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Preanesthetic drugs play an essential role in general anesthesia for smooth induction and recovery and have multiple pharmacodynamic properties; however, they are considered blockers of histamine receptor type 1. The fundamental goal was to determine the properties of orphenadrine as a pre-anesthetic in a chick model. Healthy, unsexed chicks were used. Up-and-down methods determined the safety profile of orphenadrine for the average lethal dose and the average analgesic dose. We administered orphenadrine at different doses and times. We then calculated the onset, duration, and recovery of anesthesia using xylazine and ketamine, as well as the body temperature and breathing rate of the chicks that had undergone general anesthesia. The median lethal dose was 121.10±8.49 mg/kg, intraperitoneal (IP), and the median analgesic dose was 2.49±0.21 mg/kg IP. Orphenadrine at 2.5, 5, and 10 mg/kg produced analgesia in a dose-dependent manner. Administration of orphenadrine at 5 mg/kg and IP at different times significantly prolonged the duration of anesthesia for xylazine and ketamine in a time-dependent manner, and body temperature and breathing rate were significantly decreased in the lateral recumbency situation in comparison with pre-lateral recumbency and post-lateral recumbency (recovery). Orphenadrine at 5,10, and 20 mg/kg, IP followed by 30 minutes produced a significant decrease in the onset of anesthesia, prolonged duration, and shortened recovery time compared with ketamine and xylazine alone. Orphenadrine also made a significant decrease in body temperature before lateral recumbency compared with xylazine and ketamine. Body temperature and breathing rate were significantly lower in lateral recumbency than in pre- and post-lateral recumbency. Conclusion: Orphenadrine is a safe drug because of the wide range between the average lethal and analgesic doses. It is also a good preanesthetic drug that prolongs the duration of anesthesia and shortens the recovery time in a Chick's model. However, because it has a hypothermic property, it must be used with caution when used as a preanesthetic.

The rapid growth of available wearable technologies, particularly in the healthcare sector, has ushered in a new era of digital health. This progress has introduced new possibilities for the monitoring of vital signs, including breathing rate (BR). BR is a crucial health parameter used to assess an individual's overall well-being; specifically, it can be considered a precise indicator of pathological conditions and stressors. The aim of this study is to conduct a metrological characterization of one of the most widely used BR sensors for the measurement of BR (i.e., Zephyr BioHarness 3.0), comparing it to a BR gold standard monitor (i.e., a spirometer), in determined test conditions, including both natural and defined BR patterns. Additionally, the Monte Carlo method (MCM) was applied to evaluate the propagation of the measurement uncertainty in the identification of the peaks of respiratory signal, used to calculate BR. Results reveal that the Zephyr BioHarness 3.0 sensor provides highly accurate BR measurements, with a precision of ±1 bpm. Bland-Altman analysis indicates a 95 % confidence interval of [-2; 3] bpm, demonstrating a close agreement with the reference instrument. The Pearson's correlation coefficient of 0.95 further validates the linear correlation between the reference/test measurements. The simulation based on MCM provides an expanded uncertainty of ±2 bpm (coverage factor k = 2) in BR estimation due to the uncertainty in the peaks identification (compatible with the accuracy provided by the manufacturer). These results highlight the Zephyr BioHarness 3.0 sensor reliability for BR monitoring while emphasizing the significance of accounting for different disturbing factors, e.g., uncertainty in peak detection during data analysis, also to provide a rigorous level of confidence in the measurement results, hence being able to properly interpret them in biomedical applications.

In this short article, we present a new method to use a smartphone placed unattached on a subject’s chest in the supine position to obtain heartbeat and breathing signals and estimate heart and breathing rates, simultaneously. We collected 3-axis accelerometer, gyroscope, and magnetometer signals and performed sensor fusion to extract a user’s breathing signal and breathing rate. A hidden Markov model was used to segment the ballistocardiograph/seismocardiograph signals and extract the heart rate. The smartphone application was verified against breathing belt measurements and electrocardiogram measurements. We modified and proposed several suitable signal quality metrics for seismocardiograph signals. The overall results show that the application accurately estimated the breathing and heart rates, achieving a minimum mean percent error of 2.52% for breathing and 2.33% for heart rate. This work is a big step forward for vital sign estimation using inexpensive pervasive devices.

This paper introduces and evaluates an innovative sensor for unobtrusive in-car respiration monitoring, mounted on the backrest of the driver’s seat. The sensor seamlessly integrates into the vehicle, measuring breathing rates continuously without requiring active participation from the driver. The paper proves the feasibility of unobtrusive in-car measurements over long periods of time. Operation of the sensor was investigated over 12 participants sitting in the driver seat. A total of 107 min of driving in diverse conditions with overall coverage rate of 84.45% underscores the sensor potential to reliably capture physiological changes in breathing rate for fatigue and stress detection.

Vital sign monitoring is dominated by precise but costly contact-based sensors. Contactless devices such as radars provide a promising alternative. In this article, the effects of lateral radar positions on breathing and heartbeat extraction are evaluated based on a sleep study. A lateral radar position is a radar placement from which multiple human body zones are mapped onto different radar range sections. These body zones can be used to extract breathing and heartbeat motions independently from one another via these different range sections. Radars were positioned above the bed as a conventional approach and on a bedside table as well as at the foot end of the bed as lateral positions. These positions were evaluated based on six nights of sleep collected from healthy volunteers with polysomnography (PSG) as a reference system. For breathing extraction, comparable results were observed for all three radar positions. For heartbeat extraction, a higher level of agreement between the radar foot end position and the PSG was found. An example of the distinction between thoracic and abdominal breathing using a lateral radar position is shown. Lateral radar positions could lead to a more detailed analysis of movements along the body, with the potential for diagnostic applications.

Personality traits, the consistent individual behavioral differences, are currently gaining much attention in studies of natural bird populations. However, associations between personality traits and parasite infections are not often investigated. Even less attention has been given to studies of birds in the high-elevation region such as the Tibetan plateau. This research aims to examine the relationship between avian malaria parasites and two personality traits in a population of the Chestnut Thrush (Turdus rubrocanus) breed in the Tibetan plateau.Our results revealed no evidence of sex bias in malaria parasite prevalence. Furthermore, we found no effect of infection status on two personality scores: activity and boldness. Additionally, no effects on the activity level or boldness were observed for different parasite lineages of Haemoproteus, Leucocytozoon, the sex of the birds, or their interactions. Similarly, we did not find any relationship between activity level and boldness with nestling numbers, sex, or their interactions. Notably, individuals with a larger number of offspring tended to display greater boldness. Our findings indicate that blood parasite infections are common in this population but do not significantly impact the personality of the birds.

Breathing interventions have been shown to improve sport performance. Although evidence exists to support the role of perceived arousal as a critical underlying mechanism of breathing interventions, methodological differences in the literature preclude clear understanding of potential contributing factors to the effectiveness of such interventions. Under neutral contexts, we have demonstrated attention, dyspnea, and hindrance may need to be considered as mediators of how breathing frequency affects motor performance. We sought to extend our previous findings to determine how breathing frequency affects motor performance under varying emotional conditions. Participants (N = 35, Mage = 21.68, SD = 2.96; 20 females) performed slow, normal, and fast metronome-paced breathing while viewing pleasant and unpleasant stimuli prior to executing a pinch grip task. Performance was assessed via reaction time (RT), variability (V) and error (AE). Assessment of indices of perceived arousal included measuring heart rate variability (HRV) and visual analog scale responses. Visual analog scales were also used to assess attention, dyspnea, and hindrance. Repeated measures ANOVAs showed slow breathing increased RT and HRV compared to normal and fast breathing under emotional conditions (all p’s

The characterization of breathing dynamics provides researchers and clinicians the ability to differentiate respiratory compensation, impairment, disease progression, ventilator assistance, and the onset of respiratory failure. However, within many sub-fields of respiratory physiology, we still have challenges identifying changes within the breathing dynamics and critical respiratory states. We discuss one fundamental modeling of breathing and how modeling imprecise assumptions decades ago regarding breathing are still propagating into our quantitative analysis today, limiting our characterization and modeling of breathing. The assumption that breathing is a continuous sinusoidal wave that can consist of a single frequency which is composed of a stationary time-invariant process has limited our expanded discussion of breathing dynamics, modeling, functional testings, and metrics. Therefore, we address major misnomers regarding breathing dynamics, specifically rate, rhythm, frequency, and period. We demonstrate how these misnomers impact the characterization and modeling through the force equations that are linked to the Work of Breathing (WoB) and our interpretation of breathing dynamics through the fundamental models and create possible erroneous evaluations of work of breathing. This discussion and simplified non-periodic WoB models ultimately sets the foundation for improved quantitative approaches needed to further our understanding of breathing dynamics, compensation, and adaptation.

Abnormalities in cardiorespiratory measurements have repeatedly been found in patients with panic disorder (PD) during laboratory-based assessments. However, recordings performed outside laboratory settings are required to test the ecological validity of these findings. Wearable devices, such as sensor-imbedded garments, biopatches, and smartwatches, are promising tools for this purpose. We systematically reviewed the evidence for wearables-based cardiorespiratory assessments in PD by searching for publications on the PubMed, PsycINFO, and Embase databases, from inception to 30 July 2022. After the screening of two-hundred and twenty records, eight studies were included. The limited number of available studies and critical aspects related to the uncertain reliability of wearables-based assessments, especially concerning respiration, prevented us from drawing conclusions about the cardiorespiratory function of patients with PD in daily life. We also present preliminary data on a pilot study conducted on volunteers at the Villa San Benedetto Menni Hospital for evaluating the accuracy of heart rate (HR) and breathing rate (BR) measurements by the wearable Zephyr BioPatch compared with the Quark-b2 stationary testing system. Our exploratory results suggested possible BR and HR misestimation by the wearable Zephyr BioPatch compared with the Quark-b2 system. Challenges of wearables-based cardiorespiratory assessment and possible solutions to improve their reliability and optimize their significant potential for the study of PD pathophysiology are presented.

Competitive indoor climbing has increased in popularity at the youth, collegiate, and Olympic levels. A critical aspect for improving performance is characterizing the physiologic response to different climbing strategies (e.g., work/rest patterns, pacing) and techniques (e.g., body position and movement) relative to location on climbing wall with spatially varying characteristics (e.g., wall inclinations, position of foot/hand holds). However, this response is not well understood due to the limited capabilities of climbing-specific measurement and assessment tools. In this study, we developed a novel method to examine time-resolved sensor-based measurements of multiple personal biometrics at different microlocations (finely spaced positions; MLs) along a climbing route. For the ML-specific biometric system (MLBS), we integrated continuous data from wearable biometric sensors and smartphone-based video during climbing, with a customized visualization and analysis system to determine three physiologic parameters (heart rate, breathing rate, ventilation rate) and one body movement parameter (hip acceleration), which are automatically time-matched to the corresponding video frame to determine ML-specific biometrics. Key features include: (1) biometric sensors that are seamlessly embedded in the fabric of an athletic compression shirt, and do not interfere with climbing performance, (2) climbing video, and (3) an interactive graphical user interface to rapidly visualize and analyze the time-matched biometrics and climbing video, determine timing sequence between the biometrics at key events, and calculate summary statistics. To demonstrate the capabilities of MLBS, we examined the relationship between changes in ML-specific climbing characteristics and changes in the physiologic parameters. Our study demonstrates the ability of MLBS to determine multiple time-resolved biometrics at different MLs, in support of developing and assessing different climbing strategies and training methods to help improve performance.

Waterless transportation for live grouper is a novel mode of transport that not only saves money, but also lowers wastewater pollution. Technical obstacles remain, however, in achieving intelligent monitoring and a greater survival rate. During live grouper waterless transportation, the stress response is a key indicator that affects the survival life-span of the grouper. Studies based on breathing rate analysis have demonstrated that among many stress response parameters, breathing rate is the most direct parameter to reflect the intensity. Conventional measurement methods, which set up sensors on the gills of groupers, interfere with the normal breathing of living aquatic products and are complex in system design. We designed a new breathing monitoring system based on a completely non-destructive approach. The system allows the real-time monitoring of living aquatic products’ breathing rate by simply placing the millimeter wave radar on the inner wall of the incubator and facing the gills. The system we developed can detect more parameters in the future, and can replace the existing system to simplify the study of stress responses.

Assessments of respiratory response and animal activity are useful endpoints in drug pharmacology and safety research. We investigated whether continuous, direct monitoring of breathing rate and body motion in animals in the home cage using the Vum Digital Smart House can complement standard measurements in enabling more granular detection of the onset and severity of physiologic events related to lung injury in a well-established rodent model of paraquat (PQ) toxicity. In rats administered PQ, breathing rate was significantly elevated while body motion was significantly reduced following dosing and extending throughout the 14-day study duration for breathing rate and at least 5 days for both nighttime and daytime body motion. Time course differences in these endpoints in response to the potential ameliorative test article bardoxolone were also readily detected. More complete than standard in-life measurements, breathing rate and body motion tracked injury progression continuously over the full study time period and aligned with, and informed on interval changes in clinical pathology. In addition, breathing rates correlated with terminal pathology measurements, such as normalized lung weights and histologic alveolar damage and edema. This study is a preliminary evaluation of the technology; our results demonstrate that continuously measured breathing rate and body motion served as physiologically relevant readouts to assess lung injury progression and drug response in a respiratory injury animal model.

Breathing rate is considered one of the fundamental vital signs and a highly informative indicator of physiological state. Given that the monitoring of heart activity is less complex than the monitoring of breathing, a variety of algorithms have been developed to estimate breathing activity from heart activity. However, estimating breathing rate from heart activity outside of laboratory conditions is still a challenge. The challenge is even greater when new wearable devices with novel sensor placements are being used. In this paper, we present a novel algorithm for breathing rate estimation from photoplethysmography (PPG) data acquired from a head-worn virtual reality mask equipped with a PPG sensor placed on the forehead of a subject. The algorithm is based on advanced signal processing and machine learning techniques and includes a novel quality assessment and motion artifacts removal procedure. The proposed algorithm is evaluated and compared to existing approaches from the related work using two separate datasets that contains data from a total of 37 subjects overall. Numerous experiments show that the proposed algorithm outperforms the compared algorithms, achieving a mean absolute error of 1.38 breaths per minute and a Pearson’s correlation coefficient of 0.86. These results indicate that reliable estimation of breathing rate is possible based on PPG data acquired from a head-worn device.

The Sleep Number smart bed uses embedded ballistocardiography, together with network connectivity, signal processing, and machine learning, to detect heart rate (HR), breathing rate (BR), and sleep vs. wake states. This study evaluated the performance of the smart bed relative to polysomnography (PSG) in estimating epoch-by-epoch HR, BR, sleep vs. wake, mean overnight HR and BR, and summary sleep variables. Forty-five participants (aged 22–64 years; 55% women) slept one night on the smart bed with standard PSG. Smart bed data were compared to PSG by Bland–Altman analysis and Pearson correlation for epoch-by-epoch HR and epoch-by-epoch BR. Agreement in sleep vs. wake classification was quantified using Cohen’s kappa, ROC analysis, sensitivity, specificity, accuracy, and precision. Epoch-by-epoch HR and BR were highly correlated with PSG (HR: r = 0.81, |bias| = 0.23 beats/min; BR: r = 0.71, |bias| = 0.08 breaths/min), as were estimations of mean overnight HR and BR (HR: r = 0.94, |bias| = 0.15 beats/min; BR: r = 0.96, |bias| = 0.09 breaths/min). Calculated agreement for sleep vs. wake detection included kappa (prevalence and bias-adjusted) = 0.74 ± 0.11, AUC = 0.86, sensitivity = 0.94 ± 0.05, specificity = 0.48 ± 0.18, accuracy = 0.86 ± 0.11, and precision = 0.90 ± 0.06. For all-night summary variables, agreement was moderate to strong. Overall, the findings suggest that the Sleep Number smart bed may provide reliable metrics to unobtrusively characterize human sleep under real life-conditions.

The present paper proposes the design of a sleep monitoring platform. It consists of an entire sleep monitoring system based on a smart glove sensor called UpNEA worn during the night for signals acquisition, a mobile application, and a remote server called AeneA for cloud computing. UpNEA acquires a 3-axis accelerometer signal, a photoplethysmography (PPG), and a peripheral oxygen saturation (SpO2) signal from the index finger. Overnight recordings are sent from the hardware to a mobile application and then transferred to AeneA. After cloud computing, the results are shown in a web application, accessible for the user and the clinician. The AeneA sleep monitoring activity performs different tasks: sleep stages classification and oxygen desaturation assessment; heart rate and respiration rate estimation; tachycardia, bradycardia, atrial fibrillation, and premature ventricular contraction detection; and apnea and hypopnea identification and classification. The PPG breathing rate estimation algorithm showed an absolute median error of 0.5 breaths per minute for the 32 s window and 0.2 for the 64 s window. The apnea and hypopnea detection algorithm showed an accuracy (Acc) of 75.1%, by windowing the PPG in one-minute segments. The classification task revealed 92.6% Acc in separating central from obstructive apnea, 83.7% in separating central apnea from central hypopnea and 82.7% in separating obstructive apnea from obstructive hypopnea. The novelty of the integrated algorithms and the top-notch cloud computing products deployed, encourage the production of the proposed solution for home sleep monitoring.

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.

The aim of this paper is designing an algorithm dubbed "pattern" to detect electrocardiogram (ECG) components accurately by searching exactly in the right places of peaks and getting exhaustive information related to the heart. Then, using the obtained results to propose a method for constructing respiration signal properly, by calculating the mean of R peaks to determine inspiration and expiration phases and calculating the amount of change for other peaks to be added during inspiration phase and subtracted during the expiration phase. The proposed method improves envelope method which only depends on the size of R to construct respiration signals. The results show that the pattern algorithm is guaranteed method and useful for detecting ECG components and exploiting them for constructing respiration signal work better than envelope method.

Research works on operator monitoring underline the benefit of taking into consideration several signal modalities to improve accuracy for an objective mental state diagnosis. Heart rate (HR) is one of the most utilized systemic measures to assess cognitive workload (CW), whereas, respiration parameters are hardly utilized. This study aims at verifying the contribution of analyzing respiratory signals to extract features to evaluate driver’s activity and CW variations in driving. Eighteen subjects participated in the study. The participants carried out two different cognitive tasks requiring different CW demands, a single task as well as a competing cognitive task realized while driving in a simulator. Our results confirm that both HR and breathing rate (BR) increase in driving and are sensitive to CW. However, HR and BR are differently modulated by the CW variations in driving. Specifically, HR is affected by both driving activity and CW, whereas, BR is suitable to evidence a variation of CW only when driving is not required. On the other hand, spectral features characterizing respiratory signal could be also used similarly to HR variability indices to detect high CW episodes. These results hint the use of respiration as an alternative to HR to monitor the driver mental state in autonomic vehicles in order to predict the available cognitive resources if the user has to take over the vehicle.

Continued developments of sensor technology including hardware miniaturization and increased sensitivity have enabled the development of less intrusive methods to monitor physiological parameters during daily life. In this work, we present methods to recover cardiac and respiratory parameters using accelerometer and gyroscope sensors on the wrist. We demonstrate accurate measurements in a controlled laboratory study where participants (n = 12) held three different positions (standing up, sitting down and lying down) under relaxed and aroused conditions. In particular, we show it is possible to achieve a mean absolute error of 1.27 beats per minute (STD: 3.37) for heart rate and 0.38 breaths per minute (STD: 1.19) for breathing rate when comparing performance with FDA-cleared sensors. Furthermore, we show comparable performance with a state-of-the-art wrist-worn heart rate monitor, and when monitoring heart rate of three individuals during two consecutive nights of in-situ sleep measurements.

Since predominant high temperatures could alter thermic equilibrium, the knowledge of dairy cattle thermoregulation characteristics on tropical environment is very important. The higher energy consume to maintain homeothermy could damage production and reproduction. Therefore, this revision aimed to analyze some thermoregulatory characteristics and fur of dairy cattle housed in tropical environment. The maximum and minimum values of rectal temperature found was 41.14°C (½ Gir ½ Holstein) and 37.09°C (lactating cows in the morning), breathing rate of 137.12mov/min (½ Gir ½ Holstein) and 22mov.min-1 (Holstein and Girolanda), sweating rate of 239.42g.m-2 .h-1 (½ Gir ½ Holstein) and 90.5g.m-2 .h-1 (¾ Holstein Zebu), surface temperature of 44.0°C (Holstein at 12 hours) and 22.0°C (½ Gir ½ Holstein, at 6am), hair coat thickness of 5.31mm ( ½ Gir ½ Holstein) and 1.93mm (Holstein), length of hair coat of 16.11mm (Holstein) and 8.08mm (Caracu Caldeano). The rectal temperature and breathing rate of dairy cattle raised on tropical environment could be altered by intrinsic and extrinsic factors. The hair coat thickness and length are lower on summer and spring compared with fall and winter.

Nocturnal vocal activity in dolphins is often thought to be associated with feeding activity. However, when no food resources are available dolphins spend their time for the most part resting/sleeping. While unihemispherically sleeping, dolphins mostly swim slowly and synchronously in close proximity with one or more other individuals. Although vocal activity is lower during resting/sleeping, dolphins are not entirely silent the entire night. However, nothing is known about the temporal patterning of vocal activity at night and its potential relation with activity in dolphins. Here we recorded the vocal activity of a group of five captive bottlenose dolphins at night while having no feeding opportunity, examined whether there was any temporal pattern and/or a relation with breathing activity, used here as an index of overall activity. The temporal pattern revealed two peaks of intense whistle activity (8 p.m. and midnight), which were followed by a strong decrease of whistle rate and a slight decrease of respiration rate. We suggest that the high vocal activity at the peak periods might indicate socializing periods and that dolphins, like many other species, show periods of increased social and vocal interactions (chorusing?) before starting to rest/sleep, maybe to ensure the synchrony of slow swimming observed in this species. These findings contribute to a better understanding of nocturnal vocal activity in cetaceans and suggest new lines of research on vocal/social activity of dolphins in relation to presleep and resting behavior.

In this work, a fiber Bragg grating (FBG) based sensing system for wheelchair pressure ulcer prevention was developed. Six FBGs were strategically positioned in a wheelchair to monitor the more prominent bone areas, namely scapulas (right (SR) and left (SL)), ischiatic zone (right (IR) and left (IL)), and heels (right (HR) and left (HL)). The sensing architecture was tested by a female user during pressure relief exercises, to verify its effectiveness on pressure monitoring. The proposed system proves to be a compact and reliable solution for wheelchair pressure ulcer prevention, making it a suitable alternative to existing conventional electronic sensors, with the advantage of being immune to electromagnetic interferences and usable in humid environments. In addition to the pressure, the breathing rate was also monitored. By combining the proposed sensing architecture with a wheelchair user detection software, it is possible to create alerts for the user to know when a new position should be adopted, in order to relieve the pressure in a specific area, thus avoiding one of the biggest problems for such patients, pressure ulcers.

This study is based on the relationship between meditation, the present moment, and psychophysiology. We employed the metronome task to operationalize the extension of the present moment. A pre-post longitudinal study was conducted. The performance in the metronome task was compared before and after the interventions (meditation, story). The aim was to assess whether physiological changes (heart, breathing) during meditation influence the temporal-integration (TI) of metronome beats. Mindfulness meditators either meditated (n = 41) or listened to a story (n = 43). The heart and breathing activity were recorded during the intervention and compared to a resting-state condition. By applying path analyses we found that meditation led to an increase of the duration of integration intervals at the slowest metronome frequency (inter-stimulus interval, ISI = 3 s). After meditation, the higher the heart-rate variability (i.e., the root mean square of successive differences, RMSSD), the longer the duration of integration intervals at the fastest frequency (ISI = 0.33 s). Moreover, the higher the breathing rate during meditation, the greater the integration of intervals at ISI = 1 s. These findings add evidence to meditation-induced changes on the TI of metronome beats and the concept of the embodiment of mental functioning.

Although there is growing evidence that breathing is modulated by various motor and cognitive activities, the nature of breathing in musical performance has been little explored. The present study examined the temporal breath pattern in piano performance, aiming to elucidate how breath timing is related to musical organization/events and performance. In the experiments, the respiration of 15 professional and amateur pianists, playing 10 music excerpts in total (from four-octave C major scale, Hanon’s exercise, J. S. Bach’s Invention, Mozart’s Sonatas, and Debussy’s Clair de lune), was monitored by capnography. The relationship between breathing and musical characteristics was analyzed. Five major results were obtained. 1) Mean breath interval was shortened for excerpts in faster tempi. 2) Fluctuation of breath intervals was reduced for the pieces for finger exercise and those in faster tempi. Pianists showing large within-trial fluctuation also exhibited large inter-excerpt difference. 3) Inter-trial consistency of the breath patterns depended on the excerpts. Consistency was generally reduced for the excerpts that could be performed mechanically (i.e., pieces for finger exercise), but interestingly, one third of the participant showed consistent patterns for the simple scale, correlated with the ascending/descending sequences. 4) Pianists tended to exhale just after the music onsets, inhale at the rests, and inhibit inhale during the slur parts. There was correlation between breathing pattern and two-voice polyphonic structure for several participants. 5) Respiratory patterns were notably different among the pianists. Every pianist showed his or her own characteristic features commonly for various musical works. These findings suggest that breathing in piano performance depends not only on musical parameters and organization written in the score but also some pianist-dependent factors which might be ingrained to individual pianists.

The aim of the present study was to confirm whether feeding influences the resting breathing rate and to observe possible alterations in blood gas and pH levels produced by feeding in unanesthetized sloths (Bradypus variegatus). Five adult male sloths (4.1 ± 0.6 kg) were placed daily in an experimental chair for a period of at least 4 h for sitting adaptation. Five measurements were made for each sloth. However, the sloths one, two and five were studied once and the sloths three and four were studied twice. Breathing rate was determined with an impedance meter and the output signal was digitized. Arterial blood samples were collected for blood gas analysis with a BGE electrolytes analyzer and adjusted for the animal's body temperature and hemoglobin content. The data are reported as mean ± SD and were collected during the resting period (8:00-10:00 h) and during the feeding period (16:00-18:00 h). The mean breathing rate increased during mastication of ymbahuba leaves (rest: 5.0 ± 1, feeding: 10 ± 1 bpm). No significant alterations were observed in arterial pH (rest: 7.42 ± 0.05, feeding: 7.45 ± 0.03), PCO2 (rest: 35.2 ± 5.3, feeding: 33.3 ± 4.4 mmHg) or PO2 (rest: 77.5 ± 8.2, feeding: 78.4 ± 5.2 mmHg) levels. These results indicate that in unanesthetized sloths 1) feeding evokes an increase in breathing rate without a significant change in arterial pH, PCO2 or PO2 levels, and 2) the increase in breathing rate produced by feeding probably is due to the act of mastication.