In this study, we have compared the efficacy of autoregressive modelling (ARM) and fast Fourier transformation (FFT) of Doppler signals from lower extremity veins of healthy volunteers in various physiologic situations. Compared to FFT, ARM produced smooth spectra and less spectral broadening both in sonograms and power spectra. However, faulty positioning of the peaks along the time axis in FFT-derived power spectral density curves show that FFT is not a suitable method if these graphs are to be used as a diagnostic tool. Analysis of ARM-based venous sonograms and power spectral density graphs revealed that FFT should not be used in signals with high power spectral density levels and low-frequency bandwidth within limited segments of time.

The aim of this study is to scrutinize the ability of principal component analysis (PCA) over power spectral densities (PSD) for common femoral artery blood flow study. Doppler femoral artery signals of patients with occluded arteries and of healthy subjects were recorded. Then, power spectral densities of these signals were obtained using the Welch method. To clearly determine the difference between the groups of occluded patients and healthy subjects, PCA was implemented with patients and healthy matrices derived from PSD. The basic differences between the healthy and occluded patients were acquired with 1st principal component. The use of PCA of physiological waveforms is presented as a powerful method likely to be incorporated into future medical signal processing.

This research is concentrated on the diagnosis of occlusion disease through the analysis of femoral artery Doppler signals with the help of Artificial Neural Network (ANN). Doppler femoral artery signals belong to occlusion patient and healthy subjects were recorded. Afterwards, power spectral densities (PSD) of these signals were obtained using Welch method and Autoregressive (AR) modeling. Multilayer feed forward ANN trained with a Levenberg Marquart (LM) backpropagation algorithm was implemented to these PSD. The designed classification structure has about 98% sensitivity, 97–100% specifity and correct classification is calculated to be 98–99% (for AR modeling and Welch method respectively). The end results are classified as healthy and diseased. Testing results were found to be compliant with the expected results that are derived from the physician's direct diagnosis. The end benefit would be to assist the physician to make the final decision without hesitation.

In this study, we have produced discontinuous Doppler signals of carotid artery and internal jugular vein, simulating respiratory misregistration. The aim of the study is to observe the effect of signal discontinuity and its duration on power spectral density vs. frequency graphs obtained by Autoregressive Modeling. The signals were recorded from ten male volunteers. Signal interruption was performed by moving the sampling volume in and out of the vessel bidirectionally. To estimate the effect of on-line recording time and signal discontinuity on frequency spectra, we have worked on a control data of 30s with continuous signal, and three sets of data with artificially interrupted signals of 30, 60 and 90s duration. Maximum power spectral density, area under the power spectral density, and frequency level corresponding to maximum power spectral density were calculated on frequency spectra. The frequency level corresponding to maximum power spectral density provides the most statistically stable finding in our preliminary data. The signal duration of the signal had no significant effect on the statistical stability of the frequency level.

Facial nerves are very prone to risk of being cut away in the facial surgeries. In order to differentiate the normal tissues from the nerves during the surgeries, facial stimulator is very essential. These stimulators are particularly useful in triggering action potentials in the facial muscle tissue. In the case of any damage to these nerves, paralysis is unavoidable. Second use of the stimulator would be to diagnose how severe the facial problems are. Third use, which is a noninvasive application, is the employment of facial stimulator to treat and diagnose facial problems that arose from temperature differences, cuts or strain. The stimulation is achieved through DC voltage pulses that conform to user-specified amplitude, pulse duration and pulse intervals. These variables are set according to the age, sex, and physiological conditions of the patient. Peripheral Interface Controller is used to derive different pulse patterns. The current specifications of our stimulator are a range of 0.1–20 V pulse amplitude, 0.1– 2 msec pulse duration, and 0.05–1 sec pulse interval. The main benefits of our stimulator are its graphic display that shows the form of pulse, its compact size, and operation on a battery power supply and adaptability to convert to other stimulation applications.

Due to busy traffic in the intensive care units, nurses or physicians are usually challenged to monitor and control the intravenous (IV) pumps. In order to overcome this hurdle, we projected a four-phase research study to develop a nurse console that'll monitor and play with the settings of multiple IV pumps from a central location. In this paper, we studied Phase I that is simply simulation of the operational principles of an IV pump. The second phase is a11 about development of a Software that will have a settings and displaying window, which will eventually be interfaced to a single pump. Revision of the software to add networking capability to monitor and control multiple pumps that'll be integrated with a PC will take place in the third Phase. The fourth and final phase will aim to convert the communication of the whole system to wireless. Introductory phase software is developed using Delphi 5.0 programming language and this program is to help us understand the working principles of an IV Pump by simulating its setting controls and displaying. In the case of unavailability of IV Pumps for experimentation purposes, this simulation will take the place of the pump itself and will enable us to work in the office conditions rather than carrying IV pumps over from the University hospital. Volumes and flow rates of multiple fluids to be injected to the patient can be controlled and displayed in separate windows. Monitorization of beginning and ending times, capability of starting and interruption of each fluid injection are available in our simulation. The lock panel button simulates the password-protected access to the system and protection from deliberate interventions. Especially, digital screen that shows the amount of fluid already given and left in the bottle are very useful for visualization purposes.

In this study, the synchronous pursuit of hearts sounds together with ECG signals have been realized. For this purpose pre-operative and post-operative clinical data related with the patients with heart valve diseases has been recorded through a computer. Thus, an auxiliary method has been provided to determine the patient's health situation. Heart sounds have been obtained using a transducer insulated from its surroundings and ECG signals using surface ECG electrodes. The heart sound and ECG signals have been amplified and filtered independent of each other. After this process, these signals have been converted into digital data to be transferred to computer via I/O card. Thus, the results of heart sounds and ECG signals have been monitored and stored in the computer by software developed in Delphi Programmer Language. However, signals have been transferred in the frequency domain and a power density spectrum was drawn in order to minimize possible errors in medical diagnosis from sound signals stored in the time domain. Also, the durations of heart sound signals have been determined and the power density field has been calculated so that graphs can be compared together. The realized system has been tested with heart valve patients at the Cardiology Department in Erciyes University Gevher Nesibe Hospital