Showing papers by "Ervin Sejdic published in 2012"

Multimedia Signals and Systems

Abstract: Multimedia signals include different data types (text, sound, graphics, picture, animations, video, etc.), which can be time-dependent (sound, video and animation) or spatially-dependent (images, text and graphics). Hence, the multimedia systems represent an interdisciplinary cross-section of the following areas: digital signal processing, computer architecture, computer networks and telecommunications. Multimedia Signals and Systems is an introductory text, designed for students or professionals and researchers in other fields, with a need to learn the basics of signals and systems. A considerable emphasis is placed on the analysis and processing of multimedia signals (audio, images, video). Additionally, the book connects these principles to other important elements of multimedia systems such as the analysis of optical media, computer networks, QoS, and digital watermarking.

The Effects of Rhythmic Sensory Cues on the Temporal Dynamics of Human Gait

Abstract: Walking is a complex, rhythmic task performed by the locomotor system. However, natural gait rhythms can be influenced by metronomic auditory stimuli, a phenomenon of particular interest in neurological rehabilitation. In this paper, we examined the effects of aural, visual and tactile rhythmic cues on the temporal dynamics associated with human gait. Data were collected from fifteen healthy adults in two sessions. Each session consisted of five 15-minute trials. In the first trial of each session, participants walked at their preferred walking speed. In subsequent trials, participants were asked to walk to a metronomic beat, provided through visually, aurally, tactile or all three cues (simultaneously and in sync), the pace of which was set to the preferred walking speed of the first trial. Using the collected data, we extracted several parameters including: gait speed, mean stride interval, stride interval variability, scaling exponent and maximum Lyapunov exponent. The extracted parameters showed that rhythmic sensory cues affect the temporal dynamics of human gait. The auditory rhythmic cue had the greatest influence on the gait parameters, while the visual cue had no statistically significant effect on the scaling exponent. These results demonstrate that visual rhythmic cues could be considered as an alternative cueing modality in rehabilitation without concern of adversely altering the statistical persistence of walking.

Compressive sampling of swallowing accelerometry signals using time-frequency dictionaries based on modulated discrete prolate spheroidal sequences

Abstract: Monitoring physiological functions such as swallowing often generates large volumes of samples to be stored and processed, which can introduce computational constraints especially if remote monitoring is desired. In this article, we propose a compressive sensing (CS) algorithm to alleviate some of these issues while acquiring dual-axis swallowing accelerometry signals. The proposed CS approach uses a time-frequency dictionary where the members are modulated discrete prolate spheroidal sequences (MDPSS). These waveforms are obtained by modulation and variation of discrete prolate spheroidal sequences (DPSS) in order to reflect the time-varying nature of swallowing acclerometry signals. While the modulated bases permit one to represent the signal behavior accurately, the matching pursuit algorithm is adopted to iteratively decompose the signals into an expansion of the dictionary bases. To test the accuracy of the proposed scheme, we carried out several numerical experiments with synthetic test signals and dual-axis swallowing accelerometry signals. In both cases, the proposed CS approach based on the MDPSS yields more accurate representations than the CS approach based on DPSS. Specifically, we show that dual-axis swallowing accelerometry signals can be accurately reconstructed even when the sampling rate is reduced to half of the Nyquist rate. The results clearly indicate that the MDPSS are suitable bases for swallowing accelerometry signals.

A Method for Removal of Low Frequency Components Associated with Head Movements from Dual-Axis Swallowing Accelerometry Signals

Abstract: Head movements can greatly affect swallowing accelerometry signals. In this paper, we implement a spline-based approach to remove low frequency components associated with these motions. Our approach was tested using both synthetic and real data. Synthetic signals were used to perform a comparative analysis of the spline-based approach with other similar techniques. Real data, obtained data from 408 healthy participants during various swallowing tasks, was used to analyze the processing accuracy with and without the spline-based head motions removal scheme. Specifically, we analyzed the segmentation accuracy and the effects of the scheme on statistical properties of these signals, as measured by the scaling analysis. The results of the numerical analysis showed that the spline-based technique achieves a superior performance in comparison to other existing techniques. Additionally, when applied to real data, we improved the accuracy of the segmentation process by achieving a 27% drop in the number of false negatives and a 30% drop in the number of false positives. Furthermore, the anthropometric trends in the statistical properties of these signals remained unaltered as shown by the scaling analysis, but the strength of statistical persistence was significantly reduced. These results clearly indicate that any future medical devices based on swallowing accelerometry signals should remove head motions from these signals in order to increase segmentation accuracy.

Visualization of Trunk Muscle Synergies During Sitting Perturbations Using Self-Organizing Maps (SOM)

Abstract: The purpose of this study was to demonstrate the use of the self-organizing map (SOM) method for visualization, modeling, and comparison of trunk neuromuscular synergies during perturbed sitting. Thirteen participants were perturbed at the level of the sternum, in eight directions during sitting. Electromyographic (EMG) responses of ten trunk muscles involved in postural control were recorded. The SOM was used to encode the EMG responses on a 2-D projection (i.e., visualization). The result contains similar patterns mapped close together on the plot therefore forming clusters of data. Such visualization of ten EMG responses, following eight directional perturbations, allows for comparisons of direction-dependent postural synergies. Direction-dependent neuromuscular response models for each muscle were then constructed from the SOM visualization. The results demonstrated that the SOM was able to encode neuromuscular responses, and the SOM visualization showed direction-dependent differences in the postural synergies. Moreover, each muscle was modeled using the SOM-based method, and derived models showed that all muscles, except for one, produced a Gaussian fit for direction-dependent responses. Overall, SOM analysis offers a reverse engineering method for exploration and comparison of complex neuromuscular systems, which can describe postural synergies at a glance.

Quantitative classification of pediatric swallowing through accelerometry

Abstract: Background Dysphagia or swallowing disorder negatively impacts a child’s health and development. The gold standard of dysphagia detection is videofluoroscopy which exposes the child to ionizing radiation, and requires specialized clinical expertise and expensive institutionally-based equipment, precluding day-to-day and repeated assessment of fluctuating swallowing function. Swallowing accelerometry is the non-invasive measurement of cervical vibrations during swallowing and may provide a portable and cost-effective bedside alternative. In particular, dual-axis swallowing accelerometry has demonstrated screening potential in older persons with neurogenic dysphagia, but the technique has not been evaluated in the pediatric population.

Asynchronous sampling and reconstruction of sparse signals

Abstract: Asynchronous signal processing is an appropriate low-power approach for the processing of bursty signals typical in biomedical applications and sensing networks Different from the synchronous processing, based on the Shannon-Nyquist sampling theory, asynchronous processing is free of aliasing constrains and quantization error, while allowing continuous-time processing In this paper we connect level-crossing sampling with time-encoding using asynchronous sigma delta modulators, to develop an asynchronous decomposition procedure similar to the Haar transform wavelet decomposition Our procedure provides a way to reconstruct bounded signals, not necessarily band-limited, from related zero-crossings, and it is especially applicable to decompose sparse signals in time and to denoise them Actual and synthetic signals are used to illustrate the advantages of the decomposer

Recovering heart sounds from sparse samples

Abstract: Continuous monitoring of physiological functions such as heart sounds can pose severe constraints on data acquisition and processing systems, especially if remote monitoring is desired. In this paper, we investigate the utility of a recently proposed compressive sensing (CS) algorithm based on modulated discrete prolate spheroidal sequences (MDPSS) for recovering sparsely sampled heart sounds. In particular, we investigate the recordings containing opening snap (OS) or the third heart sounds (S3) in addition to first and second heart sounds. The results of numerical analysis show that heart sounds can be accurately reconstructed even when the sampling rate is reduced to 40% of the original sampling frequency.

A unified approach for the estimation of instantaneous frequency and its derivatives for non-stationary signals analysis

Abstract: A unified approach for the estimation of the first three phase derivatives of non-stationary signals is proposed in this paper. The possibility to accurately estimate phase derivatives is important in many applications dealing with objects velocity, acceleration and acceleration rate, such as the radar applications and mechanics. The estimation approach is based on definition of the complex-lag distribution. The proposed distribution is inspired by the concepts of complex analysis theory. The general form of distribution for the estimation of the first, second and third derivative of the phase is derived from the specific individual cases. The theoretical considerations are illustrated in the example with fast varying signal phase function.

Compressive asynchronous decomposition of heart sounds

Abstract: Because of the need to control power consumption, in many biomedical applications asynchronous processing of the data is more appropriate. In this paper, we present a scale-based decomposition algorithm for analog signals similar to the wavelet decomposition. Our procedure uses asynchronous sigma delta modulators (ASDMs) to represent the amplitude of a signal using the zero-crossing times of a binary signal. Changing the zero-crossing times into random sequences of pulse widths, it can be shown to be equivalent to an optimal level-crossing sampler using local averages as the quantization levels. Applying the generation of multi-level signals from the output of ASDMs for different scale parameters we are able to obtain a decomposer that in a few stages provides a close representation of the signal. To illustrate the performance of the proposed decomposition, we consider its application to the representation of heart sounds.

Mathematical Transforms Used for Multimedia Signal Processing

Abstract: The algorithms for Multimedia data processing are mostly based and derived from the general signal processing techniques. They usually include standard transforms such as the Fourier transform, Discrete cosine transform, and Wavelet transform. Hence, in order to provide a better understanding of algorithms in Multimedia systems, the fundamental concepts of commonly used mathematical transforms have been considered and explained using several illustrative examples. Beside the Fourier transform, Discrete cosine transform and Wavelet based multiresolution analysis, this chapter additionally includes transformations used in advanced multimedia applications, particularly, the time-frequency analysis and the Hermite functions expansion. For the signals in noisy environment, the concept of robust signal representations is derived in detail, as well as the nonstationary time-varying filtering approach. Therefore, this chapter provides both basic and advanced theoretical background on the mathematical transforms used in multimedia processing. Finally, an arbitrary time-frequency plane division using time-varying and frequency-varying windows is considered, together with the corresponding composite transformations.

Multimedia Signals and Systems in Telemedicine

Abstract: Nowadays, the telemedicine has been considered as a new and perspective research area which uses the advantages of multimedia systems to provide efficient medical services at the distance. The future hospitals should provide health care services to patients all over the world using multimedia systems in the frame of telemedicine technologies. Signal and image acquisition, signal and image storage, signal and image display and processing are the major components of telemedicine. Aiming to promote the advantages of telemedicine to the multimedia signal processing community, this Chapter reviews different aspects of medical practice such as telenursing, teleradiology, telesurgery, and telepharmacy.

Method and system of segmentation and time duration analysis of dual axis accelerometry signals

Abstract: The proposed invention is a method and system for the segmentation of dual-axis accelerometry signals for the purpose of identifying problematic swallowing events. The method and system employ a sensor, a data collection means including an algorithm for analysis of the data. The proposed invention considers the stochastic properties of swallowing signals in both directions, A-P and S-I to extract events associated with swallowing. A segmentation algorithm may be applied to the signals to establish the time duration of swallows and swallows may be classified with respect to gender, body mass index, age or types of swallow.