This paper presents a new approach to descriptions of stabilograms. In the proposed method, a one-dimensional angular-segment function is generated from the stabilographic trajectory data. This ...allows to reduce the data dimensionality and makes the analysis easier. Moreover, three methods of angular-segment function parameterization are also presented in this study. The obtained results confirm the usefulness of the proposed parameters for medical diagnoses.
This text provides several applications scenarios of introduced signals' modeling and analysis framework to solve the practical problems. Some of the challenging practical problems related to ...signal/data processing have been formulated in a manner that the negative free energy maximizing filtering and variational information maximizing analysis algorithms of Kumar et al. could be directly applied to solve the problems. The studied application examples include robust comparison of objects' geometries in images for child ear biometrics, biomedical signals classification, data smoothing for reflection-mode ultrasound imaging, and modeling related applications. The application examples support the mathematical theory of Kumar et al. by providing just the proof-of-concept.
Nuclear magnetic resonance imaging is a routine clinical system used for whole-body patient scanning that provides 3D images. Recent technological innovations have encouraged the use of this ...technology for noninvasive coronary, heart, and chest investigation or for research applications, but the image quality of this technique depends on several factors. Some parameters are linked to the apparatus designed to acquire the magnetic resonance image, whereas others can be controlled by the user. In this paper, the authors analyze the software-controlled magnetic-resonance-imaging parameters to reduce the health examination acquisition time by assuring a good quality of the images. This objective is of fundamental importance to both increase the number of clinical tests produced with this equipment and to reduce the radiation doses in the patients. For this purpose, the parameters that influence the time acquisition and the signal-to-noise ratio were investigated, and a software platform for optimizing the imaging acquisition time was developed.
General anesthesia is usually induced with a combination of drugs. In addition to the hypnotic agent, such as propofol, opioids are often used due to their synergistic hypnotic and analgesic ...properties. However, the effects of opioids on the EEG changes and the clinical state of the patient during anesthesia are complex and hinder the interpretation of the EEG-based depth of anesthesia indexes. In this paper, a novel technology for separating the anesthetic effects of propofol and an ultrashort-acting opioid, remifentanil, using the spectral features of EEG is proposed. By applying a floating search method, a well-performing feature set is achieved to estimate the effects of propofol during induction of anesthesia and to classify whether or not remifentanil has been coadministered. It is shown that including the detection of the presence of opioids to the estimated effect of propofol significantly improves the determination of the clinical state of the patient, i.e., if the patient will respond to a painful stimulation.
The adaptive noise canceller (ANC) is a commonly used linear system method for noise reduction in cases where the disturbing noise can be separately recorded (reference signal) and is not correlated ...with the signal of interest. In case of a periodic disturbing signal, special solutions are described in literature. Problems, however, arise when the propagation of the noise from the source to the recording sensors passes nonlinear structures. An ANC modification proposed for this case by Strobach and applied by several other researchers, thus, uses an artificial reference signal, based on event triggered averaging of segments of the recorded wanted (but disturbed) signal in order to obtain a template for the repetitive distortion sequence and to construct the artificial reference signal. The effect of the averaging and the error introduced by this approximation of the real disturbing signal was not addressed in literature until now, thus, this paper presents some basic theoretical considerations on this topic. Methods are demonstrated in simulations and real biosignal processing, and application aspects are discussed
The mutual information (MI) is a measure of both linear and nonlinear dependences. It can be applied to a time series and a time-delayed version of the same sequence to compute the auto-mutual ...information function (AMIF). Moreover, the AMIF rate of decrease (AMIFRD) with increasing time delay in a signal is correlated with its entropy and has been used to characterize biomedical data. In this paper, we aimed at gaining insight into the dependence of the AMIFRD on several signal processing concepts and at illustrating its application to biomedical time series analysis. Thus, we have analysed a set of synthetic sequences with the AMIFRD. The results show that the AMIF decreases more quickly as bandwidth increases and that the AMIFRD becomes more negative as there is more white noise contaminating the time series. Additionally, this metric detected changes in the nonlinear dynamics of a signal. Finally, in order to illustrate the analysis of real biomedical signals with the AMIFRD, this metric was applied to electroencephalogram (EEG) signals acquired with eyes open and closed and to ictal and non-ictal intracranial EEG recordings.
Improving EMG based classification of basic hand movements using EMD Sapsanis, Christos; Georgoulas, George; Tzes, Anthony ...
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC),
01/2013, Letnik:
2013
Conference Proceeding, Journal Article
This paper presents a pattern recognition approach for the identification of basic hand movements using surface electromyographic (EMG) data. The EMG signal is decomposed using Empirical Mode ...Decomposition (EMD) into Intrinsic Mode Functions (IMFs) and subsequently a feature extraction stage takes place. Various combinations of feature subsets are tested using a simple linear classifier for the detection task. Our results suggest that the use of EMD can increase the discrimination ability of the conventional feature sets extracted from the raw EMG signal.
Evaluation of Parkinson pathology is usually done with the use of ratings made with different motor functional scales. The trouble with this practice is that it is subjective, difficult and it often ...happens that the results of different tests clash between theirs. To overcome these limitations the authors propose the evaluation and the quantification of Parkinson disease by means of suitable biomedical parameters linked to the primary parkinsonian symptoms.
Twelve biomedical quantities have been defined to describe the behavior of hand grip signal; these parameters have been analyzed with statistical methods and their statistical significance has been determined to attain differentiation between pathologic and healthy subjects.
The test results highlight that only the parameters related to the dynamics of the analyzed signals (such as space-time and strength quantities) show very significant statistical difference and can be used to assess Parkinson pathology. Their use represents one attempt to take evaluation objective and very simple.
Finally, a comparative analysis of the results obtained in our study and those achieved from standard functional disability tests has been carried out highlighting the more meaningful correlations. The comparative tests show meaningful correlations that confirm and validate the goodness of the proposed parameters.
The article explains the principles and goals in creating a computer-based system for the measurement of psychomotor functioning, its functionality, and user interface. To illustrate the capabilities ...of the system, the results of analysis of the selected psychomotor tests performed in different groups of patients are presented. The usefulness of the presented tool in the quantitative study of psychomotor functioning is assessed.
Abstract Fetal monitoring using abdominally recorded signals (ADS) allows physicians to detect occurring changes in the well-being state of the fetus from the beginning of pregnancy. Mainly based on ...the fetal electrocardiogram (fECG), it provides the long-term fetal heart rate (fHR) and assessment of the fetal QRS morphology. But the fECG component in ADS is obscured by the maternal ECG (mECG), thus removal of the mECG from ADS improves fECG analysis. This study demonstrates the performance of the event-synchronous interference canceller (ESC) in mECG removal from ADS data, recorded during pregnancy and labor. Its advantage as a compensation method for extended ADS processing is discussed.
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