Modeling, Simulation and Validation of Alteration in Blood Flow and Regional Oxygenation Under Arterial Occlusion.

The paper presents the mathematical modeling along with an experimental approach for the identification of arterial occlusion condition. Arterial occlusion occurs due to development of constriction and/or thrombus in the lumen of the artery. A geometry of the thrombus has been modeled for the analysis of the arterial occlusion condition in modeling part. The proposed model of the thrombus has been simulated using Comsol® multiphysics considering different hemodynamic parameters. Variation in regional oxygen saturation (rSO2) of the arterial occlusion condition has been validated with experimental process, where occlusion of the artery has been done by applying external pressure. The experimental study has been conducted to monitor alteration in rSO2 level profile for occlusion using near infrared spectroscopy (NIRS) methodology. NIRS signal data has been collected from twenty-three subjects with no reported musculoskeletal, psychiatric, or any other neurological deficits using Mespere NeurOs® oxymeter. Experimental data reveal that the oxygenation level decreases considerably due to arterial occlusion as compared to the healthy condition at 95% of confidence interval (p < .05). Dynamic time warping algorithm reveals that variation in rSO2 due to proposed thrombus geometry has more similarity with experimental study.

Correction: Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans.

[This corrects the article DOI: 10.1371/journal.pcbi.1009386.].

Grey-box modeling and hypothesis testing of functional near-infrared spectroscopy-based cerebrovascular reactivity to anodal high-definition tDCS in healthy humans.

Transcranial direct current stimulation (tDCS) has been shown to evoke hemodynamics response; however, the mechanisms have not been investigated systematically using systems biology approaches. Our study presents a grey-box linear model that was developed from a physiologically detailed multi-compartmental neurovascular unit model consisting of the vascular smooth muscle, perivascular space, synaptic space, and astrocyte glial cell. Then, model linearization was performed on the physiologically detailed nonlinear model to find appropriate complexity (Akaike information criterion) to fit functional near-infrared spectroscopy (fNIRS) based measure of blood volume changes, called cerebrovascular reactivity (CVR), to high-definition (HD) tDCS. The grey-box linear model was applied on the fNIRS-based CVR during the first 150 seconds of anodal HD-tDCS in eleven healthy humans. The grey-box linear models for each of the four nested pathways starting from tDCS scalp current density that perturbed synaptic potassium released from active neurons for Pathway 1, astrocytic transmembrane current for Pathway 2, perivascular potassium concentration for Pathway 3, and voltage-gated ion channel current on the smooth muscle cell for Pathway 4 were fitted to the total hemoglobin concentration (tHb) changes from optodes in the vicinity of 4x1 HD-tDCS electrodes as well as on the contralateral sensorimotor cortex. We found that the tDCS perturbation Pathway 3 presented the least mean square error (MSE, median <2.5%) and the lowest Akaike information criterion (AIC, median -1.726) from the individual grey-box linear model fitting at the targeted-region. Then, minimal realization transfer function with reduced-order approximations of the grey-box model pathways was fitted to the ensemble average tHb time series. Again, Pathway 3 with nine poles and two zeros (all free parameters), provided the best Goodness of Fit of 0.0078 for Chi-Square difference test of nested pathways. Therefore, our study provided a systems biology approach to investigate the initial transient hemodynamic response to tDCS based on fNIRS tHb data. Future studies need to investigate the steady-state responses, including steady-state oscillations found to be driven by calcium dynamics, where transcranial alternating current stimulation may provide frequency-dependent physiological entrainment for system identification. We postulate that such a mechanistic understanding from system identification of the hemodynamics response to transcranial electrical stimulation can facilitate adequate delivery of the current density to the neurovascular tissue under simultaneous portable imaging in various cerebrovascular diseases.

FPGA-Based High-Performance Phonocardiography System for Extraction of Cardiac Sound Components Using Inverse Delayed Neuron Model.

The study focuses on the extraction of cardiac sound components using a multi-channel micro-electromechanical system (MEMS) microphone-based phonocardiography system. The proposed multi-channel phonocardiography system classifies the cardiac sound components using artificial neural networks (ANNs) and synaptic weights that are calculated using the inverse delayed (ID) function model of the neuron. The proposed ANN model was simulated in MATLABR and implemented in a field-programmable gate array (FPGA). The proposed system examined both abnormal and normal samples collected from 30 patients. Experimental results revealed a good sensitivity of 99.1% and an accuracy of 0.9.

Improvements in Medical System Safety Analytics for Authentic Measure of Vital Signs Using Fault-Tolerant Design Approach.

The study presents a novel design method that improves system availability using fault-tolerant features in a non-invasive medical diagnostic system. This approach addresses the effective detection of functional faults, improves the uninterruptible system operating period with reduced false alarms, and provides an authentic measure of vital cardiac signs using diverse multimodal sensing elements like the photoplethysmogram (PPG) and the ECG. Most systems rely on a 1oo1 (one-out-of-one) design method, which inherently limits accuracy in existing practice. In this proposed approach, the quality of segregated authentic vital sign measured values could tremendously benefit the performance of resourceful nursing with negligible alarm fatigue and predict illness more accurately. The system builds upon the selected 2oo2 (two-out-of-two) safety-related design architecture and is evaluated with implemented functions like the fault detection and identification logic, the correlation coefficient-based safety function, and the fault-tolerant safe degradation switching mechanism for accurate measurements. The system was tested on 50 adults of various age groups. The analyzed captured data showed highly accurate vital sign data in this fault-tolerant approach with reduced false alarms. The proposed design method evaluated safety-related mechanisms along with a combination of the same and diverse sensors in a medical monitoring device, showing more reliable functioning of the system and authentic data for better nursing. This design approach showed a 45-55% increased improvement in system availability, thus allowing for accurate and uninterruptable tracking of vital signs for better nursing during critical times in the ICU.

Statistical Analysis to Find out the Optimal Locations for Non Invasive Brain Stimulation.

Non-invasive brain electrical stimulation (NIBES) techniques are progressively used for modulation of neuronal membrane potentials, which alters cortical excitability. The neuronal activity depends on position of channel locations for electrodes and the amount and direction of injected weak current through the target neurons area. In the present paper hybrid near infrared spectroscopy and electroencephalogram (NIRS-EEG) open access dataset for brain computer interface (BCI) has been used to find the best locations for NIBES. The percentage oxygen saturation has been calculated with the help of provided NIRS experimental dataset of changes in concentration of oxy-hemoglobin (HbO2) and deoxy-hemoglobin (Hb) in thirty-six scalp site locations of twenty-eight healthy subjects. The variation in standard deviation have been calculated for given pre-processed EEG signals of thirty locations for same twenty-eight healthy subjects. The statistical one-way ANOVA method has been used to find out the best channels and locations which are having less variation in all motion artifacts. In this method, F value is calculated for these locations and those locations are selected which are significant at 99% confidence interval (P < 0.01). In this study, out of sixty-six locations sixteen best locations have been selected for non-invasive brain electrical stimulation. This pilot study has been used to find out the appropriate locations on the scalp sites to place the electrodes to provide weak direct current stimulation which are less affected by motion artifacts.

Cortical Excitability through Anodal Transcranial Direct Current Stimulation: a Computational Approach.

The present study analyzes the effect of various anodal transcranial direct current stimulation (tDCS) configurations in terms of electric field and voltage distribution. The work aims to assess the role of tDCS configurations considering subject's specific anatomy in a computational framework. The study considers the effect of conventional and high definition transcranial direct current stimulation (HD-tDCS) by using synthetic magnetic resonance image (MRI) volumes for normal brain and brain with multiple sclerosis (MS) lesions. The configurations presented in this study compare the effect of various m x n HD-tDCS and conventional tDCS on standard Montreal Neurological Institute (MNI152) head model which is a T1 MRI volume obtained by averaging 152 individuals at 1 mm3 resolution. The study evaluates the role of disc, ring, and pad electrodes in various configurations of tDCS application. The approximate surface area for each electrode in HD-tDCS application considered in the study is 113 mm2. The significant difference in voltage distribution has been observed due to 1 × 1 HD-tDCS configuration on synthetic MRI of normal and lesion brain using disc and ring electrodes. For region specific approach, outer ring structured electrode configuration - an extended m x n HD-tDCS configuration is presented in this study. The proposed outer ring HD-tDCS configuration has been compared with m × 1 and m × 2 HD-tDCS configurations with different types of electrodes in terms of focality, induced electric field and voltage generated. On the basis of the insights gained from the analysis of various tDCS configurations on standard, normal and lesion structural data, the design of HD-tDCS as a tool in neuro-rehabilitation has been proposed. This computational model approach is useful in fixing various parameters of current stimulation: intensity, type and arrangement of electrodes and target region by using structural MRI data of an individual prior to the real stimulation in clinical trials.

Non Invasive Brain Stimulation Study Based on Ischemic Stroke Patients.

Non-invasive brain stimulation (NIBS) methods are progressively used as neuromodulator and showing optimistic potential for medical practice. In present study experimental NIRS-tDCS raw dataset of twenty-two sub-acute ischemic stroke patients has been used to explore the significant variation in measured NIRS signal namely cerebral oxygenation, oxy-hemoglobin and deoxy-hemoglobin before and after tDCS. Pearson correlation statistical method is used to determine the strength and relationship between hemodynamic responses. The negative correlation has been shown between oxy-hemoglobin and deoxy-hemoglobin before and after tDCS at 99% confidence interval (P<; 0.01). One sample t-test is used to determine the pre to post tDCS significant change in regional cerebral oxygenation, oxy-hemoglobin and deoxy-hemoglobin independently at 99% confidence interval (P<; 0.01). On the basis of significant change in the NIRS measurement parameters (HbO2, Hb and rSO2) the healthy and lesioned hemisphere of patients suffering from sub-acute ischemic stroke have been classified. A significant increase in pre to post rSO2 has been found in the healthy hemispheres of patients. For the lesioned hemisphere, the two cases were found. One is due to the decrease in rSO2 after tDCS and significant change from pre to post rSO2. The second is negligible pre to post change in the rSO2 and insignificant variation in rSO2.

Molecular Scale Optimum Hydrophobicity To Establish an Enhanced Probe-Protein Interaction: Near-Infrared Imaging of Albumin Biosynthesis Modulation.

Albumin is the most abundant serum protein and shows variation in its synthesis rate in different physiological and pathophysiological conditions. Thus, there might be an association expected between serum albumin concentration and body health. A library of NIR probes engineered with the optimum hydrophobicity has been developed and characterized using spectroscopy techniques and was employed to understand the variation of hepatic albumin synthesis rates on physiological and pathophysiological states. Given the importance of hydrophobicity in rendering an effective interaction of small molecules with biomolecules, strategic structure interaction relationship studies led us toward the development of a potent emissive molecular probe through chemical library development. By exploration of these newly developed molecular probes, our study elegantly showed how a pathophysiological condition like the hyperinsulinemic state significantly downregulates albumin biosynthesis in HepG2 cells using fluorescence microscopy as a tool. An excellent correlation between the albumin transcript level and fluorescence intensity inside the cells has been observed. The key role of hydrophobicity resulting in an effective interaction of the probes with albumin, thus leading to strong optical signals, has been experimentally demonstrated in this report. Also, a siRNA interference technique has been utilized to establish the excellent selectivity of the developed probes with excitation as well as emission in the NIR region. We therefore have established through our experimental findings that suitable cell permeable emissive molecular markers with a high degree of albumin specificity can be used as a good optical tool for studying the effect of hyperinsulinemia on albumin biosynthesis modulation.

Coronary artery disease detection using photoplethysmography.

This paper presents a technique for coronary artery disease (CAD) detection through photoplethysmography (PPG). This work is aimed at developing a non-invasive, inexpensive screening technique suitable for home monitoring. Time domain analysis of PPG signal and its second derivative has been carried out to extract distinguishing features. Support Vector Machine based classifier has been used to classify CAD patients. ICU patient data from MIMIC-II dataset has been used for performance evaluation. Sensitivity of 85% and specificity of 78% has been achieved for the analysed data.

Cardiac arrhythmia detection using photoplethysmography.

Cardiovascular Diseases (CVDs) cause a very large number of casualties around the world every year and cardiac arrhythmias contribute to significant proportion of CVD related deaths. Bedside cardiac activity monitors in hospitals are based on electrocardiogram (ECG) processing and are known to produce too many false alarms. Moving beyond bedside care, ECG is not very suitable for use in wearable devices. Photoplethysmography (PPG) on the other hand provides an inexpensive and more wearable device-friendly alternative. This work presents a technique to detect life threatening arrhythmias using only PPG waveforms. PhysioNet Challenge 2015 data is used to detect five types of arrhythmias namely, tachycardia, bradycardia, asystole, ventricular tachycardia and ventricular fibrillation. A novel technique is employed to assign pulse quality index to every PPG pulse and highest quality portion of the signal is used for detection. Results indicate that PPG provides a viable alternative for conventional ECG based detection. An overall true positive rate (TPR) of 93% was achieved with true negative rate (TNR) of 53.78% suggesting that PPG is a viable option for arrhythmia detection.

Near-Infrared Spectroscopy - Electroencephalography-Based Brain-State-Dependent Electrotherapy: A Computational Approach Based on Excitation-Inhibition Balance Hypothesis.

Stroke is the leading cause of severe chronic disability and the second cause of death worldwide with 15 million new cases and 50 million stroke survivors. The poststroke chronic disability may be ameliorated with early neuro rehabilitation where non-invasive brain stimulation (NIBS) techniques can be used as an adjuvant treatment to hasten the effects. However, the heterogeneity in the lesioned brain will require individualized NIBS intervention where innovative neuroimaging technologies of portable electroencephalography (EEG) and functional-near-infrared spectroscopy (fNIRS) can be leveraged for Brain State Dependent Electrotherapy (BSDE). In this hypothesis and theory article, we propose a computational approach based on excitation-inhibition (E-I) balance hypothesis to objectively quantify the poststroke individual brain state using online fNIRS-EEG joint imaging. One of the key events that occurs following Stroke is the imbalance in local E-I (that is the ratio of Glutamate/GABA), which may be targeted with NIBS using a computational pipeline that includes individual "forward models" to predict current flow patterns through the lesioned brain or brain target region. The current flow will polarize the neurons, which can be captured with E-I-based brain models. Furthermore, E-I balance hypothesis can be used to find the consequences of cellular polarization on neuronal information processing, which can then be implicated in changes in function. We first review the evidence that shows how this local imbalance between E-I leading to functional dysfunction can be restored in targeted sites with NIBS (motor cortex and somatosensory cortex) resulting in large-scale plastic reorganization over the cortex, and probably facilitating recovery of functions. Second, we show evidence how BSDE based on E-I balance hypothesis may target a specific brain site or network as an adjuvant treatment. Hence, computational neural mass model-based integration of neurostimulation with online neuroimaging systems may provide less ambiguous, robust optimization of NIBS, and its application in neurological conditions and disorders across individual patients.

EEG-NIRS based assessment of neurovascular coupling during anodal transcranial direct current stimulation--a stroke case series.

A method for electroencephalography (EEG) - near-infrared spectroscopy (NIRS) based assessment of neurovascular coupling (NVC) during anodal transcranial direct current stimulation (tDCS). Anodal tDCS modulates cortical neural activity leading to a hemodynamic response, which was used to identify impaired NVC functionality. In this study, the hemodynamic response was estimated with NIRS. NIRS recorded changes in oxy-hemoglobin (HbO2) and deoxy-hemoglobin (Hb) concentrations during anodal tDCS-induced activation of the cortical region located under the electrode and in-between the light sources and detectors. Anodal tDCS-induced alterations in the underlying neuronal current generators were also captured with EEG. Then, a method for the assessment of NVC underlying the site of anodal tDCS was proposed that leverages the Hilbert-Huang Transform. The case series including four chronic (>6 months) ischemic stroke survivors (3 males, 1 female from age 31 to 76) showed non-stationary effects of anodal tDCS on EEG that correlated with the HbO2 response. Here, the initial dip in HbO2 at the beginning of anodal tDCS corresponded with an increase in the log-transformed mean-power of EEG within 0.5Hz-11.25Hz frequency band. The cross-correlation coefficient changed signs but was comparable across subjects during and after anodal tDCS. The log-transformed mean-power of EEG lagged HbO2 response during tDCS but then led post-tDCS. This case series demonstrated changes in the degree of neurovascular coupling to a 0.526 A/m(2) square-pulse (0-30 s) of anodal tDCS. The initial dip in HbO2 needs to be carefully investigated in a larger cohort, for example in patients with small vessel disease.

Primary study for detection of arterial blood pressure waveform components.

The paper presents a technique to detect significant systolic peaks, the percussion (P) and tidal peak (T) and diastolic peak (D) from the arterial blood pressure (ABP) waveform. The technique is aimed at robust detection even in presence of significant noise. Singular Value Decomposition (SVD) based dominant period extraction of the ABP waveform followed by wavelet transform and local peak detection is applied to detect the points of interest. MIMIC-II ABP databse serves as a training dataset to select SVD and wavelet transform parameters and CSL Benchmark database is used to analyze the technique. Salient systolic peak detection for the CSL dataset was performed with positive predictive value and sensitivity figures of 98.48% and 99.24% respectively.

Corticospinal excitability changes to anodal tDCS elucidated with NIRS-EEG joint-imaging: An ischemic stroke study.

Transcranial direct current stimulation (tDCS) has been shown to modulate corticospinal excitability. We used near-infrared spectroscopy (NIRS)-electroencephalography (EEG) joint-imaging during and after anodal tDCS to measure changes in mean cerebral haemoglobin oxygen saturation (rSO2) along with changes in the log-transformed mean-power of EEG within 0.5 Hz-11.25 Hz. In two separate studies, we investigated local post-tDCS alterations from baseline at the site of anodal tDCS using NIRS-EEG/tDCS joint-imaging as well as local post-tDCS alterations in motor evoked potentials (MEP)-measure of corticospinal excitability. In the first study, we found that post-tDCS changes in the mean rSO2 from baseline mostly correlated with the corresponding post-tDCS change in log-transformed mean-power of EEG within 0.5 Hz-11.25 Hz. Moreover, a decrease in log-transformed mean-power of EEG within 0.5 Hz-11.25 Hz corresponded with an increase in the MEP-measure of corticospinal excitability--found in the second study. Therefore, we propose to combine NIRS-EEG/tDCS joint-imaging with corticospinal excitability investigation in a single study to confirm these finding. Furthermore, we postulate that the innovative technologies for portable NIRS-EEG neuroimaging may be leveraged to objectively quantify the progress (e.g., corticospinal excitability alterations) and dose tDCS intervention as an adjuvant treatment during neurorehabilitation.

Development of Point of Care Testing Device for Neurovascular Coupling From Simultaneous Recording of EEG and NIRS During Anodal Transcranial Direct Current Stimulation.

This paper presents a point of care testing device for neurovascular coupling (NVC) from simultaneous recording of electroencephalogram (EEG) and near infrared spectroscopy (NIRS) during anodal transcranial direct current stimulation (tDCS). Here, anodal tDCS modulated cortical neural activity leading to hemodynamic response can be used to identify the impaired cerebral microvessels functionality. The impairments in the cerebral microvessels functionality may lead to impairments in the cerebrovascular reactivity (CVR), where severely reduced CVR predicts the chances of transient ischemic attack and ipsilateral stroke. The neural and hemodynamic responses to anodal tDCS were studied through joint imaging with EEG and NIRS, where NIRS provided optical measurement of changes in tissue oxy-([Formula: see text] and deoxy-([Formula: see text]) hemoglobin concentration and EEG captured alterations in the underlying neuronal current generators. Then, a cross-correlation method for the assessment of NVC underlying the site of anodal tDCS is presented. The feasibility studies on healthy subjects and stroke survivors showed detectable changes in the EEG and the NIRS responses to a 0.526 A/[Formula: see text] of anodal tDCS. The NIRS system was bench tested on 15 healthy subjects that showed a statistically significant (p < 0.01) difference in the signal-to-noise ratio (SNR) between the ON- and OFF-states of anodal tDCS where the mean SNR of the NIRS device was found to be 42.33 ± 1.33 dB in the ON-state and 40.67 ± 1.23 dB in the OFF-state. Moreover, the clinical study conducted on 14 stroke survivors revealed that the lesioned hemisphere with impaired circulation showed significantly (p < 0.01) less change in [Formula: see text] than the nonlesioned side in response to anodal tDCS. The EEG study on healthy subjects showed a statistically significant (p < 0.05) decrease around individual alpha frequency in the alpha band (8-13 Hz) following anodal tDCS. Moreover, the joint EEG-NIRS imaging on 4 stroke survivors showed an immediate increase in the theta band (4-8 Hz) EEG activity after the start of anodal tDCS at the nonlesioned hemisphere. Furthermore, cross-correlation function revealed a significant (95% confidence interval) negative cross correlation only at the nonlesioned hemisphere during anodal tDCS, where the log-transformed mean-power of EEG within 0.5-11.25 Hz lagged [Formula: see text] response in one of the stroke survivors with white matter lesions. Therefore, it was concluded that the anodal tDCS can perturb the local neural and the vascular activity (via NVC) which can be used for assessing regional NVC functionality where confirmatory clinical studies are required.

Anterior temporal artery tap to identify systemic interference using short-separation NIRS measurements: A NIRS/EEG-tDCS study.

Transcranial direct current stimulation (tDCS) has been shown to modulate neural activity. Neural activity has been shown to be closely related, spatially and temporally, to cerebral blood flow (CBF) that supplies glucose via neurovascular coupling. Therefore, noninvasive and continuous monitoring of neural activity is possible with a measure of cerebral hemoglobin oxygenation using near-infrared spectroscopy (NIRS). In principal accordance, NIRS can capture the hemodynamic response to tDCS but the challenge remains in removing the systemic interference occurring in the superficial layers of the head that are also affected by tDCS. An approach may be to use short optode separations to measure systemic hemodynamic fluctuations occurring in the superficial layers which can then be used as regressors to remove the systemic contamination. Here, we demonstrate that temporal artery tap may be used to better identify systemic interference using this short-separation NIRS. Moreover, NIRS-EEG joint-imaging during anodal tDCS was used to measure changes in mean cerebral haemoglobin oxygen saturation (rSO2) along with changes in the log-transformed mean-power of EEG within 0.5 Hz-11.25 Hz. We found that percent change in the mean rSO2 better correlated with the corresponding percent change in log-transformed mean-power of EEG within 0.5 Hz-11.25 Hz frequency band after removing the systemic contamination using the temporal artery tap method. Based on our findings, we propose that anterior temporal artery tap technique presented in this paper may be able to classify carotid stenosis, external carotid artery stenosis, and internal carotid artery stenosis patients using the laterality in the hemodynamic response evoked by anodal tDCS both at the brain as well as at the superficial layers. These findings may have important implications for both prognosis and rehabilitation of patients with intracranial stenosis.

Noninvasive blood glucose sensing using near infra-red spectroscopy and artificial neural networks based on inverse delayed function model of neuron.

In this paper, a non-invasive blood glucose sensing system is presented using near infra-red(NIR) spectroscopy. The signal from the NIR optodes is processed using artificial neural networks (ANN) to estimate the glucose level in blood. In order to obtain accurate values of the synaptic weights of the ANN, inverse delayed (ID) function model of neuron has been used. The ANN model has been implemented on field programmable gate array (FPGA). Error in estimating glucose levels using ANN based on ID function model of neuron implemented on FPGA, came out to be 1.02 mg/dl using 15 hidden neurons in the hidden layer as against 5.48 mg/dl using ANN based on conventional neuron model.

Fuzzy entropy based motion artifact detection and pulse rate estimation for fingertip photoplethysmography.

The paper presents a fingertip photoplethysmography (PPG) based technique to estimate the pulse rate of the subject. The PPG signal obtained from a pulse oximeter is used for the analysis. The input samples are corrupted with motion artifacts due to minor motion of the subjects. Entropy measure of the input samples is used to detect the motion artifacts and estimate the pulse rate. A three step methodology is adapted to identify and classify signal peaks as true systolic peaks or artifact. CapnoBase database and CSL Benchmark database are used to analyze the technique and pulse rate estimation was performed with positive predictive value and sensitivity figures of 99.84% and 99.32% respectively for CapnoBase and 98.83% and 98.84% for CSL database respectively.

Field programmable gate array based fuzzy neural signal processing system for differential diagnosis of QRS complex tachycardia and tachyarrhythmia in noisy ECG signals.

The paper reports of a Field Programmable Gate Array (FPGA) based embedded system for detection of QRS complex in a noisy electrocardiogram (ECG) signal and thereafter differential diagnosis of tachycardia and tachyarrhythmia. The QRS complex has been detected after application of entropy measure of fuzziness to build a detection function of ECG signal, which has been previously filtered to remove power line interference and base line wander. Using the detected QRS complexes, differential diagnosis of tachycardia and tachyarrhythmia has been performed. The entire algorithm has been realized in hardware on an FPGA. Using the standard CSE ECG database, the algorithm performed highly effectively. The performance of the algorithm in respect of QRS detection with sensitivity (Se) of 99.74% and accuracy of 99.5% is achieved when tested using single channel ECG with entropy criteria. The performance of the QRS detection system has been compared and found to be better than most of the QRS detection systems available in literature. Using the system, 200 patients have been diagnosed with an accuracy of 98.5%.