The Accuracy of Wrist-Worn Photoplethysmogram-Measured Heart and Respiratory Rates in Abdominal Surgery Patients: Observational Prospective Clinical Validation Study

BACKGROUND

Postoperative deterioration is often preceded by abnormal vital parameters. Therefore, vital parameters of postoperative patients are routinely measured by nursing staff. Wrist-worn sensors could potentially provide an alternative tool for the measurement of vital parameters in low-acuity settings. These devices would allow more frequent or even continuous measurements of vital parameters without relying on time-consuming manual measurements, provided their accuracy in this clinical population is established.

OBJECTIVE

This study aimed to assess the accuracy of heart rate (HR) and respiratory rate (RR) measures obtained via a wearable photoplethysmography (PPG) wristband in a cohort of postoperative patients.

METHODS

The accuracy of the wrist-worn PPG sensor was assessed in 62 post-abdominal surgery patients (mean age 55, SD 15 years; median BMI 34, IQR 25-40 kg/m²). The wearable obtained HR and RR measurements were compared to those of the reference monitor in the postanesthesia or intensive care unit. Bland-Altman and Clarke error grid analyses were performed to determine agreement and clinical accuracy.

RESULTS

Data were collected for a median of 1.2 hours per patient. With a coverage of 94% for HR and 34% for RR, the device was able to provide accurate measurements for the large majority of the measurements as 98% and 93% of the measurements were within 5 bpm or 3 rpm of the reference signal. Additionally, 100% of the HR and 98% of the RR measurements were clinically acceptable on Clarke error grid analysis.

CONCLUSIONS

The wrist-worn PPG device is able to provide measurements of HR and RR that can be seen as sufficiently accurate for clinical applications. Considering the coverage, the device was able to continuously monitor HR and report RR when measurements of sufficient quality were obtained.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03923127; https://www.clinicaltrials.gov/ct2/show/NCT03923127.

Fatigue after neurosurgery in patients with a brain tumor: The role of autonomic dysregulation and disturbed sleep

Background Fatigue is prevalent in patients with a brain tumor and high levels of fatigue persist after neurosurgical tumor resection. The underlying mechanisms are insufficiently understood and this study examines the role of autonomic nervous system dysregulation and objective sleep characteristics in fatigue among post-surgical patients. Methods Patients undergoing craniotomy (N = 52; age 52.1 ± 15.0 years; 44% women) were evaluated at 3 months after surgery (median = 86 days). Fatigue was measured using the Multidimensional Fatigue Inventory. Autonomic nervous system indices were based on 24-h heart rate variability (HRV) analysis. Sleep parameters were measured using actigraphy: total sleep duration, efficiency, onset latency and wake after sleep onset (WASO). Data analyses of this cross-sectional study included correlation and multiple regression analysis. Results Fatigue scores were significantly elevated in tumor resection patients compared to healthy reference norms (p's < 0.05) with no differences between patients with glioma (N = 32) versus meningioma (N = 20). Associations between HRV indices and fatigue were non-significant (r values <0.16, p values > 0.25). Sleep duration was associated with physical fatigue (r = 0.35, p = 0.02), whereas WASO was associated with mental fatigue levels (r = 0.40, p = 0.006). Disturbed sleep measures were associated with HRV indices of reduced parasympathetic nervous system activity in glioma patients but not in meningioma patients. Conclusions Multiple nocturnal awakenings may result in mental fatigue and longer sleep time was associated with physical fatigue, which may reflect compensatory sleep patterns. Future intervention studies addressing sleep quality may be beneficial in treating fatigue in patients following neurosurgery for tumor resection.

Cardiorespiratory fitness estimation from heart rate and body movement in daily life

Low cardiorespiratory fitness (CRF) increases risk of all-cause mortality and cardiovascular events. Periodic CRF assessment can have an important preventive function. The objective of this study was to develop a protocol-free method to estimate CRF in daily life based on heart rate (HR) and body acceleration measurements. Acceleration and HR data were collected from 37 subjects (men = 49%) while they performed a standardized laboratory activity protocol (sitting, walking, running, cycling) and during a 5-day free-living monitoring period. CRF was determined by oxygen uptake (V̇o_2max) during maximal exercise testing. A doubly labeled water-validated equation was used to predict total energy expenditure (TEE) from acceleration data. A fitness index was defined as the ratio between TEE and HR (TEE-pulse). Activity recognition techniques were used to process acceleration features and classify sedentary, ambulatory, and other activity types. Regression equations based on TEE-pulse data from each activity type were developed to predict V̇o_2max. TEE-pulse measured within each activity type of the laboratory protocol was highly correlated with V̇o_2max (r from 0.74-0.91). Averaging the outcome of each activity-type specific equation based on TEE-pulse from the laboratory data led to accurate estimates of V̇o_2max [root mean square error (RMSE): 300 mL O₂/min, or 10%]. The difference between laboratory and free-living determined TEE-pulse was 3.7 ± 11% (r = 0.85). The prediction method preserved the prediction accuracy when applied to free-living data (RMSE: 367 mL O₂/min, or 12%). Measurements of body acceleration and HR can be used to predict V̇o_2max in daily life. Activity-specific prediction equations are needed to achieve highly accurate estimates of CRF.NEW & NOTEWORTHY This is among the very few studies validating, in free-living conditions, a method to estimate cardiorespiratory fitness using heart rate and body acceleration data. A novel parameter called TEE-pulse, which was defined as the ratio between accelerometer-determined energy expenditure and heart rate, was highly correlated with maximal oxygen uptake (V̇o_2max). Activity classification and the use of activity-selective prediction equations outperformed previously published methods for estimating V̇o_2max from heart rate and acceleration data.

Detecting Atrial Fibrillation and Atrial Flutter in Daily Life Using Photoplethysmography Data

OBJECTIVE

Photoplethysmography (PPG) enables unobtrusive heart rate monitoring, which can be used in wrist-worn applications. Its potential for detecting atrial fibrillation (AF) has been recently presented. Besides AF, another cardiac arrhythmia increasing stroke risk and requiring treatment is atrial flutter (AFL). Currently, the knowledge about AFL detection with PPG is limited. The objective of our study was to develop a model that classifies AF, AFL, and sinus rhythm with or without premature beats from PPG and acceleration data measured at the wrist in daily life.

METHODS

A dataset of 40 patients was collected by measuring PPG and accelerometer data, as well as electrocardiogram as a reference, during 24-hour monitoring. The dataset was split into 75%-25% for training and testing a Random Forest (RF) model, which combines features from PPG, inter-pulse intervals (IPI), and accelerometer data, to classify AF, AFL, and other rhythms. The performance was compared to an AF detection algorithm combining traditional IPI features for determining the robustness of the accuracy in presence of AFL.

RESULTS

The RF model classified AF/AFL/other with sensitivity and specificity of 97.6/84.5/98.1% and 98.2/99.7/92.8%, respectively. The results with the IPI-based AF classifier showed that the majority of false detections were caused by AFL.

CONCLUSION

The PPG signal contains information to classify AFL in the presence of AF, sinus rhythm, or sinus rhythm with premature contractions.

SIGNIFICANCE

PPG could indicate presence of AFL, not only AF.

The cardinal exercise stopper: Muscle fatigue, muscle pain or perception of effort?

The capacity to sustain high-intensity aerobic exercise is essential for endurance performance. Therefore, it is important to understand what is the factor limiting time to exhaustion (TTE) in healthy and fit adults. In Study 1, maximal voluntary cycling power (MVCP) was measured in 11 volunteers before and immediately after a high-intensity TTE test on cycle ergometer. Cadence was 60 rpm in both the MVCP and TTE tests. Despite a 35% loss in MVCP, power produced during the final MVCP test (mean ± SD 469 ± 111 W) was significantly higher than the power required by the TTE test (269 ± 55 W) (P < 0.001). In Study 2, 12 participants performed a cold pressor test (CPT) to the limit of tolerance followed by a high-intensity TTE test on cycle ergometer. Ratings of pain unpleasantness (RPU) during the TTE test were anchored to the unpleasantness of pain experienced during the CPT. On average, the RPU was 9.7 ± 0.4 at completion of the CPT and 5.0 ± 0.9 at exhaustion during the TTE test. The difference between these two ratings of pain unpleasantness was statistically significant (P < 0.001). In both Studies 1 and 2, the slope of the rating of perceived exertion (RPE) during the TTE test correlated significantly with TTE (r = -0.75 and -0.83, P < 0.01). Results of this two-part investigation suggest that perception of effort, rather than severe locomotor muscle fatigue or intolerably unpleasant muscle pain, is the cardinal exercise stopper during high-intensity aerobic exercise.

Comparison between electrocardiogram- and photoplethysmogram-derived features for atrial fibrillation detection in free-living conditions

OBJECTIVE

Atrial fibrillation (AF) is the most commonly experienced arrhythmia and it increases the risk of stroke and heart failure. The challenge in detecting the presence of AF is the occasional and asymptomatic manifestation of the condition. Long-term monitoring can increase the sensitivity of detecting intermittent AF episodes, however it is either cumbersome or invasive and costly with electrocardiography (ECG). Photoplethysmography (PPG) is an unobtrusive measuring modality enabling heart rate monitoring, and promising results have been presented in detecting AF. However, there is still limited knowledge about the applicability of the PPG solutions in free-living conditions. The aim of this study was to compare the inter-beat interval derived features for AF detection between ECG and wrist-worn PPG in daily life.

APPROACH

The data consisted of 24 h ECG, PPG, and accelerometer measurements from 27 patients (eight AF, 19 non-AF). In total, seven features (Shannon entropy, root mean square of successive differences (RMSSD), normalized RMSSD, pNN40, pNN70, sample entropy, and coefficient of sample entropy (CosEn)) were compared. Body movement was measured with the accelerometer and used with three different thresholds to exclude PPG segments affected by movement.

MAIN RESULTS

CosEn resulted as the best performing feature from ECG with Cohens kappa 0.95. When the strictest movement threshold was applied, the same performance was obtained with PPG (kappa  =  0.96). In addition, pNN40 and pNN70 reached similar results with the same threshold (kappa  =  0.95 and 0.94), but were more robust with respect to movement artefacts. The coverage of PPG was 24.0%-57.6% depending on the movement threshold compared to 92.1% of ECG.

SIGNIFICANCE

The inter-beat interval features derived from PPG are equivalent to the ones from ECG for AF detection. Movement artefacts substantially worsen PPG-based AF monitoring in free-living conditions, therefore monitoring coverage needs to be carefully selected. Wrist-worn PPG still provides a promising technology for long-term AF monitoring.

Atrial Fibrillation Detection Using a Novel Cardiac Ambulatory Monitor Based on Photo-Plethysmography at the Wrist

Background Long-term continuous cardiac monitoring would aid in the early diagnosis and management of atrial fibrillation ( AF ). This study examined the accuracy of a novel approach for AF detection using photo-plethysmography signals measured from a wrist-based wearable device. Methods and Results ECG and contemporaneous pulse data were collected from 2 cohorts of AF patients: AF patients (n=20) undergoing electrical cardioversion ( ECV ) and AF patients (n=40) that were prescribed for 24 hours ECG Holter in outpatient settings ( HOL ). Photo-plethysmography and acceleration data were collected at the wrist and processed to determine the inter-pulse interval and discard inter-pulse intervals in presence of motion artifacts. A Markov model was deployed to assess the probability of AF given irregular pattern in inter-pulse interval sequences. The AF detection algorithm was evaluated against clinical rhythm annotations of AF based on ECG interpretation. Photo-plethysmography recordings from apparently healthy volunteers (n=120) were used to establish the false positive AF detection rate of the algorithm. A total of 42 and 855 hours (AF: 21 and 323 hours) of photo-plethysmography data were recorded in the ECV and HOL cohorts, respectively. AF was detected with >96% accuracy ( ECV, sensitivity=97%; HOL , sensitivity=93%; both with specificity=100%). Because of motion artifacts, the algorithm did not provide AF classification for 44±16% of the monitoring period in the HOL group. In healthy controls, the algorithm demonstrated a <0.2% false positive AF detection rate. Conclusions A novel AF detection algorithm using pulse data from a wrist-wearable device can accurately discriminate rhythm irregularities caused by AF from normal rhythm.

Cortical substrates of the effects of caffeine and time-on-task on perception of effort

Caffeine intake results in a decrease in perception of effort, but the cortical substrates of this perceptual effect of caffeine are unknown. The aim of this randomized counterbalanced double-blind crossover study was to investigate the effect of caffeine on the motor-related cortical potential (MRCP) and its relationship with rating of perceived effort (RPE). We also investigated whether MRCP is associated with the increase in RPE occurring over time during submaximal exercise. Twelve healthy female volunteers performed 100 intermittent isometric knee extensions at 61 ± 5% of their maximal torque 1.5 h after either caffeine (6 mg/kg) or placebo ingestion, while RPE, vastus lateralis electromyogram (EMG), and MRCP were recorded. RPE and MRCP amplitude at the vertex during the first contraction epoch (0–1 s) were significantly lower after caffeine ingestion compared with placebo ( P < 0.05) and were significantly higher during the second half of the submaximal intermittent isometric knee-extension protocol compared with the first half ( P < 0.05). No significant effects of caffeine and time-on-task were found for EMG amplitude and submaximal force output variables. The covariation between MRCP and RPE across both caffeine and time-on-task ( r10 = −0.335, P < 0.05) provides evidence in favor of the theory that perception of effort arises from neurocognitive processing of corollary discharges from premotor and motor areas of the cortex. Caffeine seems to reduce perception of effort through a reduction in the activity of cortical premotor and motor areas necessary to produce a submaximal force, and time-on-task has the opposite effect.

Estimation of maximal oxygen uptake via submaximal exercise testing in sports, clinical, and home settings

Assessment of the functional capacity of the cardiovascular system is essential in sports medicine. For athletes, the maximal oxygen uptake [Formula: see text] provides valuable information about their aerobic power. In the clinical setting, the (VO(2max)) provides important diagnostic and prognostic information in several clinical populations, such as patients with coronary artery disease or heart failure. Likewise, VO(2max) assessment can be very important to evaluate fitness in asymptomatic adults. Although direct determination of [VO(2max) is the most accurate method, it requires a maximal level of exertion, which brings a higher risk of adverse events in individuals with an intermediate to high risk of cardiovascular problems. Estimation of VO(2max) during submaximal exercise testing can offer a precious alternative. Over the past decades, many protocols have been developed for this purpose. The present review gives an overview of these submaximal protocols and aims to facilitate appropriate test selection in sports, clinical, and home settings. Several factors must be considered when selecting a protocol: (i) The population being tested and its specific needs in terms of safety, supervision, and accuracy and repeatability of the VO(2max) estimation. (ii) The parameters upon which the prediction is based (e.g. heart rate, power output, rating of perceived exertion [RPE]), as well as the need for additional clinically relevant parameters (e.g. blood pressure, ECG). (iii) The appropriate test modality that should meet the above-mentioned requirements should also be in line with the functional mobility of the target population, and depends on the available equipment. In the sports setting, high repeatability is crucial to track training-induced seasonal changes. In the clinical setting, special attention must be paid to the test modality, because multiple physiological parameters often need to be measured during test execution. When estimating VO(2max), one has to be aware of the effects of medication on heart rate-based submaximal protocols. In the home setting, the submaximal protocols need to be accessible to users with a broad range of characteristics in terms of age, equipment, time available, and an absence of supervision. In this setting, the smart use of sensors such as accelerometers and heart rate monitors will result in protocol-free VO(2max) assessments. In conclusion, the need for a low-risk, low-cost, low-supervision, and objective evaluation of VO(2max) has brought about the development and the validation of a large number of submaximal exercise tests. It is of paramount importance to use these tests in the right context (sports, clinical, home), to consider the population in which they were developed, and to be aware of their limitations.

The face of effort: frowning muscle activity reflects effort during a physical task

It is a common observation that exertion of effort is associated with a specific facial expression. However, this facial expression has never been quantified during physical tasks and its relationship with effort is unknown. The aims of the present study were to measure frowning muscle activity during a physical task with electromyography (EMG) and to investigate the relationship between facial EMG and effort. Effort was experimentally manipulated by increasing task difficulty and inducing muscle weakness. Twenty men performed leg extensions with four relative workloads. The fatigue group (n=10) repeated the leg extensions after fatiguing eccentric exercise, and the control group repeated just the leg extensions. Facial EMG amplitude, ratings of perceived effort (RPE), and leg EMG amplitude increased significantly with increasing task difficulty and with muscle fatigue. Facial EMG, RPE, and leg EMG all correlated significantly. The results suggest that frowning muscle activity reflects effort during physical tasks.

Locomotor muscle fatigue increases cardiorespiratory responses and reduces performance during intense cycling exercise independently from metabolic stress

Locomotor muscle fatigue, defined as an exercise-induced reduction in maximal voluntary force, occurs during prolonged exercise, but its effects on cardiorespiratory responses and exercise performance are unknown. In this investigation, a significant reduction in locomotor muscle force (−18%, P < 0.05) was isolated from the metabolic stress usually associated with fatiguing exercise using a 100-drop-jumps protocol consisting of one jump every 20 s from a 40-cm-high platform. The effect of this treatment on time to exhaustion during high-intensity constant-power cycling was measured in study 1 ( n = 10). In study 2 ( n = 14), test duration (871 ± 280 s) was matched between fatigue and control condition (rest). In study 1, locomotor muscle fatigue caused a significant curtailment in time to exhaustion (636 ± 278 s) compared with control (750 ± 281 s) ( P = 0.003) and increased cardiac output. Breathing frequency was significantly higher in the fatigue condition in both studies despite similar oxygen consumption and blood lactate accumulation. In study 2, high-intensity cycling did not induce further fatigue to eccentrically-fatigued locomotor muscles. In both studies, there was a significant increase in heart rate in the fatigue condition, and perceived exertion was significantly increased in study 2 compared with control. These results suggest that locomotor muscle fatigue has a significant influence on cardiorespiratory responses and exercise performance during high-intensity cycling independently from metabolic stress. These effects seem to be mediated by the increased central motor command and perception of effort required to exercise with weaker locomotor muscles.