Continuous Measurement Of Heart Rate Research Articles

First Real-Life Data on the Diving Response in Healthy Children.

Swimming and diving are popular recreational activities, representing an effective option in maintaining and improving cardiovascular fitness in healthy people. To date, only little is known about the cardiovascular adaption to submersion in children. This study was conducted to improve an understanding thereof. We used a stepwise apnea protocol with apnea at rest, apnea with facial immersion, and at last apnea during whole body submersion. Continuous measurement of heart rate, oxygen saturation, and peripheral resistance index was done. Physiologic data and analysis of influencing factors on heart rate, oxygen saturation, and peripheral vascular tone response are reported. The current study presents the first data of physiologic diving response in children. Data showed that facial or whole body submersion leads to a major drop in heart rate, and increase of peripheral resistance, while the oxygen saturation seems to be unaffected by static apnea in most children, with apnea times of up to 75s without change in oxygen saturation.

Privacy and Utility of Private Synthetic Data for Medical Data Analyses

The increasing availability and use of sensitive personal data raises a set of issues regarding the privacy of the individuals behind the data. These concerns become even more important when health data are processed, as are considered sensitive (according to most global regulations). Privacy Enhancing Technologies (PETs) attempt to protect the privacy of individuals whilst preserving the utility of data. One of the most popular technologies recently is Differential Privacy (DP), which was used for the 2020 U.S. Census. Another trend is to combine synthetic data generators with DP to create so-called private synthetic data generators. The objective is to preserve statistical properties as accurately as possible, while the generated data should be as different as possible compared to the original data regarding private features. While these technologies seem promising, there is a gap between academic research on DP and synthetic data and the practical application and evaluation of these techniques for real-world use cases. In this paper, we evaluate three different private synthetic data generators (MWEM, DP-CTGAN, and PATE-CTGAN) on their use-case-specific privacy and utility. For the use case, continuous heart rate measurements from different individuals are analyzed. This work shows that private synthetic data generators have tremendous advantages over traditional techniques, but also require in-depth analysis depending on the use case. Furthermore, it can be seen that each technology has different strengths, so there is no clear winner. However, DP-CTGAN often performs slightly better than the other technologies, so it can be recommended for a continuous medical data use case.

RPPG Signal Measurement Based on Time-do-main Attention Network

The measurement of heart rate without touching the object being measured is referred to as “non-contact heart rate estimation.” Telemedicine, education, and a variety of other fields can all benefit from this approach, which is capable of achieving continuous heart rate measurement under certain conditions. The video segmentation network and the backbone network are cascaded in this paper’s cascaded heart rate estimation model. Adding temporal attention based on the existing 3D convolutional network model, the video segmentation network divides the video into multiple segments and fuses the relevant temporal features. It then sends the fusion results to the backbone network with the temporal attention mechanism. Mechanisms and modules like spatiotemporal convolution to make heart rate measurement more reliable and use a custom joint loss function to cut out other kinds of periodic signals’ influence. The trial results show the way that the proposed calculation can successfully lessen movement ancient rarity and light change clamor.Additionally, the dataset UBFC-rPPG demonstrates the model’s efficacy.

A Robust rPPG Approach for Continuous Heart Rate Measurement Based on Face

A Robust rPPG Approach for Continuous Heart Rate Measurement Based on Face

Pregnancy outcomes in infertility patients diagnosed with sleep disordered breathing with wireless wearable sensors

ObjectiveTo study the feasibility of home-based assessment of sleep disordered breathing (SDB) on early pregnancy success after in vitro fertilization with novel wearable sensors. DesignProspective observational study. SettingPatients 18 to 45 years old undergoing autologous IVF at an academic infertility center. Patients30 women (24–44 years old) InterventionParticipants provided medical history, completed sleep surveys, and a single night of home sleep monitoring prior to IVF with a novel, FDA-cleared wireless sensor system (ANNE® Sleep, Sibel Health), to collect continuous measurements of heart rate, respiratory rate, pulse oxygenation, respiratory effort/snoring, peripheral arterial tonometry, pulse arrival time, and pulse transit time, an accepted surrogate of continuous blood pressure generated by pulse arrival time and pulse transit time. Sleep nights were reviewed to derive the apnea hypopnea index (AHI), defined as the average number of apnea or hypopnea events per hour. An AHI of greater than or equal to 5 events/hour was considered abnormal. Main outcome measureRate of clinical pregnancy (defined as intrauterine gestational sac with a yolk sac) after IVF. Logistic regression models were used to estimate the unadjusted and adjusted odds ratio. ResultsThe overall rate of sleep disordered breathing of any severity was 57%. Participants with SDB had a mean AHI of 13.4 compared to 2.7 events/hr (p<0.01), were younger, and more likely to have polycystic ovary syndrome. Of the 29 patients undergoing an embryo transfer, clinical pregnancy and livebirth occurred in 35% of women with SDB compared to 58% without SDB (p = 0.22). After adjusting for age, SDB reduced pregnancy rates but was not statistically significant (aOR 0.23, 95% CI: 0.04–1.5, p = 0.12). Though polycystic ovary syndrome was associated with higher rates of SDB it was not independently associated with lower pregnancy rates. ConclusionScreening for sleep disordered breathing using home-based wireless, wearable sensors was well accepted and easily performed by infertile patients in this cohort. Sleep disordered breathing of any severity was associated with an 77% (95% CI: 0.08–1.8) lower likelihood of clinical pregnancy and live birth independent of underlying diagnosis. Future larger studies will be needed to understand the role of sleep disordered breathing and IVF outcomes.

Digital Platform to Continuously Monitor Patients Using a Smartwatch: Preliminary Report.

BackgroundMonitoring vital signs such as oximetry, blood pressure, and heart rate is important to follow the evolution of patients. Smartwatches are a revolution in medicine allowing the collection of such data in a continuous and organic way. However, it is still a challenge to make this information available to health care professionals to make decisions during clinical follow-up.ObjectiveThis study aims to build a digital solution that displays vital sign data from smartwatches, collected remotely, continuously, reliably, and from multiple users, with trigger warnings when abnormal results are identified.MethodsThis is a single-center prospective study following the guidelines “Evaluating digital health products” from the UK Health Security Agency. A digital platform with 3 different applications was created to capture and display data from the mobile phones of volunteers with smartwatches. We selected 80 volunteers who were followed for 24 weeks each, and the synchronization interval between the smartwatch and digital solution was recorded for each vital sign collected.ResultsIn 14 weeks of project progress, we managed to recruit 80 volunteers, with 68 already registered in the digital solution. More than 2.8 million records have already been collected, without system downtime. Less than 5% of continuous heart rate measurements (bpm) were synchronized within 2 hours. However, approximately 70% were synchronized in less than 24 hours, and 90% were synchronized in less than 119 hours.ConclusionsThe digital solution is working properly in its role of displaying data collected from smartwatches. Vital sign values are being monitored by the research team as part of the monitoring of volunteers. Although the digital solution proved unsuitable for monitoring urgent events, it is more than suitable for use in outpatient clinical use. This digital solution, which is based on cloud technology, can be applied in the future for telemonitoring in regions lacking health care professionals. Accuracy and reliability studies still need to be performed at the end of the 24-week follow-up.

Joint Profiles of Sedentary Time and Physical Activity in Adults and Their Associations with Cardiometabolic Health.

This study aimed to identify and characterize joint profiles of sedentary time and physical activity among adults and to investigate how these profiles are associated with markers of cardiometabolic health. The participants included 3702 of the Northern Finland Birth Cohort 1966 at age 46 yr, who wore a hip-worn accelerometer during waking hours and provided seven consecutive days of valid data. Sedentary time, light-intensity physical activity, and moderate- to vigorous-intensity physical activity on each valid day were obtained, and a data-driven clustering approach ("KmL3D") was used to characterize distinct joint profiles of sedentary time and physical activity intensities. Participants self-reported their sleep duration and performed a submaximal step test with continuous heart rate measurement to estimate their cardiorespiratory fitness (peak heart rate). Linear regression was used to determine the association between joint profiles of sedentary time and physical activities with cardiometabolic health markers, including adiposity markers and blood lipid, glucose, and insulin levels. Four distinct groups were identified: "active couch potatoes" ( n = 1173), "sedentary light movers" ( n = 1199), "sedentary exercisers" ( n = 694), and "movers" ( n = 636). Although sufficiently active, active couch potatoes had the highest daily sedentary time (>10 h) and lowest light-intensity physical activity. Compared with active couch potatoes, sedentary light movers, sedentary exercisers, and movers spent less time in sedentary by performing more physical activity at light-intensity upward and had favorable differences in their cardiometabolic health markers after accounting for potential confounders (1.1%-25.0% lower values depending on the health marker and profile). After accounting for sleep duration and cardiorespiratory fitness, waking activity profiles characterized by performing more physical activity at light-intensity upward, resulting in less time spent in sedentary, were associated with better cardiometabolic health.

P1630: WEARABLES IN TRANSFUSION MEDICINE: CHALLENGES AND FUTURE PERSPECTIVE

Background: The digital era has granted us new techniques like photoplethysmogram or ECG-based wearable devices, that can remotely monitor physiological parameters of patients, including heart rate and activity measures continuously. These developments yield many opportunities but also great challenges. For instance, in the Myelodysplastic syndrome (MDS), most patients will become RBC transfusion dependent during the course of their disease. It has been well established that Hb-level alone is an insufficient marker to guide in RBC transfusions. Nonetheless, we base transfusion regiments on Hb-thresholds combined with a subjective interpretations of the patient’s quality of life. This leads to great variability in transfusion strategies causing patients to often be over- or undertransfused. We therefore need objective parameters to evaluate and guide our transfusion strategies. Aims: We intend to share our practical knowledge of the encountered challenges. Methods: Following pilots with the Withings Steel HR and VitalPatch (Table 1.), we have started the REMOTE 2 trial (NTR: NL9289) and are collaborating internationally to initiate larger trials. Here we have gathered the experiences we deem important for researchers new to the field. Results: When choosing the device, first establish the desired outcomes. Is a true continuous heart rate collection necessary, or will a semi-continuous measurement suffice? Within an elderly MDS population a more manageable device with a long battery-life can help reduce data missingness. On the other hand, with only daily averages of parameters, a deeper understanding of interaction of the collected parameters is challenging. Also, product placement will impact the outcome, as wrist-worn devices are more susceptible to noise than chest-worn devices. Importantly, inter-device variability has been reported to be high. Therefore, it is strongly preferable to use one device only in a study. Many wearable biosensors are not medically validated (yet). We believe, however, this should not discourage the investigator to use such a device. Unvalidated continuous heart rate measurements have been shown to produce very accurate data. And importantly, there are currently no validated – or unvalidated – parameters to evaluate these patients. Physiological parameters are highly impacted by numerous factors like weather and daily schedules. Large sample sizes should reduce this natural variability, but trials involving MDS-patients have thus far been unable to collect more than 38 patients in one study. Combining groups, like thalassemia and myelofibrosis, will increase the sample size. However, subgroup analysis will still lack power. Therefore, international collaborations are necessary to acquire sufficient sample sizes to answer questions like: What parameters are of value to evaluate transfusion strategies? How do these parameters respond to different 1) amounts of RBCs; 2) thresholds; and 3) timing of transfusion? After answering these first questions, we can look at how these parameters change with longer-standing changes, and how deleterious the fluctuations in Hbmass are to the patient. Image:Summary/Conclusion: Depending on the research context, intervention and the desired outcomes, one should carefully choose the required device. While various devices may mork, the trade-off between ease of use and data granularity can make a substantial difference when analysing the data. For sufficient sample sizes, international collaborations are required to answer the many questions in order to improve the care of chronic transfusion dependent patients.

Accuracy of Wearable Photoplethysmography Sensors for Continuous Heart Rate Monitoring in Telehealth Applications.

The demand for extended care for people suffering from heart failure is omnipresent. Wearables providing continuous heart rate measurement through optical sensors are of great interest due to their ease of use without the need for medical staff and their low cost. In this study, seven wearables were tested in fifteen measurement runs, with a duration of fourteen-hour each, and compared to a reference sensor. By calculating the Pearson correlation and the root mean square error, as well as the graphical representation by a Bland Altman plot, it was found that these wearables lack sufficient accuracy and may not be suitable for medical purposes.

Enhancement of a Camera-Based Continuous Heart Rate Measurement Algorithm

Enhancement of a Camera-Based Continuous Heart Rate Measurement Algorithm

Sympathetic transduction of blood pressure during graded lower body negative pressure in young healthy adults.

Sympathetic transduction of blood pressure (BP) is correlated negatively with resting muscle sympathetic nerve activity (MSNA) in cross-sectional data, but the acute effects of increasing MSNA are unclear. Sixteen (4 female) healthy adults (26 ± 3 years) underwent continuous measurement of heart rate, BP, and MSNA at rest and during graded lower body negative pressure (LBNP) at -10, -20, and -30 mmHg. Sympathetic transduction of BP was quantified in the time (signal averaging) and frequency (MSNA-BP gain) domains. The proportions of MSNA bursts firing within each tertile of BP were calculated. As expected, LBNP increased MSNA burst frequency (P < 0.01) and burst amplitude (P < 0.02), although the proportions of MSNA bursts firing across each BP tertile remained stable (all P > 0.44). The MSNA-diastolic BP low-frequency transfer function gain (P = 0.25) was unchanged during LBNP; the spectral coherence was increased (P = 0.03). Signal-averaged sympathetic transduction of diastolic BP was unchanged (from 2.1 ± 1.0 at rest to 2.4 ± 1.5, 2.2 ± 1.3, and 2.3 ± 1.4 mmHg; P = 0.43) during LBNP, but diastolic BP responses following nonburst cardiac cycles progressively decreased (from -0.8 ± 0.4 at rest to -1.0 ± 0.6, -1.2 ± 0.6, and -1.6 ± 0.9 mmHg; P < 0.01). As a result, the difference between MSNA burst and nonburst diastolic BP responses was increased (from 2.9 ± 1.4 at rest to 3.4 ± 1.9, 3.4 ± 1.9, and 3.9 ± 2.1 mmHg; P < 0.01). In conclusion, acute increases in MSNA using LBNP did not alter traditional signal-averaged or frequency-domain measures of sympathetic transduction of BP or the proportion of MSNA bursts firing at different BP levels. The factors that determine changes in the firing of MSNA bursts relative to oscillations in BP require further investigation.

Continuous Monitoring of Vital Signs With Wearable Sensors During Daily Life Activities: Validation Study.

BackgroundContinuous telemonitoring of vital signs in a clinical or home setting may lead to improved knowledge of patients’ baseline vital signs and earlier detection of patient deterioration, and it may also facilitate the migration of care toward home. Little is known about the performance of available wearable sensors, especially during daily life activities, although accurate technology is critical for clinical decision-making.ObjectiveThe aim of this study is to assess the data availability, accuracy, and concurrent validity of vital sign data measured with wearable sensors in volunteers during various daily life activities in a simulated free-living environment.MethodsVolunteers were equipped with 4 wearable sensors (Everion placed on the left and right arms, VitalPatch, and Fitbit Charge 3) and 2 reference devices (Oxycon Mobile and iButton) to obtain continuous measurements of heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2), and temperature. Participants performed standardized activities, including resting, walking, metronome breathing, chores, stationary cycling, and recovery afterward. Data availability was measured as the percentage of missing data. Accuracy was evaluated by the median absolute percentage error (MAPE) and concurrent validity using the Bland-Altman plot with mean difference and 95% limits of agreement (LoA).ResultsA total of 20 volunteers (median age 64 years, range 20-74 years) were included. Data availability was high for all vital signs measured by VitalPatch and for HR and temperature measured by Everion. Data availability for HR was the lowest for Fitbit (4807/13,680, 35.14% missing data points). For SpO2 measured by Everion, median percentages of missing data of up to 100% were noted. The overall accuracy of HR was high for all wearable sensors, except during walking. For RR, an overall MAPE of 8.6% was noted for VitalPatch and that of 18.9% for Everion, with a higher MAPE noted during physical activity (up to 27.1%) for both sensors. The accuracy of temperature was high for VitalPatch (MAPE up to 1.7%), and it decreased for Everion (MAPE from 6.3% to 9%). Bland-Altman analyses showed small mean differences of VitalPatch for HR (0.1 beats/min [bpm]), RR (−0.1 breaths/min), and temperature (0.5 °C). Everion and Fitbit underestimated HR up to 5.3 (LoA of −39.0 to 28.3) bpm and 11.4 (LoA of −53.8 to 30.9) bpm, respectively. Everion had a small mean difference with large LoA (−10.8 to 10.4 breaths/min) for RR, underestimated SpO2 (>1%), and overestimated temperature up to 2.9 °C.ConclusionsData availability, accuracy, and concurrent validity of the studied wearable sensors varied and differed according to activity. In this study, the accuracy of all sensors decreased with physical activity. Of the tested sensors, VitalPatch was found to be the most accurate and valid for vital signs monitoring.

EARLY PREGNANCY OUTCOMES AFTER IVF AND SLEEP DISORDERED BREATHING

While sleep disordered breath (SDB) is associated with multiple medical comorbidities and adverse late stage pregnancy complications such as preeclampsia and gestational diabetes, there is little understanding of its impact on early pregnancy outcomes after IVF. Patients between 18 to 45 years old undergoing autologous IVF and anticipating an embryo transfer were eligible for participation in this single-arm prospective observational study. Women with current treatment of obstructive sleep apnea were excluded. Demographics, medical history, and sleep surveys including the STOP-BANG Questionnaire, Epworth Sleepiness Survey, Pittsburgh Sleep Quality Index, and the Insomnia Severity Index were collected. Participants completed a single night of home sleep monitoring prior to IVF with a novel sensor system composed of two wireless patches located at the suprasternal notch and the index finger (ANNE Sleep, Sibel Health), which collected continuous measurements of heart rate, respiratory rate, peripheral arterial tonometry, temperature, blood pressure, and pulse oxygenation. Sleep nights were reviewed for SDB determined by an apnea hypopnea index (AHI), defined as the average number of apneic events per hour based on American Academy of Sleep Medicine scoring guidelines. IVF cycle and early pregnancy outcomes were followed to at least 12 weeks. The primary exposure was SDB (AHI 5 events/hr) and the primary outcome was rate of clinical pregnancy (defined as intrauterine gestational sac with a yolk sac) after IVF. Continuous variables were compared using Student’s t-test or Mann–Whitney U test based on normality, while χ2 or Fisher’s exact tests were used to compare categorical variables by SDB exposure. Logistic regression assessed predictors of clinical pregnancy after adjusting for confounders. A total of 30 subjects were recruited from an academic fertility center. The overall rate of SDB was 58%. Participants with SDB had a mean AHI of 13.4 compared to 2.7 events/hr (p<0.01), were younger, and more likely to have ovulatory dysfunction. There were otherwise no significant differences in body mass index (BMI), parity, IVF cycle stimulation parameters, embryological yield, or sleep survey results. Clinical pregnancy occurred in only 38% of women with SDB vs 64% in those without (p=0.18). After adjusting for age, BMI, and ovulatory dysfunction, SDB was an independent risk factor for reduced clinical pregnancy rates (aOR 0.13, 95% CI: 0.02-0.83, p=0.03). Though SDB occurred more frequently among women with ovulatory dysfunction (88% vs 46%, p=0.04), SDB remained a risk factor for unsuccessful pregnancy after IVF, independent of underlying infertility diagnosis. Sleep disordered breathing of any severity is associated with an 87% (95% CI: 0.02-0.83) lower likelihood of clinical pregnancy after IVF.

Effect of transportation and social isolation on facial expressions of healthy horses.

Horses have the ability to generate a remarkable repertoire of facial expressions, some of which have been linked to the affective component of pain. This study describes the facial expressions in healthy horses free of pain before and during transportation and social isolation, which are putatively stressful but ordinary management procedures. Transportation was performed in 28 horses by subjecting them to short-term road transport in a horse trailer. A subgroup (n = 10) of these horses was also subjected to short-term social isolation. During all procedures, a body-mounted, remote-controlled heart rate monitor provided continuous heart rate measurements. The horses’ heads were video-recorded during the interventions. An exhaustive dataset was generated from the selected video clips of all possible facial action units and action descriptors, time of emergency, duration, and frequency according to the Equine Facial Action Coding System (EquiFACS). Heart rate increased during both interventions (p<0.01), confirming that they caused disruption in sympato-vagal balance. Using the current method for ascribing certain action units (AUs) to specific emotional states in humans and a novel data-driven co-occurrence method, the following facial traits were observed during both interventions: eye white increase (p<0.001), nostril dilator (p<0.001), upper eyelid raiser (p<0.001), inner brow raiser (p = 0.042), tongue show (p<0.001). Increases in ‘ear flicker’ (p<0.001) and blink frequency (p<0.001) were also seen. These facial actions were used to train a machine-learning classifier to discriminate between the high-arousal interventions and calm horses, which achieved at most 79% accuracy. Most facial features identified correspond well with previous findings on behaviors of stressed horses, for example flared nostrils, repetitive mouth behaviors, increased eye white, tongue show, and ear movements. Several features identified in this study of pain-free horses, such as dilated nostrils, eye white increase, and inner brow raiser, are used as indicators of pain in some face-based pain assessment tools. In order to increase performance parameters in pain assessment tools, the relations between facial expressions of stress and pain should be studied further.

Measurement of Heart Rate Using the Polar OH1 and Fitbit Charge 3 Wearable Devices in Healthy Adults During Light, Moderate, Vigorous, and Sprint-Based Exercise: Validation Study.

BackgroundAccurate, continuous heart rate measurements are important for health assessment, physical activity, and sporting performance, and the integration of heart rate measurements into wearable devices has extended its accessibility. Although the use of photoplethysmography technology is not new, the available data relating to the validity of measurement are limited, and the range of activities being performed is often restricted to one exercise domain and/or limited intensities.ObjectiveThe primary objective of this study was to assess the validity of the Polar OH1 and Fitbit Charge 3 devices for measuring heart rate during rest, light, moderate, vigorous, and sprint-type exercise.MethodsA total of 20 healthy adults (9 female; height: mean 1.73 [SD 0.1] m; body mass: mean 71.6 [SD 11.0] kg; and age: mean 40 [SD 10] years) volunteered and provided written informed consent to participate in the study consisting of 2 trials. Trial 1 was split into 3 components: 15-minute sedentary activities, 10-minute cycling on a bicycle ergometer, and incremental exercise test to exhaustion on a motorized treadmill (18-42 minutes). Trial 2 was split into 2 components: 4 × 15-second maximal sprints on a cycle ergometer and 4 × 30- to 50-m sprints on a nonmotorized resistance treadmill. Data from the 3 devices were time-aligned, and the validity of Polar OH1 and Fitbit Charge 3 was assessed against Polar H10 (criterion device). Validity was evaluated using the Bland and Altman analysis, Pearson moment correlation coefficient, and mean absolute percentage error.ResultsOverall, there was a very good correlation between the Polar OH1 and Polar H10 devices (r=0.95), with a mean bias of −1 beats·min-1 and limits of agreement of −20 to 19 beats·min-1. The Fitbit Charge 3 device underestimated heart rate by 7 beats·min-1 compared with Polar H10, with a limit of agreement of −46 to 33 beats·min-1 and poor correlation (r=0.8). The mean absolute percentage error for both devices was deemed acceptable (<5%). Polar OH1 performed well across each phase of trial 1; however, validity was worse for trial 2 activities. Fitbit Charge 3 performed well only during rest and nonsprint-based treadmill activities.ConclusionsCompared with our criterion device, Polar OH1 was accurate at assessing heart rate, but the accuracy of Fitbit Charge 3 was generally poor. Polar OH1 performed worse during trial 2 compared with the activities in trial 1, and the validity of the Fitbit Charge 3 device was particularly poor during our cycling exercises.

A single chip PPG sensor with enhanced IR sensitivity for low power and small size

A single chip Photoplethysmography(PPG) sensor was developed for continuous measurements of heart rate from a mobile device. In order to utilize it in various mobile applications, it was necessary to achieve low power and small size of PPG sensors. For low power and small chip size of the PPG sensor, a photodiode(PD) for sensing signals and an analog front end(AFE) for signal amplification and ADC should be implemented in a single chip. The single chip PPG sensor which is implemented on a standard CMOS process with low operating voltage could be more suitable for mobile devices. In order to operate at a low voltage, reduction of Si thickness is required, and for this, high quantum efficiency(QE) of 43% at 940nm were obtained at 3um thickness by back side trench(BST) pattern and ARL optimization. In addition, to improve the performance of the PPG sensor, the leakage current of &lt;0.1nA and capacitance of &lt;200pF were measured by 20um pixel array. As a result, the low-power, small size single-chip PPG sensor showed similar performance to conventional high-voltage and large PPG sensor.

Remote Heart Rate Measurement From Near-Infrared Videos Based on Joint Blind Source Separation With Delay-Coordinate Transformation

Noncontact and low-cost heart rate (HR) measurement based on imaging photoplethysmography (iPPG) technology is commonly desired for health care monitoring. However, the usually employed red-green-blue (RGB) cameras are sensitive to illumination variations and cannot work under dark situations. In this study, we propose a novel framework of applying joint blind source separation with delay-coordinate transformation (DCT-JBSS) to evaluate HR from a single-channel near-infrared (NIR) camera in dark situation. First, three facial regions of interest (ROIs) are determined by face detection technique and a single-channel signal is constructed through a frame-by-frame pixel averaging within each ROI. Second, each single-channel signal is transformed into time-delayed multichannel signal through DCT and then treated as a separate ROI signal set. Third, the three ROI signal sets are simultaneously processed by JBSS to derive the underlying shared HR source component vector (SCV), which is usually ordered the first and has the highest correlation across each signal set. Finally, the fast Fourier transform (FFT) is applied to the HR SCV and the corresponding dominant frequency (within the range from 0.7 to 2.5 Hz) with the highest signal-to-noise ratio (SNR) is determined as the target HR frequency. The proposed framework, as well as several other typical iPPG methods, is validated on public DROZY and MR-NIRP databases. The proposed method achieves the best performance, providing a probable way to widen the application of remote and continuous HR measurement during night conditions.

Validity of simplified, calibration-less exercise intensity measurement using resting heart rate during sleep: a method-comparison study with respiratory gas analysis

BackgroundThe recent development of wearable devices has enabled easy and continuous measurement of heart rate (HR). Exercise intensity can be calculated from HR with indices such as percent HR reserve (%HRR); however, this requires an accurate measurement of resting HR, which can be time-consuming. The use of HR during sleep may be a substitute that considers the calibration-less measurement of %HRR. This study examined the validity of %HRR on resting HR during sleep in comparison to percent oxygen consumption reserve (%VO2R) as a gold standard. Additionally, a 24/7%HRR measurement using this method is demonstrated.MethodsTwelve healthy adults aged 29 ± 5 years underwent treadmill testing using the Bruce protocol and a 6-min walk test (6MWT). The %VO2R during each test was calculated according to a standard protocol. The %HRR during each exercise test was calculated either from resting HR in a sitting position (%HRRsitting), when lying awake (%HRRlying), or during sleep (%HRRsleeping). Differences between %VO2R and %HRR values were examined using Bland-Altman plots. A 180-day, 24/7%HRR measurement with three healthy adults was also conducted. The %HRR values during working days and holidays were compared.ResultsIn the treadmill testing, the mean difference between %VO2R and %HRRsleeping was 1.7% (95% confidence interval [CI], − 0.2 to 3.6%). The %HRRsitting and %HRRlying values were 10.8% (95% CI, 8.8 to 12.7%) and 7.7% (95% CI, 5.4 to 9.9%), respectively. In the 6MWT, mean differences between %VO2R and %HRRsitting, %HRRlying and %HRRsleeping were 12.7% (95% CI, 10.0 to 15.5%), 7.0% (95% CI, 4.0 to 10.0%) and − 2.9% (95% CI, − 5.0% to − 0.7%), respectively. The 180-day, 24/7%HRR measurement presented significant differences in %HRR patterns between working days and holidays in all three participants.ConclusionsThe results suggest %HRRsleeping is valid in comparison to %VO2R. The results may encourage a calibration-less, 24/7 measurement model of exercise intensity using wearable devices.Trial registrationUMIN000034967.Registered 21 November 2018 (retrospectively registered).

Noncontact Measurement of Autonomic Nervous System Activities Based on Heart Rate Variability Using Ultra-Wideband Array Radar

The noncontact measurement of vital signs using ultra-wideband radar has been attracting increasing attention because it can unobtrusively provide information about the physical and mental condition of people. In particular, the continuous measurement of a person's time-varying instantaneous heart rate can estimate the activity level of the autonomic nervous system without the person wearing any sensors. Continuous heart rate measurement using radar is, however, a difficult task because accuracy is compromised by numerous factors, such as the posture and motion of the target person. In this study, we introduce techniques for increasing the accuracy and reliability of the noncontact measurement of heart rate variability. We demonstrate the performance of the proposed techniques by applying them to radar measurement data from a sleeping person, and we also compare its accuracy with electrocardiogram data.

Recreational Basketball Small-Sided Games Elicit High-Intensity Exercise With Low Perceptual Demand.

Stojanović, E, Stojiljković, N, Stanković, R, Scanlan, AT, Dalbo, VJ, and Milanović, Z. Recreational basketball small-sided games elicit high-intensity exercise with low perceptual demand. J Strength Cond Res 35(11): 3151-3157, 2021-The purpose of this study was to describe and compare the internal and external load imposed on players during 1-a-side, 2-a-side, and 3-a-side recreational basketball small-sided games (SSGs). Twelve recreationally active, male college students were monitored across 10 minutes of 1-a-side, 2-a-side, and 3-a-side basketball SSG. Internal load variables included continuous measurement of heart rate (HR) responses, as well as rating of perceived exertion (RPE) and blood lactate concentration (BLa), after each game. External load variables included measurement of the total distance covered as well as the frequency of accelerations and decelerations. Blood lactate concentration and RPE were moderately (p < 0.05) greater in 1-a-side SSG than 3-a-side SSG. Total accelerations and decelerations were higher in 1-a-side and 2-a-side SSG compared with 3-a-side SSG (p < 0.05, moderate-large). All SSG formats resulted in players spending more time (p < 0.05, moderate-large) at higher HR intensities (81-100% HRmax) than lower intensities (≤80% HRmax). Furthermore, players covered greater distances (p < 0.05, large-very large) at lower intensities (0-12 km·h-1) and completed more accelerations and decelerations (p < 0.05, large-very large) at lower intensities (<2 m·s-2) than at higher intensities across SSG formats. Basketball SSG consisting of 1-3 players elicits an intermittent activity profile, promoting the extensive utilization of anaerobic and aerobic metabolism pathways, which potentially can lead to marked improvements in cardiovascular and musculoskeletal fitness in the general population when administered in recreational settings. Moreover, recreational basketball SSG with only 1 player per team elicits higher BLa, RPE, distances covered at low speeds as well as acceleration and deceleration volumes than SSG with 3 players per team.