Respiratory Belt Research Articles

Respiratory Rate Estimation from Thermal Video Data Using Spatio-Temporal Deep Learning.

Thermal videos provide a privacy-preserving yet information-rich data source for remote health monitoring, especially for respiration rate (RR) estimation. This paper introduces an end-to-end deep learning approach to RR measurement using thermal video data. A detection transformer (DeTr) first finds the subject's facial region of interest in each thermal frame. A respiratory signal is estimated from a dynamically cropped thermal video using 3D convolutional neural networks and bi-directional long short-term memory stages. To account for the expected phase shift between the respiration measured using a respiratory effort belt vs. a facial video, a novel loss function based on negative maximum cross-correlation and absolute frequency peak difference was introduced. Thermal recordings from 22 subjects, with simultaneous gold standard respiratory effort measurements, were studied while sitting or standing, both with and without a face mask. The RR estimation results showed that our proposed method outperformed existing models, achieving an error of only 1.6 breaths per minute across the four conditions. The proposed method sets a new State-of-the-Art for RR estimation accuracy, while still permitting real-time RR estimation.

Learning end-to-end respiratory rate prediction of dairy cows from red, green, and blue videos

Respiratory rate (RR) is an important indicator of the health and welfare status of dairy cows. In recent years, progress has been made in monitoring the RR of dairy cows using video data and learning methods. However, existing approaches often involve multiple processing modules, such as region of interest (ROI) detection and tracking, which can introduce errors that propagate through successive steps. The objective of this study was to develop an end-to-end computer vision method to predict RR of dairy cows continuously and automatically. The method leverages the capabilities of a state-of-the-art Transformer model, VideoMAE, which divides video frames into patches as input tokens, enabling the automated selection and featurization of relevant regions, such as a cow's abdomen, for predicting RR. The original encoder of VideoMAE was retained, and a classification head was added on top of it. Further, the weights of the first 11 layers of the pre-trained model were kept, whereas the weights of the final layer and classifier were fine-tuned using video data collected in a tiestall barn from 6 dairy cows. Respiratory rates measured using a respiratory belt for individual cows were serving as the ground truth (GT). The evaluation of the developed model was conducted using multiple metrics, including mean absolute error (MAE) of 2.58 breaths per minute (bpm), root mean squared error (RMSE) of 3.52 bpm, root mean squared prediction error (RMSPE; as a proportion of observed mean) of 15.03%, and Pearson r of 0.86. Compared with a conventional method involving multiple processing modules, the end-to-end approach performed better in terms of MAE, RMSE, and RMSPE. These results suggest the potential to implement the developed computer vision method for an end-to-end solution, for monitoring RR of dairy cows automatically in a tiestall setting. Future research on integrating this method with other behavioral detection and animal identification algorithms for animal monitoring in a freestall dairy barn can be beneficial for a broader application.

Respiration recording for fMRI: breathing belt versus spine coil sensor

Abstract Physiological signals such as pulse and respiration strongly contribute to non-neuronal signal change of the blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI). This has been observed not only during task-based but also during resting-state fMRI measurements, where the confounding influence of physiological signals is most pronounced. Over the last decades, a variety of techniques evolved, aiming at detecting and removing physiological artifacts in fMRI time series. These follow either a solely data-driven approach or rely on externally recorded physiological data. To record cardiac and respiratory signals, typically pulse oximetry or electrocardiography (ECG) and a respiration belt are used, respectively. New technologies allow to capture respiratory signal directly with a sensor placed within the spine coil in the patient table, eliminating the need of a respiration belt, which considerably increases participants’ comfort. However, little is known about the effectiveness of these new technologies and how they compare to the standard respiration belt recording. In the current study, we compared the two devices, respiration belt and spine coil sensor, in their suitability for physiological noise removal during a visual perception task and during rest. We did not find any differences in resting-state functional connectivity (RSFC), stimulus-related activity, or residual noise between data corrected with the two recording devices. Our results show that spine coil-derived respiration recordings are as good as belt respiration recordings for physiological noise removal in task-induced activity, with spine coil recordings having an additional advantage in terms of participants’ comfort and artifact susceptibility.

Autonomous Triboelectric Smart Textile Sensor for Vital Sign Monitoring.

Wearable smart textile sensors for monitoring vital signs are fast, noninvasive, and highly desirable for personalized health management to diagnose health anomalies such as cardiovascular diseases and respiratory dysfunction. Traditional biosignal sensors, with power consumption issues, constrain the use of wearable medical devices. This study introduces an autonomous triboelectric smart textile sensor (AUTS) made of reduced graphene oxide/manganese dioxide/polydimethylsiloxane (RGO-M-PDMS) and polytetrafluoroethylene (TEFLON)-knitted silver electrode, offering promise for vital sign monitoring with self-powering, flexibility, and wearability. The sensor exhibits impressive output performance, with a sensitivity of 7.8 nA/kPa, response time of ≈40 ms, good stability of >15,000 cycles, stretchability of up to 40%, and machine washability of >20 washes. The AUTS has been integrated to the TriBreath respiratory belt for monitoring respiratory signals and pulse strap for pulse signals concurrently at different body pulse points. These sensors wirelessly transmitted the acquired biosignals to a smartphone, demonstrating the potential of a self-powered and real-time vital sign monitoring system.

Quantitative validation of the suprasternal pressure signal to assess respiratory effort during sleep

Objective. Intra-esophageal pressure (Pes) measurement is the recommended gold standard to quantify respiratory effort during sleep, but used to limited extent in clinical practice due to multiple practical drawbacks. Respiratory inductance plethysmography belts (RIP) in conjunction with oronasal airflow are the accepted substitute in polysomnographic systems (PSG) thanks to a better usability, although they are partial views on tidal volume and flow rather than true respiratory effort and are often used without calibration. In their place, the pressure variations measured non-invasively at the suprasternal notch (SSP) may provide a better measure of effort. However, this type of sensor has been validated only for respiratory events in the context of obstructive sleep apnea syndrome (OSA). We aim to provide an extensive verification of the suprasternal pressure signal against RIP belts and Pes, covering both normal breathing and respiratory events. Approach. We simultaneously acquired suprasternal (207) and esophageal pressure (20) signals along with RIP belts during a clinical PSG of 207 participants. In each signal, we detected breaths with a custom algorithm, and evaluated the SSP in terms of detection quality, breathing rate estimation, and similarity of breathing patterns against RIP and Pes. Additionally, we examined how the SSP signal may diverge from RIP and Pes in presence of respiratory events scored by a sleep technician. Main results. The SSP signal proved to be a reliable substitute for both esophageal pressure (Pes) and respiratory inductance plethysmography (RIP) in terms of breath detection, with sensitivity and positive predictive value exceeding 75%, and low error in breathing rate estimation. The SSP was also consistent with Pes (correlation of 0.72, similarity 80.8%) in patterns of increasing pressure amplitude that are common in OSA. Significance. This work provides a quantitative analysis of suprasternal pressure sensors for respiratory effort measurements.

Importance of both Hemidiaphragms in Maintaining Optimal Breathing Mechanics, Respiratory Rate, and Hemoglobin Oxygen Saturation: a Case Study

Background: The mechanical process of breathing consists of the abdominal breathing (AB) driven/generated by the diaphragm, and thoracic breathing (TB) generated by the intercostal muscles. The coordinated movements of the two portions of diaphragm account for 80% of the inspiration, although their exact roles are still investigated. While bilateral diaphragmatic paralysis causes severe shortness of breath, unilateral hemidiaphragm paralysis is asymptomatic at rest, making it challenging to diagnose. Objective: To measure and compare the amplitudes of abdominal and chest movements in different body positions between a healthy individual and an individual with unilateral diaphragmatic paralysis (phrenic nerve injury). Methods: Changes in the circumference of the abdomen and chest were measured during inhalation and exhalation with respiratory plethysmography belts (placed on standardized reproducible positions on the chest, and abdomen) in different body positions: sitting (SI), standing (ST), lying (SU) and prone (PR) in a healthy (H) individual and an individual with unilateral diaphragmatic paralysis. (Ph). Breathing frequency and other parameters were calculated from the measured signals. Furthermore, the blood oxygen saturation (SpO2) was measured with a pulse oximeter. Results: Percent (%) contribution of abdominal breathing H/Ph: SI: 29.6/16.0; ST: 72.8/50.3; SU: 90.6/-53.5; PR: 32.8/1.1. A negative sign shows paradoxical breathing. Respiratory rate (1/min) H/Ph: SI:18.7/19.4; ST: 19.0/15.0; SU: 15.9/37.5; PR: 16.6/35.9. Phase angle of abdominal and thoracic breathing curves (degrees) H/Ph: SI: 4.09/-5.73; ST: -20.82/-9.48; SU: 3.68/184.29; PR: 25.08/-26.51. In case of a negative sign, chest breathing precedes abdominal expansion, and vice versa in the case of a positive sign. A value around 180 degrees indicates paradoxical breathing, seen in Ph, when SpO2 significantly decreased: SI: 93% vs. SU: 82%. Conclusions: In different body positions, the amplitude changes of the abdomen and chest differed substantially during the complete respiratory cycle. Both portions of diaphragm are important because in unilateral phrenic nerve injury, abdominal breathing markedly decreased in most body positions compared to a healthy individual. Furthermore, paradoxical breathing occurred in a supine position, as indicated by a change in the phase angle. The lowest respiratory rate was measured in standing position (15/min), in which the participation of the abdomen/chest ratio was 50.3%, / 49.7%, while the highest value was obtained in supine position (38 breaths/min), which coincided by a decreased hemoglobin oxygen saturation / i.e. oxygen intake. In case of hemidiaphragm paralysis, the diminished mechanical breathing effciency requires a higher respiratory rate to sustain/maintain hemoglobin oxygen saturation. However, this elevated respiratory rate also increases energy consumption, potentially resulting in dyspnea during physical exertion / exercise. Ministry of Innovation and Technology (MIT) of Hungary-NRDI TKP2020-NKA-17, TKP2021-EGA-37, and National Research, Development, and Innovation Offce (NKFIH) OTKA K 132596 K_19, and Hungarian Academy of Sciences, Post-Covid 2021-34, and HUN-REN-SE: 02068 of Hungary. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Body Position Dependent Participation of Abdominal and Thoracic Breathing Movements During the Breathing Cycle

Aims: Both abdominal and thoracic breathing movements play important roles in the mechanics of breathing, participating differently in various body positions with abdominal breathing having a greater role. Recent studies showed that an early proning position of awake, non-intubated patients during the COVID-19 pandemic, even during pregnancy (PMID: 32320506, PMID: 33309507, PMID: 34915799) significantly affected the ventilatory parameters and mortality of SARS-CoV-2 patients. Thus, we hypothesized that in different body positions the participation of abdominal (AB) and thoracic breathing (TB) during the complete respiratory cycle (CRC) is different. To test this, we measured the participation of AB and TB to the CRC in different body positions under resting conditions. Methods: In young participants (N=26) age between 18 and 24 (M=21.3±1.6), changes in abdominal and chest circumferences were measured using plethysmography respiratory belts, during inhalation and exhalation in standing (ST), sitting (SI), supine (SU), prone (PR), and all on fours (AF) body positions. Respiratory frequency was also measured. Results: In different positions, the contribution of AB and TB to CRC were significantly different (F(4,100)=4.999, p=0.004, η2p=0.17). AB was significantly higher than TB in all positions (p<0.001). More specifically, AB gradually increased, while TB gradually decreased in the following order: SU(AB/TB) = 74.8±12.9%/25.2%, ST = 69±16%/31%, PR = 66.8±20.2%/33.2%, SI = 65.5±14.8%/34.5%, AF = 61.1±15.1%/38.9%. A significantly higher value was measured in the SU position compared to AF (p<0.001) and SI (p=0.011) positions; PR and ST positions showed intermediate values, which were not significantly different from those yielded by either of the other positions. Respiratory frequency was similar in different body positions. Conclusions: These data show that different body positions significantly affect the participation of abdominal and thoracic breathing during resting condition, underscoring not only the importance of respiratory distress patients positioning during hospitalization, but its usefulness in developing a respiratory training plan for elite athletes to optimize their physical and mental performance in competitive sports. AK: Ministry of Innovation and Technology (MIT) of Hungary-NRDI TKP2020-NKA-17, TKP2021-EGA-37, and National Research, Development, and Innovation Offce (NKFIH) OTKA K 132596 K_19, and Hungarian Academy of Sciences, Post-Covid 2021-34, and HUN-REN-SU: 02068 of Hungary, JT: ÚNKP-22-4-II-SE-4 (JT), TKP2021-EGA-25. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Feasibility of the application of frequency modulated continuous wave radar trigger technique in abdominal magnetic resonance imaging

Objective: To evaluate and compare the image quality of T2-weighted abdominal scans using a respiratory belt trigger (RBT) and frequency-modulated continuous wave (FMCW)-trigger (FT) techniques and to explore the feasibility of FT in abdominal magnetic resonance imaging (MRI).Methods: The study prospectively included 28 subjects, each undergoing abdominal scans with both RBT and FT. The analysis focused on 64 inconsistent trigger segments from the respiratory curves triggered by RBT and FMCW. Parameters such as inconsistent trigger type (ITT), number of inconsistent trigger points (ITPs), ratio of ITP (ITR), and single-segment ITR (SITR) were derived from these curves. Image quality was evaluated by two observers using subjective scoring, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The assessments classified image quality as either “good” or “poor.” Consistency in image quality assessment between observers was determined using the kappa test and intraclass correlation coefficient (ICC). The chi-square test, Student’s t-test, and the Mann–Whitney U test were employed to compare the categorical and continuous variables between the RBT and FT groups.Results: The observers showed a high level of agreement in image quality assessment. There were no significant differences in ITR, SITR, acquisition time, SNR, and CNR between the RBT and FT groups (all p > 0.05). Both subjective and objective evaluations indicated no notable difference in image quality between the two groups (p > 0.05).Conclusion: The FMCW trigger technique is a viable alternative to the traditional respiratory belt trigger in scenarios of relatively stable breathing. It offers potential benefits, such as reducing operational demands on technicians and improving MRI workflow efficiency.

Extended MRI-based PET motion correction for cardiac PET/MRI

PurposeA 2D image navigator (iNAV) based 3D whole-heart sequence has been used to perform MRI and PET non-rigid respiratory motion correction for hybrid PET/MRI. However, only the PET data acquired during the acquisition of the 3D whole-heart MRI is corrected for respiratory motion. This study introduces and evaluates an MRI-based respiratory motion correction method of the complete PET data.MethodsTwelve oncology patients scheduled for an additional cardiac 18F-Fluorodeoxyglucose (18F-FDG) PET/MRI and 15 patients with coronary artery disease (CAD) scheduled for cardiac 18F-Choline (18F-FCH) PET/MRI were included. A 2D iNAV recorded the respiratory motion of the myocardium during the 3D whole-heart coronary MR angiography (CMRA) acquisition (~ 10 min). A respiratory belt was used to record the respiratory motion throughout the entire PET/MRI examination (~ 30–90 min). The simultaneously acquired iNAV and respiratory belt signal were used to divide the acquired PET data into 4 bins. The binning was then extended for the complete respiratory belt signal. Data acquired at each bin was reconstructed and combined using iNAV-based motion fields to create a respiratory motion-corrected PET image. Motion-corrected (MC) and non-motion-corrected (NMC) datasets were compared. Gating was also performed to correct cardiac motion. The SUVmax and TBRmax values were calculated for the myocardial wall or a vulnerable coronary plaque for the 18F-FDG and 18F-FCH datasets, respectively.ResultsA pair-wise comparison showed that the SUVmax and TBRmax values of the motion corrected (MC) datasets were significantly higher than those for the non-motion-corrected (NMC) datasets (8.2 ± 1.0 vs 7.5 ± 1.0, p < 0.01 and 1.9 ± 0.2 vs 1.2 ± 0.2, p < 0.01, respectively). In addition, the SUVmax and TBRmax of the motion corrected and gated (MC_G) reconstructions were also higher than that of the non-motion-corrected but gated (NMC_G) datasets, although for the TBRmax this difference was not statistically significant (9.6 ± 1.3 vs 9.1 ± 1.2, p = 0.02 and 2.6 ± 0.3 vs 2.4 ± 0.3, p = 0.16, respectively). The respiratory motion-correction did not lead to a change in the signal to noise ratio.ConclusionThe proposed respiratory motion correction method for hybrid PET/MRI improved the image quality of cardiovascular PET scans by increased SUVmax and TBRmax values while maintaining the signal-to-noise ratio.Trial registration METC162043 registered 01/03/2017.

Performance enhancement of thermal image analysis for noncontact cardiopulmonary signal extraction

Infrared thermography (IRT) has emerged as a tool for the rapid and non-contact detection of febrile individuals in places of mass gathering. This study explores the feasibility of extracting cardiopulmonary signals (i.e., respiration and cardiac pulse signals) by analyzing thermal image sequences. A high IR spatial resolution (320 × 240 pixels) IRT was applied to acquire facial thermal image sequences at a frame rate of 60 frames per second (fps). The respiration signal was extracted by monitoring the temperature changes in the region of interest (ROI) of the nostrils caused by breathing, that is, the temperature increase during the exhalation phase and the temperature decrease during the inhalation phase. The respiration signal was extracted by picking up the rise and fall motions of the shoulders caused by breathing. The cardiac pulse signal was extracted by measuring tiny head motions accompanying the cardiac cycle on the thermal image sequences. The system was tested on 11 subjects in a laboratory setting to assess the respiration performance and pulse signal extraction. Bland–Altman and Pearson's correlation plots were used to compare the noncontact respiration rate (RR) and pulse rate (PR) measurements with contact-type ECG and respiration belt. The mean difference in the RR was − 0.2 bpm with the 95 % limit of − 5.0 to 4.6 bpm, correlation of 0.83, root mean square error (RMSE) of 2.4 bpm, and mean absolute percentage error (MAPE) of 22 %. Regarding the PR, the mean difference of 4.2 bpm with the 95 % limit of − 18 to 26 bpm, correlation of 0.67, RMSE of 12 bpm, and MAPE of 15 % were determined from comparison of the ECG and thermal camera. In summary, our findings suggest that the proposed thermal image analysis method for measuring RR and PR is promising, particularly for RR measurements. Further validation and refinement are required for the PR measurements. The results indicate that this noncontact approach has potential for various medical applications.

BreathFinder: A Method for Non-Invasive Isolation of Respiratory Cycles Utilizing the Thoracic Respiratory Inductance Plethysmography Signal.

The field of automatic respiratory analysis focuses mainly on breath detection on signals such as audio recordings, or nasal flow measurement, which suffer from issues with background noise and other disturbances. Here we introduce a novel algorithm designed to isolate individual respiratory cycles on a thoracic respiratory inductance plethysmography signal using the non-invasive signal of the respiratory inductance plethysmography belts. The algorithm locates breaths using signal processing and statistical methods on the thoracic respiratory inductance plethysmography belt and enables the analysis of sleep data on an individual breath level. The algorithm was evaluated against a cohort of 31 participants, both healthy and diagnosed with obstructive sleep apnea. The dataset consisted of 13 female and 18 male participants between the ages of 20 and 69. The algorithm was evaluated on 7.3 hours of hand-annotated data from the cohort, or 8782 individual breaths in total. The algorithm was specifically evaluated on a dataset containing many sleep-disordered breathing events to confirm that it did not suffer in terms of accuracy when detecting breaths in the presence of sleep-disordered breathing. The algorithm was also evaluated across many participants, and we found that its accuracy was consistent across people. Source code for the algorithm was made public via an open-source Python library. The proposed algorithm achieved an estimated 94% accuracy when detecting breaths in respiratory signals while producing false positives that amount to only 5% of the total number of detections. The accuracy was not affected by the presence of respiratory related events, such as obstructive apneas or snoring. This work presents an automatic respiratory cycle algorithm suitable for use as an analytical tool for research based on individual breaths in sleep recordings that include respiratory inductance plethysmography.

Numerical simulation study on dust transport law in antibiotic raw material drug powder screening workshop

To study the distribution pattern of drug dust in the antibiotic raw material drug powder screening workshop and improve the working environment, we used COMSOL Multiphysics 6.0 software to simulate and study the airflow distribution and dust transport law in the powder screening workshop. The results indicated that the dust in the powder screening workshop diffused rapidly with the airflow and reached a stable state at the 100th second. After the dust migrated to a stable state, the area with excessive dust concentration (dust concentration>6 mg/m(3)) widely distributed, mainly distributed in the middle and lower parts of the wall opposite the air inlet from the rotary vibrating screen. The distribution of dust showed a characteristic of local aggregation, and dust transport was related to airflow movement, which was prone to aggregation in areas with low airflow velocity and eddy currents. On the plane of the human respiratory belt height (h=1.5 m), the concentration near the dust producing surface was high, with local concentrations exceeding 32 mg/m(3). It was the key area for dust prevention and control. And the working environment can be improved by changing the air flow distribution in the workshop or other dust reduction methods.

Differences in the swallowing process of newborns and healthy preterm infants: first results with a non-invasive bioimpedance and electromyography measurement system

PurposePreterm infants (PI) have difficulty coordinating sucking, swallowing and breathing, and there is a risk of aspiration. The causes of this are not yet sufficiently understood. The aim of this study was to test a novel measurement device to measure breathing and pharyngeal processes involved in swallowing externally in everyday life to identify possible differences in neonates (NB) and PI.MethodsForty healthy NB were studied at 4–8 weeks of age (mean: 6.7 weeks) and 20 healthy PI (mean gestational age 30.5 weeks) at postmenstrual age (PMA) 34/35 weeks (mean PMA 35.1 weeks) during a single feeding. Surface electrodes were used to measure bioimpedance and electromyography reflecting swallow-related changes in the pharynx and muscle activation of the tongue and submental muscles. A respiratory belt was combined with recording of the depth of chest movements and the occurrence of pauses in breathing.ResultsVelocity and extent of pharyngeal closure did not differ significantly across the feeding period (velocity: p=0.09, closure: p=0.17), but during the first two suck–swallow bursts PI had greater velocity (p<0.001*) and extent of pharyngeal closure (p=0.004*) than NB. The duration of swallowing phases was significantly longer in PIs (p<0.001*), their muscle activation decreased faster (p<0.001*), and they had more pauses in breathing than NBs.ConclusionsThe novel measurement device allowed, for the first time in everyday life, the measurement of factors influencing swallowing and breath–swallow coordination in NBs and PIs. PIs showed differences from NBs most likely due to differences in muscle strength and condition.

A Radar-Based Opioid Overdose Detection Device for Public Restrooms: Design, Development, and Evaluation Study.

The opioid epidemic is a growing crisis worldwide. While many interventions have been put in place to try to protect people from opioid overdoses, they typically rely on the person to take initiative in protecting themselves, requiring forethought, preparation, and action. Respiratory depression or arrest is the mechanism by which opioid overdoses become fatal, but it can be reversed with the timely administration of naloxone. In this study, we described the development and validation of an opioid overdose detection radar (ODR), specifically designed for use in public restroom stalls. In-laboratory testing was conducted to validate the noncontact, privacy-preserving device against a respiration belt and to determine the accuracy and reliability of the device. We used an ODR system with a high-frequency pulsed coherent radar sensor and a Raspberry Pi (Raspberry Pi Ltd), combining advanced technology with a compact and cost-effective setup to monitor respiration and detect opioid overdoses. To determine the optimal position for the ODR within the confined space of a restroom stall, iterative testing was conducted, considering the radar's bounded capture area and the limitations imposed by the stall's dimensions and layout. By adjusting the orientation of the ODR, we were able to identify the most effective placement where the device reliably tracked respiration in a number of expected positions. Experiments used a mock restroom stall setup that adhered to building code regulations, creating a controlled environment while maintaining the authenticity of a public restroom stall. By simulating different body positions commonly associated with opioid overdoses, the ODR's ability to accurately track respiration in various scenarios was assessed. To determine the accuracy of the ODR, testing was performed using a respiration belt as a reference. The radar measurements were compared with those obtained from the belt in experiments where participants were seated upright and slumped over. The results demonstrated favorable agreement between the radar and belt measurements, with an overall mean error in respiration cycle duration of 0.0072 (SD 0.54) seconds for all recorded respiration cycles (N=204). During the simulated overdose experiments where participants were slumped over, the ODR successfully tracked respiration with a mean period difference of 0.0091 (SD 0.62) seconds compared with the reference data. The findings suggest that the ODR has the potential to detect significant deviations in respiration patterns that may indicate an opioid overdose event. The success of the ODR in these experiments indicates the device should be further developed and implemented to enhance safety and emergency response measures in public restrooms. However, additional validation is required for unhealthy opioid-influenced respiratory patterns to guarantee the ODR's effectiveness in real-world overdose situations.

Evaluation of the effectiveness of non-contact respiration rate detection for post-crash care application

The ability of emergency medical services (EMS) personnel to understand the mortality and morbidity risks associated with different injuries is critical for effective motor vehicle collision (MVC) post-crash care. Interwoven with this ability is the practice of accurate and efficient patient triage. Triage allows EMS to gain a better understanding of the physiological and physical status of a patient and their injuries, with the intention of identifying additional resources needed, potential treatment options, and the most appropriate care destination. An interactive, in-vehicle triage system, based on the Simple Triage and Rapid Treatment protocol, under development could lead to improved MVC triage accuracy and efficiency. As a component of that system, this study examines the effectiveness of using non-contact respiration rate detection technologies integrated into a vehicle cabin. The selected technologies included ultrasonic respiration detection, thermal respiration detection, and pressurebased detection which were all compared against data collected from a respiration belt. All technologies were integrated into a 2015 Ford Taurus. Testing took place inside the running vehicle and considered occupant weight, cabin temperature, occupant clothing weight, and environmental sound as experimental factors. Respiration rate was then calculated using a 30-second sliding window where the means and standard deviations were used to compare the accuracy and precision of the sensor systems across the experimental factors. The sensor type, temperature level, and sound level main effects significantly influenced the mean respiration rate. For the standard deviation of respiration rate, significant effects were found for the sensor type, sound level, and clothing weight main effects. Among the tested sensor systems, the pressure sensor was found to best match the accuracy and precision of the respiration belt. Future work should address limitations in the approach used for this proof-of-concept work.

On the thermographic measurement of the respiratory rate

Abstract Respiration is a vital process for normal function at every level of organization of living beings. A simple and noncontact measurement of the respiratory rate certainly offers advantages in many situations compared to classical measurements, e.g., with a respiratory measurement belt. Thus, we started a study for thermographic detection of breathing rate. For this purpose, several subjects were filmed with an infrared (IR) camera and the recordings were subjected to pixel value analysis using MATLAB. By using different regions of interest (ROIs), the pixel values were averaged and mapped graphically. The resulting graphs generally show a periodic breathing process based on the temperature changes within the selected ROIs. To put this pixel value analysis into perspective, control measurements were taken with a BIOPAC-system using a respiratory measurement belt to measure abdominal/thoracic respiration. The two sets of measurements were compared by cross correlation and a moderately strong anti-correlation was demonstrated.

Simultaneous T2 -weighted real-time MRI of two orthogonalslices.

MR guidance is used during therapy to detect and compensate for lesion motion. T2 -weighted MRI often has a superior lesion contrast in comparison to T1 -weighted real-time imaging. The purpose of this work was to design a fast T2 -weighted sequence capable of simultaneously acquiring two orthogonal slices, enabling real-time tracking of lesions. To generate a T2 contrast in two orthogonal slices simultaneously, a sequence (Ortho-SFFP-Echo) was designed that samples the T2 -weighted spin echo (S- ) signal in a TR-interleaved acquisition of two slices. Slice selection and phase-encoding directions are swapped between the slices, leading to a unique set of spin-echo signal conditions. To minimize motion-related signal dephasing, additional flow-compensation strategies are implemented. In both the abdominal breathing phantom and in vivo experiments, a time series was acquired using Ortho-SSFP-Echo. The centroid of the target was tracked in postprocessing steps. In the phantom, the lesion could be identified and delineated in the dynamic images. In the volunteer experiments, the kidney was visualized with a T2 contrast at a temporal resolution of 0.45 s under free-breathing conditions. A respiratory belt demonstrated a strong correlation with the time course of the kidney centroid in the head-foot direction. A hypointense saturation band at the slice overlap did not inhibit lesion tracking in the semi-automatic postprocessing steps. The Ortho-SFFP-Echo sequence delivers real-time images with a T2 -weighted contrast in two orthogonal slices. The sequence allows for simultaneous acquisition, which could be beneficial for real-time motion tracking in radiotherapy or interventional MRI.

Remote Respiratory and Cardiac Motion Patterns Separation with 4D Imaging Radars.

Radar-based noncontact physiological signals monitoring is meaningful for daily health monitoring, post-disaster rescue, and public security. This paper focuses on the theoretical and experimental study of noncontact respiratory and cardiac motion signals separation employing remote sensing by a four-dimensional (4D) imaging radar. To adaptively separate respiratory and cardiac motion patterns, we propose a variational mode separation (VMS) algorithm. VMS is established on optimizing a variational problem to separate different modes. It minimizes the energy overlap of the heartbeat and respiration signals as well as their harmonics with an equality constraint. Both simulation and real scene data results show that the proposed VMS algorithm is suitable for separating the weaker cardiac motion pattern from the strong respiratory motion pattern, restraining the influence of respiration harmonics on the heartbeat component. Also, the continuous remote monitoring of respiratory rate (RR) and heart rate (HR) by employing the proposed method in a real scene shows a strong consistency with the reference respiration belt and electrocardiogram (ECG). The root mean square error (RMSE) of RR and HR for the noncontact measurement are 0.13 breaths per minute (brpm) and 1.7 beats per minute (bpm), respectively.

The role of EPID in vivo dosimetry in the risk management of stereotactic lung treatments.

In this work we report our experience with the use of in vivo dosimetry (IVD) in the risk management of stereotactic lung treatments. Acommercial software based on the electronic portal imaging device (EPID) signal was used to reconstruct the actual planning target volume (PTV) dose of stereotactic lung treatments. The study was designed in two phases: i)in the observational phase, the IVD results of 41consecutive patients were reviewed and out-of-tolerance cases were studied for root cause analysis; ii)in the active phase, the IVD results of 52patients were analyzed and corrective actions were taken when needed. Moreover, proactive preventions were further introduced to reduce the risk of future failures. The error occurrence rate was analyzed to evaluate the effectiveness of proactive actions. Atotal of 330fractions were analyzed. In the first phase, 13errors were identified. In the active phase, 12errors were detected, 5of which needed corrective actions; in 4patients the actions taken corrected the error. Several preventions and barriers were introduced to reduce the risk of future failures: the planning checklist was updated, the procedure for vacuum pillows was improved, and use of the respiratory compression belt was optimized. Adecrease in the failure rate was observed, showing the effectiveness of procedural adjustment. The use of IVD allowed the quality of lung stereotactic body radiation therapy (SBRT) treatments to be improved. Patient-specific and procedural corrective actions were successfully taken as part of risk management, leading to an overall improvement in the dosimetric accuracy.

Feasibility study of the Nox-T3 device to detect swallowing and respiration pattern in neurologically impaired patients in the acute phase

Dysphagia is a frequent complication in neurologically impaired patients, which can lead to aspiration pneumonia and thus prolonged hospitalization or even death. It is essential therefore, to detect and assess dysphagia early for best patient care. Fiberoptic endoscopic and Videofluoroscopy evaluation of swallowing are the gold standard exams in swallowing studies but neither are perfectly suitable for patients with disorders of consciousness (DOC). In this study, we aimed to find the sensitivity and specificity of the Nox-T3 sleep monitor for detection of swallowing. A combination of submental and peri-laryngeal surface electromyography, nasal cannulas and respiratory inductance plethysmography belts connected to Nox-T 3 allows recording swallowing events and their coordination with breathing, providing time-coordinated patterns of muscular and respiratory activity. We compared Nox-T3 swallowing capture to manual swallowing detection on fourteen DOC patients. The Nox-T3 method identified swallow events with a sensitivity of 95% and a specificity of 99%. In addition, Nox-T3 has qualitative contributions, such as visualization of the swallowing apnea in the respiratory cycle which provide additional information on the swallowing act that is useful to clinicians in the management and rehabilitation of the patient. These results suggest that Nox-T3 could be used for swallowing detection in DOC patients and support its continued clinical use for swallowing disorder investigation.