Jörg Habetha

Detection of S1 and S2 Heart Sounds by High Frequency Signatures

A new unsupervised and low complexity method for detection of S1 and S2 components of heart sound without the ECG reference is described The most reliable and invariant feature applied in current state-of-the-art of unsupervised heart sound segmentation algorithms is implicitly or explicitly the S1-S2 interval regularity. However; this criterion is inherently prone to noise influence and does not appropriately tackle the heart sound segmentation of arrhythmic cases. A solution based upon a high frequency marker; which is extracted from heart sound using the fast wavelet decomposition, is proposed in order to estimate instantaneous heart rate. This marker is physiologically motivated by the accentuated pressure differences found across heart valves, both in native and prosthetic valves, which leads to distinct high frequency signatures of the valve closing sounds. The algorithm has been validated with heart sound samples collected from patients with mechanical and bio prosthetic heart valve implants in different locations, as well as with patients with native valves. This approach exhibits high sensitivity and specificity without being dependent on the valve type nor their implant position. Further more, it exhibits invariance with respect to normal sinus rhythm (NSR) arrhythmias and sound recording location

IP over wireless mobile ATM-guaranteed wireless QoS by HiperLAN/2

Wireless local area networks (WLANs) designed as wireless ATM systems to extend the services of fixed ATM networks to mobile users appear best suited to provide a guaranteed quality of service (QoS) for wireless IP networks. HiperLAN/2 is an ETSI/BRAN standard providing convergence layers for both IP and ATM classes of service. Besides a description of HiperLAN/2 and its Home Environment Extension, the performance for IP traffic flows is presented from analysis and from simulating a prototype implementation. Co-existence with the IEEE 802.11a WLAN is discussed and the ability of HiperLAN/2 to guarantee QoS even when coexisting is analyzed. Ad hoc networking of HiperLAN/2 is analyzed and two possible extensions of the system are introduced and their performance evaluated, namely, adaptive antennas and wireless base stations.

Detection of Atrial Fibrillation using model-based ECG analysis

Atrial fibrillation (AF) is an arrhythmia that can lead to several patient risks. This kind of arrhythmia affects mostly elderly people, in particular those who suffer from heart failure (one of the main causes of hospitalization). Thus, detection of AF becomes decisive in the prevention of cardiac threats. In this paper an algorithm for AF detection based on a novel algorithm architecture and feature extraction methods is proposed. The aforementioned architecture is based on the analysis of the three main physiological characteristics of AF: i) P wave absence ii) heart rate irregularity and iii) atrial activity (AA). Discriminative features are extracted using model-based statistic and frequency based approaches. Sensitivity and specificity results (respectively, 93.80% and 96.09% using the MIT-BIH AF database) show that the proposed algorithm is able to outperform state-of-the-art methods.

Third Heart Sound Detection Using Wavelet Transform-Simplicity Filter

Heart failure and heart valvar diseases are chronic heart disorders which are potentially diagnosed using heart sound characteristics. Heart sound components S1 and S2 exhibit significant characteristics for valvar dysfunction while pathological S3 sound is a prominent sign for heart failure in elderly people. In this paper, a new automatic detection method of the S3 heart sound is proposed. The method is build upon wavelet transform-simplicity filter which separates S1, S2 and S3 sounds from background noise enabling heart sound segmentation even in the presence of heart murmurs or noise sources. The algorithm uses physiologically inspired criteria to assess the presence of S3 heart sound components and to perform their segmentation. Heart sound samples recorded from children as well as from elderly patients with heart failure were used to test the method. The achieved sensitivity and specificity were 90.35% and 92.35%, respectively.

The MyHeart project: A framework for personal health care applications

MyHeart is a so-called Integrated Project of the European Union aimed at developing intelligent systems for the prevention and monitoring of cardiovascular status. The approach of the MyHeart project is to monitor Vital Body Signs (VBS) with wearable technology, to process the measured data and to give the user (therapy) recommendations from the system. Using its broad base of technical and business expertise, four concepts adressing cardiac health have been developed and tested on a technical, business, realisability and usability level.

MC-CDMA based IEEE 802.11 wireless LAN

In this paper, a modified version of the IEEE 802.11a protocol is proposed and evaluated. We combine multicarrier code division multiple access (MC-CDMA), a novel, high capacity multicarrier modulation technique, with the standard medium access control (MAC) protocol of the 802.11 wireless local area network (WLAN). The suggested system utilizes spread spectrum to divide the channel bandwidth into parallel codechannels, and allows for a number of mobile terminals to share the medium in a more fair and efficient way. The proposed system has been evaluated using a protocol simulator, MACNET-2, and the performance results are discussed in this paper.

A Low-power and Compact-sized Wearable Bio-impedance Monitor with Wireless Connectivity

In this paper, we present a new bio-impedance monitor for wearable and continuous monitoring applications. The system consumes less than 14.4mW when measuring impedance, and 0.9mW when idling. Its compact size (4.8cm × 3cm × 2cm) makes it suitable for portable and wearable use. The proposed system has an accuracy of 0.5Ω and resolution of 0.2Ω on both resistance (R) and reactance (X) measurements, for impedance ranging between (j0.7)Ω to (54+j5)Ω with 2.9<<5.7. We also report the results of the system validation using passive loads as human tissue model, and show our wireless and miniaturized bio-impedance monitoring system has comparable performances with a reference system.

Heart murmur recognition and segmentation by complexity signatures

Heart sound analysis has been a topic of investigation for several years. Since heart sounds directly encode the mechanical activity of the heart, they enable the assessment and follow-up of several types of heart disorders in pre-symptomatic states. Murmurs are the most common abnormality signature in many heart disorders. This paper introduces an algorithm for heart murmur identification. In the presence of murmurs, heart sounds exhibit chaotic behavior. In the proposed method this is assessed based upon the nonlinear dynamics of the signal. In order to segment murmurs from other heart sound components, the signal is transformed into a phase space that is later reconstructed using the embedded matrix. Based on the phase space, the complexity and the strength of the signal are computed. These features are the basis for sound component boundary location. The method has been tested with a database of heart sounds that include diverse heart lesions and heart murmurs. The algorithms achieved 91.09% sensitivity and 95.25% specificity.

Power saving efficiency of a novel packet aggregation scheme for high-throughput WLAN stations at different data rates

Multiple MCS and receiver aggregation (MMRA) is a method to aggregate several MAC protocol data units (MPDUs) that are intended for different receivers and can be transmitted at different modulation and coding schemes (MCS) in the next generation of WLAN, the IEEE 802.11n protocol. Traditional aggregation schemes only link MPDUs between the same source and destination device pair together. The main purpose of aggregation is to reduce the number of access attempts to the medium and thereby significantly increase the protocol efficiency and data throughput. Analytical computations show that MMRA performs better not only in time efficiency compared to other single-rate aggregation schemes, where MPDUs aggregates belonging to different receivers are limited to the lowest MCS, but above all MMRA outperforms single-rate aggregation schemes in terms of power efficiency. MMRA provides a power saving frame format structure, which will allow receiving stations to reduce power consumption and save battery life, crucial for small handled devices.

Fuzzy Rule-Based Mobility and Load Management for Self- Organizing Wireless Networks

Mobility management in a cluster-based, multihop ad hoc network is studied. It is shown that the process of clustering the network into groups of stations has similarities to data analysis, in particular, pattern recognition. In data analysis, the term clustering refers to the process of unsupervised learning, which also describes the situation in a mobile ad hoc network.In this paper, existing data-clustering algorithms are first classified into different categories. Some of the most important types of algorithms are afterwards described, and their applicability to the problem of mobility management in an ad hoc network is studied. It is shown that most of the pattern-recognition algorithms are not suited to the application under consideration.This is why we have developed a new clustering scheme that incorporates some of the ideas of the data classification schemes. The new clustering scheme is based on a rule-based fuzzy inference engine. The main idea consists of the consideration of dynamic clustering events chosen as a consequence of the fuzzy rules. Four types of clustering events are considered.The performance of the clustering algorithm has been evaluated by computer simulation.