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Inclinometry and video analyses can provide objective measures of physical workloads. The study aim was to measure and observe arm, back and head postures and movements among forklift truck operators (FLTOs) during a working day, analyzing differences between types of forklift trucks and to assess reported workload and health. Twenty-five male FLTOs in a high-level warehouse were randomly included. The data collected comprised technical measurements, video analyses of postures and movements, and a questionnaire measuring health, pain and workload. On average, the FLTOs rotated their head more than 45 degrees, in total, 232 times/h. Video analysis revealed that FLTOs periodically drive the forklift truck sideways with the head rotated in the direction of travel, and in periods look upwards, in which the head is highly rotated and extended. Inclinometry and observations during the working day has the potential to be a valuable part of risk assessment promoting occupational safety and health.

The purpose of this article is to develop an online method to identify the hydrodynamic coefficients of pitch plane of an autonomous underwater vehicle. To obtain necessary data for the identification, the dive plane dynamics should be excited through diving maneuvers. Hence, a controller is needed whose performance and stability are appropriate. To design such a controller, first, hydrodynamic coefficients are approximated using semi-empirical methods. Based on these approximated coefficients, a classic controller is designed at the next step. Since the estimation of these coefficients is uncertain, µ-analysis is employed to verify the robustness of stability and performance of the controller. Using the verified robust controller, some oscillating maneuvers are carried out that excite the dive plane dynamics. Using sensor fusion and unscented Kalman filter, smooth and high-rate data of depth is provided for the depth controller. A recursive identification algorithm is developed to identify the hydrodynamic coefficients of heave and pitch motions. It turns out that some inputs required by the identification are not measured directly by the sensors. But the devised fusion algorithm is able to provide the necessary data for identification. Finally, using the identified coefficients and employing pole placement method, a new controller with better performance is synthesized online. To evaluate the performance of the identification and fusion algorithms, a 6-degree-of-freedom simulation of an autonomous underwater vehicle is carried out.

This paper presents a method for identification of the hydrodynamic coefficients of the dive plane of an autonomous underwater vehicle. The proposed identification method uses the governing equations of motion to estimate the coefficients of the linear damping, added mass and inertia, cross flow drag and control. Parts of data required by the proposed identification method are not measured by the onboard instruments. Hence, an optimal fusion algorithm is devised which estimates the required data accurately with a high sampling rate. To excite the dive plane dynamics and obtain the required measurements, diving maneuvers should be performed. Hence, a reliable controller with satisfactory performance and stability is needed. A cascaded controller is designed based on the coefficients obtained using a semi-empirical method and its robustness to the uncertainties is verified by the µ-analysis method. The performance and accuracy of the identification and fusion algorithms are investigated through 6-DOF numerical simulations of a realistic autonomous underwater vehicle.

This article aims to identify the roll channel parameters of an autonomous underwater vehicle. These parameters include hydrodynamic coefficients, motor torque, eccentricity, misalignments and mounting imperfections. In the proposed method, an approximation of the hydrodynamic coefficients is made at first via semi-empirical methods. In the next step, a proportional–integral–derivative controller is designed with respect to the approximated coefficients. Since the approximations can be very uncertain, the robustness of stability and performance of the proportional–integral–derivative controller is evaluated throughout µ-analysis. Finally, the unknown parameters are identified using the recorded data of on-board sensors during motion of the vehicle. The identification is based on minimization of the one-step prediction error. The minimization problem is nonlinear in unknown parameters, and particle swarm optimization is used to find an optimal solution. The performance of the proposed method is exhibited through a 6-degrees-of-freedom simulation of an autonomous underwater vehicle.

This paper develops a structured controller synthesis method which satisfies robust stability and robust performance. In the proposed method (µ-CDM), coefficient diagram method (CDM) is employed to synthesize a structured controller and µ-analysis is used to evaluate the robustness of the controller. A supervisory particle swarm optimization utilizes the CDM and µ-analysis in an iterative manner in order to reach an optimal robustness bound. To evaluate the performance of the proposed method, it has been used to synthesize a robust autopilot for an aerospace system. Numerical simulations confirm the feasibility of µ-CDM and show the acceptable closed-loop performance in presence of various model uncertainties. The performance of the proposed controller is compared with that of a conventional CDM controller and a D–K iterations controller.

Background Renal denervation (RDN) reduces sympathetic tone and may alter the sympathetic-parasympathetic balance. The autonomic nervous system is partly a regulator of innate immunity via the cholinergic anti-inflammatory pathway (CAP) which inhibits inflammation via the vagus nerve. Placental Growth Factor (PlGF) influences a neuro-immunological pathway in the spleen which may contribute to hypertension. The aim of this study was to investigate if modulation of renal sympathetic nerve activity affects CAP in terms of cytokine release as well as levels of PlGF. Methods Ten patients treated with RDN (Medtronic Inc), were analyzed for TNF, IL-1b and IL-10 and Lipopolysaccharide (LPS)-stimulated cytokine release before RDN, 1 day after and at 3- and 6-months follow-up. Four patients who underwent elective coronary angiography served as disease controls (DC). Results Baseline TNF was significantly lower 1 day after RDN (p = 0.03). LPS-stimulated (0, 10 and 100 ng/mL) TNF and IL-1b were significantly lower 1 day after RDN (TNF p = 0.0009, p = 0.0009 and p = 0.001, IL-1b; p = 0.0001, p = 0.002 and p = 0.005). IL-10 was significantly higher one day after RDN (p = ns, p = 0.02 and p = 0.01). These differences however declined during follow up. A more marked TNF reduction was achieved with a cholinergic analogue, GTS-21, in LPS-stimulated whole blood as compared with samples without GTS-21. Cytokine levels in controls did not differ before and 1 day after coronary angiography. PlGF was significantly higher in RDN patients and DC compared with healthy controls but did not change during follow-up. Conclusion RDN has an immediate effect on TNF in vivo and cytokine release ex vivo but seems to wane over time suggesting that current RDN techniques may not have long-lasting immunomodulatory effect. Repeated and extended stimulation of CAP in resistant hypertension by targeting neural circuits may be a potential therapeutic strategy for treatment of both hypertension and inflammation. Electronic supplementary material The online version of this article (10.1186/s10020-019-0097-y) contains supplementary material, which is available to authorized users.

Reduced heart rate variability (HRV) is an indicator of a malfunctioning autonomic nervous system. Resonant frequency breathing is a potential non-invasive means of intervention for improving the balance of the autonomic nervous system and increasing HRV. However, such breathing exercises are regarded as boring and monotonous tasks. The use of gaming elements (gamification) or a full gaming experience is a well-recognised method for achieving higher motivation and engagement in various tasks. However, there is limited documented knowledge on how to design a game for breathing exercises. In particular, the influence of additional interactive elements on the main course of training has not yet been explored. In this paper, we evaluated the satisfaction levels achieved using different game elements and how disruptive they were to the main task, i.e., paced breathing training. An Android flight game was developed with three game modes that differ in the degrees of multitasking they require. Design, development, and evaluation were conducted using a user-centred approach, including context analysis, the design of game principle mock-ups, the selection of game principles through a survey, the design of the game mechanics and GUI mock-up, and icon testing, and the performance of a summative study through user questionnaires and interviews. A summative evaluation of the developed game was performed with 11 healthy participants (ages 40–67) in a controlled setting. The results confirm the potential of video games for motivating players to engage in HRV biofeedback training. The highest training performance on the first try was achieved through pure visualisation rather than in a multitasking mode. Players had higher motivation to play the more challenging game and were more interested in long-term engagement. A framework for gamified HRV biofeedback research is presented. It has been shown that multitasking has considerable influence on HRV biofeedback and should be used with an adaptive challenge level.

Vibrotactile feedback training may be one possible method for interventions that target at learning better work techniques and improving postures in manual handling. This study aimed to evaluate the short term effect of real-time vibrotactile feedback on postural exposure using a smart workwear system for work postures intervention in simulated industrial order picking. Fifteen workers at an industrial manufacturing plant performed order-picking tasks, in which the vibrotactile feedback was used for postural training at work. The system recorded the trunk and upper arm postures. Questionnaires and semi-structured interviews were conducted about the users' experience of the system. The results showed reduced time in trunk inclination ≥20°, ≥30° and ≥45° and dominant upper arm elevation ≥30° and ≥45° when the workers received feedback, and for trunk inclination ≥20°, ≥30° and ≥45° and dominant upper arm elevation ≥30°, after feedback withdrawal. The workers perceived the system as useable, comfortable, and supportive for learning. The system has the potential of contributing to improved postures in order picking through an automated short-term training program.

This paper presents a new method that integrates heart rate, respiration, and motion information obtained from a wearable sensor system to estimate energy expenditure. The system measures electrocardiography, impedance pneumography, and acceleration from upper and lower limbs. A multilayer perceptron neural network model was developed, evaluated, and compared to two existing methods, with data from 11 subjects (mean age, 27 years, range, 21&ndash, 65 years) who performed a 3-h protocol including submaximal tests, simulated work tasks, and periods of rest. Oxygen uptake was measured with an indirect calorimeter as a reference, with a time resolution of 15 s. When compared to the reference, the new model showed a lower mean absolute error (MAE = 1.65 mL/kg/min, R2 = 0.92) than the two existing methods, i.e., the flex-HR method (MAE = 2.83 mL/kg/min, R2 = 0.75), which uses only heart rate, and arm-leg HR+M method (MAE = 2.12 mL/kg/min, R2 = 0.86), which uses heart rate and motion information. As indicated, this new model may, in combination with a wearable system, be useful in occupational and general health applications.

Impedance cardiography (ICG) is a noninvasive method for monitoring cardiac dynamics using electrical bioimpedance (EBI) measurements. Since its appearance more than 40 years ago, ICG has been used for assessing hemodynamic parameters. This paper presents a measurement system based on two System on Chip (SoC) solutions and Raspberry PI, implementing both a full three-lead ECG recorder and an impedance cardiographer, for educational and research development purposes. Raspberry PI is a platform supporting Do-It-Yourself project and education applications across the world. The development is part of Biosignal PI, an open hardware platform focusing in quick prototyping of physiological measurement instrumentation. The SoC used for sensing cardiac biopotential is the ADAS1000, and for the EBI measurement is the AD5933. The recordings were wirelessly transmitted through Bluetooth to a PC, where the waveforms were displayed, and hemodynamic parameters such as heart rate, stroke volume, ejection time and cardiac output were extracted from the ICG and ECG recordings. These results show how Raspberry PI can be used for quick prototyping using relatively widely available and affordable components, for supporting developers in research and engineering education. The design and development documents will be available on www.BiosignalPI.com , for open access under a Non Commercial-Share A like 4.0 International License.

In this work, we want to introduce combined heart rate and respiration monitoring for more accurate energy expenditure tracking on free-living subjects. We have developed a wearable cardiorespiratory monitoring system with unobtrusive heart rate measurement and ventilation estimation function for this purpose. The system is based on a garment with integrated textile electrodes for one-lead electrocardiogram and impedance pneumography measurements. A pilot experiment has been performed to prove the concept and to evaluate the characteristics of heart rate and ventilation estimated by our system in relation to energy expenditure. In the experiment, ventilation shows a better linearity in relation to the energy expenditure at the low intensity region than heart rate. Based on these characteristics, a model combining heart rate and ventilation for energy expenditure estimation is proposed which shows a significantly lower estimation error than the heart rate only model.

Introduction Reliability in visual cardiotocography interpretation is unsatisfying, which has led to the development of computerized cardiotocography. Computerized analysis is well established for antenatal fetal surveillance but has yet not performed sufficiently during labor. We aimed to investigate the capacity of a new computerized algorithm compared with visual assessment in identifying intrapartum fetal heart rate baseline and decelerations. Material and methods In all, 312 intrapartum cardiotocography tracings with variable decelerations were analyzed by the computerized algorithm and visually examined by two observers, blinded to each other and the computer analysis. The width, depth and area of each deceleration was measured. Four cases (>100 variable decelerations) were subjected to in-depth detailed analysis. The outcome measures were bias in seconds (width), beats per minute (depth), and beats (area) between computer and observers using Bland-Altman analysis. Interobserver reliability was determined by calculating intraclass correlation and Spearman rank analysis. Results The analysis (312 cases) showed excellent intraclass correlation (0.89-0.95) and very strong Spearman correlation (0.82-0.91). The detailed analysis of >100 decelerations in four cases revealed low bias between the computer and the two observers; width 1.4 and 1.4 seconds, depth 5.1 and 0.7 beats per minute, and area 0.1 and -1.7 beats. This was comparable to the bias between the two observers: 0.3 seconds (width), 4.4 beats per minute (depth) and 1.7 beats (area). The intraclass correlation was excellent (0.90-.98). Conclusion A novel computerized algorithm for intrapartum cardiotocography analysis is as accurate as gold standard visual assessment, with high correlation and low bias.

Background The cholinergic anti-inflammatory pathway (CAP) modulates inflammatory responses through the vagus nerve and the α-7-nicotinic acetylcholine receptor (α7nAChR) on macrophages and immune cells. Sympathetic/parasympathetic imbalance and chronic inflammation are both linked to poor outcome in dialysis patients. The aim of this study was to investigate CAP activity in these patients. Methods Twenty dialysis patients, 12 hemodialysis (HD) and 8 peritoneal dialysis (PD) patients (12 male, 8 female; age range 47–83 years) and 8 controls (5 male, 3 female; age range 31–52 years) were analyzed for C-reactive protein (CRP), tumor necrosis factor (TNF), interleukin-1b (IL-1b), IL-6 and IL-10 at baseline. The cytokines were then assessed after whole blood stimulation ex vivo with lipopolysaccharide (LPS) (10 and 100 ng/mL) and again in the presence of 45 and 90 μmol/L GTS-21, a cholinergic α7nAChR agonist. Results CRP, TNF, IL-1 and IL-6 were significantly higher, whereas IL-10 was significantly lower at baseline in patients compared with controls. After LPS stimulation, TNF increased significantly more in patients than in controls but decreased to similar levels in both groups after addition of GTS-21. IL-6 attenuation was comparable with TNF and the IL-1b pattern was similar but remained significantly higher in patients. Interestingly, IL-10 increased after GTS-21 in a dose-dependent manner, but only in patients. Results in HD and PD patients did not differ. Conclusions The response of immune cells after LPS exposure and cholinergic stimulation suggests a functional CAP in dialysis patients. It may thus be possible to target the α7nAChR control of cytokine release as an anti-inflammatory strategy and thereby improve outcome in these patients.

Background Nailfold capillaroscopy (NC) is a diagnostic imaging technique that is used to assess the blood capillary network in the nailfold area. NC is routinely used for patients with microcirculation problems, such as systemic sclerosis and other connective tissue diseases. Experts commonly use subjective evaluation as a reference point in images of nailfold video capillaroscopy, so it is important to reduce the inherent ambiguities in human judgment and diagnosis. Image quality is an important factor that affects measurement error and assessment time of NC images. Objective In this study, a new image enhancement technique was introduced and evaluated subjectively. Methods In total, 475 nailfold video capillaroscopy images from 18 healthy subjects and 41 systemic lupus erythematosus patients were used. The images were randomly divided into two sets, one each with 275 and 200. Eight independent observers who were familiar with the capillaroscopy technique participated in this study. The set of 275 images was evaluated by three observers with the forced–choice pairwise comparison method. Elliptic broken line (EBL) was used to count the number of capillaries. The intra- and inter-observer reliability of the original and enhanced images was evaluated on 200 images by five observers. Result Except for eight images, all observers preferred the enhanced images in the visual quality comparison method. The intra-class correlation coefficient (ICC) of intra- and inter-observer reliability increased from 0.76–0.84 to 0.82–0.89, respectively, when using the enhancement method. Conclusion By improving the image quality, more capillary details will be visible, and an observer can document more details that may not be visible in the original image and can do so more efficiently.

Vehicle crashes lead to huge economic and social consequences, and one non-negligible cause of accident is driver sleepiness. Driver sleepiness analysis based on the monitoring of vehicle acceleration, steering and deviation from the road or physiological and behavioral monitoring of the driver, e.g., monitoring of yawning, head pose, eye blinks and eye closures, electroencephalogram, electrooculogram, electromyogram and electrocardiogram (ECG), have been used as a part of sleepiness alert systems. Heart rate variability (HRV) is a potential method for monitoring of driver sleepiness. Despite previous positive reports from the use of HRV for sleepiness detection, results are often inconsistent between studies. In this work, we have re-evaluated the feasibility of using HRV for detecting drivers’ sleepiness during real road driving. A database consists of ECG measurements from 10 drivers, driving during morning, afternoon and night sessions on real road were used. Drivers have reported their average sleepiness level by using the Karolinska sleepiness scale once every five minutes. Statistical analysis was performed to evaluate the potential of HRV indexes to distinguish between alert, first signs of sleepiness and severe sleepiness states. The results suggest that individual subjects show different reactions to sleepiness, which produces an individual change in HRV indicators. The results motivate future work for more personalized approaches in sleepiness detection.

Nailfold capillaroscopy is a practical method for identifying and obtaining morphological changes in capillaries which might reveal relevant information about diseases and health. Capillaroscopy is harmless, and seems simple and repeatable. However, there is lack of established guidelines and instructions for acquisition as well as the interpretation of the obtained images; which might lead to various ambiguities. In addition, assessment and interpretation of the acquired images are very subjective. In an attempt to overcome some of these problems, in this study a new modified technique for assessment of nailfold capillary density is introduced. The new method is named elliptic broken line (EBL) which is an extension of the two previously known methods by defining clear criteria for finding the apex of capillaries in different scenarios by using a fitted elliptic. A graphical user interface (GUI) is developed for pre-processing, manual assessment of capillary apexes and automatic correction of selected apexes based on 90° rule. Intra- and inter-observer reliability of EBL and corrected EBL is evaluated in this study. Four independent observers familiar with capillaroscopy performed the assessment for 200 nailfold videocapillaroscopy images, form healthy subject and systemic lupus erythematosus patients, in two different sessions. The results show elevation from moderate (ICC=0.691) and good (ICC=0.753) agreements to good (ICC=0.750) and good (ICC=0.801) for intra- and inter-observer reliability after automatic correction of EBL. This clearly shows the potential of this method to improve the reliability and repeatability of assessment which motivates us for further development of automatic tool for EBL method.

This article aims to compensate the velocity and position errors that exist when the star sensor starts to work in a strapdown inertial navigation system aided by celestial navigation. These systems are integrated via unscented Kalman filter to estimate the current attitude and the gyros fixed bias, precisely. Since an accurate integration is desired, the nonlinear attitude equations are utilized in filter and these equations are propagated through a precise discretization method. Then, implementing the back-propagation and smoothing techniques, the initial attitude and the accelerometers fixed bias are also estimated. Finally, carrying out a parallel navigation, the velocity and position errors are compensated. The validity of the proposed method is investigated through simulation of launch vehicle navigation. Simulation results show a great reduction in velocity and position errors.

During the last decades, Electrical Bioimpedance Spectroscopy (EBIS) has been applied mainly by using the frequency-sweep technique, across a range of many different applications. Traditionally, the tissue under study is considered to be time-invariant and dynamic changes of tissue activity are ignored by treating the changes as a noise source. A new trend in EBIS is simultaneous electrical stimulation with several frequencies, through the application of a multi-sine, rectangular or other waveform. This method can provide measurements fast enough to sample dynamic changes of different tissues, such as myocard. This high sampling rate comes at a price of reduction in SNR and the increase in complexity of devices. Although the frequency-sweep technique is often inadequate for monitoring the dynamic changes in a variant system, it can be used successfully in applications focused on the time-invariant or slowly-variant part of a system. However, in order to successfully use frequency-sweep EBIS for monitoring time-variant systems, it is paramount to consider the effects of aliasing and especially the folding of higher frequencies, on the desired frequency e.g. DC level. This paper discusses sub-Nyquist sampling of thoracic EBIS measurements and its application in the case of monitoring pulmonary oedema. It is concluded that by considering aliasing, and with proper implementation of smoothing filters, as well as by using random sampling, frequency-sweep EBIS can be used for assessing time-invariant or slowly-variant properties of time-variant biological systems, even in the presence of aliasing. In general, undersampling is not always a problem, but does always require proper consideration.

Capillaries play a crucial role in the microcircu-latory system by exchanging metabolic substrates and waste products between blood and various tissues. The behavior of capillaries is affiliated with the number of capillaries per unit volume of tissue. Among the various noninvasive techniques available for analyzing skin microcirculation, nailfold capillaroscopy is considered to be a simple and easy-to-perform technique that allows a direct in-vivo visualization of the capillary network. Capillary density is one of the most important parameters in the studies involving capillaroscopy images. Capillary density in most of studies is defined as the number of capillaries in one millimeter span of the distal row in each finger or toe. This definition is silent about counting or excluding the number of capillary with different shapes. However, there is no single standard for counting the number of capillaries in a span of one millimeter. In this paper, a novel method is proposed for determining the nailfold capillary density. This method is a modified combination of two existing techniques: the direct observation and the 90° method. Compared to the two existing approaches, the proposed method is more straightforward and easy to use for cases in which the capillaries have different shapes and sizes. Through different examples, we have shown how this method can be used to select the apex point of capillary and subsequently count the number of capillaries with several papillae.

Heart rate variability (HRV) biofeedback is a method based on paced breathing at specific rate called resonance frequency by giving online feedbacks from user respiration and its effect on HRV. Since the HRV is also influence by different factors like stress and emotions, stress related to an unfamiliar measurement device, cables and skin electrodes may cover the underling effect of such kind of intervention. Wearable systems are usually considered as intuitive solutions which are more familiar to the end-user and can help to improve usability and hence reducing the stress. In this work, a prototype of a knitted garment using intarsia technique is developed and evaluated. Results show the satisfactory level of quality for Electrocardiogram and thoracic electrical bioimpedance i.e. for respiration monitoring as a part of HRV biofeedback system. Using intarsia technique and conductive yarn for making the connection instead of cables will reduce the complexity of fabrication in textile production and hence reduce the final costs in a final commercial product. Further development of garment and Android application is ongoing and usability and efficiency of final prototype will be evaluated in detail. QC 20181120

Electrical bioimpedance has been used for several decades to assess body fluid distribution and body composition by using single frequency and bioimpedance spectroscopic (BIS) techniques. It remains uncertain whether BIS methods have better performance compare to single frequency regression equations. In this work the performance of two BIS methods and four different 50 kHz single frequency prediction equations was studied in a data set of wrist-to-ankle tetrapolar BIS measurements (5-1000 kHz) together with reference values of total body water obtained by tritium dilution in 92 patients. Data were compared using regression techniques and Bland-Altman plots. The results of this study showed that all methods produced similarly high correlation and concordance coefficients, indicating good accuracy as a method. Limits of agreement analysis indicated that the population level performance of Sun's prediction equations was very similar to the performance of both BIS methods. However, BIS methods in practice have slightly better predictive performance than the single-frequency equations as judged by higher correlation and the limits of agreement from the Bland-Altman analysis. In any case, the authors believe that an accurate evaluation of performance of the methods cannot be done as long as the evaluation is done using Bland-Altman analysis, the commonly accepted technique for this kind of performance comparisons.

The reduced Heart Rate Variability (HRV) is believed to be associated with several diseases such as congestive heart failure, diabetes and chronic kidney diseases (CKD). In these cases, HRV biofeedback may be a potential intervention method to increase HRV which in turn is beneficial to these patients. In this work, a real-time Android biofeedback application based on a Bluetooth enabled ECG and thoracic electrical bioimpedance (respiration) measurement device has been developed. The system performance and usability have been evaluated in a brief study with eight healthy volunteers. The result demonstrates real-time performance of system and positive effects of biofeedback training session by increased HRV and reduced heart rate. Further development of the application and training protocol is ongoing to investigate duration of training session to find an optimum length and interval of biofeedback sessions to use in potential interventions.

Homecare is a potential solution for problems associated with an aging population. This may involve several physiological measurements, and hence a flexible but affordable measurement device is needed. In this work, we have designed an ADAS1000-based four-lead electrocardiogram (ECG) and respiration monitoring system. It has been implemented using Raspberry PI as a platform for homecare applications. ADuM chips based on iCoupler technology have been used to achieve electrical isolation as required by IEC 60601 and IEC 60950 for patient safety. The result proved the potential of Raspberry PI for the design of a compact, affordable, and medically safe measurement device. Further work involves developing a more flexible software for collecting measurements from different devices (measuring, e.g., blood pressure, weight, impedance spectroscopy, blood glucose) through Bluetooth or user input and integrating them into a cloud-based homecare system.

Biological signals recorded from surface electrodes contain interference from other signals which are not desired and should be considered as noise. Heart activity is especially present in EEG and EMG recordings as a noise. In this work, two ECG elimination methods are implemented; ensemble average subtraction (EAS) and wavelet denoising methods. Comparison of these methods has been done by use of simulated signals achieved by adding ECG to neonates EEG. The result shows successful elimination of ECG artifacts by using both methods. In general EAS method which remove estimate of all ECG components from signal is more trustable but it is also harder for implementation due to sensitivity to noise. It is also concluded that EAS behaves like a high-pass filter while wavelet denoising method acts as low-pass filter and hence the choice of one method depends on application.