distributed, and heterogeneous in nature, these systems require a great diversity of intelligent techniques including expert systems, fuzzy logic, neural networks, and genetic algorithms. However, in complex decision making, many different components or sub-tasks are involved, each of which requires different types of processing. Thus multiple such techniques are required resulting in systems called hybrid intelligent systems. That is, hybrid solutions are crucial for complex problem solving and decision making. There is a growing demand for these systems in many areas including financial investment planning, engineering design, medical diagnosis, and cognitive simulation. However, the design and development of these systems is difficult because they have a large number of parts or components that have many interactions. From a multi-agent perspective, agents in multi-agent systems (MAS) are autonomous and can engage in flexible, high-level interactions. MASs are good at complex, dynamic interactions. Thus a multi-agent perspective is suitable for modeling, design, and construction of hybrid intelligent systems. The aim of this thesis is to develop an agent-based framework for constructing hybrid intelligent systems which are mainly used for complex problem solving and decision making. Existing software development techniques (typically, object-oriented) are inadequate for modeling agent-based hybrid intelligent systems. There is a fundamental mismatch between the concepts used by object-oriented developers and the agent-oriented view. Although there are some agent-oriented methodologies such as the Gaia methodology, there is still no specifically tailored methodology available for analyzing and designing agent-based hybrid intelligent systems. To this end, a methodology is proposed, which is specifically tailored to the analysis and design of agent-based hybrid intelligent systems. The methodology consists of six models - role model, interaction model, agent model, skill model, knowledge model, and organizational model. This methodology differs from other agent-oriented methodologies in its skill and knowledge models. As good decisions and problem solutions are mainly based on adequate information, rich knowledge, and appropriate skills to use knowledge and information, these two models are of paramount importance in modeling complex problem solving and decision making. Follow the methodology, an agent-based framework for hybrid intelligent system construction used in complex problem solving and decision making was developed. The framework has several crucial characteristics that differentiate this research from others. Four important issues relating to the framework are also investigated. These cover the building of an ontology for financial investment, matchmaking in middle agents, reasoning in problem solving and decision making, and decision aggregation in MASs. The thesis demonstrates how to build a domain-specific ontology and how to access it in a MAS by building a financial ontology. It is argued that the practical performance of service provider agents has a significant impact on the matchmaking outcomes of middle agents. It is proposed to consider service provider agents' track records in matchmaking. A way to provide initial values for the track records of service provider agents is also suggested. The concept of ‘reasoning with multimedia information’ is introduced, and reasoning with still image information using symbolic projection theory is proposed. How to choose suitable aggregation operations is demonstrated through financial investment application and three approaches are proposed - the stationary agent approach, the token-passing approach, and the mobile agent approach to implementing decision aggregation in MASs. Based on the framework, a prototype was built and applied to financial investment planning. This prototype consists of one serving agent, one interface agent, one decision aggregation agent, one planning agent, four decision making agents, and five service provider agents. Experiments were conducted on the prototype. The experimental results show the framework is flexible, robust, and fully workable. All agents derived from the methodology exhibit their behaviors correctly as specified.

Do healthy cities work? A logic of method for assessing impact and outcome of healthy cities

In this article, we discuss an appropriate methodology for assessing complex urban programs such as the WHO European Healthy Cities Network. The basic tenets and parameters for this project are reviewed, and situated in the broader urban health tradition. This leads to a delineation of the types of questions researchers can address when looking at a complex urban health program. Such questions reach appropriately beyond traditional public health concepts involving proximal and distal determinants of health (and associated upstream, midstream, and downstream rhetoric). Espousing a multi-level, reciprocal pathways perspective on Healthy Cities research, we also adopt a distinction between impacts and outcomes of Healthy Cities. The former are value driven, the latter intervention-driven. These approaches lead to the acknowledgment of a logic of method that includes situational and contextual appreciation of unique Healthy City experiences in a Realist Evaluation paradigm. The article concludes with a reflection of evaluation and assessment procedures applied to Phase IV (2003-2008) of the WHO European Healthy Cities Network and an interpretation of response rates to the range of methods that have been adopted.

Intelligent 3D programmable surface

Creating a highly programmable surface operating at relatively high speed and in real time is an area of research with many challenges. Such a system has applications in the field of optical telescopes, product manufacturing, and giant 3D-screens and billboards for advertising and artwork. This paper covers certain aspects of a keynote presentation at ISDT 2010 including system design, modularity, programmability and the system control intelligence. An overview of the system architecture, actuator design, electronics and distributed control will provide an insight into how the system is controlled and self-tuned for a number of applications. A simulation environment that has been developed to streamline system reconfiguration will also be presented, demonstrating translation of complex mathematical functions into 3D shapes virtually before being displayed on the physical surface.

A head mountable deep brain stimulation device for laboratory animals

Deep brain stimulation has emerged as an effective method to treat certain medical conditions. Electrical charges are injected into the target tissue through a conducting electrode exciting the tissue. A variety of DBS devices have been developed based on different operation principles. Majority of these devices, however, employ complex circuitry and are bulky. In clinical trials, laboratory animals need to freely move around and perform activities whilst receiving brain stimulation for days. This paper presents a simple lightweight head mountable deep brain stimulation device that can be carried by the animal during the course of a clinical trial. The device produces continuous current pulses of specific characteristics. It employs passive charge balancing to minimize undesirable effects on the target tissue. The device is constructed and its performance tested.

Anaesthesia monitoring using fuzzy logic

Objective. Humans have a limited ability to accurately and continuously analyse large amount of data. In recent times, there has been a rapid growth in patient monitoring and medical data analysis using smart monitoring systems. Fuzzy logic-based expert systems, which can mimic human thought processes in complex circumstances, have indicated potential to improve clinicians' performance and accurately execute repetitive tasks to which humans are ill-suited. The main goal of this study is to develop a clinically useful diagnostic alarm system based on fuzzy logic for detecting critical events during anaesthesia administration. Method. The proposed diagnostic alarm system called fuzzy logic monitoring system (FLMS) is presented. New diagnostic rules and membership functions (MFs) are developed. In addition, fuzzy inference system (FIS), adaptive neuro fuzzy inference system (ANFIS), and clustering techniques are explored for developing the FLMS' diagnostic modules. The performance of FLMS which is based on fuzzy logic expert diagnostic systems is validated through a series of offline tests. The training and testing data set are selected randomly from 30 sets of patients' data. Results. The accuracy of diagnoses generated by the FLMS was validated by comparing the diagnostic information with the one provided by an anaesthetist for each patient. Kappa-analysis was used for measuring the level of agreement between the anaesthetist's and FLMS's diagnoses. When detecting hypovolaemia, a substantial level of agreement was observed between FLMS and the human expert (the anaesthetist) during surgical procedures. Conclusion. The diagnostic alarm system FLMS demonstrated that evidence-based expert diagnostic systems can diagnose hypovolaemia, with a substantial degree of accuracy, in anaesthetized patients and could be useful in delivering decision support to anaesthetists.

A low power micro deep brain stimulation device for murine preclinical research

Deep brain stimulation has emerged as an effective medical procedure that has therapeutic efficacy in a number of neuropsychiatric disorders. Preclinical research involving laboratory animals is being conducted to study the principles, mechanisms, and therapeutic effects of deep brain stimulation. A bottleneck is, however, the lack of deep brain stimulation devices that enable long term brain stimulation in freely moving laboratory animals. Most of the existing devices employ complex circuitry, and are thus bulky. These devices are usually connected to the electrode that is implanted into the animal brain using long fixed wires. In long term behavioral trials, however, laboratory animals often need to continuously receive brain stimulation for days without interruption, which is difficult with existing technology. This paper presents a low power and lightweight portable microdeep brain stimulation device for laboratory animals. Three different configurations of the device are presented as follows: 1) single piece head mountable; 2) single piece back mountable; and 3) two piece back mountable. The device can be easily carried by the animal during the course of a clinical trial, and that it can produce non-stop stimulation current pulses of desired characteristics for over 12 days on a single battery. It employs passive charge balancing to minimize undesirable effects on the target tissue. The results of bench, in-vitro, and in-vivo tests to evaluate the performance of the device are presented.

Control of polystyrene batch reactor using fuzzy logic controller

Control of polymerization reactors is a challenging issue for researchers due to the complex reaction mechanisms. A lot of reactions occur simultaneously during polymerization. This leads to a polymerization system that is highly nonlinear in nature. In this work, a nonlinear advanced controller, named fuzzy logic controller (FLC), is developed for monitoring the batch free radical polymerization of polystyrene (PS) reactor. Temperature is used as an intermediate control variable to control polymer quality, because the products quality and quantity of polymer are directly depends on temperature. Different FLCs are developed through changing the number of fuzzy membership functions (MFs) for inputs and output. The final tuned FLC results are compared with the results of another advanced controller, named neural network based model predictive controller (NN-MPC). The simulation results reveal that the FLC performance is better than NN-MPC in terms of quantitative and qualitative performance criterion.

A highly interactive 3D programmable surface

Abstract : This presentation will focus on design, modularity, development and control of a highly interactive programmable surface created within the CISR. The system is comprised of thousands of pneumatic cylinders controlled simultaneously in real-time to create a highly dynamic and responsive 3 dimensional surface. The idea behind this research project was the creation of a dynamically responsive surface that configures in real-time according to input from a variety of electronic inputs (movements, sound, etc). The surface is also viewed potentially as a universal motional simulator platform. A simulator that was developed for ease of system reconfiguration demonstrates the translation of complex mathematical functions into 3D shapes in the virtual world before being generated on the real surface. Application areas span from optical telescope to product manufacturing and giant 3D screens billboards for advertising and artwork.

N7-(carboxymethyl)guanine-lithium crystalline complex: a bioinspired solid electrolyte

Electrochemical device with components having direct significance to biological life processes is a potent futuristic strategy for the realization of all-round green and sustainable development. We present here synthesis design, structural analysis and ion transport of a novel solid organic electrolyte (G7Li), a compound reminiscent of ion channels, derived from regioisomeric N7-guanine-carboxylate conjugate and Li-ions. G7Li, with it's in-built supply of Li(+)-ions, exhibited remarkably high lithium-ion transference number (= 0.75) and tunable room temperature ionic conductivity spanning three decades (≈10(-7) to 10(-3) Ω(-1) cm(-1)) as a function of moisture content. The ionic conductivity show a distinct reversible transition around 80-100 °C, from a dual Li(+) and H(+) (<100 °C) to a pure Li(+) conductor (>100 °C). Systematic studies reveal a transition from water-assisted Li-ion transport to Li hopping-like mechanism involving guanine-Li coordination. While as-synthesized G7Li has potential in humidity sensors, the anhydrous G7Li is attractive for rechargeable batteries.