EEG Signal Analysis and Classification

The aim of this paper is to present a novel measurement method for the detection of the respiratory activity (respiration rate and respiration period) based on the use of a continuous wave (6 GHz) microwave radar reflectometry technique. The paper aims, in particular, to explore the effect on the signal quality of distance D between the sensing apparatus and the patient. The measurement method proposed is based on the measurement of the phase variation of the reflection coefficient (S 11 ) signal measured by a vectorial network analyzer connected to a double ridge horn antenna. The S 11 signal has been compared with the synchronous acquisition made by means of a laser Doppler vibrometer (LDVi), measuring the thorax oscillations caused by the respiratory activity. Both signals have been filtered in order to eliminate the effect of high frequency disturbances (heartbeat) and noise. Results show an high correlation between respiration peaks measured with the proposed system and with LDVi; a reduction of the amplitude of the S 11 signal phase (as well as the SNR) is reported in correspondence to an increasing of the distance D (−0.11 dB/cm). Tests have been repeated for standing as well as for sitting condition of the subject confirming a better signal quality for the later. Despite the fact that S 11 phase variation and SNR are reduced by the distance D, in our experiments, it is still possible to correctly measure the respiration period up to 2.5 m. Data measured show that the reflectometeric approach can be used to monitor at distance with sufficient high SNR (18 dB at 2.5 m) the respiration activity of a subject without the need of a direct contact with the subject skin by means of electrods of sensing belts.

Non contact monitoring of the respiration activity by electromagnetic sensing.

The paper present aspects regarding importance of using cloud computing technology for big data processing from biosensors. The wireless sensors for personal area network have applications have been used in healthcare monitoring application. There are some limitations of wireless sensors in terms of memory, energy, computation, communication, scalability and efficient management of the big data collected from biosensors. In healthcare area is need for powerful and scalable high-performance computing and massive storage infrastructure for real-time processing, storing and analyzing (online or offline) of the biosensors data by using complex algorithms for extract required values from database. The patients can interact with hospitals or doctor in offline or online, but the data must be storage by using cloud computing technology because this allow computing, storage and software services (SaaS) with customization possibilities and virtualization at low cost. The Cloud Computing can provide an open, flexible, and reconfigurable platform (PaaS) for monitoring and controlling applications.

Cloud computing for big data from biomedical sensors monitoring, storage and analyze

Previousin vitro testing mainly in aortic position and clinical experience often based on Doppler echocardiographic observations demonstrated an excellent haemodynamic behavior of the On-X valve. However, integrative studies including simultaneous haemodynamic pressure and flow measurements and Doppler echocardiography are lacking. Using our computer controlled mock loop system, two samples of the Mitral 27/29 and one sample of the Conform-X Mitral 25/33 are tested in mitral position. Data include transvalvular pressure gradient and flow as well as transthoracic Doppler echocardiography. The valves were tested in 3 pressure conditions (ventricular systolic pressure of 100, 130, and 160 mmHg) at three different heart rates (60, 100, and 140 beats/min). In addition, ventricular pressure conditions simulating fibrillation were imposed. Both valve types show similar hydrodynamic characteristics and have an effective orifice area of 2.1 cm 2 and a performance index of 0.56 for a cardiac output of 3.5 l/min. Regurgitant volumes remain below 6 ml.

Experimental and numerical modeling of heart valve dynamics

Fretting is defined as a complex process of relative, oscillating micro-displacements of contacting surfaces, as a result of which destruction of the surface layers of these contacting elements takes place [33, 34]. Adhesive damaging of surfaces and the formation of fatigue cracks causes the creation of wear particle as well as their subsequent oxidation and hardening. These products act as an abrasive and are broken up, and their amount increases until the contacting surfaces are separated by a layer of oxide particles and wear conditions are stabilized. Materials conveyance processes, which take place with intensive oxidation, are also observed in the contact area [19]. Four primary mechanisms are responsible for fretting wear processes: adhesion, fatigue, abrasion, and corrosion [20]. Depending on the type and direction of motion, fretting is divided into: tangential, radial, torsional, and rotational fretting [36–38]. Its main consequence is a drastic reduction of the durability and the operational reliability period of devices. The phenomenon of fretting applies to most biomaterials, including metals, polymers, as well as ceramic materials [5, 14, 22, 37]. Advances in implantology impose the application of materials fulfilling ever-greater requirements concerning biofunctionality, with preservation of full biotolerance of implants in the human body [10, 25]. Metallic materials are widely used in dental prosthetics and surgery. They are used, among other things, to reconstruct or replace missing teeth and as elements of orthodontic apparatus for correction of malocclusions [2, 23]. The most commonly used materials are precious metals (gold, platinum, palladium), alloys of cobalt, titanium, and nickel, as well as austenitic steels [3, 5, 6, 11]. It should also be mentioned that, due to the toxic properties of some of these materials Jan Ryszard DąbRowski Marcin klekoTkA Jarosław siDun

Joseph Palladino

Papers

The Biomedical Engineering Handbook: Second Edition.