Munna Khan

A computer based wireless system for online acquisition, monitoring and digital processing of ECG waveforms

Various ECG instruments have addressed a wide variety of clinical and technical issues. However, there is still scope for improvement in them particularly in the area of their susceptibility to noise, lack of universal connectivity and off-line processing. A prototype system has been developed that caters to these limitations. It includes an analog system and a FM transceiver pair interfaced through sound port of the computer. The real time acquired data is viewed and filtered using MATLAB software. The ECG system described captures the bio-signal faithfully in real time wireless mode with minimum noise and has universal connectivity.

A Review of Measurement and Analysis of Heart Rate Variability

Electrocardiogram (ECG) is one of the most important physiological parameter that gives correct assessment of heart function. QRS complex is a prominent waveform in an ECG that provides the basis for analyzing heart rate variability (HRV). HRV refers to the beat-to-beat alterations in heart rate. Commercial devices these days provide preset computerized measurement of HRV, thus providing the cardiologist a simple tool for both research and clinical learning. To obtain meaningful data from the ECG, a noise free inter-beat interval (IBI) time series is required to be extracted. This is realized using standard peak detection algorithms packed with data acquisition hardware and software. The aim of this paper is to describe various QRS detection methods used to derive HRV. It also reviews various time and frequency domain HRV parameters. The significance and meaning of these different measures of HRV are a potential area of research.

Prediction of quantitative intrathoracic fluid volume to diagnose pulmonary oedema using LabVIEW

Pulmonary oedema is a life-threatening disease that requires special attention in the area of research and clinical diagnosis. Computer-based techniques are rarely used to quantify the intrathoracic fluid volume (IFV) for diagnostic purposes. This paper discusses a software program developed to detect and diagnose pulmonary oedema using LabVIEW. The software runs on anthropometric dimensions and physiological parameters, mainly transthoracic electrical impedance (TEI). This technique is accurate and faster than existing manual techniques. The LabVIEW software was used to compute the parameters required to quantify IFV. An equation relating per cent control and IFV was obtained. The results of predicted TEI and measured TEI were compared with previously reported data to validate the developed program. It was found that the predicted values of TEI obtained from the computer-based technique were much closer to the measured values of TEI. Six new subjects were enrolled to measure and predict transthoracic impedance and hence to quantify IFV. A similar difference was also observed in the measured and predicted values of TEI for the new subjects.

Thorax Physiological Monitoring and Modeling for Diagnosis of Pulmonary Edema

In this paper, the authors prove that variations in thoracic volumes are greatly responsive to the act of breathing i.e., inspiration and expiration. These variations may be adopted for diagnosing various respiration related diseases and pulmonary edema. In this study, the authors present a method to estimate the thoracic volume non-invasively using anthropometric dimensions. The change in the geometry of thorax with the act of breathe is recorded by measuring the anthropometric parameters for nine healthy human subjects. The model based approach shows the extent of its sensitivity in terms of volumetric variations with the state of inspiration and expiration. Many deaths occur due to unavailability of health care and monitoring systems in rural areas and developing countries. The technique presented in this paper takes care of these situations and the volumetric estimation of thorax is independent of any instrumentation, expensive equipment, and clinical environment.

Online acquisition and wireless transmission of carotid pulse waveforms to analyse posture related changes

The physiological parameters of the fighter plane pilot undergo drastic changes leading to G stress accumulation. Heart rate is considered primary mechanism which plays a great role in acceleration protection research especially for G-LOC (G-induced loss of consciousness). Various methods based on various principles have been developed to study heart rate so far. Carotid pulse waveforms obtained from the human subject with the help of piezoelectric transducer may be used to analyse the cardiac activity. Change in heart rate due to change in the posture may be used to explain G stress effect on humans. Carotid signal is acquired by placing piezoelectric sensor based system on the subject’s carotid artery. The piezoelectric sensor has a transducing element which is efficient and effective to sense movement due to carotid pulse and produce piezoelectric signal data in response thereto. The real time data of carotid pulse waveforms of 12 human subjects are acquired and filtered using MATLAB software in various body postures. RR period and pulse amplitudes are quantified from real time recorded carotid signal by visual inspection. Further Statistical analysis is done to calculate the heart rate. The filtered stored data is transmitted wirelessly from one PC to another PC using Teamviewer software.

A computer based prediction for diagnosis of Pulmonary Edema

Pulmonary Edema (PE) is a life threatening disease that needs special attention in the area of research and clinical diagnosis. The computer based technique is rarely reported to quantify the intrathoracic fluid for the diagnosis purpose. In the present paper software has been developed to detect and diagnose pulmonary edema using LabVIEW. The developed software is based on physiological measurements and parameters. The computer based technique is accurate and faster. The reported anthropometric measurements are used to determine transthoracic electrical impedance (TEI) and percent control (PC). The programming of LabVIEW software is done and used to compute the parameters involved to find quantitative PE. An equation relating percent control and thoracic fluid volume (TFV) is obtained using Microsoft Excel. The results of predicted TEI and measured TEI are compared to verify the developed program. It is found that the predicted values of TEI of developed computer based technique are much closer to the measured values of TEI in the present work.

Real time acquisition and PC to PC wireless transmission of human carotid pulse waveform

Carotid pulse is an established physiological parameter used to deduce cardiac information. Technological advances allow non-invasive measurement of carotid waveform, but involve complex electronics. Simple and relatively inexpensive method is devised here to acquire the carotid pulse. Measurements were made non-invasively on human subjects in various postures using piezoelectric sensor. Transducer output is interfaced directly to a computer in real time and carotid wave is viewed successfully on virtual oscilloscope. Stored data is digitally filtered, visually analyzed and transferred wirelessly from one computer to another using windows hyper-terminal and XBee RF transceiver module. Automated analysis algorithm can be further developed.

Acoustic analysis of speech under stress

When a person is emotionally charged, stress could be discerned in his voice. This paper presents a simplified and a non-invasive approach to detect psycho-physiological stress by monitoring the acoustic modifications during a stressful conversation. Voice database consists of audio clips from eight different popular FM broadcasts wherein the host of the show vexes the subjects who are otherwise unaware of the charade. The audio clips are obtained from real-life stressful conversations (no simulated emotions). Analysis is done using PRAAT software to evaluate mean fundamental frequency (F0) and formant frequencies (F1, F2, F3, F4) both in neutral and stressed state. Results suggest that F0 increases with stress; however, formant frequency decreases with stress. Comparison of Fourier and chirp spectra of short vowel segment shows that for relaxed speech, the two spectra are similar; however, for stressed speech, they differ in the high frequency range due to increased pitch modulation.

Wireless Transmission of EMG Signal and Analysis of Its Correlation with Simultaneously Acquired Carotid Pulse Wave Using Dual Channel System

The paper represents work on the challenge of real time, non-invasive simultaneous acquisition and wireless transmission of human physiological parameters using easy and cost effective approach. Electromyograph (EMG) signal detection and analysis is utilized in various clinical and biomedical applications including generation of control signal for prosthetic tools. However, better solutions to obtain noise free signal using compact detection arrangement and wireless communication technologies are being upgraded. In this work, surface EMG signal is acquired under various levels of bicep muscle contractions using simple computer interface and processed using MATLAB based Filter algorithm for online clean display and wireless transmission. EMG and Carotid artery pulsation are then acquired in time coherence to analyse the effect of rectus abdominis muscle contractions on carotid pulse wave and developed into a stand alone MATLAB executable file. The effect manifests as raised amplitude in the Carotid pulse wave form. Hence, a clear correlation is established between surface EMG signal and Carotid artery pulsation to give a compact, cost efficient solution to physiological signal monitoring.

Sub-vocal phoneme-based EMG pattern recognition and its application in diagnosis

Sub-vocal speech recognition provides Silent speech communication that does not disturb or interfere with the surrounding, thus confidential information can be submitted securely. Sub-vocal speech depends on the brains normal output of peripheral nerves and muscles. In this paper, we introduce a new method for statistical features extraction to detect and classify the for sub-vocal EMG pattern. This method is based on exploring the both time and frequency domain information to explore the features. Discrete Wavelet Transform (DWT) is used for signal processing and sub-band feature extraction. Two features Mean absolute deviation and standard deviation have been extracted from different sub-band. Then, these features were fed into a linear classifier to classify the pattern of sub-vocal phonemes. Results showed that accuracy, sensitivity and specificity rates ranges from 70% to 80% is achieved, hence can be used to design expert system for the application in diagnosis purposes.