When Francis Bacon stated in the 16th century that “knowledge itself is power” he could have had no concept of the dilemma facing professionals in the 21st century. The root of this dilemma is the exponential increase in both data and information, in the absence of any widely adopted international standards for data representation. Accessibility to information is also an issue. As far back as 1...

Digitization of biomedical signals has been used in several areas. Some of these include ambulatory monitoring, phone line transmission, database storage, and several other applications in health and biomedical engineering. These applications have helped in diagnostics, patient care, and remote treatment. One example is the digital transmission of ECG signals, from the patient’s house or ambula...

Independent component analysis (ICA) is a method for automatically identifying the underlying factors in a given data set. This rapidly evolving technique is currently finding applications in analysis of biomedical signals (e.g. ERP, EEG, fMRI, optical imaging), and in models of visual receptive fields and separation of speech signals. This article illustrates these applications, and provides a...

During the analysis of real biomedical signals it can almost always be seen noise that distorts the image. The presence of interference is associated with the specific acquisition of these signals. For example in the case of bioelectric signals, disturbances may come from the hardware retrieves those signals, the powerline or the bioelectric activity of body cells. The bioelectric signals, whic...

Recording of physiological and psychological variables in real-life condition is useful in treatment of patients with health problem. In developing countries, delays in giving medical assistance to individuals (patients) usually occur due to the cumbersome process of getting patients’ information to medical personnel. Due to advancement of low cost and portable electronic devices, this paper pr...

In this paper, the performance of Empirical Mode Decomposition (EMD) applied in biomedical signals is investigated and especially it is considered the case of electrocardiogram (ECG). Synthetic ECG signals corrupted with White Gaussian Noise (WGN) as well as real ECG records are employed and a variety of time series lengths is processed with EMD in order to extract the Intrinsic Mode Functions ...

Fatigue at the wheel has been strongly related to car accidents. Traditionally, this phenomenon has been studied in laboratory conditions by means of performance testing. Here, we aimed to improve road safety assessing driver fatigue at the wheel in real scenarios. For this purpose, we have built BioTracker R ©: a flexible non invasive platform. A smartphone and a microcontroller unit are the c...

This paper describes the development of an untethered patient monitoring system. The system acquires three basic biomedical signals from the patient plus a distress call button signal. The three basic signals are electrocardiogram (EKG), phonocardiograms (PCG) and temperature. The signals are transmitted by a RF carrier, received and read into a personal computer through a parallel port interfa...

The paper deals with the use of wavelet transform for signal and image de-noising employing a selected method of thresholding of appropriate decomposition coefficients. The proposed technique is based upon the analysis of wavelet transform and it includes description of global modification of its values. The whole method is verified for simulated signals and applied for processing of biomedical...