Smart Metering is an important component of Smart Grids. Detailed load profiles are available through smart metering at a high resolution. Load profiles allow inferring detailed information on the end user by non-intrusive load monitoring. Therefore, these load profiles need to be regarded as sensitive data, and treated with security and privacy in mind. We propose a method that allows conditional access to different resolution levels of the load data, allowing access on a "need-to-know" basis only. For this purpose, a multiresolution representation of the load data is created using the simple Haar wavelet transform. Securing the portions of the wavelet representation pertaining to each resolution with a unique key allows to implement conditional access for smart meter data.
The Artificial Accommodation System is a micro mechatronic system which will be implanted into the capsular bag to replace the human crystalline lens. Depending on the patients' actual need for accommodation, the system autonomously adapts the refractive power of its integrated optical element in a way that the projection on the patients' retina results in a sharp image. As the Artificial Accommodation System is an active implant, its subsystems have to be supplied with electrical energy. Therefore an inductive power supply system will be developed which is able to autonomously power the Artificial Accommodation System over a period of 24h and can be recharged wirelessly. This Paper describes the design process of the coils needed for inductively transferring power to the implant. It can be shown that by means of optimization it is possible to transfer 50 mW of power to the interior of the Artificial Accommodation System.
Recently, Magnetic Resonance Imaging (MRI) system which operates up to under 3 T is being used in clinical practice in Japan. In order to achieve the requirement of obtaining more high-quality images and short imaging time, devices utilize high magnetic field (>3 T) and high power electromagnetic (EM) wave pulses has been developed. The rise of the static magnetic field is proportional to the increase of the EM wave frequency which brings down issues of variation in capacitance used in the radio frequency (RF) coil for MRI system. In addition, increasing power causes problems of withstanding voltage and these approach leads to generation of non-uniform magnetic field inside the RF coil. Hence, if we can develop the birdcage coil for MRI system with no lumped circuit elements, it is extremely useful. In this paper, birdcage coil without the use of lumped circuit elements for 4 T MRI system was proposed and its magnetic field distribution was investigated. As a result, it was confirmed that the proposed birdcage coil has equivalent performances of the conventional birdcage coil which includes several capacitors.
In this study, we review the sinogram domain gap-filling methods for the positron emission tomograph (PET) data. We restricted our literature search to the published methods for the diamond shaped gaps which exist in the PENN-PET (University of Pennsylvania, Philadelphia, PA, USA), the MDAPET (M. D. Anderson Cancer Center, University of Texas, Houston, TX, USA), and the ECAT HRRT (CTI PET Systems, Knoxville, TN, USA) PET scanner sinogram data. We only included the methods which were also tested with the real scanner data (either physical phantom data or real patient data) besides the numerical phantom data. We categorized the methods into three classes: 1) interpolation methods; 2) model based methods, and 3) transform based methods. The general characteristics of the methods are explained. For the detailed information on the gap-filling methods such as implementation details, the reader should refer to the original article in which that gap-filling method was proposed. We discuss the performances of the gap-filling methods under the light of the corresponding comparison articles in the literature.
We report on a work in progress aiming at automatically analysing electrocardiograms with the help of wavelet bases. The objective we have fixed was to introduce a parsimonious and computationally efficient method --- that can be ultimately incorporated on standard ECG recording devices --- to automatically localise points of interest and decide whether they are normal or not and, for abnormal points, assign them a given class of abnormality. The task we have already achieved is the localisation and identification of normal QRS complexes. Identification and localisation of other features, like premature atrial or ventricular beats, fibrillation, noise, bundle branch block beats, ectopic beats, etc. is in progress but the so far obtained preliminary results are very encouraging.
In this paper we analyze the synergy between forensic image head data consistency analysis and detection of doubles JPEG compression artifacts. We show that image head consistency testing is an effective method for detecting digital images that have been modified. On the other hand, when it is not combined with other forensic methods such as double JPEG detection, a high number of altered photos remained undetected. The same can also be claimed about double JPEG detection. When employed separately without conjunction with other methods, the majority of altered photos remained undetected. In this paper, a quantitative study on this topic is carried out. We show that combining various image forensic methods is a must.
In this invited paper an overview of the Computed Tomography-based cancer radiotherapy planning is given. All planning steps are described with details, i.e. its goals, existing solutions and typical realizations. On this background, as an example, a complete procedure of prostate cancer radiotherapy planning is presented in which application of Level-Set segmentation method guided by a priori atlas-type knowledge is proposed. Developed procedure was verified on data base consisting of 266 CT slices of 4 patients.
In this contribution, a device for long term measurement of heart rate is described. The device is created based on development kit STM32-Primer2. Heart rate frequency is calculated from selected electrocardiograph lead from the external module. The device allows simultaneous recoding of acceleration which makes is appropriate for physical activity detection of the test subject. The recorded data is saved on a memory card as signals in raw form, which can be used for subsequent processing in various research areas. Modular solution is suitable for connection of other modules. This device is designed for research and educational purposes in the field of medical devices and signal processing.
There are many different methods for evaluation of alertness level of a person. The commonly used questionnaires and some physiological test such as flicker-fusion (FF) test are not objective. Other objective methods based on the analysis of biological signals can be used for validation of these tests. The present study is focused on analysis of spectral features of EEG measured in sleep deprived subjects during experiment containing FF test performing. The results of the study show that FF test does not affect electrical brain activity dramatically and, thus, can be used for alertness level evaluation. It is also shown that subjective determination of state using questionnaires can differ from those obtained by objective method based on the analysis of EEG. These results can be useful for correct interpretation of FF test results.
Utilizing information and communications (ICT) technologies for healthcare and medical purposes has obtained a lot of interest and attention during the recent years. All over the world, in Europe, Asia and the USA, several universities, research institutes and companies have contributed via numerous programs, collaborations, and projects for the topic. This paper gives a collage of the latest interests in the research of the field carried out by the Centre for Wireless Communications (CWC), University of Oulu, Finland. We are also summarizing our views of the future development in this very important field. Wireless technology will be one of the key elements when improving safety and effectiveness of healthcare processes in its different application sectors.
Metamaterials are complex materials with artificial structure which have special features. These features attract many scientists to use metamaterial structure in many research areas [1]. The metamaterials can enhance properties of microwave and optical passive and active components and also to exceed some limitation of devices used in technical practice [1]. Examples of scientific and technical fields which are concerned are electrical engineering, micro- and nanotechnology, microwave engineering, optics, optoelectronics, and semiconductor technologies, biomedical engineering [1]. In plasmonics, the interplay between propagating electromagnetic waves and free-electron oscillations in materials are exploited to create new components and applications [1]. On the other hand, metamaterials refer to artificial composites in which small artificial elements, through their collective interaction, create a desired and unexpected macroscopic response function that is not present in the constituent materials [1].
This paper describes a modified and enhanced version of the GPL-licensed, ITK-/VTK-based segmentation software ITK-SNAP. The modified software is entitled IMPPACT-SNAP and was motivated by the requirement for preoperative inspection and manual refinement of surface mesh liver segmentations in the research project IMPPACT. In this context, the liver segmentations are used for simulating the radiofrequency ablation of liver tumors to optimize the outcome of the treatment. The implemented modifications add the functionality of visualizing and manually deforming surface mesh segmentations and improve the navigational features of the software. The result is an easy-to-use tool that builds on ITK-SNAP's user-oriented GUI and framework.
In this paper, we describe two cutting-edge technologies for the emerging wearable healthcare applications: application specific integrated circuit (ASIC) and printed electronics on a flexible paper substrate. The ASIC enables a compact integration of active circuit blocks on a chip. Due to its tiny size, the ASIC makes the wearable unit unobtrusive and maximizes the wearer's comfort. The electrical performance of a paper based inkjet printed flexible cable is also exhibited. Combining the two technologies together, an example of electrocardiogram (ECG) signal recording is presented.
This paper presents a new method for segmenting multiple brain structures by using an optimized mixture of different Active Contour Models (ACMs). Prior constraints and structures' neighboring interaction are modelled for each structure. Prior information is also captured by a training process, in which structure's dependent local and global weights are calculated. The local weights regulate locally the combination of each term during the evolution, acting as an experienced balancer between image and prior information. The ideal proportion of relation between the mixture of different ACMs and the prior model is defined by the optimum global weights. As proof of concept, the method is applied on the very challenging task of segmenting hippocampus and amygdala structures.
As described herein, we propose an unsupervised method for segmentation of magnetic resonance (MR) brain images by hybridizing the self-mapping characteristics of 1-D Self-Organizing Maps (SOMs) and using incremental learning functions of fuzzy Adaptive Resonance Theory (ART). As the proposed method requires the appropriate parameters to segment tissues (such as cerebrospinal fluid, gray matter and white matter) that are necessary for brain atrophy diagnosis, first we derive the optimal parameter set through the preliminary experiments. The main contribution of this work is to evaluate the effectiveness of the proposed method, considering the conventional methods that are highly accurate in terms of usefulness as classification techniques. We focus on Fuzzy C-means (FCM) and Expectation Maximization Gaussian Mixture (EM-GM) with previous setting of the number of clusters, and then Mean Shift (MS) without previous setting of the number of clusters. Through the comparative experiments on the two metrics, we confirmed that our method could achieve higher accuracy than these conventional methods. Additionally, we propose a Computer-Aided Diagnosis (CAD) system for use with brain dock examinations based on case analyses of diagnostic reading. We construct a prototype system for reducing loads on diagnosticians during quantitative analysis of the degree of brain atrophy. Field tests of 193 examples of brain dock medical examinees reveal that the system efficiently supports diagnostic work in the clinical field: the alteration of brain atrophy attributable to aging can be quantified easily, irrespective of the diagnostician.
The objective of this study is to perform a quantitative performance analysis of diversity effect for in-body to on-body ultra wideband (UWB) transmission for capsule endoscope. UWB technology has a potential to provide real-time image transmission from inside to outside of human body owing to its inherent features. However, it suffers from large attenuation together with shadowing in human tissues. In view of this distinctive property, a diversity scheme is expected to provide an effective improvement on this wireless link performance. Based on finite-difference time-domain (FDTD) numerically-derived in-body to on-body characteristics, we derive probability density function (PDF) for combined communication channels with two different approximation methods and compare their accuracy at first. Then we calculate average bit error rate (BER) with pulse position modulation (PPM) and on-off keying (OOK) modulation scheme to clarify the possible diversity effect.
Security protection is critical to body sensor networks, since they collect sensitive personal information. Generally speaking, security protection of body sensor network relies on key distribution protocols. Most existing key distribution protocols are designed to run in general wireless sensor networks, and are not suitable for body sensor networks. After carefully examining the characteristics of body sensor networks, we propose an Elliptic Curve Diffie Hellman version of Symmetric Hash commitment before knowledge protocol (ECDH-SHCBK). Thanks to ECDH-SHCBK, dynamically distributing keys becomes possible. As opposite to present solutions, this protocol does not need any pre-deployment of keys or secrets. Therefore, compromised and expired keys can be easily changed. This protocol exploits human users as temporary trusted third parties. We, thus, show that the human interactive channels can help us to design secure body sensor networks.
In this paper we introduce an ultrasound image segmentation evaluation framework for kidney tumor. Ultrasound image segmentation algorithms can be divided into edge based, region based, texture based, active contour and model base technique. We tested the performance of algorithms in each category using a kidney phantom and kidney cyst ultrasound image. We found that the algorithms we implemented are more suitable for relatively homogeneous kidney tumors. For more heterogeneous tumors we should use more complicated segmentation techniques and some of these advanced techniques are discussed in this paper.
Muscle fiber conduction velocity is generally measured by the estimation of the time delay between electromyography recording channels. In the present paper, we propose to identify the best estimator of a constant time delay among those based on generalized correlation methods. To this end, small observation windows are considered and the fractional part of time delay was calculated using a parabolic interpolation. The results show that only Eckart and Hannan-Thomson approaches outperform the basic cross-correlation method when the signal to noise ratio (SNR) is up to 0 dB and the observation duration is 250 ms. This study will be a background for further extension to time-varying delay estimation.
Due to demographic reasons the percentage of elderly citizens in developed countries is rapidly increasing and as a consequence prevention of age-related problems is getting more important. Falls are amongst the most frequent causes for injuries to the aging population and many efforts have been concentrated in fall detection and prevention. This paper presents the design, implementation and experimental analysis of a portable wireless fall detector.
