Biomedical subjects

Zahra M K Moussavi

Publications and source records attributed to Zahra M K Moussavi.

5 recordsLinked to original sources

PubMed2006

A robust method for heart sounds localization using lung sounds entropy.

Heart sounds are the main unavoidable interference in lung sound recording and analysis. Hence, several techniques have been developed to reduce or cancel heart sounds (HS) from lung sound records. The first step in most HS cancellation techniques is to detect the segments including HS. This paper proposes a novel method for HS localization using entropy of the lung sounds. We investigated both Shannon and Renyi entropies and the results of the method using Shannon entropy were superior. Another HS localization method based on multiresolution product of lung sounds wavelet coefficients adopted from was also implemented for comparison. The methods were tested on data from 6 healthy subjects recorded at low (7.5 ml/s/kg) and medium 115 ml/s/kg) flow rates. The error of entropy-based method using Shannon entropy was found to be 0.1 +/- 0.4% and 1.0 +/- 0.7% at low and medium flow rates, respectively, which is significantly lower than that of multiresolution product method and those of other methods reported in previous studies. The proposed method is fully automated and detects HS included segments in a completely unsupervised manner.

Adult↗

PubMed2006

Center of mass approximation and prediction as a function of body acceleration.

In order to maintain postural stability, the central nervous system must maintain equilibrium of the total center of body mass (COM) in relation to its base of support. Thus, the trajectory of the COM provides an important measure of postural stability. Three different models were developed to estimate the COM and the results tested on 16 subjects: namely a neural network, an adaptive fuzzy interface system and a hybrid genetic algorithm sum-of-sines model. The inputs to the models were acquired via two accelerometers, one representing the trunk segment placed on T2 and the second representing the limb segment placed on the shank below the knee joint. The portability, ease of use and low cost (compared with video motion analysis systems) of the accelerometers increases the range of clinics to which the system will be available. The subjects performed a multisegmental movement task on fixed and foam surfaces, thus covering a relatively wide dynamic scope. The results are encouraging for obtaining COM estimates that have clinical applications; the genetic sum-of-sines model was found to be superior when compared to the other two models.

Acceleration↗

PubMed2006

A robust method for estimating respiratory flow using tracheal sounds entropy.

The relationship between respiratory sounds and flow is of great interest for researchers and physicians due to its diagnostic potentials. Due to difficulties and inaccuracy of most of the flow measurement techniques, several researchers have attempted to estimate flow from respiratory sounds. However, all of the proposed methods heavily depend on the availability of different rates of flow for calibrating the model, which makes their use limited by a large degree. In this paper, a robust and novel method for estimating flow using entropy of the band pass filtered tracheal sounds is proposed. The proposed method is novel in terms of being independent of the flow rate chosen for calibration; it requires only one breath for calibration and can estimate any flow rate even out of the range of calibration flow. After removing the effects of heart sounds (which distort the low-frequency components of tracheal sounds) on the calculated entropy of the tracheal sounds, the performance of the method at different frequency ranges were investigated. Also, the performance of the proposed method was tested using 6 different segment sizes for entropy calculation and the best segment sizes during inspiration and expiration were found. The method was tested on data of 10 healthy subjects at five different flow rates. The overall estimation error was found to be 8.3 +/- 2.8% and 9.6 +/- 2.8% for inspiration and expiration phases, respectively.

Adult↗

PubMed2005

On modeling center of foot pressure distortion through a medium.

The center of foot pressure (COP) is a commonly used output measure of the postural control system as it is indicative of the systems stability. A dense piece of foam, i.e., a sponge, can be used to emulate random environmental conditions that distort the ground reaction forces received and interpreted by the cutaneous sensors in the feet; thus introducing uncertainty into the control system. In this paper, the density and size of the sponge was selected such that a subject's weight did not cause full compression. In general, the COP is measured from the bottom of the sponge. As the sponge is used to distort ground reaction forces, it is reasonable then to assume that the COP signal would also be distorted. The use of other sensory information to identify state of balance, and compute necessary balance adjustments, is therefore required. In addition to a sponge, many different types of specialized footwear and inserts are used for people with peripheral neuropathy, such as diabetics. However, it is difficult to design diabetic footwear without a better understanding of the mechanical and physiological effects that different surfaces typical of outdoor terrains, such as a sponge, which cannot be predicted without the sense of the foot, have on balance. Therefore, the goal of this study was to investigate the change of the COP signal from the top and bottom of the sponge. Portable force sensing mats from Vista Medical were used to obtain the COP from the top and bottom of the sponge. The COP measured on the bottom of the sponge is not the same as the COP measured on the top, particularly in the medial-lateral direction. Several linear and nonlinear models were used to identify the unknown plant; i.e., the sponge. Overall, the nonlinear neural network method had superior performance when compared with the linear models. Thus, the results indicate that the signals from the top and bottom of the sponge are in fact different, and furthermore, they are nonlinearly related. A nonlinear mathematical model is proposed which describes COP distortion through a medium such as a sponge. Although the values for the model parameters determined were for a particular sponge, this study suggests that a neural network plant identification model may be applied to any medium other than the sponge; the information can then be used to determine how the balance control model is affected given the sensory information received.

Adult↗

PubMed2004

Classification of normal and dysphagic swallows by acoustical means.

This paper proposes a noninvasive, acoustic-based method to differentiate between individuals with and without dysphagia or swallowing dysfunction. Swallowing sound signals, both normal and abnormal (i.e., at risk of some degree of dysphagia) were recorded with accelerometers over the trachea. Segmentation based on waveform dimension trajectory (a distance-based technique) was developed to segment the nonstationary swallowing sound signals. Two characteristic sections emerged, Opening and Transmission, and 24 characteristic features were extracted and subsequently reduced via discriminant analysis. A discriminant algorithm was also employed for classification, with the system trained and tested using the leave-one-out approach. Overall, 350 signals were used from three bolus consistencies (semisolid, thick and thin liquids). A final screening algorithm correctly classified 13 of 15 control subjects and 11 of 11 subjects with some degree of dysphagia and/or neurological impairments. The proposed method has great potential to reduce the need for videofluoroscopic swallowing studies (the current gold standard method for swallowing assessment, which is invasive and nonportable) and to assist in the overall clinical assessment of swallowing sound signals.

Adolescent↗