Validity and reliability of cardiorespiratory measurements recorded by the LifeShirt during exercise tests

Development of a Miniaturized Mechanoacoustic Sensor for Continuous, Objective Cough Detection, Characterization and Physiologic Monitoring in Children With Cystic Fibrosis

Cough is an important symptom in children with acute and chronic respiratory disease. Daily cough is common in Cystic Fibrosis (CF) and increased cough is a symptom of pulmonary exacerbation. To date, cough assessment is primarily subjective in clinical practice and research. Attempts to develop objective, automatic cough counting tools have faced reliability issues in noisy environments and practical barriers limiting long-term use. This single-center pilot study evaluated usability, acceptability and performance of a mechanoacoustic sensor (MAS), previously used for cough classification in adults, in 36 children with CF over brief and multi-day periods in four cohorts. Children whose health was at baseline and who had symptoms of pulmonary exacerbation were included. We trained, validated, and deployed custom deep learning algorithms for accurate cough detection and classification from other vocalization or artifacts with an overall area under the receiver-operator characteristic curve (AUROC) of 0.96 and average precision (AP) of 0.93. Child and parent feedback led to a redesign of the MAS towards a smaller, more discreet device acceptable for daily use in children. Additional improvements optimized power efficiency and data management. The MAS's ability to objectively measure cough and other physiologic signals across clinic, hospital, and home settings is demonstrated, particularly aided by an AUROC of 0.97 and AP of 0.96 for motion artifact rejection. Examples of cough frequency and physiologic parameter correlations with participant-reported outcomes and clinical measurements for individual patients are presented. The MAS is a promising tool in objective longitudinal evaluation of cough in children with CF.

Publication guidelines for human heart rate and heart rate variability studies in psychophysiology-Part 1: Physiological underpinnings and foundations of measurement

This Committee Report provides methodological, interpretive, and reporting guidance for researchers who use measures of heart rate (HR) and heart rate variability (HRV) in psychophysiological research. We provide brief summaries of best practices in measuring HR and HRV via electrocardiographic and photoplethysmographic signals in laboratory, field (ambulatory), and brain-imaging contexts to address research questions incorporating measures of HR and HRV. The Report emphasizes evidence for the strengths and weaknesses of different recording and derivation methods for measures of HR and HRV. Along with this guidance, the Report reviews what is known about the origin of the heartbeat and its neural control, including factors that produce and influence HRV metrics. The Report concludes with checklists to guide authors in study design and analysis considerations, as well as guidance on the reporting of key methodological details and characteristics of the samples under study. It is expected that rigorous and transparent recording and reporting of HR and HRV measures will strengthen inferences across the many applications of these metrics in psychophysiology. The prior Committee Reports on HR and HRV are several decades old. Since their appearance, technologies for human cardiac and vascular monitoring in laboratory and daily life (i.e., ambulatory) contexts have greatly expanded. This Committee Report was prepared for the Society for Psychophysiological Research to provide updated methodological and interpretive guidance, as well as to summarize best practices for reporting HR and HRV studies in humans.

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

Background

Continuous 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.

Objective

The 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.

Methods

Volunteers 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).

Results

A 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.

Conclusions

Data 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.

Telemonitoring Techniques for Lung Volume Measurement: Accuracy, Artifacts and Effort

Telemonitoring becomes more important in pulmonary research. It can be used to decrease the pressure on the health care system, to lower the costs of health care and to increase quality of life of patients. Previous studies show contradictory results regarding the effectiveness of telemonitoring. According to multiple researchers, inefficiency can be a result of poor study design, low data quality and usability issues. To counteract these issues, this review proves for an in-depth explanation of four (potential) telemonitoring systems in terms of work principle, accuracy, disturbing factors and usability. The evaluated systems are portable spirometry/breath-by-breath analyzers, respiratory inductance and magnetic plethysmography and electrical impedance tomography. These insights can be used to select the optimal technique for a specific purpose in future studies.

Wearable Respiration Monitoring: Interpretable Inference With Context and Sensor Biomarkers

Continuous monitoring of breathing rate (BR), minute ventilation (VE), and other respiratory parameters could transform care for and empower patients with chronic cardio-pulmonary conditions, such as asthma. However, the clinical standard for measuring respiration, namely Spirometry, is hardly suitable for continuous use. Wearables can track many physiological signals, like ECG and motion, yet respiration tracking faces many challenges. In this work, we infer respiratory parameters from wearable ECG and wrist motion signals. We propose a modular and generalizable classification-regression pipeline to utilize available context information, such as physical activity, in learning context-conditioned inference models. Novel morphological and power domain features from the wearable ECG are extracted to use with these models. Exploratory feature selection methods are incorporated in this pipeline to discover application-driven interpretable biomarkers. Using data from 15 subjects, we evaluate two implementations of the proposed inference pipeline: for BR and VE. Each implementation compares generalized linear model, random forest, support vector machine, Gaussian process regression, and neighborhood component analysis as regression models. Permutation, regularization, and relevance determination methods are used to rank the ECG features to identify robust ECG biomarkers across models and activities. This work demonstrates the potential of wearable sensors not only in continuous monitoring, but also in designing biomarker-driven preventive measures.

Feasibility Assessment of Wearable Respiratory Monitors for Ambulatory Inhalation Topography

Background: Natural environment inhalation topography provides useful information for toxicant exposure, risk assessment and cardiopulmonary performance. Commercially available wearable respiratory monitors (WRMs), which are currently used to measure a variety of physiological parameters such as heart rate and breathing frequency, can be leveraged to obtain inhalation topography, yet little work has been done. This paper assesses the feasibility of adapting these WRMs for measuring inhalation topography. Methods: Commercially available WRMs were compiled and assessed for the ability to report chest motion, data analysis software features, ambulatory observation capabilities, participant acceptability, purchasing constraints and affordability. Results: The following WRMs were found: LifeShirt, Equivital EQ02 LifeMonitor, Smartex WWS, Hexoskin Smart Garment, Zephyr BioHarness, Nox T3&A1, BioRadio, SleepSense Inductance Band, and ezRIP & zRIP Durabelt. None of the WRMs satisfied all six assessment criteria in a manner enabling them to be used for inhalation topography without modification and development. Conclusions: The results indicate that there are WRMs with core technologies and characteristics that can be built upon for ambulatory inhalation topography measurement in the NE.

Laboratory Validation of Hexoskin Biometric Shirt at Rest, Submaximal Exercise, and Maximal Exercise While Riding a Stationary Bicycle

OBJECTIVE

Evaluate Hexoskin performance on a stationary bike against "gold standard" laboratory equipment and develop adjustment models for future use in field settings.

METHODS

Compared respiratory rate (RR), tidal volume (VT), minute ventilation (VE), and heart rate (HR) measured by the Hexoskin shirt to simultaneous spirometry and full 12-lead electrocardiogram during a laboratory based incremental exercise test on a stationary bicycle.

RESULTS

Data from 17 participants demonstrated Hexoskin VT and VE had the best agreement in the submaximal exercise level (discrepancies less than or equal to 5.3%) with larger discrepancies observed at rest (less than or equal to 15.3%) and at maximal exercise level (less than or equal to 11.7%). The discrepancies for HR and RR were lower at all levels (less than 10%). Adjusting for sex and body weight allowed for a single VE algorithm across the entire range of effort (r = 0.89).

CONCLUSION

These discrepancies are acceptable for field use in comparison to the ranges typical of bicycle commuting.

Inferring Respiratory Minute Volume from Wrist Motion

Exposure to air pollutants poses major health risk for patients with chronic pulmonary diseases such as asthma, bronchitis, and emphysema. Such risk can be mitigated by continuous exposure tracking. The effective dose of exposure is directly proportional to the respiratory minute volume, aka minute ventilation (VE). Till date, the clinical standard for measuring VE is Spirometry, a highly invasive and cumbersome modality, which is not suitable for continuous day-to-day use. This paper presents a novel non-invasive method toward continuous assessment of VE using a wrist-mount wearable motion sensor. Data from 25 healthy subjects were collected while they performed ambulatory and sedentary activities and physical exercises. Noise and artifacts of the motion signal are removed and the processed signal is used to extract explanatory features. The features are used to train and evaluate multiple regression models, among which, the probabilistic Gaussian process regression achieves the best performance in inferring VE from the wearable motion signal. The effects of inter- and intra-personal variations are explored to demonstrate the potential of the proposed method for continuously monitoring pollutant exposure risk in respiratory health applications.

Smart Shirts for Monitoring Physiological Parameters: Scoping Review

BACKGROUND

The recent trends of technological innovation and widescale digitization as potential solutions to challenges in health care, sports, and emergency service operations have led to the conception of smart textile technology. In health care, these smart textile systems present the potential to aid preventative medicine and early diagnosis through continuous, noninvasive tracking of physical and mental health while promoting proactive involvement of patients in their medical management. In areas such as sports and emergency response, the potential to provide comprehensive and simultaneous physiological insights across multiple body systems is promising. However, it is currently unclear what type of evidence exists surrounding the use of smart textiles for the monitoring of physiological outcome measures across different settings.

OBJECTIVE

This scoping review aimed to systematically survey the existing body of scientific literature surrounding smart textiles in their most prevalent form, the smart shirt, for monitoring physiological outcome measures.

METHODS

A total of 5 electronic bibliographic databases were systematically searched (Ovid Medical Literature Analysis and Retrieval System Online, Excerpta Medica database, Scopus, Cumulative Index to Nursing and Allied Health Literature, and SPORTDiscus). Publications from the inception of the database to June 24, 2019 were reviewed. Nonindexed literature relevant to this review was also systematically searched. The results were then collated, summarized, and reported.

RESULTS

Following the removal of duplicates, 7871 citations were identified. On the basis of title and abstract screening, 7632 citations were excluded, whereas 239 were retrieved and assessed for eligibility. Of these, 101 citations were included in the final analysis. Included studies were categorized into four themes: (1) prototype design, (2) validation, (3) observational, and (4) reviews. Among the 101 analyzed studies, prototype design was the most prevalent theme (50/101, 49.5%), followed by validation (29/101, 28.7%), observational studies (21/101, 20.8%), and reviews (1/101, 0.1%). Presented prototype designs ranged from those capable of monitoring one physiological metric to those capable of monitoring several simultaneously. In 29 validation studies, 16 distinct smart shirts were validated against reference technology under various conditions and work rates, including rest, submaximal exercise, and maximal exercise. The identified observational studies used smart shirts in clinical, healthy, and occupational populations for aims such as early diagnosis and stress detection. One scoping review was identified, investigating the use of smart shirts for electrocardiograph signal monitoring in cardiac patients.

CONCLUSIONS

Although smart shirts have been found to be valid and reliable in the monitoring of specific physiological metrics, results were variable for others, demonstrating the need for further systematic validation. Analysis of the results has also demonstrated gaps in knowledge, such as a considerable lag of validation and observational studies in comparison with prototype design and limited investigation using smart shirts in pediatric, elite sports, and emergency service populations.

Validity and Reliability of the Hexoskin Wearable Biometric Vest During Maximal Aerobic Power Testing in Elite Cyclists

Elliot, CA, Hamlin, MJ, and Lizamore, CA. Validity and reliability of the Hexoskin wearable biometric vest during maximal aerobic power testing in elite cyclists. J Strength Cond Res 33(5): 1437-1444, 2019-The purpose of this study was to investigate the validity and reliability of the Hexoskin vest for measuring respiration and heart rate (HR) in elite cyclists during a progressive test to exhaustion. Ten male elite cyclists (age 18-52 yrs, height 179.3 ± 6.0 cm, body mass 73.2 ± 9.1 kg, V[Combining Dot Above]O2max 60.7 ± 7.8 ml·kg·min, mean ± SD) conducted a maximal aerobic cycle ergometer test using a ramped protocol (starting at 100 W with 25 W increments each min to failure) during 2 separate occasions over a 3-4-day period. Compared with the criterion measure (MetaMax 3B) the Hexoskin vest showed mainly small typical errors (1.3-6.2%) for HR and breathing frequency (f), but larger typical errors (9.5-19.6%) for minute ventilation (V[Combining Dot Above]E) during the progressive test to exhaustion. The typical error indicating the reliability of the Hexoskin vest at moderate-intensity exercise between tests was small for HR (2.6-2.9%) and f (2.5-3.2%) but slightly larger for V[Combining Dot Above]E (5.3-7.9%). We conclude that the Hexoskin vest is sufficiently valid and reliable for measurements of HR and f in elite athletes during high-intensity cycling but the calculated V[Combining Dot Above]E value by the Hexoskin vest produced during such exercise should be used with caution because of the lower validity and reliability of this variable.

Training and Evaluation of Human Cardiorespiratory Endurance Based on a Fuzzy Algorithm

Cardiorespiratory endurance refers to the ability of the heart and lungs to deliver oxygen to working muscles during continuous physical activity, which is an important indicator of physical health. Cardiorespiratory endurance is typically measured in the laboratory by maximum oxygen uptake (VO_2max) which is not a practical method for real-life use. Given the relative difficulty in measuring oxygen consumption directly, we can estimate cardiorespiratory endurance on the basis of heart beat. In this paper, we proposed a fuzzy system based on the human heart rate to provide an effective cardiorespiratory endurance training program and the evaluation of cardiorespiratory endurance levels. Trainers can respond correctly with the help of a smart fitness app to obtain the desired training results and prevent undesirable events such as under-training or over-training. The fuzzy algorithm, which is built for the Android mobile phone operating system receives the resting heart rate (RHR) of the participants via Bluetooth before exercise to determine the suitable training speed mode of a treadmill for the individual. The computer-based fuzzy program takes RHR and heart rate recovery (HRR) after exercise as inputs to calculate the cardiorespiratory endurance level. The experimental results show that after 8 weeks of exercise training, the RHR decreased by an average of 11%, the HRR increased by 51.5%, and the cardiorespiratory endurance evaluation level was also improved. The proposed system can be combined with other methods for fitness instructors to design a training program that is more suitable for individuals.

Utility of a smartphone based system (cvrphone) to accurately determine apneic events from electrocardiographic signals

Background

Sleep disordered breathing manifested as sleep apnea (SA) is prevalent in the general population, and while it is associated with increased morbidity and mortality risk in some patient populations, it remains under-diagnosed. The objective of this study was to assess the accuracy of respiration-rate (RR) and tidal-volume (TV) estimation algorithms, from body-surface ECG signals, using a smartphone based ambulatory respiration monitoring system (cvrPhone).

Methods

Twelve lead ECG signals were collected using the cvrPhone from anesthetized and mechanically ventilated swine (n = 9). During ECG data acquisition, the mechanical ventilator tidal-volume (TV) was varied from 250 to 0 to 750 to 0 to 500 to 0 to 750 ml at respiratory rates (RR) of 6 and 14 breaths/min, respectively, and the RR and TV values were estimated from the ECG signals using custom algorithms.

Results

TV estimations from any two different TV settings showed statistically significant difference (p < 0.01) regardless of the RR. RRs were estimated to be 6.1±1.1 and 14.0±0.2 breaths/min at 6 and 14 breaths/min, respectively (when 250, 500 and 750 ml TV settings were combined). During apnea, the estimated TV and RR values were 11.7±54.9 ml and 0.0±3.5 breaths/min, which were significantly different (p<0.05) than TV and RR values during non-apnea breathing. In addition, the time delay from the apnea onset to the first apnea detection was 8.6±6.7 and 7.0±3.2 seconds for TV and RR respectively.

Conclusions

We have demonstrated that apnea can reliably be detected using ECG-derived RR and TV algorithms. These results support the concept that our algorithms can be utilized to detect SA in conjunction with ECG monitoring.

An IoT System for Remote Health Monitoring in Elderly Adults Through a Wearable Device and Mobile Application

With the increase in global life expectancy and the advance of technology, the creation of age-friendly environments is a priority in the design of new products for elderly people healthcare. This paper presents a proposal for a real-time health monitoring system of older adults living in geriatric residences. This system was developed to help caregivers to have a better control in monitoring the health of their patients and have closer communication with their patients’ family members. To validate the feasibility and effectiveness of this proposal, a prototype was built, using a biometric bracelet connected to a mobile application, which allows real-time visualization of all the information generated by the sensors (heart rate, body temperature, and blood oxygenation) in the bracelet. Using these data, caregivers can make decisions about the health status of their patients. The evaluation found that the users perceived the system to be easy to learn and use, providing initial evidence that our proposal could improve the quality of the adult’s healthcare.

Estimation of respiratory variables from thoracoabdominal breathing distance: a review of different techniques and calibration methods

The precise measurement of respiratory variables, such as tidal volume, minute ventilation, and respiratory rate, is necessary to monitor respiratory status, overcome several diseases, improve patient health conditions and reduce health care costs. This measurement has conventionally been performed by breathing into a mouthpiece connected to a flow rate measuring device. However, a mouthpiece can be uncomfortable for the subject and is difficult to use for long-term monitoring. Other noninvasive systems and devices have been developed that do not require a mouthpiece to quantitatively measure respiratory variables. These techniques are based on measuring size changes of the rib cage (RC) and abdomen (ABD), as lung volume is known to be a function of these variables. Among these systems, we distinguish respiratory inductive plethysmography (RIP), respiratory magnetometer plethysmography (RMP), and optoelectronic plethysmography devices. However, these devices should be previously calibrated for the correct evaluation of respiratory variables. The most popular calibration methods are isovolume manoeuvre calibration (ISOCAL), qualitative diagnostic calibration (QDC), multiple linear regression (MLR) and artificial neural networks (ANNs). The aim of this review is first to present how thoracoabdominal breathing distances can be used to estimate respiratory variables and second to present the different techniques and calibration methods used for this purpose.

Supplemental Carbon Dioxide Stabilizes the Upper Airway in Volunteers Anesthetized with Propofol

BACKGROUND

Propofol impairs upper airway dilator muscle tone and increases upper airway collapsibility. Preclinical studies show that carbon dioxide decreases propofol-mediated respiratory depression. We studied whether elevation of end-tidal carbon dioxide (PETCO2) via carbon dioxide insufflation reverses the airway collapsibility (primary hypothesis) and impaired genioglossus muscle electromyogram that accompany propofol anesthesia.

METHODS

We present a prespecified, secondary analysis of previously published experiments in 12 volunteers breathing via a high-flow respiratory circuit used to control upper airway pressure under propofol anesthesia at two levels, with the deep level titrated to suppression of motor response. Ventilation, mask pressure, negative pharyngeal pressure, upper airway closing pressure, genioglossus electromyogram, bispectral index, and change in end-expiratory lung volume were measured as a function of elevation of PETCO2 above baseline and depth of propofol anesthesia.

RESULTS

PETCO2 augmentation dose-dependently lowered upper airway closing pressure with a decrease of 3.1 cm H2O (95% CI, 2.2 to 3.9; P < 0.001) under deep anesthesia, indicating improved upper airway stability. In parallel, the phasic genioglossus electromyogram increased by 28% (23 to 34; P < 0.001). We found that genioglossus electromyogram activity was a significant modifier of the effect of PETCO2 elevation on closing pressure (P = 0.005 for interaction term).

CONCLUSIONS

Upper airway collapsibility induced by propofol anesthesia can be reversed in a dose-dependent manner by insufflation of supplemental carbon dioxide. This effect is at least partly mediated by increased genioglossus muscle activity.

Wearable and Implantable Sensors for Biomedical Applications

Mobile health technologies offer great promise for reducing healthcare costs and improving patient care. Wearable and implantable technologies are contributing to a transformation in the mobile health era in terms of improving healthcare and health outcomes and providing real-time guidance on improved health management and tracking. In this article, we review the biomedical applications of wearable and implantable medical devices and sensors, ranging from monitoring to prevention of diseases, as well as the materials used in the fabrication of these devices and the standards for wireless medical devices and mobile applications. We conclude by discussing some of the technical challenges in wearable and implantable technology and possible solutions for overcoming these difficulties.

Effectively Measuring Respiratory Flow With Portable Pressure Data Using Back Propagation Neural Network

Continuous respiratory monitoring is an important tool for clinical monitoring. The most widely used flow measure device is nasal cannulae connected to a pressure transducer. However, most of these devices are not easy to carry and continue working in uncontrolled environments which is also a problem. For portable breathing equipment, due to the volume limit, the pressure signals acquired by using the airway tube may be too weak and contain some noise, leading to huge errors in respiratory flow measures. In this paper, a cost-effective portable pressure sensor-based respiratory measure device is designed. This device has a new airway tube design, which enables the pressure drop efficiently after the air flowing through the airway tube. Also, a new back propagation (BP) neural network-based algorithm is proposed to stabilize the device calibration and remove pressure signal noise. For improving the reliability and accuracy of proposed respiratory device, a through experimental evaluation and a case study of the proposed BP neural network algorithm have been carried out. The results show that giving proper parameters setting, the proposed BP neural network algorithm is capable of efficiently improving the reliability of newly designed respiratory device.

Effects of Depth of Propofol and Sevoflurane Anesthesia on Upper Airway Collapsibility, Respiratory Genioglossus Activation, and Breathing in Healthy Volunteers

BACKGROUND

Volatile anesthetics and propofol impair upper airway stability and possibly respiratory upper airway dilator muscle activity. The magnitudes of these effects have not been compared at equivalent anesthetic doses. We hypothesized that upper airway closing pressure is less negative and genioglossus activity is lower during deep compared with shallow anesthesia.

METHODS

In a randomized controlled crossover study of 12 volunteers, anesthesia with propofol or sevoflurane was titrated using a pain stimulus to identify the threshold for suppression of motor response to electrical stimulation. Measurements included bispectral index, genioglossus electromyography, ventilation, hypopharyngeal pressure, upper airway closing pressure, and change in end-expiratory lung volume during mask pressure drops.

RESULTS

A total of 393 attempted breaths during occlusion maneuvers were analyzed. Upper airway closing pressure was significantly less negative at deep versus shallow anesthesia (-10.8 ± 4.5 vs. -11.3 ± 4.4 cm H2O, respectively [mean ± SD]) and correlated with the bispectral index (P < 0.001), indicating a more collapsible airway at deep anesthesia. Respiratory genioglossus activity during airway occlusion was significantly lower at deep compared with light anesthesia (26 ± 21 vs. 35 ± 24% of maximal genioglossus activation, respectively; P < 0.001) and correlated with bispectral index (P < 0.001). Upper airway closing pressure and genioglossus activity during airway occlusion did not differ between sevoflurane and propofol anesthesia.

CONCLUSIONS

Propofol and sevoflurane anesthesia increased upper airway collapsibility in a dose-dependent fashion with no difference at equivalent anesthetic concentrations. These effects can in part be explained by a dose-dependent inhibiting effect of anesthetics on respiratory genioglossus activity.

Pilot Randomized Study of a Gratitude Journaling Intervention on Heart Rate Variability and Inflammatory Biomarkers in Patients With Stage B Heart Failure

OBJECTIVE

Stage B, asymptomatic heart failure (HF) presents a therapeutic window for attenuating disease progression and development of HF symptoms, and improving quality of life. Gratitude, the practice of appreciating positive life features, is highly related to quality of life, leading to development of promising clinical interventions. However, few gratitude studies have investigated objective measures of physical health; most relied on self-report measures. We conducted a pilot study in Stage B HF patients to examine whether gratitude journaling improved biomarkers related to HF prognosis.

METHODS

Patients (n = 70; mean [standard deviation] age = 66.2 [7.6] years) were randomized to an 8-week gratitude journaling intervention or treatment as usual. Baseline (T1) assessments included the six-item Gratitude Questionnaire, resting heart rate variability (HRV), and an inflammatory biomarker index. At T2 (midintervention), the six-item Gratitude Questionnaire was measured. At T3 (postintervention), T1 measures were repeated but also included a gratitude journaling task.

RESULTS

The gratitude intervention was associated with improved trait gratitude scores (F = 6.0, p = .017, η = 0.10), reduced inflammatory biomarker index score over time (F = 9.7, p = .004, η = 0.21), and increased parasympathetic HRV responses during the gratitude journaling task (F = 4.2, p = .036, η = 0.15), compared with treatment as usual. However, there were no resting preintervention to postintervention group differences in HRV (p values > .10).

CONCLUSIONS

Gratitude journaling may improve biomarkers related to HF morbidity, such as reduced inflammation; large-scale studies with active control conditions are needed to confirm these findings.

TRIAL REGISTRATION

Clinicaltrials.govidentifier:NCT01615094.

Validation of the Hexoskin wearable vest during lying, sitting, standing, and walking activities

We tested the validity of the Hexoskin wearable vest to monitor heart rate (HR), breathing rate (BR), tidal volume (VT), minute ventilation, and hip motion intensity (HMI) in comparison with laboratory standard devices during lying, sitting, standing, and walking. Twenty healthy young volunteers participated in this study. First, participants walked 6 min on a treadmill at speeds of 1, 3, and 4.5 km/h followed by increasing treadmill grades until 80% of their predicted maximal heart rate. Second, lying, sitting, and standing tasks were performed (5 min each) followed by 6 min of treadmill walking at 80% of their ventilatory threshold. Analysis of each individual’s mean values under each resting or exercise condition by the 2 measurement systems revealed low coefficient of variation and high intraclass correlation values for HR, BR, and HMI. The Bland–Altman results from HR, BR, and HMI indicated no deviation of the mean value from zero and relatively small variability about the mean. VT and minute ventilation were provided in arbitrary units by the Hexoskin device; however, relative magnitude of change from Hexoskin closely tracked the laboratory standard method. Hexoskin presented low variability, good agreement, and consistency. The Hexoskin wearable vest was a valid and consistent tool to monitor activities typical of daily living such as different body positions (lying, sitting, and standing) and various walking speeds.

Measurement and Data Transmission Validity of a Multi-Biosensor System for Real-Time Remote Exercise Monitoring Among Cardiac Patients

BACKGROUND

Remote telemonitoring holds great potential to augment management of patients with coronary heart disease (CHD) and atrial fibrillation (AF) by enabling regular physiological monitoring during physical activity. Remote physiological monitoring may improve home and community exercise-based cardiac rehabilitation (exCR) programs and could improve assessment of the impact and management of pharmacological interventions for heart rate control in individuals with AF.

OBJECTIVE

Our aim was to evaluate the measurement validity and data transmission reliability of a remote telemonitoring system comprising a wireless multi-parameter physiological sensor, custom mobile app, and middleware platform, among individuals in sinus rhythm and AF.

METHODS

Participants in sinus rhythm and with AF undertook simulated daily activities, low, moderate, and/or high intensity exercise. Remote monitoring system heart rate and respiratory rate were compared to reference measures (12-lead ECG and indirect calorimeter). Wireless data transmission loss was calculated between the sensor, mobile app, and remote Internet server.

RESULTS

Median heart rate (-0.30 to 1.10 b∙min-1) and respiratory rate (-1.25 to 0.39 br∙min-1) measurement biases were small, yet statistically significant (all P≤.003) due to the large number of observations. Measurement reliability was generally excellent (rho=.87-.97, all P<.001; intraclass correlation coefficient [ICC]=.94-.98, all P<.001; coefficient of variation [CV]=2.24-7.94%), although respiratory rate measurement reliability was poor among AF participants (rho=.43, P<.001; ICC=.55, P<.001; CV=16.61%). Data loss was minimal (<5%) when all system components were active; however, instability of the network hosting the remote data capture server resulted in data loss at the remote Internet server during some trials.

CONCLUSIONS

System validity was sufficient for remote monitoring of heart and respiratory rates across a range of exercise intensities. Remote exercise monitoring has potential to augment current exCR and heart rate control management approaches by enabling the provision of individually tailored care to individuals outside traditional clinical environments.

Respiratory inductance plethysmography-a rationale for validity during exercise

INTRODUCTION

The aim of this study was to provide a rationale for future validations of a priori calibrated respiratory inductance plethysmography (RIP) when used under exercise conditions. Therefore, the validity of a posteriori-adjusted gain factors and accuracy in resultant breath-by-breath RIP data recorded under resting and running conditions were examined.

METHODS

Healthy subjects, 98 men and 88 women (mean ± SD: height = 175.6 ± 8.9 cm, weight = 68.9 ± 11.1 kg, age = 27.1 ± 8.3 yr), underwent a standardized test protocol, including a period of standing still, an incremental running test on treadmill, and multiple periods of recovery. Least square regression was used to calculate gain factors, respectively, for complete individual data sets as well as several data subsets. In comparison with flowmeter data, the validity of RIP in breathing rate (fR) and inspiratory tidal volume (VTIN) were examined using coefficients of determination (R). Accuracy was estimated from equivalence statistics.

RESULTS

Calculated gains between different data subsets showed no equivalence. After gain adjustment for the complete individual data set, fR and VTIN between methods were highly correlated (R = 0.96 ± 0.04 and 0.91 ± 0.05, respectively) in all subjects. Under conditions of standing still, treadmill running, and recovery, 86%, 98%, and 94% (fR) and 78%, 97%, and 88% (VTIN), respectively, of all breaths were accurately measured within ± 20% limits of equivalence.

CONCLUSION

In case of the best possible gain adjustment, RIP confidentially estimates tidal volume accurately within ± 20% under exercise conditions. Our results can be used as a rationale for future validations of a priori calibration procedures.

Evaluation of a wearable physiological status monitor during simulated fire fighting activities

A physiological status monitor (PSM) has been embedded in a fire-resistant shirt. The purpose of this research study was to examine the ability of the PSM-shirt to accurately detect heart rate (HR) and respiratory rate (RR) when worn under structural fire fighting personal protective equipment (PPE) during the performance of various activities relevant to fire fighting. Eleven healthy, college-aged men completed three activities (walking, searching/crawling, and ascending/descending stairs) that are routinely performed during fire fighting operations while wearing the PSM-shirt under structural fire fighting PPE. Heart rate and RR recorded by the PSM-shirt were compared to criterion values measured concurrently with an ECG and portable metabolic measurement system, respectively. For all activities combined (overall) and for each activity, small differences were found between the PSM-shirt and ECG (mean difference [95% CI]: overall: -0.4 beats/min [-0.8, -0.1]; treadmill: -0.4 beats/min [-0.7, -0.1]; search: -1.7 beats/min [-3.1, -.04]; stairs: 0.4 beats/min [0.04, 0.7]). Standard error of the estimate was 3.5 beats/min for all tasks combined and 1.9, 5.9, and 1.9 beats/min for the treadmill walk, search, and stair ascent/descent, respectively. Correlations between the PSM-shirt and criterion heart rates were high (r = 0.95 to r = 0.99). The mean difference between RR recorded by the PSM-shirt and criterion overall was 1.1 breaths/min (95% CI: -1.9 to -0.4). The standard error of the estimate for RR ranged from 4.2 breaths/min (treadmill) to 8.2 breaths/min (search), with an overall value of 6.2 breaths/min. These findings suggest that the PSM-shirt provides valid measures of HR and useful approximations of RR when worn during fire fighting duties.

Validation of heart rate derived from a physiological status monitor-embedded compression shirt against criterion ECG

Firefighters are subject to extreme environments and high physical demands when performing duty-related tasks. Recently, physiological status monitors (PSM) have been embedded into a compression shirt to enable firefighters to measure, visualize, log, and transmit vital metrics such as heart rate (HR) to aid in cardiovascular risk identification and mitigation, thereby attempting to improve the health, fitness, and safety of this population. The purpose of this study was to validate HR recorded by the PSM-embedded compression shirt against a criterion standard laboratory ECG-derived HR when worn concurrently with structural firefighting personal protective equipment (PPE) during four simulated firefighting activities. Ten healthy, college-age men (mean ± SD: age: 21 ± 1 yr; body mass: 91 ± 10 kg; body mass index: 26.9 ± 3.1 kg/m(2)) completed four tasks that are routinely performed during firefighting operations: outdoor fast-paced walking (FW), treadmill walking (TW), searching/crawling (SC), and ascending/descending stairs (AD). They wore the PSM-embedded compression shirt under structural firefighting PPE. HR was recorded concurrently by the PSM-embedded compression shirt and a portable metabolic measurement system accompanied with a standard 12-lead electrocardiograph that was used to provide criterion measures of HR. For all four tasks combined there was very high correlation of PSM and ECG HR (r > 0.99; SEE 0.84 /min) with a mean difference (bias) of -0.02 /min and limits of agreement of -0.07 to 0.02 /min. For individual tasks, the correlations were also high (r-values = 0.99; SEE 0.81-0.89). The mean bias (limits of agreement) was: FW 0.03 (-0.09 to 0.14); TW 0.04 (-0.05 to 0.12); SC -0.01 (-0.12 to 0.10); AD -0.13 (-0.21 to -0.04) /min. These findings demonstrate that the PSM-embedded compression shirt provides a valid measure of HR during simulated firefighting activities when compared with a standard 12-lead ECG.

Validity and reliability of multiparameter physiological measurements recorded by the Equivital LifeMonitor during activities of various intensities

The Equivital LifeMonitor EQ02 is a multiparameter body-worn system capable of logging and transmitting physiological data describing a wearer's cardiorespiratory and thermal status. A number of vital signs can be acquired by the system, including electrocardiography, respiratory inductance plethysmography, posture/activity, multipoint skin temperature, and core temperature. The validity and reliability of the multiparameter physiological data recorded by the EQ02 were assessed. Participants performed resting, low-, and moderate intensity activities and wore the EQ02 and other calibrated laboratory physiological monitoring devices simultaneously. Heart rate, respiratory rate, multipoint skin temperature, and core temperature recorded by the EQ02 were compared with measurements recorded by standard devices. Results show that the validity error scores for HR and RR for all three activities were not significantly different from zero, and the CV, 95% LOA, and r were all clinically accepted. The validity error score for MT(SK) (0.59°C) falls outside the limits of 0.5°C, but the differences were parallel, r remained high (0.96), and 95% LOA remained narrow (±0.88°C). The validity error score for T(C) (-0.1°C) was similar in direction and magnitude to other studies, and r (0.98) and 95% LOA (±0.22°C) showed acceptable agreement between devices. The reliability error scores for HR, RR, MT(SK), and T(C) between trials were significantly different from zero. The 95% LOA, CV, and ICC for the EQ02 were similar to standard devices and were all clinically accepted. These findings demonstrate the validity and reliability of the EQ02 for ambulatory monitoring of multiple physiological parameters and suggest that the system could be used to provide a complete human physiological monitoring platform for the study of occupational health, environmental hygiene, and other application fields requiring ambulatory monitoring of multiparameter physiological status.

Cycle ergometer tests in children with cystic fibrosis: reliability and feasibility

The aim of this study was to assess the reliability and feasibility of cycle ergometer tests in young children with cystic fibrosis (CF). Children with CF aged 6-11 years and with stable lung disease performed two cycle ergometry tests (intermittent sprint and continuous incremental) on two occasions 1 week apart. Reliability was assessed using repeated-measures ANOVA. Bias was considered to be significant at P < 0.05 level and a coefficient of variation (CV) below 10% was considered acceptable. Feasibility and acceptability data were also collected. Sixteen children with CF completed the study: (9M:7F), 8.7(1.8) years, FEV(1) %predicted: 88.1(17.4). Power measurements recorded during the intermittent sprint test demonstrated significant bias over days (P < 0.05) and CVs were between 10% and 15%. Peak work capacity recorded during the continuous incremental test was reliable (bias P < 0.05, CV < 10%), as was heart rate and SpO(2) recorded during both tests (bias P < 0.05, CV < 10%). No problems were experienced in administering the tests and all children completed both tests on two separate occasions. There was a mixed response to questions on acceptability of tests. This is the first study to provide information on the reliability of performance measures recorded during an intermittent sprint protocol (peak power) and a continuous incremental cycle ergometry (peak work capacity) in children with CF.

Development of a respiratory inductive plethysmography module supporting multiple sensors for wearable systems

In this paper, we present an RIP module with the features of supporting multiple inductive sensors, no variable frequency LC oscillator, low power consumption, and automatic gain adjustment for each channel. Based on the method of inductance measurement without using a variable frequency LC oscillator, we further integrate pulse amplitude modulation and time division multiplexing scheme into a module to support multiple RIP sensors. All inductive sensors are excited by a high-frequency electric current periodically and momentarily, and the inductance of each sensor is measured during the time when the electric current is fed to it. To improve the amplitude response of the RIP sensors, we optimize the sensing unit with a matching capacitor parallel with each RIP sensor forming a frequency selection filter. Performance tests on the linearity of the output with cross-sectional area and the accuracy of respiratory volume estimation demonstrate good linearity and accurate lung volume estimation. Power consumption of this new RIP module with two sensors is very low. The performance of respiration measurement during movement is also evaluated. This RIP module is especially desirable for wearable systems with multiple RIP sensors for long-term respiration monitoring.

Cardiorespiratory measurements during field tests in CF: use of an ambulatory monitoring system

Respiratory inductive plethysmography (e.g., LifeShirt) may offer in-depth study of the cardiorespiratory responses during field exercise tests. The aims of this study were to assess the reliability, discriminate validity, and responsiveness of cardiorespiratory measurements recorded by the LifeShirt during field exercise tests in adults with CF. To assess reliability and discriminate validity, participants with CF and stable lung disease and healthy participants performed the 6-Minute Walk Test (6MWT) and Modified Shuttle Test (MST) on two occasions. To assess responsiveness, participants with CF experiencing an exacerbation performed the 6MWT at the start and end of an admission for intravenous antibiotics. The LifeShirt was worn during all exercise tests. Reliability and discriminate validity were assessed in 18 participants with CF (mean (SD) age: 26 (10) years; FEV1 %predicted: 69.2 (23)%) and 18 healthy participants (age: 24 (5) years, FEV1 % predicted: 92 (8)%). There was no difference in 6MWT and MST performance between days and reliability of cardiorespiratory measures was acceptable (bias: P > 0.05; CV < 10%). Participants with CF demonstrated a significantly greater response to exercise (e.g., ventilation, respiratory rate) compared to healthy participants indicating discriminate validity. Responsiveness was assessed in 12 participants with CF: clinical measurements and 6MWT performance improved (61 (81) min; P < 0.05) however, cardiorespiratory measurements recorded by the LifeShirt remained the same (bias: P > 0.05; CV < 10%). This study provides evidence that cardiorespiratory responses can be measured non-invasively during field exercise tests in adults with CF. Reliability and discriminate validity of key cardiorespiratory measurements recorded by the LifeShirt were demonstrated. Some information on responsiveness is reported.

Restoration of vagal tone: a possible mechanism for functional abdominal pain

Functional abdominal pain (FAP) causes disruption of daily activities/missed school days, over utilization of healthcare, unnecessary surgeries, and anxiety in 10-15% of children. Its etiology is not clearly understood, however the success of several clinical protocols suggests that autonomic dysregulation is a factor. In this study autonomic activity, including heart rate variability (HRV), was compared between children with FAP and a comparison group. Twenty children with FAP and 10 children without FAP between the ages of 5 and 17 years old were compared on autonomic regulation using an ambulatory system at baseline and 8 weeks later. Children with FAP participated in 6 sessions of HRV biofeedback aimed at normalizing autonomic balance. At baseline, children with FAP appear to have more autonomic dysregulation than children without FAP. After completing HRV biofeedback, the FAP group was able to significantly reduce their symptoms in relation to significantly increasing their autonomic balance. In a sample of children with FAP, it appears that HRV biofeedback treatment improved their symptoms and that a change in vagal tone was a potential mediator for this improvement. The present study appears to point to excessive vagal withdrawal as an underlying mechanism of FAP.

Heart rate variability in bipolar mania and schizophrenia

BACKGROUND

Autonomic nervous system (ANS) dysfunction and reduced heart rate variability (HRV) have been reported in a wide variety of psychiatric disorders, but have not been well characterized in bipolar mania. We recorded cardiac activity and assessed HRV in acutely hospitalized manic bipolar (BD) and schizophrenia (SCZ) patients compared to age- and gender-matched healthy comparison (HC) subjects.

METHOD

HRV was assessed using time domain, frequency domain, and nonlinear analyses in 23 manic BD, 14 SCZ, and 23 HC subjects during a 5min rest period. Psychiatric symptoms were assessed by administration of the Brief Psychiatric Rating Scale (BPRS) and the Young Mania Rating Scale (YMRS).

RESULTS

Manic BD patients demonstrated a significant reduction in HRV, parasympathetic activity, and cardiac entropy compared to HC subjects, while SCZ patients demonstrated a similar, but non-significant, trend towards lower HRV and entropy. Reduction in parasympathetic tone was significantly correlated with higher YMRS scores and the unusual thought content subscale on the BPRS. Decreased entropy was associated with increased aggression and diminished personal hygiene on the YMRS scale.

CONCLUSION

Cardiac function in manic BD individuals is characterized by decreased HRV, reduced vagal tone, and a decline in heart rate complexity as assessed by linear and nonlinear methods of analysis. Autonomic dysregulation is associated with more severe psychiatric symptoms, suggesting HRV dysfunction in this disorder may be dependent on the phase of the illness.