Respiratory Measurements Research Articles

The concealed information test with a continuously moving stimulus.

The Concealed Information Test (CIT) aims to extract concealed crime-related knowledge using physiological measures. In the present study, we propose a new variant of the CIT that contains a continuously moving stimulus. A total of 81 participants were either informed or not about the specific location of an upcoming terrorist attack. The CIT consisted of a map with a superimposed moving dot, combined with measurements of respiration and electrodermal activity. The results revealed both respiratory suppression and an increase in skin conductance when the moving dot passed the target location only in informed participants. These findings showed that this new variant of the CIT can differentiate between groups of informed and uninformed individuals and an exploratory analysis revealed it can help narrow down a search area.

Noncontace Monitoring of Respiration and Heartbeat Based on Two-Wave Model Using a Millimeter-Wave MIMO FM-CW Radar

This paper deals with the non-contact measurement of heartbeat and respiration using a millimeter-wave multiple-input–multiple-output (MIMO) frequency-modulated continuous-wave (FM-CW) radar. Monitoring heartbeat and respiration is useful for detecting cardiac diseases and understanding stress levels. Contact sensors are not suitable for these sorts of long-term measurements due to the discomfort and skin irritation they cause. Therefore, the use of non-contact sensors, such as radars, is desirable. In this study, we obtained heartbeat and respiration information from phase data measured using a millimeter-wave MIMO FM-CW radar. We propose a two-wave model based on a Fourier series expansion and extract respiration and heartbeat information as a minimization problem. This model makes it possible to produce respiration and heartbeat waveforms. The produced heartbeat waveform can be used for estimating the interbeat interval (IBI). Experiments were conducted to confirm the usefulness of the proposed method. Moreover, the estimated results were compared with the contact sensor’s results. The results for both types of sensors were in good agreement.

Optimized psilocybin production in tryptophan catabolism-repressed fungi.

The high therapeutic potential of psilocybin, a prodrug of the psychotropic psilocin, holds great promise for the treatment of mental disorders such as therapy-refractory depression, alcohol use disorder and anorexia nervosa. Psilocybin has been designated a 'Breakthrough Therapy' by the US Food and Drug Administration, and therefore a sustainable production process must be established to meet future market demands. Here, we present the development of an invivo psilocybin production chassis based on repression of l-tryptophan catabolism. We demonstrate the proof of principle in Saccharomyces cerevisiae expressing the psilocybin biosynthetic genes. Deletion of the two aminotransferase genes ARO8/9 and the indoleamine 2,3-dioxygenase gene BNA2 yielded a fivefold increase of psilocybin titre. We transferred this knowledge to the filamentous fungus Aspergillus nidulans and identified functional ARO8/9 orthologs involved in fungal l-tryptophan catabolism by genome mining and cross-complementation. The double deletion mutant of A. nidulans resulted in a 10-fold increased psilocybin production. Process optimization based on respiratory activity measurements led to a final psilocybin titre of 267 mg/L in batch cultures with a space-time-yield of 3.7 mg/L/h. These results demonstrate the suitability of our engineered A. nidulans to serve as a production strain for psilocybin and other tryptamine-derived pharmaceuticals.

DBPR116, a Prodrug of BPRMU191, in Combination with Naltrexone as a Safer Opioid Analgesic Than Morphine via Peripheral Administration.

The development of opioid analgesics with reduced adverse effects is an unmet need. In a previous study, we discovered a unique combination of BPRMU191 and morphinan antagonists that produced potent antinociception with reduced adverse effects after central administration (intrathecal or intracerebroventricular). BPRMU191/naltrexone exhibits notable in vitro and in vivo pharmacological properties. However, the poor blood-brain barrier penetrative ability of BPRMU191 restricts its clinical application. In this study, we utilized a prodrug strategy to deliver sufficient brain concentrations of BPRMU191 and selected compound 2 (DBPR116) with the best physicochemical and pharmacological properties among other in vivo active prodrugs. The in vivo pharmacological studies of compound 2/naltrexone, including thermally stimulated pain, cancer pain, constipation, sedation, psychological dependence, heart rate, and respiratory frequency measurements, demonstrated that it was a safer opioid analgesic than morphine in pain control.

The H222P-Lamin mutation induces heart failure via impaired mitochondrial calcium uptake in human cardiac laminopathy

Abstract Background Mutations in LMNA gene, which encodes lamins A/C, cause a variety of diseases, called laminopathies. Some mutations are particularly associated with the occurrence of dilated cardiomyopathy. The pathological mechanisms are still unclear limiting the development of specific therapies. Purpose Here, we focused on a mutation in the LMNA gene (c.665A>C, p.His222Pro), associated with the Emery-Dreyfuss Muscular dystrophy. We used LMNA H222P mutant human induced pluripotent stem cells (hiPSCs) and CRISPR/Cas9 corrected isogenic control hiPSCs to better characterize the cardiac phenotype associated with the mutation. Methods LMNA H222P mutant and the isogenic control hiPSCs clones were differentiated into cardiomyocytes (CMs). Immunofluorescence staining was performed on hiPSC-CMs to quantify their sarcomere organization (SarcOrgScore) using a Matlab code. Ring-shaped cardiac organoids were generated to compare the contractile properties of the two clones. Calcium transients in mutant and corrected hiPSC-CMs were measured by live confocal imaging. Mitochondrial respiration was measured by Seahorse. Results hiPSC-CMs were generated from the LMNA H222P mutant and the corrected hiPSCs with no difference in the differentiation yield (proportion of troponin-positive cells: 92.74% for LMNA H222P vs. 89.38% for Ctrl-iso1, p=0.1038). The nuclei of LMNA H222P mutant hiPSC-CMs showed morphological abnormalities, typically observed with Lamin A/C mutations. hiPSC-CMs displayed well-formed sarcomeres and their organization was similar between the two cell lines. However, 3D cardiac organoids generated with LMNA H222P hiPSC-CMs showed an impaired contractility compared to control organoids. Calcium transient recordings in LMNA H222P mutant hiPSC-CMs showed a significantly higher calcium transient amplitude with a significantly slower calcium re-uptake. Transcriptomic analyses suggested a global mitochondrial dysfunction and in particular an impaired mitochondrial calcium uptake with a significantly decreased expression of the mitochondrial calcium uniporter (MCU). This decrease in MCU expression was confirmed by Western blot and was accompanied by an increased MICU1 : MCU ratio, as well as an increased PDH Ser232 and Ser300 phosphorylation, indicating a decreased mitochondrial calcium uptake in the LMNA H222P mutant hiPSC-CMs. Finally, measurement of mitochondrial respiration using Seahorse showed lower basal and maximal respiration in LMNA H222P hiPSC-CMs. Conclusions LMNA H222P mutant hiPSC-CMs exhibit contractile dysfunction associated with mitochondrial dysfunction with impaired MCU complex activity, decreased mitochondrial calcium homeostasis, and reduced mitochondrial energy production.

Sodium Alginate/MXene-Based Flexible Humidity Sensors with High-Humidity Durability and Application Potentials in Breath Monitoring and Non-Contact Human–Machine Interfaces

Flexible humidity sensors (FHSs) with fast response times and durability to high-humidity environments are highly desirable for practical applications. Herein, an FHS based on crosslinked sodium alginate (SA) and MXene was fabricated, which exhibited high sensitivity (impedance varied from 107 to 105 Ω between 10% and 90% RH), good selectivity, prompt response times (response/recover time of 4 s/11 s), high sensing linearity (R2 = 0.992) on a semi-logarithmic scale, relatively small hysteresis (~5% RH), good repeatability, and good resistance to highly humid environments (negligible changes in sensing properties after being placed in 98% RH over 24 h). It is proposed that the formation of the crosslinking structure of SA and the introduction of MXene with good conductivity and a high specific surface area contributed to the high performance of the composite FHS. Moreover, the FHS could promptly differentiate the respiration status, recognize speech, and measure fingertip movement, indicating potential in breath monitoring and non-contact human–machine interactions. This work provides guidance for developing advanced flexible sensors with a wide application scope in wearable electronics.

Monitoring and modulating respiratory drive in mechanically ventilated patients.

Respiratory drive is frequently deranged in the ICU, being associated with adverse clinical outcomes. Monitoring and modulating respiratory drive to prevent potentially injurious consequences merits attention. This review gives a general overview of the available monitoring tools and interventions to modulate drive. Airway occlusion pressure (P0.1) is an excellent measure of drive and is displayed on ventilators. Respiratory drive can also be estimated based on the electrical activity of respiratory muscles and measures of respiratory effort; however, high respiratory drive might be present in the context of low effort with neuromuscular weakness. Modulating a deranged drive requires a multifaceted intervention, prioritizing treatment of the underlying cause and adjusting ventilator settings for comfort. Additional tools include changes in PEEP, peak inspiratory flow, fraction of inspired oxygen, and sweep gas flow (in patients receiving extracorporeal life-support). Sedatives and opioids have differential effects on drive according to drug category. Monitoring response to any intervention is warranted and modulating drive should not preclude readiness to wean assessment or delay ventilation liberation. Monitoring and modulating respiratory drive are feasible based on physiological principles presented in this review. However, evidence arising from clinical trials will help determine precise thresholds and optimal interventions.

A novel missense mutation in ISCA2 causes aberrant splicing and leads to multiple mitochondrial dysfunctions syndrome 4

BackgroundIron–sulfur cluster assembly 2 (ISCA2) deficiency is linked to an autosomal recessive disorder known as multiple mitochondrial dysfunctions syndrome 4 (MMDS4). This disorder is characterized by leukodystrophy and neuroregression. Currently, most of the reported patients are from Saudi Arabia. All these patients carry a homozygous founder variant (NM_194279.2:c.229G>A:p.Gly77Ser) in ISCA2.MethodsWe describe a patient who underwent full clinical evaluation, including metabolic, neurological, and radiological examinations. Standard genetic testing, including whole exome sequencing coupled with autozygome analysis, was undertaken, as were assessments of mitochondrial DNA (mtDNA) copy number and mtDNA sequencing on DNA extracted from blood and cultured fibroblasts. Functional workup consisted of splicing assessment of ISCA2 using RT-PCR, biochemical assessment of complex I status using dipstick assays, and mitochondrial respiration measurements using a Seahorse XFp analyzer.ResultsWe present the clinical and functional characterization of a novel homozygous ISCA2 missense variant (NM_194279.3:c.70A>G:p.Arg24Gly), leading to aberrant splicing in a patient presenting with neuroregression, generalized spasticity with exaggerated deep tendon reflexes and head lag, and progressive loss of acquired milestones. The novel variant was fully segregated in a wider family and was absent in a large control cohort, ethnically matching in-house exomes, local databases such as CGMdb and Saudi Human Genome Program, and ClinVar.ConclusionsOur analyses revealed that the variant is pathogenic, disrupting normal ISCA2 splicing and presumably leading to a truncated protein that disturbs metabolic pathways in patient-derived cells.

Camera-Based Respiratory Imaging System for Monitoring Infant Thoracoabdominal Patterns of Respiration.

Existing respiratory monitoring techniques primarily focus on respiratory rate measurement, neglecting the potential of using thoracoabdominal patterns of respiration for infant lung health assessment. To bridge this gap, we exploit the unique advantage of spatial redundancy of a camera sensor to analyze the infant thoracoabdominal respiratory motion. Specifically, we propose a camera-based respiratory imaging (CRI) system that utilizes optical flow to construct a spatio-temporal respiratory imager for comparing the infant chest and abdominal respiratory motion, and employs deep learning algorithms to identify infant abdominal, thoracoabdominal synchronous, and thoracoabdominal asynchronous patterns of respiration. To alleviate the challenges posed by limited clinical training data and subject variability, we introduce a novel multiple-expert contrastive learning (MECL) strategy to CRI. It enriches training samples by reversing and pairing different-class data, and promotes the representation consistency of same-class data through multi-expert collaborative optimization. Clinical validation involving 44 infants shows that MECL achieves 70% in sensitivity and 80.21% in specificity, which validates the feasibility of CRI for respiratory pattern recognition. This work investigates a novel video-based approach for assessing the infant thoracoabdominal patterns of respiration, revealing a new value stream of video health monitoring in neonatal care.

Remote physiological signal recovery with efficient spatio-temporal modeling.

Contactless physiological signal measurement has great applications in various fields, such as affective computing and health monitoring. Physiological measurements based on remote photoplethysmography (rPPG) are realized by capturing the weak periodic color changes. The changes are caused by the variation in the light absorption of skin surface during systole and diastole stages of a functioning heart. This measurement mode has advantages of contactless measurement, simple operation, low cost, etc. In recent years, several deep learning-based rPPG measurement methods have been proposed. However, the features learned by deep learning models are vulnerable to motion and illumination artefacts, and are unable to fully exploit the intrinsic temporal characteristics of the rPPG. This paper presents an efficient spatiotemporal modeling-based rPPG recovery method for physiological signal measurements. First, two modules are utilized in the rPPG task: 1) 3D central difference convolution for temporal context modeling with enhanced representation and generalization capacity, and 2) Huber loss for robust intensity-level rPPG recovery. Second, a dual branch structure for both motion and appearance modeling and a soft attention mask are adapted to take full advantage of the central difference convolution. Third, a multi-task setting for joint cardiac and respiratory signals measurements is introduced to benefit from the internal relevance between two physiological signals. Last, extensive experiments performed on three public databases show that the proposed method outperforms prior state-of-the-art methods with the Pearson's correlation coefficient higher than 0.96 on all three datasets. The generalization ability of the proposed method is also evaluated by cross-database and video compression experiments. The effectiveness and necessity of each module are confirmed by ablation studies.

Ultrasensitive Ultrasoft Buckled Crack‐Based Sensor for Respiration Measurement and Enhanced Human–Machine Interface

Wearable strain sensors have transformed the real‐time monitoring of health conditions and human–machine interactions. However, recently developed wearable strain sensors exhibit several limitations. For example, when a sensor is designed with high sensitivity to detect strain, it struggles to accurately measuring the deformation of low‐stiffness materials like skin. Additionally, finding the optimal balance between sensitivity, durability, hysteresis, and strain range in sensor design is challenging. To address these challenges, a Buckled, Ultrasoft, Crack‐based, Large strain, EpiDermal (BUCKLED) sensor is developed. This sensor integrates the benefits of soft structure engineering with high sensitivity of crack‐based sensing mechanisms to ensure optimal skin deformation measurements. The BUCKLED sensor exhibits significant improvements in compliance (18 500 mm N−1), stretchability (100%), hysteresis (2%), durability (10 000 cycles with 100% strain), and force sensitivity () owing to its buckled shape, confirming its ability to detect subtle movements with enhanced accuracy. The sensor's high compliance allows it to accurately measure low‐stiffness objects, ensuring reliable performance. Furthermore, the sensor's tunability is demonstrating its effectiveness in applications such as respiratory monitoring, facial expression recognition, and silent speech interfaces. Consequently, the proposed sensor is versatile and holds great potential for a wide range of sensing applications.

Association between allostatic load and accelerated white matter brain aging: findings from the UK biobank.

White matter (WM) brain age, a neuroimaging-derived biomarker indicating WM microstructural changes, helps predict dementia and neurodegenerative disorder risks. The cumulative effect of chronic stress on WM brain aging remains unknown. In this study, we assessed cumulative stress using a multi-system composite allostatic load (AL) index based on inflammatory, anthropometric, respiratory, lipidemia, and glucose metabolism measures, and investigated its association with WM brain age gap (BAG), computed from diffusion tensor imaging data using a machine learning model, among 22 951 European ancestries aged 40 to 69 (51.40% women) from UK Biobank. Linear regression, Mendelian randomization, along with inverse probability weighting and doubly robust methods, were used to evaluate the impact of AL on WM BAG adjusting for age, sex, socioeconomic, and lifestyle behaviors. We found increasing one AL score unit significantly increased WM BAG by 0.29years in association analysis and by 0.33years in Mendelian analysis. The age- and sex-stratified analysis showed consistent results among participants 45-54 and 55-64years old, with no significant sex difference. This study demonstrated that higher chronic stress was significantly associated with accelerated brain aging, highlighting the importance of stress management in reducing dementia and neurodegenerative disease risks.

Moisture-mineral interactions drive bacterial and organic matter turnover in glacier-sourced riparian sediments undergoing pedogenesis

Glacial recession is occurring at unprecedented rates resulting in increased sediment accumulations in some riverine ecosystems providing new mineral surfaces for soil formation. Soils and sediments have an enormous potential to retain carbon (C), predominantly due to sorption to mineral surfaces. However, C persistence may be sensitive to climate-change induced temperature and moisture variations. We coupled ultrahigh resolution organic matter composition classification with bacterial characterization and respiration measurements to test the combined pedogenic effects of temperature (4 vs 20 °C) and moisture (50 vs 100% water-filled pore space) on C turnover in sediments maintained under different mineralogical conditions (illite-amended vs non-amended). Here we show that the inhibition of CO2 emissions from the combined effect of increased moisture content and illite was reflected in the turnover of key molecular signatures, such as the nominal oxidation state of C, often irrespective of temperature. However, shifts in bacterial communities from a coupled moisture-mineral interaction, were temperature-dependent. Our results highlight the importance of moisture in driving mineral-organic interactions and suggest that C in clay-rich, water-saturated sediments is both thermodynamically unfavorable and mineral-protected from microbial consumption.

High-sensitivity humidity sensor based on Mach-Zehnder interferometer in seven-core fiber

A Mach-Zehnder Interferometer (MZI) based on seven-core fiber (SCF) for humidity sensing is proposed and experimentally demonstrated. The MZI is formed by sandwiched a section of SCF in between two single mode fibers (SMFs), while a fiber taper and a brief multimode fiber (MMF) act as fiber couplers to excite and couple the intermodal interference in the SCF. The optical field distribution and coupling efficiency of the MZI with different SCF lengths are analysed. The theoretical results show that the MZI is sensitive to SCF lengths, and it is expected to obtain highly sensitive humidity response. Humidity sensing experiments shows a high sensitivity of 0.6603 nm/%RH over a relative humidity (RH) range of 44–83 %RH, and the maximum measurement uncertainty introduced by the long-term stability is 0.0006 %RH. Human respiration measurement exhibits the response time and recovery time of the MZI are 0.44 s and 1.24 s respectively. The temperature effect is also experimentally investigated. Such an all-fiber MZI presents advantages of simple configuration, high sensitivity and good stability, making it has potential in humidity measurement fields.

Measurement of Mitochondrial Respiration in Human and Mouse Skeletal Muscle Fibers by High-Resolution Respirometry.

Mitochondrial function, a cornerstone of cellular energy production, is critical for maintaining metabolic homeostasis. Its dysfunction in skeletal muscle is linked to prevalent metabolic disorders (e.g., diabetes and obesity), muscular dystrophies, and sarcopenia. While there are many techniques to evaluate mitochondrial content and morphology, the hallmark method to assess mitochondrial function is the measurement of mitochondrial oxidative phosphorylation (OXPHOS) by respirometry. Quantification of mitochondrial OXPHOS provides insight into the efficiency of mitochondrial oxidative energy production and cellular bioenergetics. A high-resolution respirometer provides highly sensitive, robust measurements of mitochondrial OXPHOS in permeabilized muscle fibers by measuring real-time changes in mitochondrial oxygen consumption rate. The use of permeabilized muscle fibers, as opposed to isolated mitochondria, preserves mitochondrial networks, maintains mitochondrial membrane integrity, and ultimately allows for more physiologically relevant measurements. This system also allows for the measurement of fuel preference and metabolic flexibility - dynamic aspects of muscle energy metabolism. Here, we provide a comprehensive guide for mitochondrial OXPHOS measurements in human and mouse skeletal muscle fibers using a high-resolution respirometer. Skeletal muscle groups are composed of different fiber types that vary in their mitochondrial fuel preference and bioenergetics. Using a high-resolution respirometer, we describe methods for evaluating both aerobic glycolytic and fatty acid substrates to assess fuel preference and metabolic flexibility in a fiber-type-dependent manner. The protocol is versatile and applicable to both human and rodent muscle fibers. The goal is to enhance the reproducibility and accuracy of mitochondrial function assessments, which will improve our understanding of an organelle important to muscle health.

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.

Decreased diaphragm moving distance measured by ultrasound speckle tracking reflects poor prognosis in amyotrophic lateral sclerosis

ObjectiveDecreased cephalocaudal diaphragm movement may indicate respiratory dysfunction in amyotrophic lateral sclerosis (ALS). We aimed to evaluate diaphragm function in ALS using ultrasound speckle tracking, an image-analysis technology that follows similar pixel patterns. MethodsWe developed an offline application that tracks pixel patterns of recorded ultrasound video images using speckle-tracking methods. Ultrasonography of the diaphragm movement during spontaneous quiet respiration was performed on 19 ALS patients and 21 controls to measure the diaphragm moving distance (DMD) in the cephalocaudal direction during a single respiration. We compared respiratory function measures and analyzed the relationship between the clinical profiles and DMD. ResultsDMD was significantly lower in ALS patients than in the control group (0.6 ± 1.4 mm vs 2.2 ± 2.2 mm, p < 0.01) and positively correlated with phrenic nerve compound motor action potential amplitude (R = 0.63, p = 0.01). DMD was negatively correlated with the change in the ALS Functional Rating Scale-Revised scores per month after the exam (R = −0.61, p = 0.02), and those with a larger rate of decline had a significantly lower DMD (p = 0.03). ConclusionsDiaphragm ultrasound speckle tracking enabled the detection of diaphragm dysfunction in ALS. SignificanceDiaphragm ultrasound speckle tracking may be useful for predicting prognosis.

Use of Long-Term Soil Respiration Measurements for Calculating the Net Carbon Balance in Ecosystems of the Central Chernozemic Region

Use of Long-Term Soil Respiration Measurements for Calculating the Net Carbon Balance in Ecosystems of the Central Chernozemic Region

Divergent apparent temperature sensitivity of forest-floor respiration across a managed boreal forest landscape

Understanding the apparent temperature sensitivity (Q10) of forest floor respiration (Q10Rff) and its plant autotrophic (Q10Ra) and soil heterotrophic (Q10Rh) components is critical for determining the strength and direction of forest carbon cycle-climate feedbacks. However, the spatial variability of Q10Rff and its controlling factors across the spatially heterogeneous boreal forest landscape remains poorly understood. In this study, we used chamber-based respiration measurements conducted on paired natural and trenching plots over three growing seasons (2016–2018) to determine Q10Rff, Q10Rh and Q10Ra to soil temperature across 50 diverse forest stands (ranging 5–211 years old) in a managed landscape in northern Sweden. Additionally, we estimated ecosystem- and landscape-scale Q10 based on conventional and tall tower eddy covariance measurements, respectively, conducted over the same landscape. Our results suggest manifold variations (i.e., 10th to 90th percentiles) of Q10Rff (1.7 to 6.6), with Q10Ra (0.9 to 7.4) showing a greater range than Q10Rh (1.6 to 5.3). Forest-floor understory biomass was the main control of variations in Q10Ra, whereas soil properties explained best those of Q10Rh. Furthermore, a seasonal hysteresis of Q10Rff was observed, with higher values mostly occurring during the late growing season. The magnitude of this hysteresis scaled with stand age in response to concurrent changes in net primary production. The Q10Rff to air temperature declined with increasing stand age, which was attributed to the increased decoupling of air and soil temperatures with canopy development. Despite the considerable stand-level variations, when averaged over the 50 forest stands, Q10Rff to air temperature converged with that of both ecosystem- and landscape-scale respiration. In conclusion, our study highlights the complexity of Q10Rff, which needs to be considered in predictions of the interactions of climate change and management with the carbon cycle of managed boreal forests.

A multilevel lightweight fish respiratory frequency measurement method – Segmentation instead of detection

Respiratory frequency is an important physiological parameter for fish health. Traditional respiration detection methods have inherent frequency measurement error problems, and segmentation provides an innovative technique for respiration measurement. By shifting the focus from detection to segmentation, this approach provides robust and reliable support for measuring fish respiratory frequency accurately. However, the existing segmentation network models face challenges related to their large scale, high computational demands, and limited deployability at the edge. To overcome these challenges, this paper introduces an easily portable, high-precision segmentation method based on lightweight network and network slimming technique, named PM-YOLOv5s-seg (Prune MobileNetv3-YOLOv5s Segmentation). PM-YOLOv5s-seg utilizes the MobileNetv3 network as its segmentation backbone, enabling the extraction of essential fish mouth features. Simultaneously, it employs depth separable convolution to reduce network parameters and calculation amounts. Furthermore, the model undergoes additional sparsification via channel pruning, significantly improving its efficiency. Finally, respiratory frequency modeling is performed on the obtained fish mouth segmentation results, utilizing innovative techniques such as Ellipse fitting, Kalman filtering, and polynomial fitting methods. Comparison with the state-of-the-art methods demonstrates the superiority of the multilevel lightweight segmentation model PM-YOLOv5s-seg in terms of detection accuracy, computational efficiency, and model size. This model achieves an optimal balance between the speed and accuracy in fish respiratory frequency measurement, which holds significant implications for fish welfare as well as disease detection.