Afsluttede PhD Projekter

Scalable Energy Management Infrastructure for Aggregation of Households

Armin Ghasem Azar

The Smart Grid represents an unprecedented opportunity to move the energy industry into a new era of reliability, availability and efficiency that will contribute to our economic and environmental health. The Smart Grid will consist of controls, computers, new technologies and equipment working together and with the electrical grid to respond to our constantly changing electric demands. Also, demand response provides an opportunity for consumers to play a significant role in the operation of the electric grid by reducing or shifting their electricity usage during peak periods in response to time-based prices. This project aims at developing a novel ICT infrastructure for the implementation of Demand Response in households. This infrastructure will enable the shifting of energy consumption from high energy-consuming loads to off-peak periods with high generation of electricity from Renewable Energy Sources.

The chief purpose of this project is to develop a novel, comprehensive and optimal scheduling strategy for varied-specific households. In this strategy, the aggregator system will optimise and manage a large number of partial loads simultaneously according to the generation of electricity from Renewable Energy Sources to shift the households’ demands to off-peak hours. The scheduling strategy needs to take into account constraints from household comfort, grid stability, market mechanisms, etc. Also, trying to optimise conflictive objectives of households and aggregator simultaneously creates a multi-objective optimisation problem. As a result, the main question is how much and when the power consumption should be shifted taking into account the inclusion of scalable and diverse-characteristic householders, different appliance types and dynamic energy price strategies. Answering this question helps the householders to benefit financially and the aggregator to balance the system optimally.

ABOUT THE PROJECT


Project title:
Scalable Energy Management Infrastructure for Aggregation of Households

PhD student: Armin Ghasem Azar

Contact: aga@eng.au.dk

Project period: Sept 2014 to Aug 2017

Main supervisor: Assoc. Prof. Rune Hylsberg Jacobsen

Research section: Electrical and Computer Engineering


Low Voltage/Low Power Design in Future Nodes (FinFET and Nanowire-based Devices)

Behzad Zeinali

The past few decades have seen the evolution of a semiconductor industry driven by technology scaling. Miniaturisation of bulk Field Effect Transistors (FETs) along with the scaling of power supply voltage have provided the benefits of higher performance, lower power and larger integration density. However, future scaling will face considerable challenges e.g. short-channel effects (SCEs) causing the design and optimisation of circuits to become very challenging.

One approach to counter these effects is to introduce alternate devices which possess inherently better robustness to SCEs in comparison to existing technology. Among these alternatives, multiple-gate FETs such as FinFETs or gate wrap-around FETs are emerging as promising candidates. FinFETs have the potential for analogue applications as well as for improving the performance of digital circuits such as static random access memories (SRAM) which are widely used in most digital and computer systems. In this respect, Intel will use the 3-D trigate transistors commercially in 22-nm technology node and so a strong interest has emerged among semiconductor industries in forming 14 and 10-nm bulk FinFET.

In this project, FinFET devices are utilised for SRAM modules in both circuit and device level designs. Also, we will investigate FinFET and its potentials for low-power applications and design some analogue and mixed-signal building blocks by FinFET in sub 14-nm technologies using the Design Kits provided by IMEC.

ABOUT THE PROJECT


Project title:
Low Voltage/Low Power Design in Future Nodes (FinFET and Nanowire-based Devices)

PhD student: Behzad Zeinali

Contact: beze@eng.au.dk

Project period: May 2014 to April 2017

Main supervisor: Assistant Prof. Farshad Moradi

Co-supervisors: Prof. (Docent) Jens Kargaard Madsen and Praveen Raghavan, IMEC

Research section: Electrical and Computer Engineering


Reliable Communication in Body Area Networks

A Body Area Network (BAN) consists of multiple, tiny, low-power, intelligent, wearable or implanted sensor nodes which are radio-enabled and can communicate wirelessly. The sensor nodes can collect various important physiological data for diagnosis or fast emergency response, and deliver various personalised therapeutic, treatment-related applications and services.

BAN is a new emerging technology that is used in areas such as healthcare, entertainment, games and sport science. It is expected to enhance the patient health care experience by providing independent living solutions for people that need constant healthcare. Furthermore, BAN can reduce the demand on the healthcare infrastructure and medical staff in the hospitals. Essentially, there is a unique combination of four major requirements in a realistic BAN:

  • Energy efficiency
  • Low complexity
  • Robustness against harsh fading conditions
  • Protection against interference and error

The aim of this project is first to investigate the characteristics of the typical BAN applications and the corresponding difficulties and limitations. The next step is to analyse these limitations to provide remedial solutions to achieve the performance requirements. The analysis is meant to address both Physical (PHY) and Medium Access Control (MAC) layers.

ABOUT THE PROJECT


Project title:
Reliable Communication in Body Area Networks

PhD student: Mohammad Sadegh Mohammadi

Contact: msmo@eng.au.dk

Project period: Aug 2013 to Feb 2017

Main supervisors: Assoc. Prof. Qi Zhang, Aarhus University and Eryk Dutkiewicz, Macquarie University

Research section: Electrical and Computer Engineering

 

 


An Ultra-Low Power Wireless Biosensing SoC Utilising Low-Voltage Techniques for Body-Worn Healthcare Applications

Xiong Zhou

The need for healthcare devices for everyday life is increasing.  These devices can provide a long-term, unobtrusive monitoring to prevent chronic diseases which are the biggest killers according to the statistics of WHO, e.g. heart disease, stroke, hypertension, diabetes, etc. Past devices are bulky and high-power and have limitations to the use away from specific places e.g. clinics and hospitals. Ultra-low-power, wireless, small-size and user-friendly are the basic requirements of today's healthcare system.

For a long time, there has been a continued expectation that the biomedical system can be power autonomous which can be facilitated by energy harvesting from the ambient energy sources such as thermal energy, kinetic (motion, vibration) energy, radio frequency and solar power. However, current works have not reached this point yet.

The topic of this project is the utilisation of low-voltage techniques to decrease the system's power as much as possible as the potential of low-voltage techniques to aggressively reduce power has not been well addressed in the literature. To satisfy this task, the system’s total power must decrease to ~100µW including analogue front-end (AFE), µP (digital processing) as well as data transmitting and receiving via radio frequency. A potential application is the Ear-EEG.

ABOUT THE PROJECT


Project title:
An Ultra-Low Power Wireless Biosensing SoC Utilising Low-Voltage Techniques for Body-Worn Healthcare Applications

PhD student: Xiong Zhou

Contact: xizh@eng.au.dk

Project period: June 2013 to June 2016

Main supervisor: Prof. (Docent) Jens Kargaard Madsen

Co-supervisors: Prof. (Docent) Preben Kidmose, Assistant Prof. Farshad Moradi

Research section: Electrical and Computer Engineering

 

 


Characterisation and Evaluation of Dry-Contact Electrodes for Ear-EEG

Simon Lind Kappel

Ear-EEG is a novel EEG (electroencephalography) recording approach in which the EEG signal is recorded from electrodes embedded on an ear-piece placed in the ear canal. The ear-EEG has great potentials within continuous brain monitoring in everyday life and will have application within both medical and consumer electronics devices.

The integration of brain monitoring based on EEG into everyday life has been hindered by the limited portability and long set-up time of current wearable systems as well as by the invasiveness of implanted systems.

To address these issues, the ear-EEG has been introduced which is a discreet, unobtrusive and user-centred approach to brain monitoring. The ear-EEG recording concept has been tested by using several standard EEG paradigms and benchmarked against standard on-scalp EEG.

All ear-EEG recordings made so far have been based on wet-electrode technology. In order to improve the usability and user-friendliness, this project will exploit so-called dry-contact electrode technology. This has impact on the design of the electrode itself, the supporting mechanics and the electronic instrumentation for acquiring the EEG signal.

ABOUT THE PROJECT


Project title:
Characterisation and Evaluation of Dry-Contact Electrodes for Ear-EEG

PhD student: Simon Lind Kappel

Contact: slk@eng.au.dk

Project period: Oct 2013 to Sept 2016

Main supervisor: Prof. (Docent) Preben Kidmose

Research section: Electrical and Computer Engineering


Enhancing Code Generation support in Formal Model Development

Peter W. V. Tran-Jørgensen

In my PhD I work on enhancing tool support for developing mission-critical systems. These are systems whose failure may lead to huge financial costs or loss of human lives. Examples of such systems range from everyday objects like cell phones or online banking systems to safety-critical systems like modern cars and flight control systems.

To ensure that the system is behaving as intended, we use mathematically based techniques to validate the behaviour of the system. One such technique is formal modelling. Based on the formal models the system's software and hardware is developed and integrated to construct a final version of the system.

To increase the chances of the software working correctly I work on developing tools that enable the software implementation to be generated automatically from the formal models. This avoids introducing problems into the software implementation, due to manual translation of model into code.

In my PhD project I explore how to enhance code generation to better support formal model development. Use of code generation enables the insights obtained during early analysis to automatically be transferred to the subsequent phases of development. In particular I am interested in finding new ways to exploit code generation to ensure the correctness of the software implementation. This is particularly important for mission-critical systems like cars and flight control systems, where system failure may have fatal consequences.

ABOUT THE PROJECT


Project title:
Enhancing Code Generation support in Formal Model Development

PhD student: Peter Würtz Vinther Tran-Jørgensen

Project period: May 2013 to April 2016

Main supervisor: Prof. Peter Gorm Larsen

Research section: Electrical and Computer Engineering


Model-Driven Software Development for Agricultural Robotics

Morten Larsen

Software development for agricultural robotics is complicated and hence time-consuming and expensive.

Agricultural robots are particularly challenging with respect to the development of software due to the combination of an open, unpredictable environment and a complex, open-ended range of tasks.

Model-driven software development is a systematic approach to automatically generated software within a given domain based on a model.

The scientific goal of this project is to improve and develop model-driven software techniques, domain models, underlying software architecture and code generation techniques. This will enable us to create a software platform for automatic generation of control programmes that suit the specific requirements of agricultural robots.

The developmental goal of this project is to provide systematic and automated techniques for the development of a software platform that can be utilised for field robots in various scenarios. This software platform will be directly applicable in the development of control programmes for specific agricultural robots.

ABOUT THE PROJECT

Project title: Model-Driven Software Development for Agricultural Robotics

PhD student: Morten Larsen

Project period: May 2013 to April 2016

Main supervisor: Senior Researcher Rasmus Nyholm Jørgensen

Co-supervisor: Prof. Peter Gorm Larsen

Research section: Electrical and Computer Engineering


Virtual Power Plant for Residential Demand Response

Sergi Rotger Griful

In the near future, there will be a higher penetration of renewable energy sources into the electrical grid. The entrance of these distributed energy resources into the system will require smarter solutions to balance the electricity production and consumption. This future grid is known as the Smart Grid.

The aim of this project is to make a large residential complex and its consumers ”Smart Grid Ready” through the development and operation of a Virtual Power Plant (VPP). A VPP can be understood as a power plant which, instead of just producing electricity, is also able to modify the energy consumption of the end-user, thus providing demand response. The designed VPP will monitor and control the energy usage in the building. Furthermore, the VPP of the building will pool and offer the overall demand response to an external entity at a higher tier in the aggregation hierarchy.

The new student’s residence at Aarhus harbour will be used as a test bed under the name of Grundfos Dormitory Lab. This is a 159 apartment building with a very low consumption profile, equipped with more than 3200 sensors.

The project deals with the Information and Communication Technology (ICT) for the construction of a VPP at building level. Specifically, this involves concept development, demand response engineering, sensing and actuation technology, data mining and forecasting as well as system integration for demonstrating part of the concepts developed. The project aims at advancing the state-of-the-art in VPP technologies for the Smart Grid.

ABOUT THE PROJECT


Project title: 
Virtual Power Plant for Residential Demand Response

PhD student: Sergi Rotger Griful

Project period: May 2013 to April 2016

Main supervisor: Assoc. Prof. Rune Hylsberg Jacobsen

Research section: Electrical and Computer Engineering


Quality of Context in Ambient Assisted Living Systems

Femina Hassan Aysha Beevi

Ambient Assisted Living (AAL) systems integrate different technologies to provide healthier and safer living environments for the elderly. The AAL systems provide AAL services such as monitoring the activities of daily living. It is important to ensure the quality of context information in the AAL system as it reacts and responds to the events that occur by making use of the context information derived from the context data. A lapse in quality could be life-threatening as it leads to a failure in anticipating and reacting to the user's needs, and a failure in adapting to the changes in the environment.

The objective of this project is to investigate how the quality of context data can be assured in high-risk physical activity contexts in the AAL systems. During this project, the context data quality in AAL systems is analysed from different data quality dimensions and novel methods will be developed for quality assurance.

The work being done in this project is part of the European FP7 CareStore project. The CareStore project aims to develop a marketplace for the easy deployment of applications and device drivers in a healthcare scenario, and develop an ambient assisted platform for the home to integrate the CareStore marketplace.

ABOUT THE PROJECT


Project title:
Quality of Context in Ambient Assisted Living Systems

PhD student: Femina Hassan Aysha Beevi

Project period: Feb 2013 to Jan 2016

Main supervisor: Assoc. Prof. Stefan Hallerstede

Co-supervisors: Assistant Prof. Christian Fischer Pedersen and Assistant Prof. Stefan Wagner

Research section: Electrical and Computer Engineering


Cybersecurity and Privacy Enforcement in an Internet-based Smart Grid

Søren Aagaard Mikkelsen

In the battle for lowering CO2 emissions, many countries encourage and financially support the deployment of renewable energy sources for generating electricity. These energy sources are typically non-dispatchable, i.e. they do not produce energy on demand. Currently, no energy storage technology exists that efficiently store the energy when it is produced for later use. Thus, it is necessary to have an Information and Communication Technology (ICT) system that can support the grid operator in accounting for these fluctuations on the grid so the energy can be consumed when it is produced; a so-called smart grid system. This need is only exacerbated further with the advent of solar panels and electric vehicles distributed on the electric grid.

The challenge of balancing the electric grid with non-deterministic generation of electricity calls for ICT solutions that can monitor and manage consumption and production in real-time. Such solutions will be based on data generated from sensors placed e.g. in residential houses. A large majority of the data produced in residential homes is, however, directly related to the residents' behaviour within their own private sphere. If security and privacy going to and from the residential homes are not carefully considered, a possible resistance towards adapting these ICT solutions could emerge. Additionally, the solution must be economically attractive for both the residential consumer and grid operator such that the potential benefit (such as energy cost savings) from getting the monitoring equipment outweighs the price of the equipment.

The aim of this project is to facilitate an economically viable ICT solution for both the residential consumers and the grid operators by using the existing Internet connection in the residential houses as pathway for communicating and transferring data. On top of a service-oriented architecture and an open communication infrastructure, the research will focus on preserving data privacy and enforce cyber-security for the residential consumers while not compromising robustness and service guarantees for the grid operators.

ABOUT THE PROJECT


Project title:
Cybersecurity and Privacy Enforcement in an Internet-based Smart Grid

PhD student: Søren Aagaard Mikkelsen

Project period: Oct 2012 to Sept 2015

Main supervisor: Assoc. Prof. Rune Hylsberg Jacobsen

Research section: Electrical and Computer Engineering


Localisation of Wireless Sensor Network Embedded in Biomass

Jakob Pilegaard Juul

When storing grain and other farm produce, proper drying and storage are important. Using wireless sensors distributed in the storage enables a farmer to monitor how the drying/storage is progressing and to take action if something is not as it should be. This helps to reduce losses and get a higher overall quality.

A number of challenges face a wireless sensor network deployed in such a scenario. Farm produce can contain relatively high amounts of water as well as high concentrations of salts leading to an unfavourable environment for wireless communication.

To help in the process of monitoring storages, the aim of this project is to develop a wireless sensor network capable of functioning reliably under the specific conditions. The system should also be able to localise the sensors of the network as this enables targeted intervention in problem areas.

ABOUT THE PROJECT


Project title:
Localisation of Wireless Sensor Network Embedded in Biomass

PhD student: Jakob Pilegaard Juul

Project period: March 2010 to July 2015

Main supervisor: Assoc. Prof. Rune Hylsberg Jacobsen

Co-supervisor: Ole Green, Kongskilde Industries A/S

Research section: Electrical and Computer Engineering


On the Extensibility of Formal Methods Tools

Luis Diogo Monteiro Duarte Couto

Extensibility is a useful property of software systems. It can be informally defined as the ability of a system to support the addition of new and unplanned functionalities.

My PhD project explores extensibility of formal methods tools, specifically the Overture tool for VDM (Vienna Development Method). I analyse and improve the extensibility of Overture through various vectors, such as software architecture and coding patterns.

My work revolves around extensions to the Overture tool that act as case studies and drive the research. Particular focus is given to the proof obligation generator extension and integration with theorem proving. Outside of specific extensions, I am interested in tool support for extending the notation itself.

In parallel to the above, I will also investigate a connection between extensibility and formal modelling by applying extensibility techniques from software engineering to the construction of extensible formal models.

ABOUT THE PROJECT


Project title:
On the Extensibility of Formal Methods Tools

PhD student: Luis Diogo Couto

Project period: Oct 2012 to Sept 2015

Main supervisor: Prof. Peter Gorm Larsen

Co-supervisor: Joey Coleman, PhD

Research section: Electrical and Computer Engineering


Intelligent Soil Tillage using Image Sensors

Thomas Jensen

The aim of this project is to research and develop a system for sensor based online control of the degree of tillage for a seedbed cultivator moving in the field.

The system will include a vision system for characterising the seedbed quality. The vision system will consist of a series of laser range scanners positioned on the seedbed cultivator which continuously generate a map of the raw and processed soil. The quality of the seedbed is correlated with aggregate size in the soil surface, i.e. the cloddiness of the soil. Large clods result in a too airy seedbed and thus the risk of drying out the seeds. On the other hand, a too processed seedbed has the risk of sealing the soil surface after heavy rain and thus resulting in bad germination. Additionally, it is a sign of too intensive seedbed cultivation and thus of an unnecessarily high energy consumption while cultivating.

The online control of tillage intensity is based on image analysis, and the seedbed cultivator is adjusted continuously while running in the field. Since the same field often consists of many types of soil, the system must be able to react to the changes in soil type and adjust the tillage intensity accordingly.

ABOUT THE PROJECT


Project title:
Intelligent Soil Tillage using Image Sensors

PhD student: Thomas Jensen

Project period: Sept 2012 to Aug 2015

Main supervisor: Prof. (Docent) Henrik Karstoft

Co-supervisors: Senior Researcher Lars Munkholm and Ole Green, Kongskilde Industries A/S

Research section: Electrical and Computer Engineering


Modelling, Simulation and Evaluation of Autonomous Agricultural Vehicle Guidance

This project deals with the challenges faced when designing and deploying an autonomous vehicle guidance system in the agricultural domain. Automatic guidance systems for agricultural machines, i.e. auto-steering systems, employ sensory input from the Global Navigation Satellite System (GNSS) and/or other localisation systems. The auto-steering systems can increase efficiency in terms of reduced overlap, less operational time and fuel.

Before an auto-steering solution can be operational on a given vehicle, it is necessary to calibrate several (control) parameters of the auto-steering system. These calibration parameters are dependent on the technical performance of the vehicle. We believe that better control parameters could be selected by utilising a simulated model of an agricultural machine. The simulated model will be able to execute and evaluate multiple candidate solutions using optimisation and search algorithms. The conjecture is that modelling and simulation would be less costly than selecting parameters and try to manually fine-tune an auto-steering system.

ABOUT THE PROJECT


Project title:
Modelling, Simulation and Evaluation of Autonomous Agricultural Vehicle Guidance

PhD student: Martin Peter Christiansen

Project period: Sept 2011 to June 2015

Main supervisor: Senior Researcher Rasmus Nyholm Jørgensen

Co-supervisors: Prof. Peter Gorm Larsen and Ole Green, Kongskilde Industries A/S

Research section: Electrical and Computer Engineering


System Level Power-Aware Design for Mission-Critical Embedded Systems

José Antonio Esparza Isasa

An embedded system is a special purpose computing device commonly operating with low computing power and sometimes under limited energy availability.

One of the techniques that can be used to develop these kinds of systems is model-driven engineering. Under this design approach, the engineer uses modelling technologies to represent the system at a high level of abstraction. Following this initial representation, the model is progressively transformed into a final implementation.

The aim of this project is to adopt this approach to design and implement embedded systems that operate under tight energy budgets. The challenge is to incorporate the notion of energy consumption into different modelling paradigms. The reason behind applying several paradigms resides in the fact that embedded systems’ energy consumption can be studied from different angles, i.e. the physical, communication or computation angle.

By using different modelling approaches, one can select the most suitable for each angle and obtain energy estimations from different points of view.

The results of this project are being applied progressively in a case study in which an electronic compression stocking to treat leg venous insufficiency is developed. The aim is to evaluate how the energy consumption predictions determined by the models relate to the actual implementation, and how the modelling process benefits system development.

ABOUT THE PROJECT


Project title:
System Level Power-Aware Design for Mission-Critical Embedded Systems

PhD student: José Antonio Esparza Isasa

Project period: May 2012 to April 2015

Main supervisor: Prof. Peter Gorm Larsen

Co-supervisor: Prof. (Docent) Finn Overgaard Hansen

Research section: Electrical and Computer Engineering


Visual Awareness Negativity and Spatial Attention

Daniel Siboska

For most of the population, our eyes have become the primary access to the world around us. However, much of the visual stimuli that enter our eyes is filtered out before it reaches our consciousness/visual awareness. Our visual system is extraordinarily good at this filtering process, though sometimes important information is filtered away which can be devastating e.g. in traffic situations.

This project seeks to explore the mechanisms that control whether visual information reaches our visual awareness or is filtered out. We will do this by measuring magnetic signals (magnetoencephalography – MEG) generated from specific areas in the brain when this process occurs and see how these mechanisms modulate the activity in the brain.

The first such mechanism we explore is how spatial attention, i.e. where we are directing our eyes, modulates this filtering process. To do this, we need to be able to control how much spatial attention the test subjects are able to allocate to a given visual stimulus. This will be achieved through the use of a gaze contingent display which can change the visual content on the screen depending on where the subject is looking.

The development of such a gaze contingent display with a faster response time than the human eye and which can be used while recording MEG signals is a prerequisite for the examination of the effect of spatial attention on our visual awareness.

ABOUT THE PROJECT


Project title:
Visual Awareness Negativity and Spatial Attention

PhD student: Daniel Siboska

Project period: Jan 2012 to April 2015

Main supervisor: Prof. (Docent) Henrik Karstoft

Research section: Electrical and Computer Engineering


Well-Founded Engineering of System of Systems

Claus Ballegård Nielsen

A System of Systems (SoS) is a system type that has risen from the increased complexity found in present-day system engineering. An SoS denotes a collaborative system which consists of many independent, heterogeneous constituent systems that combine information and functionality in order to reach a synergistic functionality that is greater than the sum of the constituent systems' abilities.

The SoS Engineering field faces the challenge of its constituent systems being individually owned and developed, which means that there is no centralised authority to take action or make decisions. As a result, decisions have to be agreed on, collaboratively, between the individual owners/developers of the constituent systems. Therefore, the interfaces, data types, communication channels and interactions between the systems need to be agreed upon during development.

The purpose of the project is to research how existing and new methods can be adapted, combined and innovated to improve the foundation of SoS engineering. The research is focused on aiding collaboration by utilising a combination between the field of software engineering and the field of systems engineering.

 

 

ABOUT THE PROJECT


Project title:
Well-Founded Engineering of System of Systems

PhD student: Claus Ballegård Nielsen

Project period: May 2011 to April 2014

Main supervisor: Prof. Peter Gorm Larsen

Research section: Electrical and Computer Engineering


Pattern Recognition Methods for Reduction of Human-Wildlife Conflicts

Kim Arild Steen

The purpose of this project is to develop methods and algorithms for automation in agriculture.

The main focus is wildlife management systems where new technology could automate or improve existing methods.

The main contribution of the work is the development of pattern recognition algorithms which are capable of detecting and recognising wildlife in an agricultural setting. This includes audio and video based systems that are capable of measuring the presence and behaviour of wildlife.

The expected result of this work is a proof of concept solution which can be used in further development and full-scale tests.

ABOUT THE PROJECT


Project title:
Pattern Recognition Methods for Reduction of Human-Wildlife Conflicts

PhD student: Kim Arild Steen

Project period: Feb 2011 to April 2014

Main supervisor: Prof. (Docent) Henrik Karstoft

Co-supervisor: Ole Green, Kongskilde Industries A/S

Research section: Electrical and Computer Engineering


Fiber Optical Load Sensors for Wind Turbines

Lars Glavind

This project is in the field of fiber optical sensors for measuring the load on a wind turbine blade.

The advantages of using an optical sensor instead of typical electronic sensors in a wind turbine blade are the immunity to lightning and the longer longevity of the sensor. A system that measures the load of the blades can provide information which can be used to optimise the production and design of a wind turbine.

The focus is on applied research on a new type of sensor that can measure the load on a wind turbine blade and provide better information about the shape of a blade during operation of the wind turbine.

ABOUT THE PROJECT


Project title:
Fiber Optical Load Sensors for Wind Turbines

PhD student: Lars Glavind

Project period: Sept 2009 to Feb 2014

Main supervisor: Prof. Martin Kristensen

Co-supervisor: Assoc. Prof. Bjarne F. Skipper

Research section: Electrical and Computer Engineering


Ear-EEG and Applications to Brain Computer Interface (BCI)

Brain Computer Interfaces (BCIs) are an emerging technology that uses electrical activity in the brain, measured by non-invasive electroencephalography (EEG), to enable direct communication between the human brain and external devices such as computers. Over the past several years, BCIs have become an important research topic because of their ability to help patients suffering from severe loss of motor functions such as ALS, stroke, etc. Indeed, such interfaces can increase an individual’s independence leading to an improved quality of life and reduced healthcare costs.

The recently introduced ear-EEG methodology is a promising enabling technology for wearable EEG systems. Ear-EEG records EEG signals within the ear canal by embedding electrodes on a customised ear piece similar to ear-plugs used in hearing-aid applications. Ear-EEG is, compared to alternative technologies, a discreet, unobtrusive, robust and user-friendly technology.

Whereas most BCIs are based on visually evoked potentials, the objective of this project is to develop auditory BCIs based on the Ear-EEG platform. This is feasible because it has been shown that auditory evoked potentials (AEP) can be recorded with good signal quality from ear-EEG.

The aim of the project is to develop new auditory paradigms where the AEPs can be easily controlled by the user’s attention, and to develop advanced signal processing algorithms for detection of the AEP modulations.

ABOUT THE PROJECT


Project title:
Ear-EEG and Applications to Brain Computer Interface (BCI)

PhD student: Faisal Farooq

Main supervisor: Prof. (Docent) Preben Kidmose

Research section: Electrical and Computer Engineering