Showing papers on "Heartbeat published in 2009"

Heartbeat Time Series Classification With Support Vector Machines

Abstract: In this study, heartbeat time series are classified using support vector machines (SVMs). Statistical methods and signal analysis techniques are used to extract features from the signals. The SVM classifier is favorably compared to other neural network-based classification approaches by performing leave-one-out cross validation. The performance of the SVM with respect to other state-of-the-art classifiers is also confirmed by the classification of signals presenting very low signal-to-noise ratio. Finally, the influence of the number of features to the classification rate was also investigated for two real datasets. The first dataset consists of long-term ECG recordings of young and elderly healthy subjects. The second dataset consists of long-term ECG recordings of normal subjects and subjects suffering from coronary artery disease.

Interoceptive awareness declines with age.

Abstract: Aging has been shown to increase sensory thresholds for a variety of exteroceptive and proprioceptive stimuli. However, the influence of aging on interoceptive awareness has received relatively little empirical attention. Here we report an inverse association between aging and interoception, as indexed by the ability to sense the heartbeat at rest. In a group of 59 participants ranging in age from 22 to 63 years, age inversely predicted heartbeat detection ability, both within and across several measurement sessions. On average, age accounted for 30% of the variance in heartbeat detection accuracy. Other attribute variables including body mass index and sex were not related to heartbeat detection ability. These findings provide clear empirical evidence that interoception, much like exteroception and proprioception, declines with age.

Levels of complexity in scale-invariant neural signals.

Abstract: Many physical and physiological signals exhibit complex scale-invariant features characterized by 1/f scaling and long-range power-law correlations, indicating a possibly common control mechanism. Specifically, it has been suggested that dynamical processes, influenced by inputs and feedback on multiple time scales, may be sufficient to give rise to 1/f scaling and scale invariance. Two examples of physiologic signals that are the output of hierarchical multiscale physiologic systems under neural control are the human heartbeat and human gait. Here we show that while both cardiac interbeat interval and gait interstride interval time series under healthy conditions have comparable 1/f scaling, they still may belong to different complexity classes. Our analysis of the multifractal scaling exponents of the fluctuations in these two signals demonstrates that in contrast to the multifractal behavior found in healthy heartbeat dynamics, gait time series exhibit less complex, close to monofractal behavior. Further, we find strong anticorrelations in the sign and close to random behavior for the magnitude of gait fluctuations at short and intermediate time scales, in contrast to weak anticorrelations in the sign and strong positive correlation for the magnitude of heartbeat interval fluctuations-suggesting that the neural mechanisms of cardiac and gait control exhibit different linear and nonlinear features. These findings are of interest because they underscore the limitations of traditional two-point correlation methods in fully characterizing physiological and physical dynamics. In addition, these results suggest that different mechanisms of control may be responsible for varying levels of complexity observed in physiological systems under neural regulation and in physical systems that possess similar 1/f scaling.

Hemodynamic measurements from individual blood cells in early mammalian embryos with Doppler swept source OCT

Abstract: The most common and lethal birth defects affect the cardiovascular (CV) system. The mouse is a superior model for identifying and understanding mammalian CV birth defects, but there is a great need for tools that can detect early and subtle deficiencies in cardiac function in mouse embryos. We combined swept source optical coherence tomography (SS-OCT) with live mouse embryo culture protocols to generate structural two-dimensional and three-dimensional imaging and hemodynamic measurements in a live 8.5 day embryo just a few hours after the beginning of a heartbeat. Our data show that individual circulating blood cells can be visualized with structural SS-OCT, and using Doppler SS-OCT the velocity of single moving blood cells were measured during different phases of the heartbeat cycle. These results demonstrate that Doppler SS-OCT is an extremely useful tool for structural and hemodynamic analysis at the earliest stages of mammalian blood circulation.

Chaotic Signatures of Heart Rate Variability and Its Power Spectrum in Health, Aging and Heart Failure

Abstract: A paradox regarding the classic power spectral analysis of heart rate variability (HRV) is whether the characteristic high- (HF) and low-frequency (LF) spectral peaks represent stochastic or chaotic phenomena. Resolution of this fundamental issue is key to unraveling the mechanisms of HRV, which is critical to its proper use as a noninvasive marker for cardiac mortality risk assessment and stratification in congestive heart failure (CHF) and other cardiac dysfunctions. However, conventional techniques of nonlinear time series analysis generally lack sufficient sensitivity, specificity and robustness to discriminate chaos from random noise, much less quantify the chaos level. Here, we apply a ‘litmus test’ for heartbeat chaos based on a novel noise titration assay which affords a robust, specific, time-resolved and quantitative measure of the relative chaos level. Noise titration of running short-segment Holter tachograms from healthy subjects revealed circadian-dependent (or sleep/wake-dependent) heartbeat chaos that was linked to the HF component (respiratory sinus arrhythmia). The relative ‘HF chaos’ levels were similar in young and elderly subjects despite proportional age-related decreases in HF and LF power. In contrast, the near-regular heartbeat in CHF patients was primarily nonchaotic except punctuated by undetected ectopic beats and other abnormal beats, causing transient chaos. Such profound circadian-, age- and CHF-dependent changes in the chaotic and spectral characteristics of HRV were accompanied by little changes in approximate entropy, a measure of signal irregularity. The salient chaotic signatures of HRV in these subject groups reveal distinct autonomic, cardiac, respiratory and circadian/sleep-wake mechanisms that distinguish health and aging from CHF.

Noninvasive technique for measurement of heartbeat regularity in zebrafish (Danio rerio) embryos

Abstract: Zebrafish (Danio rerio), due to its optical accessibility and similarity to human, has emerged as model organism for cardiac research. Although various methods have been developed to assess cardiac functions in zebrafish embryos, there lacks a method to assess heartbeat regularity in blood vessels. Heartbeat regularity is an important parameter for cardiac function and is associated with cardiotoxicity in human being. Using stereomicroscope and digital video camera, we have developed a simple, noninvasive method to measure the heart rate and heartbeat regularity in peripheral blood vessels. Anesthetized embryos were mounted laterally in agarose on a slide and the caudal blood circulation of zebrafish embryo was video-recorded under stereomicroscope and the data was analyzed by custom-made software. The heart rate was determined by digital motion analysis and power spectral analysis through extraction of frequency characteristics of the cardiac rhythm. The heartbeat regularity, defined as the rhythmicity index, was determined by short-time Fourier Transform analysis. The heart rate measured by this noninvasive method in zebrafish embryos at 52 hour post-fertilization was similar to that determined by direct visual counting of ventricle beating (p > 0.05). In addition, the method was validated by a known cardiotoxic drug, terfenadine, which affects heartbeat regularity in humans and induces bradycardia and atrioventricular blockage in zebrafish. A significant decrease in heart rate was found by our method in treated embryos (p < 0.01). Moreover, there was a significant increase of the rhythmicity index (p < 0.01), which was supported by an increase in beat-to-beat interval variability (p < 0.01) of treated embryos as shown by Poincare plot. The data support and validate this rapid, simple, noninvasive method, which includes video image analysis and frequency analysis. This method is capable of measuring the heart rate and heartbeat regularity simultaneously via the analysis of caudal blood flow in zebrafish embryos. With the advantages of rapid sample preparation procedures, automatic image analysis and data analysis, this method can potentially be applied to cardiotoxicity screening assay.

Semi-automated Optical Heartbeat Analysis of small hearts.

Abstract: We have developed a method for analyzing high speed optical recordings from Drosophila, zebrafish and embryonic mouse hearts (Fink, et. al., 2009). Our Semi-automatic Optical Heartbeat Analysis (SOHA) uses a novel movement detection algorithm that is able to detect cardiac movements associated with individual contractile and relaxation events. The program provides a host of physiologically relevant readouts including systolic and diastolic intervals, heart rate, as well as qualitative and quantitative measures of heartbeat arrhythmicity. The program also calculates heart diameter measurements during both diastole and systole from which fractional shortening and fractional area changes are calculated. Output is provided as a digital file compatible with most spreadsheet programs. Measurements are made for every heartbeat in a record increasing the statistical power of the output. We demonstrate each of the steps where user input is required and show the application of our methodology to the analysis of heart function in all three genetically tractable heart models.

Programmable earphone device with customizable controls and heartbeat monitoring

Abstract: Methods and systems for providing a programmable earphone device with customizable controls and heartbeat monitoring are described. The earphone device may include a wireless connection to a media player, a left and a right earphone, and at least one input mechanism, wherein the input mechanism is located on at least one of the left and right earphones and is customizable. The earphone device may also include an data port configured to bypass the wireless connection and receive sound data from the media player when a wired connection is detected between the media player and the earphone device. A stored customizable sound equalizer may also be included that provides different equalizer settings for each of the left and right earphones. The earphone device also includes a heartbeat monitor that detects a user's heartbeat using the left and right earphone, wherein the heartbeat monitor is customizable by the user.

System and method for minimizing the amount of data being sent on a network for supervised security systems

Abstract: A system and method are disclosed for communicating heartbeat signals representative of the condition of a security system to a monitoring station. A controller is provided that transmits a heartbeat signal to a monitoring station within a given time period and awaits an acknowledgement signal from the monitoring station. If an acknowledgement signal is received within a time interval from the transmission of the heartbeat signal, then the time period is reset and another heartbeat signal is not sent until the next time period. If an acknowledgement signal is not received by the controller within a few seconds of transmitting the heartbeat signal, then another heartbeat signal is sent from the controller to the monitoring station. Heartbeat signals are only transmitted from the controller if an acknowledgement signal is not received from the monitoring station. In this manner, the amount of data sent over a communication link is reduced.

Contact-free Measurement of Heart Rate Variability via a Microwave Sensor

Abstract: Measures of heart rate variability (HRV) are widely used to assess autonomic nervous system (ANS) function. HRV can be recorded via electrocardiography (ECG), which is both non-invasive and widely available. However, ECG needs three electrodes touching the body of the subjects, which makes them feel nervous and uncomfortable, thus potentially affecting the recording. Contact-free detection of the heartbeat via a microwave sensor constitutes another means of determining the timing of cardiac cycles by continuous monitoring of mechanical contraction of the heart. This technique can measure the heartbeat without any electrodes touching human body and penetrate the clothes at some distances, which in some instances may prove a practical basis for HRV analysis. Comparison of 5-minute recordings demonstrated that there were no significant differences in the temporal, frequency domains and in non-linear dynamic analysis of HRV measures derived from heartbeat and ECG, which suggested this technique may prove a practical alternative to ECG for HRV analysis.

Novel methods for estimating the ballistocardiogram signal using a simultaneously acquired electrocardiogram

Abstract: The ballistocardiogram (BCG) signal represents the movements of the body in response to cardiac ejection of blood. Recently, many groups have developed low-cost instrumentation for facilitating BCG measurement in the home. The standard method used in the literature for estimating the BCG pulse response has generally been ensemble averaging over several beats. Unfortunately, since the BCG pulse response is likely longer than a typical heartbeat interval, this standard approach does not yield a full-length estimate of the response. This paper describes a simple, novel algorithm for estimating the full-length BCG pulse response using the R-wave timing of a simultaneously acquired electrocardiogram (ECG). With this pulse response, the full signal can be reconstructed, enabling the analysis of slow transient effects in the BCG signal, and of the measurement noise. Additionally, while this paper focuses only on the BCG signal, the same algorithm could be applied to other biomedical signals such as the phonocardiogram or impedance cardiogram, particularly when the heartbeat interval is shorter than the duration of the cpulse response.

Maternal-fetal heartbeat phase synchronization.

Abstract: Integrated physiological systems under neural control, such as the cardiac and respiratory systems, exhibit complex dynamics with continuous noisy fluctuations even in resting “equilibrium” conditions without external perturbations (1, 2). Advances in analytic methods have made it possible to identify a surprisingly robust temporal organization embedded in physiologic fluctuations, characterized by scale-invariant (fractal), multifractal, and nonlinear features over a range of time scales (2–4). This behavior is remarkably different from the one post ulated by the classical principle of homeostasis (5), and it resembles the dynamics of certain physical systems away from equilibrium (6).

Statistics of return intervals between long heartbeat intervals and their usability for online prediction of disorders

Abstract: We study the statistics of return intervals between large heartbeat intervals (above a certain threshold Q) in 24 h records obtained from healthy subjects. We find that both the linear and the nonlinear long-term memory inherent in the heartbeat intervals lead to power-laws in the probability density function PQ(r) of the return intervals. As a consequence, the probability WQ(t; Δt) that at least one large heartbeat interval will occur within the next Δt heartbeat intervals, with an increasing elapsed number of intervals t after the last large heartbeat interval, follows a power-law. Based on these results, we suggest a method of obtaining a priori information about the occurrence of the next large heartbeat interval, and thus to predict it. We show explicitly that the proposed method, which exploits long-term memory, is superior to the conventional precursory pattern recognition technique, which focuses solely on short-term memory. We believe that our results can be straightforwardly extended to obtain more reliable predictions in other physiological signals like blood pressure, as well as in other complex records exhibiting multifractal behaviour, e.g. turbulent flow, precipitation, river flows and network traffic.

Noncontact heartbeat detection at 2.4, 5.8, and 60 GHz: A comparative study

Abstract: The aim of this work is to provide two new schemes for human noninvasive heartbeat activity monitoring using low power microwave noncontact systems and direct conversion architecture. The first system is tested at 2.4 GHz and 5.8 GHz frequencies. Another system, operating at 60 GHz, is demonstrated where higher heartbeat sensitivity detection is achieved. © 2009 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 666–669, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.24110

A novel piezoelectric pvdf film-based physiological sensing belt for a complementary respiration and heartbeat monitoring system

Abstract: Human heartbeat and respiration signals were measured from a DAQ board interfaced with a homemade voltage-amplifier with specific frequency filtering function using an elastic textile belt imbedded with a poled-PVDF film, which is designated as a physiological sensing belt (PSB), as a piezoelectric sensor and analyzed. PSB sensor systems can be easily tied on the chest, abdomen, head, wrist, or ankle for comfortable fit. The sensitivity of the imbedded PVDF film sensor is highly dependent on the thickness of coated silicon rubber layer on both sides of the PVDF film. Both respiration and heartbeat signals could be isolated from the mixture signal measured from the chest and abdomen during respiration and pulse wave velocity could be calculated using time delay obtained from waveforms measured simultaneously at the two different body positions. Finally we found the feasibility of applying the PSB as a complementary respiration monitoring system to the traditional anesthesia activities or other typ...

A Remote Compact Sensor for the Real-Time Monitoring of Human Heartbeat and Respiration Rate

Abstract: A remote compact sensor system for the detection of human vital signs (heartbeat and respiration rate) is presented. The frequency band of 24 GHz is employed for remote sensing. For the compact size, the developed sensor uses a circularly polarized electromagnetic wave with a single antenna. The sensor system is composed of radio-frequency circuits, a signal conditioning block, a data-acquisition unit, and a signal-processing part. The peak detection of the power spectral density with a tracking algorithm is utilized for the real-time detection of human vital signs. The measurement result is compared with the commercial fingertip sensor. The comparison result shows excellent agreement.

Music Playlist Recommendation Based on User Heartbeat and Music Preference

Abstract: In this paper, we present a new user heartbeat and preference aware music recommendation system. The system can not only recommend a music playlist based on the user’s music preference but also the music playlist is generated based on the user’s heartbeat. If the user’s heartbeat is higher than the normal heartbeat which is 60-100 beats per minutes (age 18 and over) or 70-100 beats per minutes (age 6-18), the system generates a user preferred music playlist using Markov decision process to transfer the user’s heartbeat back to the normal range with the minimum time cost; if the user’s heartbeat is normal, the system generates a user preferred music playlist to keep the user’s heartbeat within the normal range; If the user’s heartbeat is lower than the normal heartbeat, the system generates a user preferred music playlist using Markov decision process to uplift the user’s heartbeat back to the normal range with the minimum time cost.

Heartbeat Case Determination Using Fuzzy Logic Method on ECG Signals

Abstract: This study proposes Fuzzy Logic Method (FLM) to analyze ECG signals for determining the heartbeat case. The proposed method can accurately classify and distinguish both normal heartbeats (NORM) and abnormal heartbeats. The so called abnormal heartbeats include the left bundle branch block (LBBB), the right bundle branch block (RBBB), the ventricular premature contractions (VPC), and the atrial premature contractions (APC). ECG signal analysis comprises three main stages: (i) the qualitative features stage for qualitative feature selection of an ECG signal; (ii) fuzzy rules base establishment; and (iii) the classification stage for determining patient heartbeat cases. The fuzzy rules base receives four qualitative features of an ECG signal as its inputs and generates one output “heartbeat case”. Through fuzzy inference engine and defuzzification operations, we can make a decision to determine the heartbeat case of the patient’s heart disease. The ECG records available in the MIT-BIH arrhythmia database are utilized to illustrate the effectiveness of the proposed method. In the experiments, the sensitivities were 95.06%, 91.03%, 90.50%, 92.63% and 93.77% for NORM, LBBB, RBBB, VPC and APC, respectively. The total classification accuracy (TCA) was approximately 93.78%.

Ubiquitous Health Monitoring at Home – Sensing of Human Biosignals on Flooring, on Tatami Mat, in the Bathtub, and in the Lavatory

Abstract: In the graying society, it is important to monitor health-related biosignal with sensors in the living environment for the sake of emergency response and long-term health management. In order to use biosignal data monitoring systems daily at home, noninvasive monitoring and system maintenance are crucial. We propose a method of estimating the sleep stages of sleeping subjects through noninvasive measurement of heartbeat and respiration using a pneumatic method and an air mattress. However, the method incurs maintenance for periodically refilling the air of the mattress. In this paper, another pneumatic method, which uses an air tube made of the silicon rubber instead of the air mattress, is proposed. The change in S/N ratio in heartbeat and respiration signals, under greater background noise, are compared for the following: in a room with wooden flooring; in a room with tatami mats; in a bathtub; and in a lavatory. The results show that both the heartbeat and respiration can be measured with the S/N ratio of around 30 dB, and the signal of each heartbeat can also be confirmed provided the maximum background noise in the room with wooden flooring, in the room with tatami mats, in the bathtub, and in the lavatory are 0.1 m/s 2,0.9 m/s2, 100 mI/s, and 0.1 m/s 2, respectively.

Double-computer backup system and backup method

Abstract: The invention discloses a double-computer backup system and a backup method. The system comprises a working server and a backup server, wherein a system monitoring module is used for mutually monitoring through an interior heartbeat cable and another system monitoring module of a local server and also used for detecting the state information of detection resources sent by a resource object module connected with the system monitoring module, sending a warning to a management module of the local server and sending heartbeat information marked to be false to a system monitoring module of an end server through an exterior heartbeat cable when the resource object module is determined to have a fault; the resource object module is used for detecting various resource objects in the resource object module; the management module is used for judging whether the switching operation of double-computer resources needs to be executed or not according to the condition of warning receiving of the management module; and the resource object module is also used for providing various resource objects of the local server. The invention solves the problems of faulty switching of the double-computer resources and fissure faults caused by self faults of double-computer backup at present.

Integrated radar systems for precision monitoring of heartbeat and respiratory status

Abstract: This work presents simulation and measurement results of the vital sign parameters based on low-power microwave and millimeter-wave monitoring systems through Doppler radar techniques. The cardiac beating and the breathing of patients are examined. Three systems operating at 5.8 GHz, 24 GHz and 35 GHz, respectively, are designed, simulated, and fabricated. Using such three systems and applying signal processing techniques, measured signals obtained at distance up to 1 m from the patient of reference are presented. These results show that the heartbeat and the frequency of breath are well detected which validates our radar analysis and design approach. Performances (sensitivity, complexity, etc.) of the different systems are compared and studied, showing that the highest sensitivity detection can be achieved with the system at the highest frequency (35 GHz) in this case.

Normal heartbeat series are nonchaotic, nonlinear, and multifractal: New evidence from semiparametric and parametric tests

Abstract: We present new evidence that normal heartbeat series are nonchaotic, nonlinear, and multifractal. In addition to considering the largest Lyapunov exponent and the correlation dimension, the results of the parametric and semiparametric estimation of the long memory parameter (long-range dependence) unambiguously reveal that the underlying process is nonstationary, multifractal, and has strong nonlinearity.

System and method for operating a machine

Abstract: A system and method for operating a machine is disclosed. The system may include an input device configured to select from a plurality of modes of operation for the machine, the plurality of modes of operation comprising a manual mode, a remote mode, and an autonomous mode. The system may further include a controller coupled to the machine, the controller configured to place the machine in the selected mode of operation based on an input at the input device. The system may further include a transmitter configured to transmit a heartbeat signal. The system may further include a receiver configured to receive an acknowledgment signal from a remote system in response to the transmitted heartbeat signal.

System and method for heartbeat signal generation

Abstract: A system and method for heartbeat signal generation are provided. The method (30) includes determining (38) a communication condition and generating (42) heartbeat signals based on the determined communication condition. The system (20) includes a plurality of commu-nication cells (26) and at least one communication device (28) configured to generate heartbeat signals. A rate of generating the heartbeat signals is based on one of (i) a service priority or user group and (ii) communication requirements for a network type for each of the plurality of communica-tion cells.

Noninvasive Motion and Respiration Monitoring System

Abstract: A non-invasive motion and respiration monitor receives impulses from a subject's movement, heartbeat, and respiration. The raw signal is biased and digitized, and a signal processor applies a Fast Fourier Transform to the signal. The transformed signal is filtered to isolate the component representing heart rate from the component representing respiration. An Inverse Fast Fourier Transform is then applied to the component signals, which are sent to a processor. The processor is programmed to detect irregularities in the respiration and heart rate. If severe irregularities or complete cessation is detected in either signal, a mechanical stimulator is actuated to try to stimulate the subject, and an alarm is sounded to alert a caregiver such as a parent or nurse.

Automated synchrogram analysis applied to heartbeat and reconstructed respiration.

Abstract: Phase synchronization between two weakly coupled oscillators has been studied in chaotic systems for a long time. However, it is difficult to unambiguously detect such synchronization in experimental data from complex physiological systems. In this paper we review our study of phase synchronization between heartbeat and respiration in 150 healthy subjects during sleep using an automated procedure for screening the synchrograms. We found that this synchronization is significantly enhanced during non-rapid-eye-movement (non-REM) sleep (deep sleep and light sleep) and is reduced during REM sleep. In addition, we show that the respiration signal can be reconstructed from the heartbeat recordings in many subjects. Our reconstruction procedure, which works particularly well during non-REM sleep, allows the detection of cardiorespiratory synchronization even if only heartbeat intervals were recorded.