Human Heart Rate Research Articles

Multifunctionally wearable monitoring with gelatin hydrogel electronics of liquid metals.

Hydrogel-based flexible electronics have been of widespread interest in recent years. However, current hydrogel electronics have limitations, such as poor biocompatibility, non-reusability, low electrical response to deformation and being single-function. GelMA is a gelatin-based hydrogel that has been widely used in the biological field, such as in tissue repair and drug delivery. Could it be a good choice for high biocompatibility wearable electronics? Here, by controlling the replacement rate of amine and hydroxy functionalities, we made the common brittle GelMA into a highly stretchable hydrogel. And we report for the first time GelMA hydrogel electronics with liquid metals (LMGE), which could be fabricated by simply injecting liquid metals into the internal microchannels of the GelMA hydrogels (GelMA-30). With the unique biocompatibility, outstanding air and ion permeability, and great mechanical properties of GelMA-30, as well as the low toxicity, high conductivity and high rheology of liquid metals, LMGE can not only monitor movement changes and even the heartbeat of rats, but can also be used as a wireless monitor to supervise secretions produced during human exercise. The design of LMGE provides a general strategy for the manufacture of bio-flexible hydrogel electronics, which opens the way for the development of multi-functional biomimetic materials for integrated monitoring and repair for biomedical applications.

Experimental study on the thermal comfort and physiological responses of the elderly in unstable environments

In this study, the investigators used comparative experiments in order to study the age differences and the effects of temperature changes on physiological responses. Firstly, This paper analyzed the thermal sensation differences and the trend of changes in the design working conditions in different age groups. The researchers found that the thermal sensation of elderly people was lower than that of young people in the hot environment and higher than that of young people in the cold environment. On this basis, the heart rate changes of the elderly in the dynamic environment and the differences with the young people were studied. The results showed that the heart rate of the elderly and the young people increased with the increase of temperature in the temperature rise condition, but there was no significant difference between the two groups. In the temperature drop condition, the heart rate decreased with the decrease of temperature. Finally, an equation was developed to quantitatively predict heart rate parameters. The equation predicts human heart rate by ambient temperature, and the results show that the least square error of the prediction equation for elderly people is 46, while the average difference between the actual and predicted values is 1.2. Therefore, it is recommended to use the proposed heart rate prediction equation when predicting the healthiness of heart rate in elderly people.

Physiological effects of hyperprotein diets with the addition of Eisenia foetida in broilers. Proposal for a model for heart disease

Proposing animal models that allow predicting results in humans becomes critical when the analogies in physiology between both entities are reviewed. About heart disease, the heart rate in humans is more similar to that of chickens than that of the mouse, rat or other mammalian models generally used to study this disease. In the present work, the ethology on the attraction of chickens to earthworms as a food source was reviewed, in addition hematological, organ and urological parameters were measured in chickens fed with double and triple the protein percentage supplied with Eisenia foetida live added to the feed. commercial for the Cobb500 line. The results show a marked attraction depending on the nutritional status of the birds for Eisenia foetida and differences in hematological parameters, but not for urological parameters. The morphological characteristics of the heart showed a clear association between three times the protein load in the food and cardiac damage in 2 of 7 animals fed during 7 weeks of study. The present work represents the first contribution with the animal model approach in chickens to study cardiac damage and its possible prediction for humans.

Semiconductor nano materials in the reconstruction of wearable human body sensor

In view of the shortcomings of the current wearable human body sensor, such as poor comfort and low sensing accuracy, the application of semiconductor nano materials in the reconstruction of wearable human body sensor is studied. The best zinc concentration of 10 mm and the best reaction temperature of 75∘C were selected as experimental conditions to prepare the modified silk. The two ends of the silk sensor were connected by silver glue and wire respectively to form a single silk sensor. The sensor is placed in the wearable clothing of the wearable human body sensor, which uses the sensor to sense the physiological signal of human body and sends it to the control center. The central processing unit of the control center uses the data eigenvalue fusion decision-making method of BP neural network to process the physiological data of human body and then transmits it to the display terminal to realize the physiological data induction of human body. The experimental results show that the human body sensor can effectively sense human heart rate, blood oxygen signal, blood pressure and other physiological signals, and the sensing accuracy is above 97%.

Analysis of a Dynamic Calibration Target for Through-Wall and Through-Rubble Motion Sensing Doppler Radar

Through-wall and through-barrier motion-sensing systems are becoming increasingly important tools to locate humans concealed behind barriers and under rubble. The sensing performance of these systems is best determined with appropriately designed calibration targets, which are ones that can emulate human motion. The effectiveness of various dynamic calibration targets that emulate human respiration, heart rate, and other body motions were analyzed. Moreover, these targets should be amenable to field deployment and not manifest angular or orientation dependences. The three targets examined in this thesis possess spherical polyhedral geometries. Spherical geometries were selected due to their isotropic radar cross-sectional characteristics, which provide for consistent radar returns independent of the orientation of the radar transceiver relative to the test target. The aspect-independence of a sphere allows for more accurate and repeatable calibration of a radar than using a nonspherical calibration artifact. In addition, the radar cross section (RCS) for scattering spheres is well known and can be calculated using far-field approximations. For Doppler radar testing, it is desired to apply these calibration advantages to a dynamically expanding-and-contracting sphere-like device that can emulate motions of the human body. Monostatic RCS simulations at 3.6 GHz were documented for each geometry. The results provide a visual way of representing the effectiveness of each design as a dynamic calibration target for human detection purposes.

Multiscale Entropy Analysis of Short Signals: The Robustness of Fuzzy Entropy-Based Variants Compared to Full-Length Long Signals.

Multiscale entropy (MSE) analysis is a fundamental approach to access the complexity of a time series by estimating its information creation over a range of temporal scales. However, MSE may not be accurate or valid for short time series. This is why previous studies applied different kinds of algorithm derivations to short-term time series. However, no study has systematically analyzed and compared their reliabilities. This study compares the MSE algorithm variations adapted to short time series on both human and rat heart rate variability (HRV) time series using long-term MSE as reference. The most used variations of MSE are studied: composite MSE (CMSE), refined composite MSE (RCMSE), modified MSE (MMSE), and their fuzzy versions. We also analyze the errors in MSE estimations for a range of incorporated fuzzy exponents. The results show that fuzzy MSE versions—as a function of time series length—present minimal errors compared to the non-fuzzy algorithms. The traditional multiscale entropy algorithm with fuzzy counting (MFE) has similar accuracy to alternative algorithms with better computing performance. For the best accuracy, the findings suggest different fuzzy exponents according to the time series length.

Skin-conformable photoplethysmogram sensors for energy-efficient always-on cardiovascular monitoring systems

Skin-conformable photoplethysmogram (PPG) sensors enable continuous and accurate monitoring of physiological states to efficiently prevent cardiovascular-related diseases. Herein, novel PPG sensors consisting of polymer/oxide hybrid phototransistors, mini-light-emitting diodes, and a framework conformable to epidermis are developed. The key element, a heterojunction phototransistor for efficient energy usage, is composed of an indium gallium zinc oxide (IGZO)-based active layer for low-power consumption and a specific diketopyrrolopyrrole (DPP) polymer layer affording high near-infrared (NIR) light absorbability and hydrophobicity. Therefore, the phototransistors with NIR detectivity of 1.00 × 1013 Jones, rapid photoresponse within the human heart rate range, high reliability against perspiration and mechanical stress, and low operating voltages (< 5 V) are achieved. Using the developed PPG sensors, the heart rate and oxygen saturation of human subjects are successfully detected, which is comparable to the commercial PPG sensors. Furthermore, controlling potential barrier energy at the interface between heterojunction layers, PPG sensors that operate separately at low and high heart rates are implemented for continuous monitoring. Consequently, a distinguished configuration of skin-conformable PPG sensors and a novel concept of an always-on cardiovascular monitoring system while consuming less power are suggested. The study contributes to the development of PPG sensors and may become a potential solution for Healthcare 4.0 applications.

Modeling and Methods of Statistical Processing of a Vector Rhytmocardiosignal

Aims: We have developed a new approach to the study of human heart rate, which is based on the use of a vector rhythmocardiosignal, which includes as its component the classical rhythmocardiosignal in the form of a sequence of heart cycle durations in an electrocardiogram. Background: Most modern automated heart rate analysis systems are based on a statistical analysis of the rhythmocardiogram, which is an ordered set of R-R interval durations in a recorded electrocardiogram. However, this approach is not very informative, since R-R intervals reflect only the change in the duration of cardiac cycles over time and not the entire set of time intervals between single-phase values of the electrocardiosignal for all its phases. Objective: The aim of this paper is to present a mathematical model in the form of a vector of stationary and permanently connected random sequences of a rhythmocardiosignal with an increased resolution for its processing problems. It shows how the vector rhythmocardiosignal is formed and processed in diagnostic systems. The structure of probabilistic characteristics of this model is recorded for statistical analysis of heart rate in modern cardiodiagnostics systems. Methods: Based on a new mathematical model of a vector rhythmocardiosignal in the form of a vector of stationary and permanently connected random sequences, new methods for statistical estimation of spectral-correlation characteristics of heart rate with increased resolution have been developed. Results: The spectral power densities of the components of the vector rhythmocardiosignal are justified as new diagnostic features when performing rhythm analysis in modern cardiodiagnostics systems, complementing the known signs and increasing the informative value of heart rate analysis in modern cardiodiagnostics systems. Conclusion: The structure of probabilistic characteristics of the proposed mathematical model for heart rate analysis in modern cardiodiagnostics systems is studied. It is shown how the vector rhythmocardiosignal is formed, and its statistical processing is carried out on the basis of the proposed mathematical model and developed methods.

Noncontact Vital Sign Sensing Under Nonperiodic Body Movement Using a Novel Frequency-Locked-Loop Radar

Most conventional vital-sign radars cannot easily detect human vital sign signals under nonperiodic body movement. This article presents a novel frequency-locked loop (FLL) radar that can track the phase changes that are caused by nonperiodic body movement. A gain/phase detector and a cross correlation function (CCF) in the FLL radar greatly reduce the second harmonic, the intermodulation terms between vital sign signals and nonperiodic body movement noise, enhancing both the signal-to-noise ratio and the accuracy of detection of the vital signs. Measurements indicated that the implemented 2.4-GHz FLL radar with a gain/phase detector and CCF can effectively detect the human respiration rate (RR) and heart rate (HR) under nonperiodic body movement. Using a chest belt as the measurement reference, the standard deviation (SD) of RR and HR measurements were 1.27 and 5.69 beats/min, respectively, when the seated subject under test (SUT) swung nonperiodically his upper body. When the SUT walked away from the radar naturally at 2.6 km/h, the implemented FLL radar measured RR and HR with SDs of 2.67 and 8.28 beats/min, respectively.

Nonparametric Modelling Based Model Predictive Control for Human Heart Rate Regulation during Treadmill Exercise.

This paper applies a kernel-based nonparametric modelling method to estimate the heart rate response during treadmill exercise and proposes a model predictive control (MPC) method to perform heart rate control for an automated treadmill system. This kernel-based method introduces a kernel regularisation term, which brings prior information to the model estimation phase. By adding this prior information, the experimental protocol can be significantly simplified and only a small amount of model training experiments are needed. The model parameters were experimentally estimated from 12 participants for the treadmill exercise with a short and practical exercise protocol. The modelling results show that the model identified using the proposed method can accurately describe the heart rate response to the treadmill exercise. Based on the identified model, an MPC controller is designed to track a predefined reference heart rate profile. An advantage is the speed and acceleration of the treadmill can be limited to within a safe range for vulnerable exercisers. The proposed controller was experimentally validated in a self-developed automated treadmill system. The tracking results indicate that the desired automatic treadmill system can regulate the participants' heart rate to follow the reference profile efficiently and safely.

PSXV-20 Pilot Study: How does horse and rider vital signs respond to participation in an equine assisted psychotherapy and learning outpatient collegiate substance use recovery program?

Abstract While research supporting the psychological benefits of equine assisted psychotherapy and learning (EAPL) is expanding, little is known about the physiological impact this therapy has on the human and horse. The physical activity for younger adults may hold promise where other therapies have failed, but can this form of exercise therapy be physically demanding on the participant? Therefore, the objective of this study was to measure physiological responses of horse and human for those participating in an EAPL outpatient collegiate recovery program for substance use disorder (SUD). This pilot study assessed humans (n = 4) and horses (n = 5) participating in a collegiate recovery community EAPL SUD program. The six-week program included riding and ground activities for 1 hr/wk. Vital signs (heart and respiratory rates and pain rating) were recorded weekly at the beginning and end of each session. Human pain rating used the Wong-Baker Faces Pain Rating Scale and equines used the Equine Utrecht University Scale for Facial Assessment of Pain (EQUUS-FAP). T-tests were performed comparing measurements at the beginning and end of each session (P = 0.05). Pearson Correlations were used to determine relationships between human and horse vital signs. While no changes were seen in human heart rate, a significant decrease in respiratory rates and pain scores was found by the end of the session (Table 1). Horse heart and respiratory rates and EQUUS-FAP scores increased. A moderate correlation was determined for human and horse respiration rates (r=0.65, P = 0.00). Correlations became weaker when evaluating the other vital signs (Heart Rates: r=0.54, P = 0.00; Pain Rating Scores: r=0.27, P = 0.17). While relationships between horse and human vital signs were limited, it is important to note the differences in how the two physiologically respond to EAPL suggesting further research beyond this pilot study may be needed to investigate the physical demand of EAPL on the horse.

A Noncontact Vital Signs (NCVS) System for Potential Patient Monitoring Enabled by Robust Software Defined Radio (SDR)

This research proposes a robust non-contact vital signs (NCVS) sensor system for continuously monitoring the human respiration rate (RR) and heart rate (HR) within a distance of 1 to 2 meters. The novel Doppler-based NCVS sensor system is realized using an SDR (software defined radio) unit with optimized transmit/receive gain in commercial broadband, which filters intermediate frequency (IF) and operates at 2.4 GHz ISM band using a pair of small antennas. When compared with the vital signs data measured by traditional contact-based sensors, the NCVS sensing system demonstrates excellent accuracy in real-time RR/HR monitoring within 0.5/3 BPM (breath/beat per minute). We have obtained an IRB (Internal Review Board) approval to start a small clinical trial at Texas Tech University Health Sciences Center (TTUHSC) soon, hoping to use this system to effectively monitor vital signs of COVID-19 patients and to help telehealth delivery in the post-COVID-19 era.

Physiological and Behavioral Benefits for People and Horses during Guided Interactions at an Assisted Living Residence.

Assisted living is a fast-growing living option for seniors who require residence-based activities for maintaining mental and physical health. Guided equine interactions may benefit seniors, so an on-site equine program was started at Hacienda at the River senior living community. For research purposes, twenty-four residents and associates, aged fifty-five or over, consented to physiological measurements before, during and after four guided sessions of stroking one of three horses for 10 min over 4–6 weeks. Heart rate variability (HRV) was measured simultaneously in humans and horses during interactions. We hypothesized that human heart rate (HR) and HRV would increase during stroking and HRV power would shift toward the very low frequency (VLF) range common in horses, indicative of healthy function. During stroking, human HR increased (p < 0.05) but HRV (SDRR) and %VLF of HRV power did not change. Diastolic blood pressure (DBP), an exploratory measure, significantly increased after stroking, consistent with arousal. Two horses showed no significant changes in HR or HRV, but one relaxed. Sixteen horse–human pairs demonstrated synchronized HRV peak frequencies during sessions, suggestive of social connection. Participants used more positive than negative words describing their experience during exit interviews (p < 0.05). These data show that horses animate seniors without causing emotional stress and provide opportunities for social bonding.

Review of signal processing applications of Pyroelectric Infrared (PIR) sensors with a focus on respiration rate and heart rate detection

The article reviews signal processing applications of Pyroelectric Infrared (PIR) sensors with the main focus on the respiration and pulse rate detection. Respiration and pulse rates are vital signs that are routinely measured by healthcare providers to assess a human body's basic functions. In this paper, we review non-contact human respiratory rate and heart rate (pulse) estimation methods using the low-cost, contact-free, and non-invasive Pyroelectric Infrared (PIR) sensor. The time-varying sensor signal generated by the chest and subtle head movements are used to infer the respiratory rate and the heart rate, respectively. The PIR sensor can be mounted on the head rest of a chair or placed near a bed and can continuously estimate both the respiratory rate and the heart rate of a resting person at the same time. Experimental results indicate that a positive correlation higher than 95% between the heart rate estimates and the pulse oximeter measurements is achieved in our datasets. Similarly, a correlation coefficient of 95% is also achieved between the PIR-based respiratory rate estimates and the respiratory chest movements.

Private Weakly-Random Sequences from Human Heart Rate for Quantum Amplification.

We investigate whether the heart rate can be treated as a semi-random source with the aim of amplification by quantum devices. We use a semi-random source model called -Santha–Vazirani source, which can be amplified via quantum protocols to obtain a fully private random sequence. We analyze time intervals between consecutive heartbeats obtained from Holter electrocardiogram (ECG) recordings of people of different sex and age. We propose several transformations of the original time series into binary sequences. We have performed different statistical randomness tests and estimated quality parameters. We find that the heart can be treated as a good enough, and private by its nature, source of randomness that every human possesses. As such, in principle, it can be used as input to quantum device-independent randomness amplification protocols. The properly interpreted parameter can potentially serve as a new characteristic of the human heart from the perspective of medicine.

Layered ZnIn2S4 Single Crystals for Ultrasensitive and Wearable Photodetectors

AbstractZinc indium sulfide belongs to the family of layered ternary chalcogenides. Although ZnIn2S4 has a suitable bandgap in the visible range, its optoelectronic properties are not fully investigated. Most photodetectors based on layered semiconductors suffer from large dark currents, which hamper their performance and energy efficiency. In this work, high quality ZnIn2S4 single crystals are synthesized via chemical vapor transport. The free‐standing crystals are ≈20 μm thick and up to 2 cm2 in area and produce large photocurrents upon UV–vis illumination, while also maintaining extremely low currents in the dark. This allows to fabricate a simple photodetector with ohmic contacts, exhibiting extremely small dark currents down to 10–12 A. The ON/OFF (light/dark) switching ratio reaches value of 106, the highest reported for a layered semiconductor. Furthermore, the photodetector exhibits remarkable responsivity of 173 A W–1 and excellent detectivity of 1.7 × 1012 Jones. To demonstrate sensitivity and flexibility of the ZnIn2S4 crystals, a wearable device is also fabricated. The wearable is able to record human heart rate and compare it with signal measured by a commercial smartwatch. The results suggest a substantial research potential in further explorations of ZnIn2S4 and other ternary chalcogenides for optoelectronic applications.

Dual Activation of Phosphodiesterase 3 and 4 Regulates Basal Cardiac Pacemaker Function and Beyond.

The sinoatrial (SA) node is the physiological pacemaker of the heart, and resting heart rate in humans is a well-known risk factor for cardiovascular disease and mortality. Consequently, the mechanisms of initiating and regulating the normal spontaneous SA node beating rate are of vital importance. Spontaneous firing of the SA node is generated within sinoatrial nodal cells (SANC), which is regulated by the coupled-clock pacemaker system. Normal spontaneous beating of SANC is driven by a high level of cAMP-mediated PKA-dependent protein phosphorylation, which rely on the balance between high basal cAMP production by adenylyl cyclases and high basal cAMP degradation by cyclic nucleotide phosphodiesterases (PDEs). This diverse class of enzymes includes 11 families and PDE3 and PDE4 families dominate in both the SA node and cardiac myocardium, degrading cAMP and, consequently, regulating basal cardiac pacemaker function and excitation-contraction coupling. In this review, we will demonstrate similarities between expression, distribution, and colocalization of various PDE subtypes in SANC and cardiac myocytes of different species, including humans, focusing on PDE3 and PDE4. Here, we will describe specific targets of the coupled-clock pacemaker system modulated by dual PDE3 + PDE4 activation and provide evidence that concurrent activation of PDE3 + PDE4, operating in a synergistic manner, regulates the basal cardiac pacemaker function and provides control over normal spontaneous beating of SANCs through (PDE3 + PDE4)-dependent modulation of local subsarcolemmal Ca2+ releases (LCRs).

Research on Fatigue Detection Method of Equipment Operators Based on Multi-Source Physiological Signals

In order to effectively detect the fatigue status of equipment operators, this paper proposes a fatigue detection model that integrates multi-source physiological signals to evaluate the fatigue level of equipment operators in order to improve the efficiency of military operations and training. This method selects various physiological signals such as human heart rate, heart rate variability, body temperature, respiratory rate, blood oxygen concentration, etc. according to the working environment and working characteristics of the equipment operator, and establishes the relationship between the characteristic values of various physiological parameters and fatigue levels, And then use the optimized support vector machine to perform fusion judgment on the feature values of multi-source physiological parameters, and obtain the fatigue state of the equipment operator. Experimental results show that this method can make a more accurate judgment on the fatigue state of equipment operators, and is of great significance for ensuring the efficiency of equipment operators’ work and training.

Photomemory and Pulse Monitoring Featured Solution‐Processed Near‐Infrared Graphene/Organic Phototransistor with Detectivity of 2.4 × 1013 Jones

AbstractEmerging graphene/organic phototransistors are eye‐catching technologies owing to their unique merits including easy/low‐cost fabrication, temperature independent, and achieving various functions. However, their development in the near‐infrared (NIR) region is experiencing a bottleneck of inferior sensitivity due to low exciton dissociation efficiency and inefficient charge extraction rate. Here, a novel‐design solution‐processed graphene/organic NIR phototransistor is reported, that is, creatively introducing electron extraction layer of ZnO on graphene channel and employing organic ternary bulk heterojunction as photosensitive layer, successfully breaking that bottleneck. The phototransistor exhibits a high responsivity of 6.1 × 106 A W−1, a superior detectivity of 2.4 × 1013 Jones, and a remarkable minimum detection power of 1.75 nW cm−2 under 850 nm radiation. Considering its excellent NIR detection performance, a noncontact transmission‐type pulse monitoring is carried out with no external circuit support, from which human pulse signal and heart rate can be displayed in real time. The phototransistor, interestingly, can be switched into a photomemory function with a retention time of 1000 s in the atmosphere through a gate voltage of −20 V. The design takes the characteristics of graphene/organic phototransistors to a higher level, beyond the limit of sensitivity, and opens up a novel approach for developing multifunction devices.

Psychological behavior signal analysis for sports person during their activity session

The signal analysis helps us derive useful knowledge from biological processes to analyze, describe, and understand their origin mechanisms. However, biomedical signals are not immune and have time-consuming statistics. The major challenges of signal analysis of sportsperson are reliability and accuracy. Sports psychology uses psychological skills to discuss the optimum success and well-being of sports athletes, the developmental and social dimensions of the sport and sports facilities, and structural problems. The signal detection tool is used to detect the best combination of long-term practice predictors for active, sedentary adults’ signal. This paper proposed the wearable assisted signal detection method (WASDM) to find the sportspersons’ behavior signal analysis. This method performs an IoT based heart rate monitoring using a wearable device named intelligent bracelet mounted on the sportsperson to track the variations in his/her human heart rate. The wearable signal detector method analysis the heart rate abnormality and predicts health status, followed by an alarm to the physician and the respective personnel while performing activity session. In this research, various machine learning algorithms have been tried to perform signal analysis and prediction and compared their results to suggest the best in this application scenario. Finally, the experimental analysis shows better outcomes for the sportspersons’ psychological behavior signal analysis than the conventional methods.