Respiratory Frequency during Exercise: The Neglected Physiological Measure

Evaluation of Photoplethysmography-Based Monitoring of Respiration Rate During High-Intensity Interval Training: Implications for Healthcare Monitoring

Monitoring respiration rate (RR) is crucial in various healthcare settings, particularly during demanding (physical) activities where respiratory dynamics are critical indicators of health status. This study aimed to evaluate the accuracy of photoplethysmography (PPG)-based monitoring of RR during high-intensity interval training (HIIT) and its potential applications in healthcare. Between January and March 2024, healthy volunteers participated in a cycling HIIT session with increasing resistance levels. The RR measurements obtained using the PPG-based CardioWatch 287-2 (Corsano Health) were compared with an ECG patch-derived (Vivalink) reference. Subgroup analyses were conducted based on skin type and sex. A total of 35 participants contributed 1794 paired RR measurements. The PPG algorithm for RR monitoring showed an average root mean square (Arms) error of 2.13 breaths per minute (brpm), a bias of -0.09 brpm, and limits of agreement (LoA) from -4.28 to 4.09 brpm. Results were consistent across the different demographic subgroups. The CardioWatch 287-2 therefore demonstrated reliable RR monitoring during HIIT, supporting its potential use in healthcare settings for continuous, non-invasive respiratory monitoring, particularly in physical rehabilitation and chronic respiratory condition management.

Correlation properties of heart rate variability for exercise prescription during prolonged running at constant speeds: A randomized cross-over trial

The study explores the validity of the nonlinear index alpha 1 of detrended fluctuation analysis (DFAa1) of heart rate (HR) variability for exercise prescription in prolonged constant load running bouts of different intensities. 21 trained endurance athletes (9 w and 12 m) performed a ramp test for ventilatory threshold (vVT1 and vVT2) and DFAa1-based (vDFAa1-1 at 0.75 and vDFAa1-2 at 0.5) running speed detection as well as two 20-min running bouts at vDFAa1-1 and vDFAa1-2 (20-vDFAa1-1 and 20-vDFAa1-2), in which HR, oxygen consumption (VO2), respiratory frequency (RF), DFAa1, and blood lactate concentration [La-] were assessed. 20-vDFAa1-2 could not be finished by all participants (finisher group (FG), n = 15 versus exhaustion group (EG), n = 6). Despite similar mean external loads of vDFAa1-1 (10.6 ± 1.9 km/h) and vDFAa1-2 (13.1 ± 2.4 km/h) for all participants compared to vVT1 (10.8 ± 1.7 km/h) and vVT2 (13.2 ± 1.9 km/h), considerable differences were present for 20-vDFAa1-2 in EG (15.2 ± 2.4 km/h). 20-vDFAa1-1 and 20-DFAa1-2 yielded significant differences in FG for HR (76.2 ± 5.7 vs. 86.4 ± 5.9 %HRPEAK), VO2 (62.1 ± 5.0 vs. 77.5 ± 8.6 %VO2PEAK), RF (40.6 ± 11.3 vs. 46.1 ± 9.8 bpm), DFA-a1 (0.86 ± 0.23 vs. 0.60 ± 0.15), and [La-] (1.41 ± 0.45 vs. 3.34 ± 2.24 mmol/L). Regarding alterations during 20-vDFAa1-1, all parameters showed small changes for all participants, while during 20-vDFAa1-2 RF and DFAa1 showed substantial alterations in FG (RF: 15.6% and DFAa1: -12.8%) and more pronounced in EG (RF: 20.1% and DFAa1: -35.9%). DFAa1-based exercise prescription from incremental testing could be useful for most participants in prolonged running bouts, at least in the moderate to heavy intensity domain. In addition, an individually different increased risk of overloading may occur in the heavy to severe exercise domains and should be further elucidated in the light of durability and decoupling assessment.

Work of Breathing for Aviators: A Missing Link in Human Performance

In this study, we explore the work of breathing (WoB) experienced by aviators during the Anti-G Straining Maneuver (AGSM) to improve pilot safety and performance. Traditional airflow models of WoB fail to adequately distinguish between breathing rate and inspiratory frequency, leading to potentially inaccurate assessments. This mismatch can have serious implications, particularly in critical flight situations where understanding the true respiratory workload is essential for maintaining performance. To address these limitations, we used a non-sinusoidal model that captures the complexities of WoB under high inspiratory frequencies and varying dead space conditions. Our findings indicate that the classical airflow model tends to underestimate WoB, particularly at elevated inspiratory frequencies ranging from 0.5 to 2 Hz, where resistive forces play a significant role and elastic forces become negligible. Additionally, we show that an increase in dead space, coupled with high-frequency breathing, elevates WoB, heightening the risk of dyspnea among pilots. Interestingly, our analysis reveals that higher breathing rates lead to a decrease in total WoB, an unexpected finding suggesting that refining breathing patterns could help pilots optimize their energy expenditure. This research highlights the importance of examining the relationship between alveolar ventilation, breathing rate, and inspiratory frequency in greater depth within realistic flight scenarios. These insights indicate the need for targeted training programs and adaptive life-support systems to better equip pilots for managing respiratory challenges in high-stress situations. Ultimately, our research lays the groundwork for enhancing respiratory support for aviators, contributing to safer and more efficient flight operations.

Validity and Reliability of a New Wearable Chest Strap to Estimate Respiratory Frequency in Elite Soccer Athletes

Assessing respiratory frequency (fR) is practical in monitoring training progress in competitive athletes, especially during exercise. This study aimed to validate a new wearable chest strap (wCS) to estimate fR against ergospirometry as a criterion device in soccer players. A total of 26 elite professional soccer players (mean [standard deviation]: 23.6 [4.8] years; 180.6 [5.7] cm; 77.2 [5.4] kg) from three Italian Serie A League teams participated in this cross-sectional study. The sample included attackers, midfielders, and defenders. fR was assessed during a maximal cardiopulmonary exercise test (CPET) on a treadmill using (i) a breath-by-breath gas exchange analyzer (Vyntus® CPX, Vyaire Medical) and (ii) a novel wCS with sensors designed to assess breath frequency following chest expansions. Pearson's correlation coefficient (r), adjusted coefficient of determination (aR2), Bland-Altman plot analysis, and Lin's concordance correlation coefficient (ρc) were used for comparative analysis (correlation and concordance) among the methods. The repeated measures correlation coefficient (rrm) was used to assess the strength of the linear association between the methods. The intraclass correlation coefficient (ICC) and the Finn coefficient (rF) were used for inter-rater reliability. All statistical analyses were performed within the R statistical computing environment, with 95% confidence intervals (95% CIs) reported and statistical significance set at p < 0.05. A total of 16529 comparisons were performed after collecting the CPET data. The robust time series analysis with Hodges-Lehmann estimation showed no significant differences between both methods (p > 0.05). Correlation among devices was statistically significant and very large (r [95% CI]: 0.970 [0.970, 0.971], p < 0.01; aR2 [95% CI]: 0.942 [0.942, 0.943], p < 0.01) with strong evidence supporting consistency of the new wCS (BF10 > 100). In addition, a high concordance was found (ρc [95% CI]: 0.970 [0.969, 0.971], bias correction factor: 0.999). VyntusTM CPX, as a standard criterion, showed moderate agreement with wCS after Bland-Altman analysis (bias [95% lower to the upper limit of agreement]; % agree: 0.170 [-4.582 to 4.923] breaths·min-1; 69.9%). A strong association between measurements (rrm [95% CI]: 0.960 [0.959, 0.961]), a high absolute agreement between methods (ICC [95% CI]: 0.970 [0.970, 0.971]), and high inter-rater reliability (rF: 0.947) were found. With an RMSE = 2.42 breaths·min-1, the new wCS seems to be an valid and reliable in-field method to evaluate fR compared to a breath-by-breath gas exchange analyzer. Notwithstanding, caution is advised if methods are used interchangeably while further external validation occurs.

Validation and user experience of a dry electrode based Health Patch for heart rate and respiration rate monitoring

Successful implementation of remote monitoring of vital signs outside of the hospital setting hinges on addressing three crucial unmet needs: longer-term wear, skin comfort and signal quality. Earlier, we developed a Health Patch research platform that uses self-adhesive dry electrodes to measure vital digital biomarkers. Here, we report on the analytical validation for heart rate, heart rate variability and respiration rate. Study design included n = 25 adult participants with data acquisition during a 30-minute exercise protocol involving rest, squats, slow, and fast cycling. The Shimmer3 ECG Unit and Cosmed K5, were reference devices. Data analysis showed good agreement in heart rate and marginal agreement in respiratory rate, with lower agreement towards higher respiratory rates. The Lin's concordance coefficient was 0.98 for heart rate and 0.56 for respiratory rate. Heart rate variability (RMSSD) had a coefficient of 0.85. Participants generally expressed a positive experience with the technology, with some minor irritation from the medical adhesive. The results highlighted potential of this technology for short-to-medium term clinical use for cardiorespiratory health, due to its reliability, accuracy, and compact design. Such technology could become instrumental for remote monitoring providing healthcare professionals with continuous data, remote assessment and enhancing patient outcomes in cardiorespiratory health management.

Is breathing frequency a potential means for monitoring exercise intensity in people with atrial fibrillation and coronary heart disease when heart rate is mitigated?

PURPOSE

Moderate-intensity aerobic exercise is safe and beneficial in atrial fibrillation (AF) and coronary heart disease (CHD). Irregular or rapid heart rates (HR) in AF and other heart conditions create a challenge to using HR to monitor exercise intensity. The purpose of this study was to assess the potential of breathing frequency (BF) to monitor exercise intensity in people with AF and CHD without AF.

METHODS

This observational study included 30 AF participants (19 Male, 70.7 ± 8.7 yrs) and 67 non-AF CHD participants (38 Male, 56.9 ± 11.4 yrs). All performed an incremental maximal exercise test with pulmonary gas exchange.

RESULTS

Peak aerobic power in AF ( V ˙ O2peak; 17.8 ± 5.0 ml.kg-1.min-1) was lower than in CHD (26.7 ml.kg-1.min-1) (p < .001). BF responses in AF and CHD were similar (BF peak: AF 34.6 ± 5.4 and CHD 36.5 ± 5.0 breaths.min-1; p = .106); at the 1st ventilatory threshold (BF@VT-1: AF 23.2 ± 4.6; CHD 22.4 ± 4.6 breaths.min-1; p = .240). % V ˙ O2peak at VT-1 were similar in AF and CHD (AF: 59%; CHD: 57%; p = .656).

CONCLUSION

With the use of wearable technologies on the rise, that now include BF, this first study provides an encouraging potential for BF to be used in AF and CHD. As the supporting data are based on incremental ramp protocol results, further research is required to assess BF validity to manage exercise intensity during longer bouts of exercise.

Respiratory rates among rural Gambian children: a community-based cohort study

Normal respiratory rates (RR) for children under five in the tropics are well-documented, but data for older children are limited. This study tracked RR changes with age and examined associations with nutritional status and environmental factors. We monitored rural Gambian children aged 6 months to 14 years, recording RR during home visits twice weekly over two rainy seasons. Using a generalized additive model, we constructed RR reference curves, and a linear mixed-effect model identified factors influencing RR. A total of 830 children provided 67,512 RR measurements. Their median age was 6.07 years (interquartile range 4.21-8.55) and 400 (48.2%) were female. Age, stunting, ambient temperature, and time of RR measurement were independent predictors of respiratory rate. Strikingly, children showing signs of illness had greater variability in repeat RR measurements. We constructed a RR reference chart for children aged one to 13 years and proposed a cutoff of > 26 breaths/min for raised RR among children aged > 5 years bridging an important gap in this age group. Although the time of data collection, nutritional status, and ambient temperature were predictors of RR, their effect size is not clinically significant enough to warrant a change in the current WHO guidelines owing to the prevailing uncertainty in the measurement of RR. The finding that RRs between repeat measurements were more variable among children with signs of illness suggests that a single RR measurement may be inadequate to reliably assess the status of sick children-a population in which accurate diagnosis is essential to enable targeted interventions with lifesaving treatment.

Laser Fabrication of Humidity Sensors on Ethanol-Soaked Polyimide for Fully Contactless Respiratory Monitoring

Humidity-sensor-based fully contactless respiratory monitoring can eliminate the discomfort and infection risks associated with any wearable device. However, challenges in the facile fabrication of highly sensitive humidity sensors continue to hinder their widespread application for fully contactless respiratory monitoring. In this study, we introduce a simple method to fabricate highly sensitive humidity sensors. Our method employs laser-induced graphene (LIG) on an ethanol-soaked polyimide (PI) film as the electrode of the humidity sensor. The ethanol-soaked PI between adjacent LIG electrodes functions as the sensing material, enabling ion-conductive humidity sensing. Compared to the LIG humidity sensors fabricated on untreated PI films, LIG humidity sensors fabricated on ethanol-soaked PI films exhibit superior performance with higher linearity (R2 = 0.9936), reduced hysteresis (ΔH = 5.1% RH), and increased sensitivity (0.65%/RH). Notably, the LIG humidity sensor fabricated on the ethanol-soaked PI film can detect a person's breathing from a distance of 30 cm, a capability not achieved by sensors fabricated on untreated PI films. Moreover, incorporating these LIG humidity sensors into an array further enhances both the detection distance and the sensitivity for respiratory monitoring. Experimental results demonstrate that the LIG humidity sensor array can be employed for fully contactless on-bed respiration monitoring and for continuous, fully contactless monitoring of the respiratory rate during treadmill exercise. These results highlight the great potential of our LIG humidity sensors for various practical applications in medicine and sports.

Estimation of ventilatory thresholds during exercise using respiratory wearable sensors

Ventilatory thresholds (VTs) are key physiological parameters used to evaluate physical performance and determine aerobic and anaerobic transitions during exercise. Current assessment of these parameters requires ergospirometry, limiting evaluation to laboratory or clinical settings. In this work, we introduce a wearable respiratory system that continuously tracks breathing during exercise and estimates VTs during ramp tests. We validate the respiratory rate and VTs predictions in 17 healthy adults using ergospirometry analysis. In addition, we use the wearable system to evaluate VTs in 107 recreational athletes during ramp tests outside the laboratory and show that the mean population values agree with physiological variables traditionally used to exercise prescription. We envision that respiratory wearables can be useful in determining aerobic and anaerobic parameters with promising applications in health telemonitoring and human performance.

Breathing Monitoring in Soccer: Part I-Validity of Commercial Wearable Sensors

Growing evidence suggests that respiratory frequency (fR) is a valid marker of effort during high-intensity exercise, including sports of an intermittent nature, like soccer. However, very few attempts have been made so far to monitor fR in soccer with unobtrusive devices. This study assessed the validity of three strain-based commercial wearable devices measuring fR during soccer-specific movements. On two separate visits to the soccer pitch, 15 players performed a 30 min validation protocol wearing either a ComfTech® (CT) vest or a BioharnessTM (BH) 3.0 strap and a Tyme WearTM (TW) vest. fR was extracted from the respiratory waveform of the three commercial devices with custom-made algorithms and compared with that recorded with a reference face mask. The fR time course of the commercial devices generally resembled that of the reference system. The mean absolute percentage error was, on average, 7.03% for CT, 8.65% for TW, and 14.60% for BH for the breath-by-breath comparison and 1.85% for CT, 3.27% for TW, and 7.30% for BH when comparison with the reference system was made in 30 s windows. Despite the challenging measurement scenario, our findings show that some of the currently available wearable sensors are indeed suitable to unobtrusively measure fR in soccer.

Prolonged exercise shifts ventilatory parameters at the moderate-to-heavy intensity transition

PURPOSE

To quantify the effects of prolonged cycling on the rate of ventilation ([Formula: see text]), frequency of respiration (FR), and tidal volume (VT) associated with the moderate-to-heavy intensity transition.

METHODS

Fourteen endurance-trained cyclists and triathletes (one female) completed an assessment of the moderate-to-heavy intensity transition, determined as the first ventilatory threshold (VT1), before (PRE) and after (POST) two hours of moderate-intensity cycling. The power output, [Formula: see text], FR, and VT associated with VT1 were determined PRE and POST.

RESULTS

As previously reported, power output at VT1 significantly decreased by ~ 10% from PRE to POST. The [Formula: see text] associated with VT1 was unchanged from PRE to POST (72 ± 12 vs. 69 ± 13 L.min-1, ∆ - 3 ± 5 L.min-1, ∆ - 4 ± 8%, P = 0.075), and relatively consistent (within-subject coefficient of variation, 5.4% [3.7, 8.0%]). The [Formula: see text] associated with VT1 was produced with increased FR (27.6 ± 5.8 vs. 31.9 ± 6.5 breaths.min-1, ∆ 4.3 ± 3.1 breaths.min-1, ∆ 16 ± 11%, P = 0.0002) and decreased VT (2.62 ± 0.43 vs. 2.19 ± 0.36 L.breath-1, ∆ - 0.44 ± 0.22 L.breath-1, ∆ - 16 ± 7%, P = 0.0002) in POST.

CONCLUSION

These data suggest prolonged exercise shifts ventilatory parameters at the moderate-to-heavy intensity transition, but [Formula: see text] remains stable. Real-time monitoring of [Formula: see text] may be a useful means of assessing proximity to the moderate-to-heavy intensity transition during prolonged exercise and is worthy of further research.

Evaluation of three approaches used for respiratory measurement in healthy subjects

Objective. Respiration is one of the critical vital signs of human health status, and accurate respiratory monitoring has important clinical significance. There is substantial evidence that alterations in key respiratory parameters can be used to determine a patient's health status, aid in the selection of appropriate treatments, predict potentially serious clinical events and control respiratory activity. Although various approaches have been developed for respiration monitoring, no definitive conclusions have been drawn regarding the accuracy of these approaches because each has different advantages and limitations. In the present study, we evaluated the performance of three non-invasive respiratory measurement approaches, including transthoracic impedance (IMP), surface diaphragm electromyography-derived respiration (EMGDR) and electrocardiogram-derived respiration (ECGDR), and compared them with the direct measurement of airflow (FLW) in 33 male and 38 female healthy subjects in the resting state.Approach. The accuracy of six key respiratory parameters, including onset of inspiration (Ion), onset of expiration (Eon), inspiratory time (It), expiratory time (Et), respiratory rate (RR) and inspiratory-expiratory ratio (I:E), measured from the IMP, EMGDR and ECGDR, were compared with those annotated from the reference FLW.Main results. The correlation coefficients between the estimated inspiratory volume and reference value were 0.72 ± 0.20 for IMP, 0.62 ± 0.23 for EMGDR and 0.46 ± 0.21 for ECGDR (p< 0.01 among groups). The positive predictive value and sensitivity for respiration detection were 100% and 100%, respectively, for IMP, which were significantly higher than those of the EMGDR (97.2% and 95.5%,p< 0.001) and the ECGDR (96.9% and 90.0%,p< 0.001). Additionally, the mean error (ME) forIon,Eon,It,EtandRRdetection were markedly lower for IMP than for EMGDR and ECGDR (p< 0.001).Significance. Compared with EMGDR and ECGDR, the IMP signal had a higher positive predictive value, higher sensitivity and lower ME for respiratory parameter detection. This suggests that IMP is more suitable for dedicated respiratory monitoring and parameter evaluation.

Ventilation and perceived exertion are sensitive to changes in exercise tolerance: arm+leg cycling vs. leg cycling

Purpose: Growing evidence suggests that respiratory frequency (f R) is a marker of physical effort and a variable sensitive to changes in exercise tolerance. The comparison between arm+leg cycling (Arm+leg) and leg cycling (Leg) has the potential to further test this notion because a greater exercise tolerance is expected in the Arm+leg modality. We systematically compared Arm+leg vs. Leg using different performance tests. Methods: Twelve males underwent six performance tests in separate, randomized visits. Three tests were performed in each of the two exercise modalities, i.e. an incremental test and two time-to-exhaustion (TTE) tests performed at 90% or 75% of the peak power output reached in the Leg incremental test (PPOLeg). Exercise tolerance, perceived exertion, and cardiorespiratory variables were recorded during all the tests. Results: A greater exercise tolerance (p < 0.001) was found for Arm+leg in the incremental test (337 ± 32 W vs. 292 ± 28 W), in the TTE test at 90% of PPOLeg (638 ± 154 s vs. 307 ± 67 s), and in the TTE test at 75% of PPOLeg (1,675 ± 525 s vs. 880 ± 363 s). Unlike V ˙ O2 and heart rate, both f R and minute ventilation were lower (p < 0.003) at isotime in all the Arm+leg tests vs. Leg tests. Furthermore, a lower perceived exertion was observed in the Arm+leg tests, especially during the TTE tests (p < 0.001). Conclusion: Minute ventilation, f R and perceived exertion are sensitive to the improvements in exercise tolerance observed when comparing Arm+leg vs. Leg, unlike V ˙ O2 and heart rate.

RRDetection: Respiration Rate Estimation Using Earbuds During Physical Activities

In modern times, earbuds have become both popular and essential accessories for people to use with a wide range of devices in their everyday lives. Moreover, the respiration rate is a crucial vital sign that is sensitive to various pathological conditions. Many earbuds now come equipped with multiple sensing capabilities, including inertial and acoustic sensors. These sensors can be used by researchers to passively monitor users' vital signs, such as respiration rates. While current earbud-based breath rate estimation algorithms mostly focus on resting conditions, recent studies have demonstrated that respiration rates during physical activities can predict cardio-respiratory fitness for healthy individuals and pulmonary conditions for respiratory patients. To address this gap, we propose a novel algorithm called RRDetection that leverages the motion sensors in ordinary earbuds to detect respiration rates during light to moderate physical activities.

Respiratory Rate Estimation during Walking and Running Using Breathing Sounds Recorded with a Microphone

Emerging evidence suggests that respiratory frequency (f_R) is a valid marker of physical effort. This has stimulated interest in developing devices that allow athletes and exercise practitioners to monitor this vital sign. The numerous technical challenges posed by breathing monitoring in sporting scenarios (e.g., motion artifacts) require careful consideration of the variety of sensors potentially suitable for this purpose. Despite being less prone to motion artifacts than other sensors (e.g., strain sensors), microphone sensors have received limited attention so far. This paper proposes the use of a microphone embedded in a facemask for estimating f_R from breath sounds during walking and running. f_R was estimated in the time domain as the time elapsed between consecutive exhalation events retrieved from breathing sounds every 30 s. Data were collected from ten healthy subjects (both males and females) at rest and during walking (at 3 km/h and 6 km/h) and running (at 9 km/h and 12 km/h) activities. The reference respiratory signal was recorded with an orifice flowmeter. The mean absolute error (MAE), the mean of differences (MOD), and the limits of agreements (LOAs) were computed separately for each condition. Relatively good agreement was found between the proposed system and the reference system, with MAE and MOD values increasing with the increase in exercise intensity and ambient noise up to a maximum of 3.8 bpm (breaths per minute) and -2.0 bpm, respectively, during running at 12 km/h. When considering all the conditions together, we found an MAE of 1.7 bpm and an MOD ± LOAs of -0.24 ± 5.07 bpm. These findings suggest that microphone sensors can be considered among the suitable options for estimating f_R during exercise.

An IMU-Based Wearable System for Respiratory Rate Estimation in Static and Dynamic Conditions

PURPOSE

Breathing parameters change with activity and posture, but currently available solutions can perform measurements only during static conditions.

METHODS

This article presents an innovative wearable sensor system constituted by three inertial measurement units to simultaneously estimate respiratory rate (RR) in static and dynamic conditions and perform human activity recognition (HAR) with the same sensing principle. Two units are aimed at detecting chest wall breathing-related movements (one on the thorax, one on the abdomen); the third is on the lower back. All units compute the quaternions describing the subject's movement and send data continuously with the ANT transmission protocol to an app. The 20 healthy subjects involved in the research (9 men, 11 women) were between 23 and 54 years old, with mean age 26.8, mean height 172.5 cm and mean weight 66.9 kg. Data from these subjects during different postures or activities were collected and analyzed to extract RR.

RESULTS

Statistically significant differences between dynamic activities ("walking slow", "walking fast", "running" and "cycling") and static postures were detected (p < 0.05), confirming the obtained measurements are in line with physiology even during dynamic activities. Data from the reference unit only and from all three units were used as inputs to artificial intelligence methods for HAR. When the data from the reference unit were used, the Gated Recurrent Unit was the best performing method (97% accuracy). With three units, a 1D Convolutional Neural Network was the best performing (99% accuracy).

CONCLUSION

Overall, the proposed solution shows it is possible to perform simultaneous HAR and RR measurements in static and dynamic conditions with the same sensor system.

Peak performance and cardiometabolic responses of modern US army soldiers during heavy, fatiguing vest-borne load carriage

INTRODUCTION

Physiological limits imposed by vest-borne loads must be defined for optimal performance monitoring of the modern dismounted warfighter.

PURPOSE

To evaluate how weighted vests affect locomotion economy and relative cardiometabolic strain during military load carriage while identifying key physiological predictors of exhaustion limits.

METHODS

Fifteen US Army soldiers (4 women, 11 men; age, 26 ± 8 years; height, 173 ± 10 cm; body mass (BM), 79 ± 16 kg) performed four incremental walking tests with different vest loads (0, 22, 44, or 66% BM). We examined the effects of vest-borne loading on peak walking speed, the physiological costs of transport, and relative work intensity. We then sought to determine which of the cardiometabolic indicators (oxygen uptake, heart rate, respiration rate) was most predictive of task failure.

RESULTS

Peak walking speed significantly decreased with successively heavier vest loads (p < 0.01). Physiological costs per kilometer walked were significantly higher with added vest loads for each measure (p < 0.05). Relative oxygen uptake and heart rate were significantly higher during the loaded trials than the 0% BM trial (p < 0.01) yet not different from one another (p > 0.07). Conversely, respiration rate was significantly higher with the heavier load in every comparison (p < 0.01). Probability modeling revealed heart rate as the best predictor of task failure (marginal R², 0.587, conditional R², 0.791).

CONCLUSION

Heavy vest-borne loads cause exceptional losses in performance capabilities and increased physiological strain during walking. Heart rate provides a useful non-invasive indicator of relative intensity and task failure during military load carriage.

Wearable and Stretchable SEBS/CB Polymer Conductive Strand as a Piezoresistive Strain Sensor

A wearable and stretchable strain sensor with a gauge factor above 23 was prepared using a simple and effective technique. Conducting nanocomposite strands were prepared from styrene-b-(ethylene-co-butylene)-b-styrene triblock copolymer (SEBS) and carbon black (CB) through a solvent-processing method that uses a syringe pump. This novel nanocomposite preparation technique is a straightforward and cost-effective process and is reported in the literature for the first time. The work included two stages: the flexible nanocomposite preparation stage and the piezoresistive sensor stage. Depending on its molecular structure, the thermoelastic polymer SEBS is highly resilient to stress and strain. The main aim of this work is to fabricate a highly flexible and piezoresistive nanocomposite fibre/strand. Among the prepared composites, a composite corresponding to a composition just above the percolation threshold was selected to prepare the strain sensor, which exhibited good flexibility and conductivity and a large piezoresistive effect that was linearly dependent on the applied strain. The prepared nanocomposite sensor was stitched onto a sports T-shirt. Commercially available knee and elbow sleeves were also purchased, and the nanocomposite SEBS/CB strands were sewn separately on the two sleeves. The results showed a high sensitivity of the sensing element in the case of breathing activity (normal breathing, a 35% change, and deep breathing at 135%, respectively). In the case of knee and elbow movements, simultaneous measurements were performed and found that the sensor was able to detect movement cycles during walking.

Design and Testing of a Smart Facemask for Respiratory Monitoring during Cycling Exercise

Given the importance of respiratory frequency (f_R) as a valid marker of physical effort, there is a growing interest in developing wearable devices measuring f_R in applied exercise settings. Biosensors measuring chest wall movements are attracting attention as they can be integrated into textiles, but their susceptibility to motion artefacts may limit their use in some sporting activities. Hence, there is a need to exploit sensors with signals minimally affected by motion artefacts. We present the design and testing of a smart facemask embedding a temperature biosensor for f_R monitoring during cycling exercise. After laboratory bench tests, the proposed solution was tested on cyclists during a ramp incremental frequency test (RIFT) and high-intensity interval training (HIIT), both indoors and outdoors. A reference flowmeter was used to validate the f_R extracted from the temperature respiratory signal. The smart facemask showed good performance, both at a breath-by-breath level (MAPE = 2.56% and 1.64% during RIFT and HIIT, respectively) and on 30 s average f_R values (MAPE = 0.37% and 0.23% during RIFT and HIIT, respectively). Both accuracy and precision (MOD ± LOAs) were generally superior to those of other devices validated during exercise. These findings have important implications for exercise testing and management in different populations.

A closer look at yoga nidra- early randomized sleep lab investigations

OBJECTIVES

We aimed to examine trial feasibility plus physiological and psychological effects of a guided meditation practice, Yoga Nidra, in adults with self-reported insomnia.

METHODS

Twenty-two adults with self-reported insomnia were recruited to attend two visits at our research center. At Visit 1 (V1), participants were asked to lie quietly for ninety minutes. The primary outcome was change in electroencephalography (EEG). Heart rate variability (HRV), respiratory rate and self-reported mood and anxiety were also measured. At Visit 2 (V2), the same protocol was followed, except half of participants were randomized to practice Yoga Nidra for the first 30-min.

RESULTS

There were no between-group changes (V1-V2) in alpha EEG power at O1 (Intervention: 13 ± 70%; Control: -20 ± 40%), HRV or sleep onset latency in response to Yoga Nidra. Respiratory rate, however, showed statistically significant difference between groups (Yoga Nidra -1.4 breaths per minute (bpm) change during and - 2.1 bpm afterwards vs. Control +0.2 bpm during and + 0.4 bpm after; p = .03 for both during and after). The intervention displayed good acceptability (well-tolerated) and credibility (perceived benefit ratings) with implementation success (target sample size reached; 5% dropout rate).

CONCLUSIONS

This preliminary clinical trial provides early evidence that Yoga Nidra is a well-tolerated, feasible intervention for adults reporting insomnia. Decreased respiratory rate in response to Yoga Nidra needs to be confirmed in more definitive studies.

TRIAL REGISTRATION INFORMATION

This trial was registered on ClinicalTrials.gov as "A Closer Look at Yoga Nidra: Sleep Lab Analyses" (NCT#03685227).

Locomotor-Respiratory Entrainment upon Phonated Compared to Spontaneous Breathing during Submaximal Exercise

Recently, increased attention to breathing techniques during exercise has addressed the need for more in-depth study of the ergogenic effects of breathing manipulation. The physiological effects of phonation, as a potential breathing tool, have not yet been studied. Thus, the aim of this study was to investigate the respiratory, metabolic and hemodynamic responses of phonated exhalation and its impact on locomotor-respiratory entrainment in young healthy adults during moderate exercise. Twenty-six young, healthy participants were subjected to peak expiratory flow (PEF) measurements and a moderate steady cycling protocol based on three different breathing patterns (BrP): spontaneous breathing (BrP1), phonated breathing pronouncing "h" (BrP2) and phonated breathing pronouncing "ss" (BrP3). The heart rate, arterial blood pressure, oxygen consumption, CO2 production, respiratory rate (RR), tidal volume (VT), respiratory exchange ratio and ventilatory equivalents for both important respiratory gasses (eqO2 and eqCO2) were measured (Cosmed, Italy) simultaneously during a short period of moderate stationary cycling at a predefined cadence. To evaluate the psychological outcomes, the rate of perceived exertion (RPE) was recorded after each cycling protocol. The locomotor-respiratory frequency coupling was calculated at each BrP, and dominant coupling was determined. Phonation gradually decreased the PEF (388 ± 54 L/min at BrP2 and 234 ± 54 L/min at BrP3 compared to 455 ± 42 L/min upon spontaneous breathing) and affected the RR (18.8 ± 5.0 min-1 at BrP2 compared to 22.6 ± 5.5 min-1 at BrP1 and 21.3 ± 7.2 min-1 at BrP3), VT (2.33 ± 0.53 L at BrP2 compared to 1.86 ± 0.46 L at BrP1 and 2.00 ± 0.45 L at BrP3), dominant locomotor-respiratory coupling (1:4 at BrP2 compared to 1:3 at BrP1 and BrP2) and RPE (10.27 ± 2.00 at BrP1 compared to 11.95 ± 1.79 at BrP1 and 11.95 ± 1.01 at BrP3) but not any other respiratory, metabolic or hemodynamic measures of the healthy adults during moderate cycling. The ventilatory efficiency was shown to improve upon dominant locomotor-respiratory coupling, regardless of BrP (eqO2 = 21.8 ± 2.2 and eqCO2 = 24.0 ± 1.9), compared to the other entrainment coupling regimes (25.3 ± 1.9, 27.3 ± 1.7) and no entrainment (24.8 ± 1.5, 26.5 ± 1.3), respectively. No interaction between phonated breathing and entrainment was observed during moderate cycling. We showed, for the first time, that phonation can be used as a simple tool to manipulate expiratory flow. Furthermore, our results indicated that in young healthy adults, entrainment, rather than expiratory resistance, preferentially affected ergogenic enhancement upon moderate stationary cycling. It can only be speculated that phonation would be a good strategy to increase exercise tolerance among COPD patients or to boost the respiratory efficiency of healthy people at higher exercise loads.

A Multifunctional Network with Uncertainty Estimation and Attention-Based Knowledge Distillation to Address Practical Challenges in Respiration Rate Estimation

Respiration rate is a vital parameter to indicate good health, wellbeing, and performance. As the estimation through classical measurement modes are limited only to rest or during slow movements, respiration rate is commonly estimated through physiological signals such as electrocardiogram and photoplethysmography due to the unobtrusive nature of wearable devices. Deep learning methodologies have gained much traction in the recent past to enhance accuracy during activities involving a lot of movement. However, these methods pose challenges, including model interpretability, uncertainty estimation in the context of respiration rate estimation, and model compactness in terms of deployment in wearable platforms. In this direction, we propose a multifunctional framework, which includes the combination of an attention mechanism, an uncertainty estimation functionality, and a knowledge distillation framework. We evaluated the performance of our framework on two datasets containing ambulatory movement. The attention mechanism visually and quantitatively improved instantaneous respiration rate estimation. Using Monte Carlo dropouts to embed the network with inferential uncertainty estimation resulted in the rejection of 3.7% of windows with high uncertainty, which consequently resulted in an overall reduction of 7.99% in the mean absolute error. The attention-aware knowledge distillation mechanism reduced the model's parameter count and inference time by 49.5% and 38.09%, respectively, without any increase in error rates. Through experimentation, ablation, and visualization, we demonstrated the efficacy of the proposed framework in addressing practical challenges, thus taking a step towards deployment in wearable edge devices.

Differential control of respiratory frequency and tidal volume during exercise

The lack of a testable model explaining how ventilation is regulated in different exercise conditions has been repeatedly acknowledged in the field of exercise physiology. Yet, this issue contrasts with the abundance of insightful findings produced over the last century and calls for the adoption of new integrative perspectives. In this review, we provide a methodological approach supporting the importance of producing a set of evidence by evaluating different studies together-especially those conducted in 'real' exercise conditions-instead of single studies separately. We show how the collective assessment of findings from three domains and three levels of observation support the development of a simple model of ventilatory control which proves to be effective in different exercise protocols, populations and experimental interventions. The main feature of the model is the differential control of respiratory frequency (f_R) and tidal volume (V_T); f_R is primarily modulated by central command (especially during high-intensity exercise) and muscle afferent feedback (especially during moderate exercise) whereas V_T by metabolic inputs. Furthermore, V_T appears to be fine-tuned based on f_R levels to match alveolar ventilation with metabolic requirements in different intensity domains, and even at a breath-by-breath level. This model reconciles the classical neuro-humoral theory with apparently contrasting findings by leveraging on the emerging control properties of the behavioural (i.e. f_R) and metabolic (i.e. V_T) components of minute ventilation. The integrative approach presented is expected to help in the design and interpretation of future studies on the control of f_R and V_T during exercise.

Restricted nasal-only breathing during self-selected low intensity training does not affect training intensity distribution

Introduction: Low-intensity endurance training is frequently performed at gradually higher training intensities than intended, resulting in a shift towards threshold training. By restricting oral breathing and only allowing for nasal breathing this shift might be reduced. Methods: Nineteen physically healthy adults (3 females, age: 26.5 ± 5.1 years; height: 1.77 ± 0.08 m; body mass: 77.3 ± 11.4 kg; VO₂peak: 53.4 ± 6.6 mL·kg^-1 min^-1) performed 60 min of self-selected, similar (144.7 ± 56.3 vs. 147.0 ± 54.2 W, p = 0.60) low-intensity cycling with breathing restriction (nasal-only breathing) and without restrictions (oro-nasal breathing). During these sessions heart rate, respiratory gas exchange data and power output data were recorded continuously. Results: Total ventilation (p < 0.001, η_p ² = 0.45), carbon dioxide release (p = 0.02, η_p ² = 0.28), oxygen uptake (p = 0.03, η_p ² = 0.23), and breathing frequency (p = 0.01, η_p ² = 0.35) were lower during nasal-only breathing. Furthermore, lower capillary blood lactate concentrations were found towards the end of the training session during nasal-only breathing (time x condition-interaction effect: p = 0.02, η_p ² = 0.17). Even though discomfort was rated marginally higher during nasal-only breathing (p = 0.03, η_p ² = 0.24), ratings of perceived effort did not differ between the two conditions (p ≥ 0.06, η_p ² = 0.01). No significant "condition" differences were found for intensity distribution (time spent in training zone quantified by power output and heart rate) (p ≥ 0.24, η_p ² ≤ 0.07). Conclusion: Nasal-only breathing seems to be associated with possible physiological changes that may help to maintain physical health in endurance athletes during low intensity endurance training. However, it did not prevent participants from performing low-intensity training at higher intensities than intended. Longitudinal studies are warranted to evaluate longitudinal responses of changes in breathing patterns.

Step-adaptive sound guidance enhances locomotor-respiratory coupling in novice female runners: A proof-of-concept study

Introduction

Many runners struggle to find a rhythm during running. This may be because 20-40% of runners experience unexplained, unpleasant breathlessness at exercise onset. Locomotor-respiratory coupling (LRC), a synchronization phenomenon in which the breath is precisely timed with the steps, may provide metabolic or perceptual benefits to address these limitations. It can also be consciously performed. Hence, we developed a custom smartphone application to provide real-time LRC guidance based on individual step rate.

Methods

Sixteen novice-intermediate female runners completed two control runs outdoors and indoors at a self-selected speed with auditory step rate feedback. Then, the runs were replicated with individualized breath guidance at specific LRC ratios. Hexoskin smart shirts were worn and analyzed with custom algorithms to estimate continuous LRC frequency and phase coupling.

Results

LRC guidance led to a large significant increase in frequency coupling outdoor from 26.3 ± 10.7 (control) to 69.9 ± 20.0 % (LRC) "attached". There were similarly large differences in phase coupling between paired trials, and LRC adherence was stronger for the indoor treadmill runs versus outdoors. There was large inter-individual variability in running pace, preferred LRC ratio, and instruction adherence metrics.

Discussion

Our approach demonstrates how personalized, step-adaptive sound guidance can be used to support this breathing strategy in novice runners. Subsequent investigations should evaluate the skill learning of LRC on a longer time basis to effectively clarify its risks and advantages.

Effects of physical stress in alpine skiing on psychological, physiological, and biomechanical parameters: An individual approach

Alpine skiing is an attractive winter sport that often includes mental and physical demands. Since skiing is often done for several hours, fatigue processes occur that might lead to action errors associated with a higher risk of accidents and injuries. The aim of this study was to investigate the timing of changes in subjective, physiological, and biomechanical parameters during a physically demanding, standardized, non-competitive alpine skiing session. A group of 22 experienced male skiers carried out 10 runs, each lasting between 150 and 180 s, at a turn rate of 80 turns per minute with their best skiing technique. Immediately after the run, skiers reported ratings of fatigue, and other affective states. During skiing, breathing pattern and biomechanical data of the ski turns as radial force, turn duration, edge angle symmetry, and a composed motion quality score were recorded. Analyses of variances on skiers showing signs of fatigue (n =16) revealed that only the subjective data changed significantly over time: fatigue and worry increased, vitality and calm decreased. Subsequently, individual change points analyses were computed to localize abrupt distribution or statistical changes in time series data. For some skiers, abrupt changes at certain runs in physiological and/or biomechanical parameters were observed in addition to subjective data. The results show general effects in subjective data, and individual fatigue-related patterns concerning the onset of changes in subjective, physiological, and biomechanical parameters. Individuality of response to fatigue should be considered when studying indicators of fatigue data. Based on the general effects in subjective data, it is concluded that focusing on self-regulation and self-awareness may play a key role, as subjective variables have been shown generally sensitive to the physical stress in alpine skiing. In the future, customized algorithms that indicate the onset of fatigue could be developed to improve alpine skiers' self-awareness and self-regulation, potentially leading to fewer action errors.

Entwicklung einer KI-gestützten Bewegungstherapie bei onkologischen Palliativpatienten

HintergrundDie wechselnde Symptomlast ist eine große Hürde in der Sporttherapie von onkologischen Palliativpatienten. Die täglich variierende Symptomstärke erschwert die Einstellung einer optimalen Trainingsbelastung und stellt neben der Motivation eine große Barriere für die Teilnahme an bewegungstherapeutischen Interventionen dar. Ein durch Künstliche Intelligenz (KI) gesteuertes Training könnte helfen, die Trainingseinheiten individuell anzupassen und die Autonomie von Palliativpatienten zu erhalten.

Methoden Fünf Patienten mit fortgeschrittener unheilbarer Krebsdiagnose haben im Rahmen der Routineversorgung eine supervidierte Bewegungstherapie absolviert. Dabei wurde ein Elektrokardiogramm über einen Polar H10 Brustgurt aufgezeichnet und daraus kardiale und respiratorische Vitalparameter extrahiert. Eine Klassifikation in drei Intensitätsstufen über KI erfolgte anhand von neuronalen Netzen.

Ergebnisse Das KI-gesteuerte Training hat eine sehr hohe Klassifikationsgüte (F1-Score: 0,95±0,05) durch die Vereinigung von respiratorischen und kardialen Vitalparametern. Diese Kombination erzielt genauere Klassifikationsergebnisse als die einzelnen Datensätze für kardiale Parameter (0,93±0,06) und respiratorische Parameter (0,72±0,06). Die Berücksichtigung einer Baselinemessung hat eine positive Wirkung auf die Klassifikationsgenauigkeit.

Diskussion Diese Studie stellt die erste Untersuchung zum Einsatz von KI zur Klassifizierung von trainingswissenschaftlichen Inhalten bei onkologischen Palliativpatienten dar. Diese vulnerable Patientengruppe kann von einer objektiven Erfassung des Belastungsniveaus anhand von Parametern des kardiovaskulären Systems profitieren. Mit nur fünf Patienten wird die Aussagekraft dieser explorativen Studie über Kreuzvalidierung hergestellt. Zukünftig sollen weitere Parameter wie ein subjektives Empfinden, Alter, Größe und Geschlecht die Klassifikation weiter verbessern. In einem integrierten System ist eine individuelle Trainingssteuerung in Echtzeit möglich.

Estimation of Respiratory Frequency in Women and Men by Kubios HRV Software Using the Polar H10 or Movesense Medical ECG Sensor during an Exercise Ramp

Monitoring of the physiologic metric, respiratory frequency (RF), has been shown to be of value in health, disease, and exercise science. Both heart rate (HR) and variability (HRV), as represented by variation in RR interval timing, as well as analysis of ECG waveform variability, have shown potential in its measurement. Validation of RF accuracy using newer consumer hardware and software applications have been sparse. The intent of this report is to assess the precision of the RF derived using Kubios HRV Premium software version 3.5 with the Movesense Medical sensor single-channel ECG (MS ECG) and the Polar H10 (H10) HR monitor. Gas exchange data (GE), RR intervals (H10), and continuous ECG (MS ECG) were recorded from 21 participants performing an incremental cycling ramp to failure. Results showed high correlations between the reference GE and both the H10 (r = 0.85, SEE = 4.2) and MS ECG (r = 0.95, SEE = 2.6). Although median values were statistically different via Wilcoxon testing, adjusted median differences were clinically small for the H10 (RF about 1 breaths/min) and trivial for the MS ECG (RF about 0.1 breaths/min). ECG based measurement with the MS ECG showed reduced bias, limits of agreement (maximal bias, -2.0 breaths/min, maximal LoA, 6.1 to -10.0 breaths/min) compared to the H10 (maximal bias, -3.9 breaths/min, maximal LoA, 8.2 to -16.0 breaths/min). In conclusion, RF derived from the combination of the MS ECG sensor with Kubios HRV Premium software, tracked closely to the reference device through an exercise ramp, illustrates the potential for this system to be of practical usage during endurance exercise.

Performance of Contactless Respiratory Rate Monitoring by Albus HomeTM, an Automated System for Nocturnal Monitoring at Home: A Validation Study

Respiratory rate (RR) is a clinically important predictor of cardio-respiratory deteriorations. The mainstay of clinical measurement comprises the manual counting of chest movements, which is variable between clinicians and limited to sporadic readings. Emerging solutions are limited by poor adherence and acceptability or are not clinically validated. Albus Home^TM is a contactless and automated bedside system for nocturnal respiratory monitoring that overcomes these limitations. This study aimed to validate the accuracy of Albus Home compared to gold standards in real-world sleeping environments. Participants undertook overnight monitoring simultaneously using Albus Home and gold-standard polygraphy with thoraco-abdominal respiratory effort belts (SomnomedicsEU). Reference RR readings were obtained by clinician-count of polygraphy data. For both the Albus system and reference, RRs were measured in 30-s segments, reported as breaths/minute, and compared. Accuracy was defined as the percentage of RRs from the Albus system within ±2 breaths/minute of reference counts. Across a diverse validation set of 32 participants, the mean accuracy exceeded 98% and was maintained across different participant characteristics. In a Bland-Altman analysis, Albus RRs had strong agreement with reference mean differences and the limits of agreement of -0.4 and ±1.2 breaths/minute, respectively. Albus Home is a contactless yet accurate system for automated respiratory monitoring. Validated against gold -standard methods, it enables long-term, reliable nocturnal monitoring without patient burden.

Enhancing instantaneous oxygen uptake estimation by non-linear model using cardio-pulmonary physiological and motion signals

Oxygen uptake (VO₂) is an important parameter in sports medicine, health assessment and clinical treatment. At present, more and more wearable devices are used in daily life, clinical treatment and health care. The parameters obtained by wearables have great research potential and application prospect. In this paper, an instantaneous VO₂ estimation model based on XGBoost was proposed and verified by using data obtained from a medical-grade wearable device (Beijing SensEcho) at different posture and activity levels. Furthermore, physiological characteristics extracted from single-lead electrocardiogram, thoracic and abdominal respiration signal and tri-axial acceleration signal were studied to optimize the model. There were 29 healthy volunteers recruited for the study to collect data while stationary (lying, sitting, standing), walking, Bruce treadmill test and recuperating with SensEcho and the gas analyzer (Metalyzer 3B). The results show that the VO₂ values estimated by the proposed model are in good agreement with the true values measured by the gas analyzer (R² = 0.94 ± 0.03, n = 72,235), and the mean absolute error (MAE) is 1.83 ± 0.59 ml/kg/min. Compared with the estimation method using a separate heart rate as input, our method reduced MAE by 54.70%. At the same time, other factors affecting the performance of the model were studied, including the influence of different input signals, gender and movement intensity, which provided more enlightenment for the estimation of VO₂. The results show that the proposed model based on cardio-pulmonary physiological signals as inputs can effectively improve the accuracy of instantaneous VO₂ estimation in various scenarios of activities and was robust between different motion modes and state. The VO₂ estimation method proposed in this paper has the potential to be used in daily life covering the scenario of stationary, walking and maximal exercise.

Feasibility of a tele-prehabilitation program in high-risk patients with colon or rectal cancer undergoing elective surgery: a feasibility study

Background

Prehabilitation appears to be an effective strategy to reduce postoperative complications and enhance recovery after colorectal surgery. Although many patients prefer (unsupervised) home-based prehabilitation, adherence can be problematic. Combining home-based prehabilitation with tele-monitoring might demonstrate a higher adherence than unsupervised prehabilitation; however, evidence on its feasibility and effectiveness in patients with colorectal cancer scheduled for elective surgery who are at high risk for postoperative complications is lacking. The aim of this study was to assess the feasibility of a bimodal tele-prehabilitation program in patients with colorectal cancer at high risk for postoperative complications.

Methods

High-risk patients (oxygen uptake at the ventilatory anaerobic threshold ≤11 mL/kg/min or oxygen uptake at peak exercise ≤ 18 mL/kg/min) with colorectal cancer were included in a home-based bimodal tele-prehabilitation program. The program consisted of a personalized tele-monitored moderate to high-intensity interval training intervention and nutritional counseling. Feasibility was measured by participation rate, dropout rate, adherence to the physical exercise training session’s frequency, intensity, and time, and retention rate. Patient appreciation was measured by a patient appreciation questionnaire. Changes in preoperative physical fitness as secondary outcomes were quantified by time to exhaustion on a constant work rate (cycle) test, number of repetitions on the 30-s chair-stand test, and walking speed on the 4-m gait speed test.

Results

The participation rate was 81%, there were no adverse events, and all participants managed to complete the tele-prehabilitation program (retention rate of 100%). Adherence with regard to the exercise program’s frequency, intensity, and time was respectively 91%, 84%, and 100%. All participants appreciated the tele-prehabilitation program. Time to exhaustion on the constant work rate test improved (not statistically significant) from a pre-prehabilitation median score of 317 seconds to a post-prehabilitation median score of 412 seconds (p = 0.24). Median number of repetitions on the 30-s chair-stand test improved from 12 to 16 (p = 0.01).

Conclusions

Tele-prehabilitation seems feasible in high-risk patients with colorectal cancer, but efforts should be made to further improve adherence to physical exercise training intensity. More research is needed to establish the (cost-)effectiveness of tele-prehabilitation regarding preoperative improvements in preoperative aerobic fitness and postoperative reduction of complications.

Trial registration

ISRCTN, ISRCTN64482109. Registered 09 November 2021 - Retrospectively registered.

A Systematic Review and Meta-Analysis on the Association and Differences between Aerobic Threshold and Point of Optimal Fat Oxidation

Over the past two decades, scientists have attempted to evaluate whether the point of maximal fat oxidation (FATmax) and the aerobic threshold (AerT) are connected. The existence of such a relationship would allow a more tailored training approach for athletes while improving the efficacy of individualized exercise prescriptions when treating numerous health-related issues. However, studies have reported conflicting results, and this issue remains unresolved. This systematic review and meta-analysis aimed: (i) to examine the strength of the association between FATmax and AerT by using the effect size (ES) of correlation coefficient (r) and standardized mean difference (SMD); (ii) to identify potential moderators and their influence on ES variability. This study was registered with PROSPERO (CRD42021239351) and ClinicalTrials (NCT03789045). PubMed and Google Scholar were searched and fourteen articles, consisting of overall 35 ES for r and 26 ES for SMD were included. Obtained ESs were analyzed using a multilevel random-effects meta-analysis. Our results support the presence of a significant association between FATmax and AerT exercise intensities. In conclusion, due to the large ES variance caused by clinical and methodological differences among the studies, we recommend that future studies follow strict standardization of data collection and analysis of FATmax and AerT-related outcomes.

How to Investigate the Effect of Music on Breathing during Exercise: Methodology and Tools

Music is an invaluable tool to improve affective valence during exercise, with the potential contribution of a mechanism called rhythmic entrainment. However, several methodological limitations impair our current understanding of the effect of music on relevant psychophysiological responses to exercise, including breathing variables. This study presents conceptual, methodological, and operational insight favoring the investigation of the effect of music on breathing during exercise. Three tools were developed for the quantification of the presence, degree, and magnitude of music-locomotor, locomotor-breathing, and music-breathing entrainment. The occurrence of entrainment was assessed during 30 min of moderate cycling exercise performed either when listening to music or not, and was complemented by the recording of relevant psychophysiological and mechanical variables. Respiratory frequency and expiratory time were among the physiological variables that were affected to a greater extent by music during exercise, and a significant (p < 0.05) music-breathing entrainment was found in all 12 participants. These findings suggest the importance of evaluating the effect of music on breathing responses to exercise, with potential implications for exercise prescription and adherence, and for the development of wearable devices simultaneously measuring music, locomotor, and breathing signals.

Breath Tools: A Synthesis of Evidence-Based Breathing Strategies to Enhance Human Running

Running is among the most popular sporting hobbies and often chosen specifically for intrinsic psychological benefits. However, up to 40% of runners may experience exercise-induced dyspnoea as a result of cascading physiological phenomena, possibly causing negative psychological states or barriers to participation. Breathing techniques such as slow, deep breathing have proven benefits at rest, but it is unclear if they can be used during exercise to address respiratory limitations or improve performance. While direct experimental evidence is limited, diverse findings from exercise physiology and sports science combined with anecdotal knowledge from Yoga, meditation, and breathwork suggest that many aspects of breathing could be improved via purposeful strategies. Hence, we sought to synthesize these disparate sources to create a new theoretical framework called “Breath Tools” proposing breathing strategies for use during running to improve tolerance, performance, and lower barriers to long-term enjoyment.

Facile Fabrication of Multilayer Stretchable Electronics via a Two-mode Mechanical Cutting Process

A time- and cost-effective fabrication methodology via a two-mode mechanical cutting process for multilayer stretchable electronics has been developed without using the conventional photolithography-based processes. A commercially available vinyl cutter is used for defining complex patterns on designated material layers by adjusting the applied force and the depth of the cutting blade. Two distinct modes of mechanical cutting can be achieved and employed to establish the basic fabrication procedures for common features in stretchable electronics, such as the metal interconnects, contact pads, and openings by the "tunnel cut" mode, and the flexible overall structure by the "through cut" mode. Three robust and resilient stretchable systems have been demonstrated, including a water-resistant, omnidirectionally stretchable supercapacitor array, a stretchable mesh applicable in sweat extraction and sensing, and a skin-mountable human breathing monitoring patch. Results show excellent electronic performances of these devices made of multilayer functional materials after repetitive large deformations.

Increasing Oxygen Uptake in Cross-Country Skiers by Speed Variation in Work Intervals

PURPOSE

Accumulated time at a high percentage of peak oxygen consumption (VO2peak) is important for improving performance in endurance athletes. The present study compared the acute physiological and perceived effects of performing high-intensity intervals with roller ski double poling containing work intervals with (1) fast start followed by decreasing speed (DEC), (2) systematic variation in exercise intensity (VAR), and (3) constant speed (CON).

METHODS

Ten well-trained cross-country skiers (double-poling VO2peak 69.6 [3.5] mL·min-1·kg-1) performed speed- and duration-matched DEC, VAR, and CON on 3 separate days in a randomized order (5 × 5-min work intervals and 3-min recovery).

RESULTS

DEC and VAR led to longer time ≥90% VO2peak (P = .016 and P = .033, respectively) and higher mean %VO2peak (P = .036, and P = .009) compared with CON, with no differences between DEC and VAR (P = .930 and P = .759, respectively). VAR, DEC, and CON led to similar time ≥90% of peak heart rate (HRpeak), mean HR, mean breathing frequency, mean ventilation, and mean blood lactate concentration ([La-]). Furthermore, no differences between sessions were observed for perceptual responses, such as mean rate of perceived exertion, session rate of perceived exertion or pain score (all Ps > .147).

CONCLUSIONS

In well-trained XC skiers, DEC and VAR led to longer time ≥90% of VO2peak compared with CON, without excessive perceptual effort, indicating that these intervals can be a good alternative for accumulating more time at a high percentage of VO2peak and at the same time mimicking the pronounced variation in exercise intensities experienced during XC-skiing competitions.

Estimating Respiratory Rate From Breath Audio Obtained Through Wearable Microphones

Respiratory rate (RR) is a clinical metric used to assess overall health and physical fitness. An individual's RR can change from their baseline due to chronic illness symptoms (e.g., asthma, congestive heart failure), acute illness (e.g., breathlessness due to infection), and over the course of the day due to physical exhaustion during heightened exertion. Remote estimation of RR can offer a cost-effective method to track disease progression and cardio-respiratory fitness over time. This work investigates a model-driven approach to estimate RR from short audio segments obtained after physical exertion in healthy adults. Data was collected from 21 individuals using microphone-enabled, near-field headphones before, during, and after strenuous exercise. RR was manually annotated by counting perceived inhalations and exhalations. A multi-task Long-Short Term Memory (LSTM) network with convolutional layers was implemented to process mel-filterbank energies, estimate RR in varying background noise conditions, and predict heavy breathing, indicated by an RR of more than 25 breaths per minute. The multi-task model performs both classification and regression tasks and leverages a mixture of loss functions. It was observed that RR can be estimated with a concordance correlation coefficient (CCC) of 0.76 and a mean squared error (MSE) of 0.2, demonstrating that audio can be a viable signal for approximating RR.Clinical relevance-The subject technology facilitates the use of accessible, aesthetically acceptable wearable headphones to provide a technologically efficient and cost-effective method to estimate respiratory rate and track cardio-respiratory fitness over time.

Applicability of Physiological Monitoring Systems within Occupational Groups: A Systematic Review

The emergence of physiological monitoring technologies has produced exceptional opportunities for real-time collection and analysis of workers' physiological information. To benefit from these safety and health prognostic opportunities, research efforts have explored the applicability of these devices to control workers' wellbeing levels during occupational activities. A systematic review is proposed to summarise up-to-date progress in applying physiological monitoring systems for occupational groups. Adhering with the PRISMA Statement, five databases were searched from 2014 to 2021, and 12 keywords were combined, concluding with the selection of 38 articles. Sources of risk of bias were assessed regarding randomisation procedures, selective outcome reporting and generalisability of results. Assessment procedures involving non-invasive methods applied with health and safety-related goals were filtered. Working-age participants from homogeneous occupational groups were selected, with these groups primarily including firefighters and construction workers. Research objectives were mainly directed to assess heat stress and physiological workload demands. Heart rate related variables, thermal responses and motion tracking through accelerometry were the most common approaches. Overall, wearable sensors proved to be valid tools for assessing physiological status in working environments. Future research should focus on conducting sensor fusion assessments, engaging wearables in real-time evaluation methods and giving continuous feedback to workers and practitioners.

Indirect Estimation of Breathing Rate from Heart Rate Monitoring System during Running

Recent advances in wearable technologies integrating multi-modal sensors have enabled the in-field monitoring of several physiological metrics. In sport applications, wearable devices have been widely used to improve performance while minimizing the risk of injuries and illness. The objective of this project is to estimate breathing rate (BR) from respiratory sinus arrhythmia (RSA) using heart rate (HR) recorded with a chest belt during physical activities, yielding additional physiological insight without the need of an additional sensor. Thirty-one healthy adults performed a run at increasing speed until exhaustion on an instrumented treadmill. RR intervals were measured using the Polar H10 HR monitoring system attached to a chest belt. A metabolic measurement system was used as a reference to evaluate the accuracy of the BR estimation. The evaluation of the algorithms consisted of exploring two pre-processing methods (band-pass filters and relative RR intervals transformation) with different instantaneous frequency tracking algorithms (short-term Fourier transform, single frequency tracking, harmonic frequency tracking and peak detection). The two most accurate BR estimations were achieved by combining band-pass filters with short-term Fourier transform, and relative RR intervals transformation with harmonic frequency tracking, showing 5.5% and 7.6% errors, respectively. These two methods were found to provide reasonably accurate BR estimation over a wide range of breathing frequency. Future challenges consist in applying/validating our approaches during in-field endurance running in the context of fatigue assessment.

Enhanced Breathing Pattern Detection during Running Using Wearable Sensors

Breathing pattern (BP) is related to key psychophysiological and performance variables during exercise. Modern wearable sensors and data analysis techniques facilitate BP analysis during running but are lacking crucial validation steps in their deployment. Thus, we sought to evaluate a wearable garment with respiratory inductance plethysmography (RIP) sensors in combination with a custom-built algorithm versus a reference spirometry system to determine its concurrent validity in detecting flow reversals (FR) and BP. Twelve runners completed an incremental running protocol to exhaustion with synchronized spirometry and RIP sensors. An algorithm was developed to filter, segment, and enrich the RIP data for FR and BP estimation. The algorithm successfully identified over 99% of FR with an average time lag of 0.018 s (−0.067,0.104) after the reference system. Breathing rate (BR) estimation had low mean absolute percent error (MAPE = 2.74 [0.00,5.99]), but other BP components had variable accuracy. The proposed system is valid and practically useful for applications of BP assessment in the field, especially when measuring abrupt changes in BR. More studies are needed to improve BP timing estimation and utilize abdominal RIP during running.

Non-Invasive Physiological Monitoring for Physical Exertion and Fatigue Assessment in Military Personnel: A Systematic Review

During operational activities, military personnel face extremely demanding circumstances, which when combined lead to severe fatigue, influencing both their well-being and performance. Physical exertion is the main condition leading to fatigue, and its continuous tracking would help prevent its effects. This review aimed to investigate the up-to-date progress on non-invasive physiological monitoring to evaluate situations of physical exertion as a pre-condition to fatigue in military populations, and determine the potential associations between physiological responses and fatigue, which can later result in decision-making indicators to prevent health-related consequences. Adhering to the PRISMA Statement, four databases (Scopus, Science Direct, Web of Science and PubMed) were used for a literature search based on combinations of keywords. The eligibility criteria focused on studies monitoring physiological variables through non-invasive objective measurements, with these measurements being developed in military field, combat, or training conditions. The review process led to the inclusion of 20 studies. The findings established the importance of multivariable assessments in a real-life context to accurately characterise the effects of military practices. A tendency for examining heart rate variables, thermal responses, and actigraphy measurements was also identified. The objectives and experimental protocols were diverse, but the effectiveness of non-invasive measurements in identifying the most fatigue-inducing periods was demonstrated. Nevertheless, no assessment system for standardised application was presented. Future work may include the development of assessment methods to translate physiological recordings into actionable information in real-time and mitigate the effects of fatigue on soldiers’ performance accurately.

Intercostal Muscles Oxygenation and Breathing Pattern during Exercise in Competitive Marathon Runners

The study aimed to evaluate the association between the changes in ventilatory variables (tidal volume (Vt), respiratory rate (RR) and lung ventilation (V.E)) and deoxygenation of m.intescostales (∆SmO₂-m.intercostales) during a maximal incremental exercise in 19 male high-level competitive marathon runners. The ventilatory variables and oxygen consumption (V.O₂) were recorded breath-by-breath by exhaled gas analysis. A near-infrared spectroscopy device (MOXY^®) located in the right-hemithorax allowed the recording of SmO₂-m.intercostales. To explore changes in oxygen levels in muscles with high demand during exercise, a second MOXY^® records SmO₂-m.vastus laterallis. The triphasic model of exercise intensity was used for evaluating changes in SmO₂ in both muscle groups. We found that ∆SmO₂-m.intercostales correlated with V.O_2-peak (r = 0.65; p = 0.002) and the increase of V.E (r = 0.78; p = 0.001), RR (r = 0.54; p = 0.001), but not Vt (p = 0.210). The interaction of factors (muscles × exercise-phases) in SmO₂ expressed as an arbitrary unit (a.u) was significant (p = 0.005). At VT1 there was no difference (p = 0.177), but SmO₂-m.intercostales was higher at VT2 (p < 0.001) and V.O_2-peak (p < 0.001). In high-level competitive marathon runners, the m.intercostales deoxygenation during incremental exercise is directly associated with the aerobic capacity and increased lung ventilation and respiratory rate, but not tidal volume. Moreover, it shows less deoxygenation than m.vastus laterallis at intensities above the aerobic ventilatory threshold.

Non-Contact Respiratory Monitoring Using an RGB Camera for Real-World Applications

Respiratory monitoring is receiving growing interest in different fields of use, ranging from healthcare to occupational settings. Only recently, non-contact measuring systems have been developed to measure the respiratory rate (fR) over time, even in unconstrained environments. Promising methods rely on the analysis of video-frames features recorded from cameras. In this work, a low-cost and unobtrusive measuring system for respiratory pattern monitoring based on the analysis of RGB images recorded from a consumer-grade camera is proposed. The system allows (i) the automatized tracking of the chest movements caused by breathing, (ii) the extraction of the breathing signal from images with methods based on optical flow (FO) and RGB analysis, (iii) the elimination of breathing-unrelated events from the signal, (iv) the identification of possible apneas and, (v) the calculation of fR value every second. Unlike most of the work in the literature, the performances of the system have been tested in an unstructured environment considering user-camera distance and user posture as influencing factors. A total of 24 healthy volunteers were enrolled for the validation tests. Better performances were obtained when the users were in sitting position. FO method outperforms in all conditions. In the fR range 6 to 60 breaths/min (bpm), the FO allows measuring fR values with bias of −0.03 ± 1.38 bpm and −0.02 ± 1.92 bpm when compared to a reference wearable system with the user at 2 and 0.5 m from the camera, respectively.

Sensing leg movement enhances wearable monitoring of energy expenditure

Physical inactivity is the fourth leading cause of global mortality. Health organizations have requested a tool to objectively measure physical activity. Respirometry and doubly labeled water accurately estimate energy expenditure, but are infeasible for everyday use. Smartwatches are portable, but have significant errors. Existing wearable methods poorly estimate time-varying activity, which comprises 40% of daily steps. Here, we present a Wearable System that estimates metabolic energy expenditure in real-time during common steady-state and time-varying activities with substantially lower error than state-of-the-art methods. We perform experiments to select sensors, collect training data, and validate the Wearable System with new subjects and new conditions for walking, running, stair climbing, and biking. The Wearable System uses inertial measurement units worn on the shank and thigh as they distinguish lower-limb activity better than wrist or trunk kinematics and converge more quickly than physiological signals. When evaluated with a diverse group of new subjects, the Wearable System has a cumulative error of 13% across common activities, significantly less than 42% for a smartwatch and 44% for an activity-specific smartwatch. This approach enables accurate physical activity monitoring which could enable new energy balance systems for weight management or large-scale activity monitoring.

Flexible, Highly Sensitive Paper-Based Screen Printed MWCNT/PDMS Composite Breath Sensor for Human Respiration Monitoring

Accurate measurement and monitoring of respiration is vital in patients affected by severe acute respiratory syndrome coronavirus - 2 (SARS-CoV-2). Patients with severe chronic diseases and pneumonia need continuous respiration monitoring and oxygenation support. Existing respiratory sensing techniques require direct contact with the human body along with expensive and heavy Holter monitors for continuous real-time monitoring. In this work, we propose a low-cost, non-invasive and reliable paper-based wearable screen printed sensor for human respiration monitoring as an effective alternative of existing sensing systems. The proposed sensor was fabricated using traditional screen printing of multi-walled carbon nanotubes (MWCNTs) and polydimethylsiloxane (PDMS) composite based interdigitated electrodes on paper substrate. The paper substrate was used as humidity sensing material of the sensor. The hygroscopic nature of paper during inhalation and exhalation causes a change in dielectric constant, which in turn changes the capacitance of the sensor. The composite interdigitated electrode configuration exhibited better response times with a rise time of 1.178s being recorded during exhalation and fall time of 0.88s during inhalation periods. The respiration rate of sensor was successfully examined under various breathing conditions such as normal breathing, deep breathing, workout, oral breathing, nasal breathing, fast breathing and slow breathing by employing it in a wearable mask, a mandatory wearable product during the current COVID-19 pandemic situation.Thus, the above proposed sensor may hold tremendous potential in wearable/flexible healthcare technology with good sensitivity, stability, biodegradability and flexibility at this time of need.

The psychophysiological response during post-traumatic stress disorder treatment with modular motion-assisted memory desensitisation and reconsolidation (3MDR)

Background: Psychophysiological changes are part of post-traumatic stress disorder (PTSD) symptomatology and can signal emotional engagement during psychological treatment. Objectives: The aim of this study was to explore psychophysiological responses during multi-modular motion-assisted memory desensitization and reconsolidation (3MDR) therapy. Increased self-reported distress, substantially increased heart rate (HR) and breathing rate (BR) were expected at the start of therapy and predicted to improve over time. Since physical exercise demands during therapy were low, any large HR or BR responses were considered part of the psychophysiological response. Methods: This study used pooled data collected during a randomized controlled trial of 3MDR, which demonstrated significant improvement as measured by the Clinician Administered PTSD Scale. Whilst attending therapy, HR and BR data, subjective units of distress (SUD) score and phrases to describe feelings whilst exposed to trauma-related images were collected continuously from 37 UK male military veterans with PTSD. Results: HR and BR were significantly increased throughout all sessions (p < .01 for both). Whilst HR was raised slightly remaining on average below 100 beats/minute, BR was increased substantially with average values between 40 and 50 breaths/minute. SUD scores were very high during therapy which concurred with the many negative feelings experienced during therapy sessions. Across the course of the treatment, SUD scores (p < .01) and negative feelings were reduced (p < .001), and positive feelings have increased (p < .01) significantly, reflecting improvements in clinicians assessed PTSD symptoms. Across therapy sessions, HR (p = .888) and BR (p = .466) responses did not change. Conclusions: The strong psychophysiological response alongside high levels of self-reported distress and negative feelings is interpreted as high emotional engagement during therapy. A novel finding was the very significant BR increase throughout recorded sessions. Future PTSD research should include BR response to therapy and explore breathing control as a treatment target.

Activity-Aware Vital SignMonitoring Based on a Multi-Agent Architecture

Vital sign monitoring outside the clinical environment based on wearable sensors ensures better support in assessing a patient’s health condition, and in case of health deterioration, automatic alerts can be sent to the care providers. In everyday life, the users can perform different physical activities, and considering that vital sign measurements depend on the intensity of the activity, we proposed an architecture based on the multi-agent paradigm to handle this issue dynamically. Different types of agents were proposed that processed different sensor signals and recognized simple activities of daily living. The system was validated using a real-life dataset where subjects wore accelerometer sensors on the chest, wrist, and ankle. The system relied on ontology-based models to address the data heterogeneity and combined different wearable sensor sources in order to achieve better performance. The results showed an accuracy of 95.25% on intersubject activity classification. Moreover, the proposed method, which automatically extracted vital sign threshold ranges for each physical activity recognized by the system, showed promising results for remote health status evaluation.

Applying ubiquitous sensing to estimate perceived exertion based on cardiorespiratory features

Reliable monitoring of one’s response to exercise intensity is imperative to effectively plan and manage training, but not always practical in impact sports settings. This study aimed to evaluate if an inexpensive mobile cardio-respiratory monitoring system can achieve similar performance to a metabolic cart in estimating rated perceived exertion. Eight adult men volunteered to perform treadmill tests under different conditions. Cardiorespiratory data were collected using a metabolic cart and an instrumented oral-cavity device, as well as their ratings of perceived exertion. Pearson correlation corrected for repeated measurements and stepwise regression analysis were used to observe the relationship between the cardiorespiratory features and the ratings of perceived exertion and determine the proportion of the variance of exertion that could be explained by the measurements. Minute ventilation was found to be the most associated variable to perceived exertion, closely followed by a novel metric called the audio minute volume, which can be collected by the oral-cavity device. A generalised linear model combining minute ventilation, audio minute volume, heart rate and respiration rate accounted for 64% of the variance in perceived exertion, whilst a model with only audio minute volume accounted for 56%. Our study indicates that minute ventilation is key to estimating perceived exertion during indoor running exercises. Audio minute volume was also observed to perform comparably to a lab-based metabolic cart in estimating perceived exertion. This research indicates that mobile techniques offer the potential for real-world data collection of an athlete’s physiological load and estimation of perceived exertion.