MXene-Sponge Based High-Performance Piezoresistive Sensor for Wearable Biomonitoring and Real-Time Tactile Sensing.

Electrode microfabrication technologies such as lithography and deposition have been widely applied in wearable electronics to boost interfacial coupling efficiency and device performance. However, a majority of these approaches are restricted by expensive and complicated processing techniques, as well as waste discharge. Here, helium plasma irradiation is employed to yield a molybdenum microstructured electrode, which is constructed into a flexible piezoresistive pressure sensor based on a Ti3 C2 Tx nanosheet-immersed polyurethane sponge. This electrode engineering strategy enables the smooth transition between sponge deformation and MXene interlamellar displacement, giving rise to high sensitivity (1.52 kPa-1 ) and good linearity (r2  = 0.9985) in a wide sensing range (0-100 kPa) with a response time of 226 ms for pressure detection. In addition, both the experimental characterization and finite element simulation confirm that the hierarchical structures modulated by pore size, plasma bias, and MXene concentration play a crucial role in improving the sensing performance. Furthermore, the as-developed flexible pressure sensor is demonstrated to measure human radial pulse, detect finger tapping, foot stomping, and perform object identification, revealing great feasibility in wearable biomonitoring and health assessment.

O uso de aplicativo de celular para medir frequência cardíaca e saturação periférica de oxigênio / The use of cellular application to measure heart rate and peripheral oxygen saturation

Avaliar a associação da medida de frequência cardíaca (FC) e saturação periférica de oxigênio (SpO2 ) utilizando um aplicativo de celular e um monitor multiparamétrico. Métodos: Estudo experimental e randomizado entre participantes saudáveis. Investigou o aplicativo Samsung Health® e o monitor multiparamétrico da marca Midway®, modelo: PM-60. O estudo foi estruturado em quatro etapas. Para análise estatística, aplicou correlação de Pearson e Spearman, com nível de significância de 5%. Resultados: Dos 150 participantes a idade média foi de 22,3±4,5 anos, o sexo feminino foi predominante (71,3%). Verificouse forte correlação da FC medida pelo monitor com a FC do aplicativo de celular (r=0,93) indicando correlação positiva (p<0,001). A SpO2 medida por monitor multiparamétrico e pelo aplicativo de celular revelou um r=0,05 (p=0,51), o que atesta uma correlação nula e não significativa. Conclusão: Não houve correlação entre a medida da SpO2 do monitor multiparamétrico e do aplicativo Samsung Health®, não sendo confiável a utilização deste aplicativo para monitorar e gerenciar o sinal vital SpO2 em pessoas saudáveis. A FC medida com o aplicativo é significativa, e pode ser utilizada para monitorar e gerenciar esse sinal vital.

Assess the association of the measure of heart rate (HR) and oxygen saturation (SpO2 ) using a mobile application and a multiparameter monitor. Methods: Study experimental and randomized healthy participants. Investigated the application Samsung Health® and multiparameter monitor Midway® make, model: PM-60. The study was divided into four stages. Statistical analysis was applied Pearson and Spearman correlation with 5% significance level. Results: Of the 150 participants average age was 22.3±4.5 years, females were predominant (71.3%). There was a strong correlation HR measured by the monitor application to cell FC (r=0.93) indicating a positive correlation (p<0.001). SpO2 measured by multiparameter monitor and the mobile application revealed r=0.05 (p=0.51), which demonstrates a zero and no significant correlation. Conclusion: There was no correlation between the SpO2 measurement of the multiparameter monitor and the Samsung Health® app, not being trusted to use this application to monitor and manage the vital sign SpO2 in healthy people. The HR measured with the application is significant, and can be used to monitor and manage this vital sign.

A multi-point heart rate monitoring using a soft wearable system based on fiber optic technology.

Early diagnosis can be crucial to limit both the mortality and economic burden of cardiovascular diseases. Recent developments have focused on the continuous monitoring of cardiac activity for a prompt diagnosis. Nowadays, wearable devices are gaining broad interest for a continuous monitoring of the heart rate (HR). One of the most promising methods to estimate HR is the seismocardiography (SCG) which allows to record the thoracic vibrations with high non-invasiveness in out-of-laboratory settings. Despite significant progress on SCG, the current state-of-the-art lacks both information on standardized sensor positioning and optimization of wearables design. Here, we introduce a soft wearable system (SWS), whose novel design, based on a soft polymer matrix embedding an array of fiber Bragg gratings, provides a good adhesion to the body and enables the simultaneous recording of SCG signals from multiple measuring sites. The feasibility assessment on healthy volunteers revealed that the SWS is a suitable wearable solution for HR monitoring and its performance in HR estimation is strongly influenced by sensor positioning and improved by a multi-sensor configuration. These promising characteristics open the possibility of using the SWS in monitoring patients with cardiac pathologies in clinical (e.g., during cardiac magnetic resonance procedures) and everyday life settings.

Remote Monitoring of a Work-From-Home Employee to Identify Stress: A Case Report.

How do you assess the mental wellness of your work-from-home employees? This case study reports on how an occupational health nurse used work-from-home employee's own phone and Fitbit™ smartwatch to obtain heart rate data to screen for high periods of stress. Telemedicine and telemetry allowed the occupational health nurses to screen an employee when the nurse could not assess the employee face-to-face. When the occupational health nurses identified an at-risk employee, the occupational health nurses referred the employee to the Employee Assistance Program (EAP) for counseling. Leveraging heart rate data on a smartwatch is a free intervention that is scalable and has a demonstrated outcome measure with a positive return on investment.

Detection of Tachyarrhythmias in a Large Cohort of Infants Using Direct-to-Consumer Heart Rate Monitoring.

OBJECTIVE: Current estimates of the incidence of tachyarrhythmias in infants rely on clinical documentation and may not reflect the true rate in the general population. Our aim was to describe the epidemiology of tachyarrhythmia detected in a large cohort of infants using direct-to-consumer heart rate (HR) monitoring. STUDY DESIGN: Data were collected from Owlet Smart Sock devices used in infants in the US with birthdates between February 2017 and February 2019. We queried the HR data for episodes of tachyarrhythmia (HR of ≥240 bpm for >60 seconds). RESULTS: The study included 100 949 infants (50.8% male) monitored for more than 200 million total hours. We identified 5070 episodes of tachyarrhythmia in 2508 infants. The cumulative incidence of tachyarrhythmia in our cohort was 2.5% over the first year of life. The median age at the time of the first episode of tachyarrhythmia was 36 days (range, 1-358 days). Tachyarrhythmia was more common in infants with congenital heart disease (4.0% vs 2.4%; P = .015) and in females (2.7% vs 2.0%; P < .001). The median length of an episode was 7.3 minutes (range, 60 seconds to 5.4 hours) and the probability of an episode lasting longer than 45 minutes was 16.8% (95% CI, 15.4%-18.3%). CONCLUSIONS: We found the cumulative incidence of tachyarrhythmia among infants using direct-to-consumer HR monitors to be higher than previously reported in studies relying on clinical diagnosis. This finding may represent previously undetected subclinical disease in young infants, the significance of which remains uncertain. Clinicians should be prepared to discuss these events with parents.

The accuracy of fitness watches for the measurement of heart rate and energy expenditure during moderate intensity exercise.

BACKGROUND: As new technology emerges and updated fitness watches are released to the market, it is important to examine their accuracy. The aim of the current study was to examine the accuracy of three commercially available activity trackers in assessing heart rate (HR) and energy expenditure (EE) during moderate intensity exercise. METHODS: Twenty healthy participants (Age: 20.5±0.7 yrs., Ht: 173.4±10.8 cm, BM: 72.8±13.9 kg, BMI: 24.0±2.5 kg/m2) wore two fitness watches (FB: Fitbit VersaTM, San Francisco, CA, USA; and PI: Polar IgniteTM, Polar Electro Oy, Kempele, Finland) and a chest-worn HR monitor (PTP: Polar TeamPro SensorTM, Polar Electro) during a 12-minute exercise protocol at incremental speeds. An electrocardiogram (ECG) and indirect calorimetry were used as criterion measures for HR and EE. Mean absolute percentage error (MAPE) was calculated to determine measurement error. RESULTS: The MAPE values for HR were 11.6±8.7% for the FB, 11.0±10.0% for the PI, and 6.3±5.2% for the PTP. For EE, MAPE values were 9.6±7.2% for the FB, 16.7±19.6% for the PI and 13.8±13.0% for the PTP. CONCLUSIONS: Fitness watches relying on optical measures of HR underestimate HR compared to criterion measures during moderate intensity exercise. Despite providing a more accurate measure of HR, a chest-worn monitor does not provide a more accurate estimate of EE compared to fitness watches. The Fitbit provided the most accurate measure of EE when compared to the Polar Ignite watch and chest-worn device.

Concurrent heart rate validity of wearable technology devices during trail running.

Validation of heart rate responses in wearable technology devices is generally composed of laboratory-based protocols that are steady state in nature and as a result, high accuracy measures are returned. However, there is a need to understand device validity in applied settings that include varied intensities of exercise. The purpose was to determine concurrent heart rate validity during trail running. Twenty-one healthy participants volunteered (female n = 10, [mean (SD)]: age = 31 [11] years, height = 173.0 [7] cm, mass = 75.6 [13] kg). Participants were outfitted with wearable technology devices (Garmin Fenix 5 wristwatch, Jabra Elite Sport earbuds, Motiv ring, Scosche Rhythm+ forearm band, Suunto Spartan Sport watch with accompanying chest strap) and completed a self-paced 3.22 km trail run while concurrently wearing a criterion heart rate strap (Polar H7 heart rate monitor). The trail runs were out-and-back with the first 1.61 km in an uphill direction, and the 1.61 return being downhill in nature. Validity was determined through three methods: Mean Absolute Percent Error (MAPE), Bland-Altman Limits of Agreement (LOA), and Lin's Concordance Coefficient (rC). Validity measures overall are as follows: Garmin Fenix 5 (MAPE = 13%, LOA = -32 to 162, rC = 0.32), Jabra Elite Sport (MAPE = 23%, LOA = -464 to 503, rC = 0.38), Motiv ring (MAPE = 16%, LOA = -52 to 96, rC = 0.29), Scosche Rhythm+ (MAPE = 6%, LOA = -114 to 120, rC = 0.79), Suunto Spartan Sport (MAPE = 2%, LOA = -62 to 61, rC = 0.96). All photoplethysmography-based (PPG) devices displayed poor heart rate agreement during variable intensity trail running. Until technological advances occur in PPG-based devices allowing for acceptable agreement, heart rate in outdoor environments should be obtained using an ECG-based chest strap that can be connected to a wristwatch or other comparable receiver.

Emerging Technologies for Identifying Atrial Fibrillation.

Atrial fibrillation (AF) is a major cause of morbidity and mortality globally, and much of this is driven by challenges in its timely diagnosis and treatment. Existing and emerging mobile technologies have been used to successfully identify AF in a variety of clinical and community settings, and while these technologies offer great promise for revolutionizing AF detection and screening, several major barriers may impede their effectiveness. The unclear clinical significance of device-detected AF, potential challenges in integrating patient-generated data into existing healthcare systems and clinical workflows, harm resulting from potential false positives, and identifying the appropriate scope of population-based screening efforts are all potential concerns that warrant further investigation. It is crucial for stakeholders such as healthcare providers, researchers, funding agencies, insurers, and engineers to actively work together in fulfilling the tremendous potential of mobile technologies to improve AF identification and management on a population level.

The use of internal heart rate loggers in determining cardiac breakpoints of fish.

As marine environments are influenced by global warming there is a need to thoroughly understand the relationship between physiological limits and temperature in fish. One quick screening method of a physiological thermal tipping point is the temperature at which maximum heart rate (ƒHmax) can no longer scale predictably with warming and is referred to as the Arrhenius break temperature (TAB). The use of this method has been successful for freshwater fish by using external electrodes to detect an electrocardiogram (ECG), however, the properties of this equipment pose challenges in salt water when evaluating marine fish. To overcome these challenges, this study aimed to explore the potential use of implantable heart rate loggers to quantify the TAB of Chrysoblephus laticeps, a marine Sparid, following the ECG method protocols where ƒHmax is monitored over an acute warming event and the TAB is subsequently identified using a piece-wise linear regression model. Of the nine experimental fish, only five (56%) returned accurate ƒHmax data. The TAB of successful trials was identified each time and ranged from 18.09 to 20.10 °C. This study therefore provides evidence that implantable heart rate loggers can estimate TAB of fish which can be applied to many marine species.

Accuracy of Smartphone Camera Applications for Detecting Atrial Fibrillation: A Systematic Review and Meta-analysis.

Importance: Atrial fibrillation (AF) affects more than 6 million people in the United States; however, much AF remains undiagnosed. Given that more than 265 million people in the United States own smartphones (>80% of the population), smartphone applications have been proposed for detecting AF, but the accuracy of these applications remains unclear. Objective: To determine the accuracy of smartphone camera applications that diagnose AF. Data Sources and Study Selection: MEDLINE and Embase were searched until January 2019 for studies that assessed the accuracy of any smartphone applications that use the smartphone's camera to measure the amplitude and frequency of the user's fingertip pulse to diagnose AF. Data Extraction and Synthesis: Bivariate random-effects meta-analyses were constructed to synthesize data. The study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) of Diagnostic Test Accuracy Studies reporting guideline. Main Outcomes and Measures: Sensitivity and specificity were measured with bivariate random-effects meta-analysis. To simulate the use of these applications as a screening tool, the positive predictive value (PPV) and negative predictive value (NPV) for different population groups (ie, age ≥65 years and age ≥65 years with hypertension) were modeled. Lastly, the association of methodological limitations with outcomes were analyzed with sensitivity analyses and metaregressions. Results: A total of 10 primary diagnostic accuracy studies, with 3852 participants and 4 applications, were included. The oldest studies were published in 2016 (2 studies [20.0%]), while most studies (4 [40.0%]) were published in 2018. The applications analyzed the pulsewave signal for a mean (range) of 2 (1-5) minutes. The meta-analyzed sensitivity and specificity for all applications combined were 94.2% (95% CI, 92.2%-95.7%) and 95.8% (95% CI, 92.4%-97.7%), respectively. The PPV for smartphone camera applications detecting AF in an asymptomatic population aged 65 years and older was between 19.3% (95% CI, 19.2%-19.4%) and 37.5% (95% CI, 37.4%-37.6%), and the NPV was between 99.8% (95% CI, 99.83%-99.84%) and 99.9% (95% CI, 99.94%-99.95%). The PPV and NPV increased for individuals aged 65 years and older with hypertension (PPV, 20.5% [95% CI, 20.4%-20.6%] to 39.2% [95% CI, 39.1%-39.3%]; NPV, 99.8% [95% CI, 99.8%-99.8%] to 99.9% [95% CI, 99.9%-99.9%]). There were methodological limitations in a number of studies that did not appear to be associated with diagnostic performance, but this could not be definitively excluded given the sparsity of the data. Conclusions and Relevance: In this study, all smartphone camera applications had relatively high sensitivity and specificity. The modeled NPV was high for all analyses, but the PPV was modest, suggesting that using these applications in an asymptomatic population may generate a higher number of false-positive than true-positive results. Future research should address the accuracy of these applications when screening other high-risk population groups, their ability to help monitor chronic AF, and, ultimately, their associations with patient-important outcomes.

Stress Score y LnrRMSSD como parámetros de carga interna durante una competición / Stress Score and LnrMSSD as Internal Load Parameters During Competition

El objetivo del estudio fue analizar el comportamiento del stress score (SS) y el logaritmo neperiano de la media de la raíz cuadrada de las diferencias de los intervalos sucesivos R-R (LnrMSSD) de la variabilidad de la frecuencia cardíaca (VFC) como indicadores de la carga interna mediante la modulación simpática y parasimpática, apoyado con parámetros bioquímicos de carga interna. Se evaluaron 14 atletas universitarios de balonmano (edad 22.30 ± 1.83 años). Se monitoreó la VFC y marcadores bioquímicos en seis momentos. Se analizaron las diferencias entre las tomas de cada variable mediante estadística descriptiva convencional y el tamaño del efecto con la d de Cohen y la magnitud de Hopkins. Se examinaron las correlaciones de Pearson entre variables. El LnrMSSD, SS y cortisol presentaron cambios significativos (p < .05). Se encontraron correlaciones entre los parámetros de la VFC (SS y LnrMSSD) con creatin kinasa (CK) respectivamente. Los resultados del estudio muestran que el SS puede ser una metodología fiable para la evaluación de la carga interna durante una competición

The aim of this study was to analyse the behaviour of the stress score (SS) and the Neperian logarithmof the Root Mean Square of Successive R-R Interval differences (LnrMSSD) of heart rate variability (HRV) as indicators of internal load throughout sympathetic and parasympathetic modulation, supported by biochemical parameters of internal load. 14 handball university athletes (age 22.30 ± 1.83 years) were evaluated. Six times of HRV and biochemical markers were collected. Each variable were analyzed by conventional statistics and using the Cohen´s d, and Hopkins magnitude for the sample size effect. It was analyzed the Pearson correlations between variables. The LnrMSSD, SS and cortisol presented significant changes (p< .05). Correlations were found between HRV (SS and LnrMSSD) and CK respectively. Results of this study shows that SS can be a reliable method for the evaluation of internal load during competition

AVNRT captured by Apple Watch Series 4: Can the Apple watch be used as an event monitor?

Wrist-worn devices are popular for heart rate monitoring, including use of photoplethysmography. The Apple Watch series 4 can identify atrial fibrillation. We describe a case of identification re-entrant supraventricular tachycardia not identified by outpatient rhythm monitoring, however, was identified by the Apple Watch series 4, which lead to electrophysiology study and successful ablation of atrioventricular nodal re-entrant tachycardia.

Usefulness of Noninvasively Measured Pulse Amplitude Changes During the Valsalva Maneuver to Identify Hospitalized Heart Failure Patients at Risk of 30-Day Heart Failure Events (from the PRESSURE-HF Study).

The pulse amplitude ratio (PAR), the ratio of pulse pressure at the end of the Valsalva maneuver to before the onset, correlates with cardiac filling pressure. We have developed a handheld device that uses finger photoplethysmography to measure PAR and estimate left ventricular end diastolic pressure (LVEDP). Patients hospitalized with heart failure (HF) performed three 10-second trials of a standardized Valsalva maneuver (at 20 mm Hg measured via pressure transducer), while photoplethysmography waveforms were recorded, at admission and discharge. Combined primary outcome was 30-day HF hospitalization, intravenous diuresis, or death. Fifty-two subjects had discharge PAR testing; 12 met the primary outcome. Median PAR on admission was 0.55 (interquartile range: 0.40 to 0.70, n = 48) and on discharge was 0.50 (interquartile range: 0.36 to 0.69). Mean PAR-estimated LVEDP was significantly higher in subjects that had an event (20.2 vs 16.9 mm Hg, p = 0.043). Subjects with PAR-estimated LVEDP >19.5 mm Hg had an event rate hazard ratio of 4.57 (95% confidence interval 1.37, 15.19, p = 0.013) compared with patients with LVEDP 19.5 mm Hg or below, with significantly lower 30-day event-free survival (log-rank p = 0.006). In conclusion, noninvasively estimated LVEDP using the pulse amplitude response to a Valsalva maneuver in patients hospitalized for HF changes with diuresis and identifies patients at high risk for 30-day HF events. Detection of elevated filling pressures before hospital discharge may be useful in guiding HF management to reduce HF events.

Proof-of-concept for a non-invasive, portable, and wireless device for cardiovascular monitoring in pediatric patients.

Measurement of cardiac function is vital for the health of pediatric patients with heart disease. Standard tools to measure function including echocardiogram and magnetic residence imaging are time intensive, costly, and have limited accessibility. The Vivio is a novel, non-invasive, handheld device that screens for cardiac dysfunction by analyzing intrinsic frequencies (IF) ω1 and ω2 of carotid artery waveforms. Prior studies demonstrated that left ventricular ejection fraction can be derived from IFs in adults. This study 1) studies whether the Vivio can capture carotid arterial pulse waveform data in children ages 0-19 years old; 2) tests the performance of two sensor head geometries, one larger and smaller than the standard size used in adults, designed for the pediatric population; 3) compares the IFs between pediatric age groups and adults with normal function. The Vivio successfully measured a carotid artery waveform in all children over 5 years old and 28% of children under the age of five. The small head did not accurately measure a waveform in any age group. One-way analysis of variance (ANOVA) demonstrated a difference in the IF ω1 between the adult and pediatric cohorts (F = 7.3, Prob>F = 0.0001). Post host analysis demonstrated a difference between the adult cohort (ω1 = 99 +/- 5 bpm) and the cohorts ages 0-4 (ω1 = 111 +/- 2 bpm; p = 0.0006) and 15-19 years old (ω1 = 105 +/-5 bpm; p = 0.02). One-way ANOVA demonstrated a difference in the IF ω2 between the adult and pediatric cohorts (F = 4.8, Prob>F = 0.003), specifically between the adult (ω2 = 81 +/- 13 bpm) and age 0-4 cohorts (ω2 = 48 +/- 8 bpm; p = 0.002). These results suggest that the Vivio can be used to capture carotid pulse waveform data in pediatric populations and that the data produced can be used to measure intrinsic frequencies.

A simple method for detecting chaos in nature.

Chaos, or exponential sensitivity to small perturbations, appears everywhere in nature. Moreover, chaos is predicted to play diverse functional roles in living systems. A method for detecting chaos from empirical measurements should therefore be a key component of the biologist's toolkit. But, classic chaos-detection tools are highly sensitive to measurement noise and break down for common edge cases, making it difficult to detect chaos in domains, like biology, where measurements are noisy. However, newer tools promise to overcome these limitations. Here, we combine several such tools into an automated processing pipeline, and show that our pipeline can detect the presence (or absence) of chaos in noisy recordings, even for difficult edge cases. As a first-pass application of our pipeline, we show that heart rate variability is not chaotic as some have proposed, and instead reflects a stochastic process in both health and disease. Our tool is easy-to-use and freely available.

The Relationship between Different Types of Alarm Sounds and Children's Perceived Risk Based on Their Physiological Responses.

Due to differences in cognitive ability and physiological development, the evacuation characteristics of children are different from those of adults. This study proposes a novel method of using wearable sensors to collect data (e.g., electrodermal activity, EDA; heart rate variability, HRV) on children's physiological responses, and to continuously and quantitatively evaluate the effects of different types of alarm sounds during the evacuation of children. In order to determine the optimum alarm for children, an on-site experiment was conducted in a kindergarten to collect physiological data for responses to different types of alarm sounds during the evacuation of 42 children of different ages. The results showed that: (1) The alarm sounds led to changes in physiological indicators of children aged 3-6 years, and the effects of different types of alarm sounds on EDA and HRV activities were significantly different (p < 0.05). Skin conductance (SC), skin conductance tonic (SCT) and skin conductance level (SCL) can be used as the main indicators for analysing EDA of children in this experiment (p < 0.05), and the indicators of ultralow frequency (ULF) and very low frequency (VLF) for HRV were not affected by the type of alarm sounds (p > 0.05). (2) Unlike adults, kindergarten children were more susceptible to the warning siren. The combined voice and warning alarm had optimal effects in stimulating children to perceive risk. (3) For children aged 3-6 years, gender had a significant impact on children's reception to evacuation sound signals (p < 0.05): Girls are more sensitive than boys in receiving evacuation sound signals, similar to findings of studies of risk perception of adult males and females. In addition, the higher the age, the greater the sensitivity to evacuation sound signals, which accords with results of previous studies on the evacuation dynamics of children.

Continuous Distant Measurement of the User's Heart Rate in Human-Computer Interaction Applications.

In real world scenarios, the task of estimating heart rate (HR) using video plethysmography (VPG) methods is difficult because many factors could contaminate the pulse signal (i.e., a subjects' movement, illumination changes). This article presents the evaluation of a VPG system designed for continuous monitoring of the user's heart rate during typical human-computer interaction scenarios. The impact of human activities while working at the computer (i.e., reading and writing text, playing a game) on the accuracy of HR VPG measurements was examined. Three commonly used signal extraction methods were evaluated: green (G), green-red difference (GRD), blind source separation (ICA). A new method based on an excess green (ExG) image representation was proposed. Three algorithms for estimating pulse rate were used: power spectral density (PSD), autoregressive modeling (AR) and time domain analysis (TIME). In summary, depending on the scenario being studied, different combinations of signal extraction methods and the pulse estimation algorithm ensure optimal heart rate detection results. The best results were obtained for the ICA method: average RMSE = 6.1 bpm (beats per minute). The proposed ExG signal representation outperforms other methods except ICA (RMSE = 11.2 bpm compared to 14.4 bpm for G and 13.0 bmp for GRD). ExG also is the best method in terms of proposed success rate metric (sRate).

Early prognostication of neurological outcome by heart rate variability in adult patients with out-of-hospital sudden cardiac arrest.

BACKGROUND: Most deaths of comatose survivors of out-of-hospital sudden cardiac arrest result from withdrawal of life-sustaining treatment (WLST) decisions based on poor neurological prognostication and the family's intention. Thus, accurate prognostication is crucial to avoid premature WLST decisions. However, targeted temperature management (TTM) with sedation or neuromuscular blockade against shivering significantly affects early prognostication. In this study, we investigated whether heart rate variability (HRV) analysis could prognosticate poor neurological outcome in comatose patients undergoing hypothermic TTM. METHODS: Between January 2015 and December 2017, adult patients with out-of-hospital sudden cardiac arrest, successfully resuscitated in the emergency department and admitted to the intensive care unit of the Niigata University in Japan, were prospectively included. All patients had an initial Glasgow Coma Scale motor score of 1 and received hypothermic TTM (at 34 °C). Twenty HRV-related variables (deceleration capacity; 4 time-, 3 geometric-, and 7 frequency-domain; and 5 complexity variables) were computed based on RR intervals between 0:00 and 8:00 am within 24 h after return of spontaneous circulation (ROSC). Based on Glasgow Outcome Scale (GOS) at 2 weeks after ROSC, patients were divided into good outcome (GOS 1-2) and poor outcome (GOS 3-5) groups. RESULTS: Seventy-six patients were recruited and allocated to the good (n = 22) or poor (n = 54) outcome groups. Of the 20 HRV-related variables, ln very-low frequency (ln VLF) power, detrended fluctuation analysis (DFA) (α1), and multiscale entropy (MSE) index significantly differed between the groups (p = 0.001), with a statistically significant odds ratio (OR) by univariate logistic regression analysis (p = 0.001). Multivariate logistic regression analysis of the 3 variables identified ln VLF power and DFA (α1) as significant predictors for poor outcome (OR = 0.436, p = 0.006 and OR = 0.709, p = 0.024, respectively). The area under the receiver operating characteristic curve for ln VLF power and DFA (α1) in predicting poor outcome was 0.84 and 0.82, respectively. In addition, the minimum value of ln VLF power or DFA (α1) for the good outcome group predicted poor outcome with sensitivity = 61% and specificity = 100%. CONCLUSIONS: The present data indicate that HRV analysis could be useful for prognostication for comatose patients during hypothermic TTM.

A wearable and sensitive graphene-cotton based pressure sensor for human physiological signals monitoring.

Cotton fiber is the most commonly used fabric in textiles and clothing. As compared to inorganic materials like foam, sponge and paper, cotton fibers boast higher levels of flexibility and toughness, which makes it more durable and be better integrated with clothes. In this study, a conductive cotton fiber material modified by reduced graphene oxide (rGO) was prepared, and applied in pressure sensor. The highest sensitivity of the pressure sensor constructed is 0.21 kPa-1, and the pressure range covers up to 500 kPa, which demonstrates a combination of fine sensitivity and broader pressure range. The pressure sensor developed in this study demonstrates great performance in real-time monitoring of human physiological signals like pulse, breath rate and speech recognition, boasting great application value in wearable electronics and smart clothing.

An Empirical Study Comparing Unobtrusive Physiological Sensors for Stress Detection in Computer Work.

Several unobtrusive sensors have been tested in studies to capture physiological reactions to stress in workplace settings. Lab studies tend to focus on assessing sensors during a specific computer task, while in situ studies tend to offer a generalized view of sensors' efficacy for workplace stress monitoring, without discriminating different tasks. Given the variation in workplace computer activities, this study investigates the efficacy of unobtrusive sensors for stress measurement across a variety of tasks. We present a comparison of five physiological measurements obtained in a lab experiment, where participants completed six different computer tasks, while we measured their stress levels using a chest-band (ECG, respiration), a wristband (PPG and EDA), and an emerging thermal imaging method (perinasal perspiration). We found that thermal imaging can detect increased stress for most participants across all tasks, while wrist and chest sensors were less generalizable across tasks and participants. We summarize the costs and benefits of each sensor stream, and show how some computer use scenarios present usability and reliability challenges for stress monitoring with certain physiological sensors. We provide recommendations for researchers and system builders for measuring stress with physiological sensors during workplace computer use.