Physiological measurement最新文献

{"title":"Convolution spatial-temporal attention network for EEG emotion recognition.","authors":"Lei Cao, Binlong Yu, Yilin Dong, Tianyu Liu, Jie Li","doi":"10.1088/1361-6579/ad9661","DOIUrl":"10.1088/1361-6579/ad9661","url":null,"abstract":"<p><p>In recent years, emotion recognition using electroencephalogram (EEG) signals has garnered significant interest due to its non-invasive nature and high temporal resolution. We introduced a groundbreaking method that bypasses traditional manual feature engineering, emphasizing data preprocessing and leveraging the topological relationships between channels to transform EEG signals from two-dimensional time sequences into three-dimensional spatio-temporal representations. Maximizing the potential of deep learning, our approach provides a data-driven and robust method for identifying emotional states. Leveraging the synergy between convolutional neural network and attention mechanisms facilitated automatic feature extraction and dynamic learning of inter-channel dependencies. Our method showcased remarkable performance in emotion recognition tasks, confirming the effectiveness of our approach, achieving average accuracy of 98.62% for arousal and 98.47% for valence, surpassing previous state-of-the-art results of 95.76% and 95.15%. Furthermore, we conducted a series of pivotal experiments that broadened the scope of emotion recognition research, exploring further possibilities in the field of emotion recognition.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142693142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"pyPCG: a Python toolbox specialized for phonocardiography analysis.","authors":"Kristof Müller, Janka Hatvani, Miklos Koller, Márton Áron Goda","doi":"10.1088/1361-6579/ad9af7","DOIUrl":"https://doi.org/10.1088/1361-6579/ad9af7","url":null,"abstract":"<p><strong>Objective: </strong>Phonocardiography has recently gained popularity in low-cost and remote monitoring, including passive fetal heart monitoring. The development of methods which analyse phonocardiographic data tries to capitalize on this opportunity, and in recent years a multitude of such algorithms and models have been published. In these approaches there is little to no standardization and multiple parts of these models have to be reimplemented on a case-by-case basis. Datasets containing heart sound recordings also lack standardization in both data storage and labeling, especially in fetal phonocardiography.</p><p><strong>Approach: </strong>We are presenting a toolbox that can serve as a basis for a future standard framework for heart sound analysis. This toolbox contains some of the most widely used processing steps and with these, complex analysis pipelines can be created. These functions can be tested individually.</p><p><strong>Main results: </strong>Due to the interdependence of the steps, we validated the current segmentation stage using two phonocardiogram datasets, a fetal dataset comprising 50 one-minute abdominal PCG recordings, which include 6758 S1 and 6729 S2 labels and a filtered version of the dataset used in the 2022 PhysioNet Challenge, containing 413 records with 9795 S1 and 9761 S2 labels. Our results were compared to other common and publicly available segmentation methods, such as peak detection with the Neurokit2 library, and the Hidden Semi-Markov Model by Springer et al. Our best model achieved a 96.1% F1 score and 11.7 ms mean absolute error for fetal S1 detection, and 81.3% F1 score and 50.5 ms mean absolute error for PhysioNet S1 detection.</p><p><strong>Significance: </strong>Our detection method outperformed all other tested methods on the fetal dataset and&#xD;achieved results comparable to the state of the art on the PhysioNet dataset. Accurate segmentation of signals is critical for the calculation of accurate statistical measures and the creation of classification models. Our toolbox contains functions for both feature extraction and calculation of statistics which are compatible with the previous steps. All of our methods can be fine tuned for specific datasets. pyPCG is available on https://pypcg-toolbox.readthedocs.io/en/latest/.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142785704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beat the heat: wearable-based study of perceived heat stress and physiological strain in swiss track workers in a controlled climate chamber.","authors":"Cristina G Vázquez, Manuel Fujs, Michael F Koller, Peter Wolf, Giulia Da Poian","doi":"10.1088/1361-6579/ad9683","DOIUrl":"10.1088/1361-6579/ad9683","url":null,"abstract":"<p><p>Increasing temperatures pose new challenges for track workers (TWs), who endure prolonged exposure to extreme heat and humidity. New methods are critically needed to assess their performance and heat tolerance, aiming to mitigate workplace accidents and long-term health consequences. This study aimed to investigate the physiological effects of heat exposure on TWs, using wearable sensors to monitor key physiological parameters under controlled environmental conditions. Nineteen TWs participated in the study, which included two experimental sessions simulating different thermal environments: a typical Swiss summer night and a hot summer day. Participants' core body temperature, heart rate (HR), and skin temperature were monitored using wearable sensors, and physiological indexes were computed. In addition, perceptual strain index (PeSI) and psychomotor vigilance task (PVT) response times were recorded. Statistically significant increases in physiological parameters were observed under hotter conditions. The study identified statistically significant correlations between the PeSI and the physiological strain index and between PeSI and HR. Perceptual scores were consistently higher than the values derived from physiological measurements, suggesting a greater subjective experience of heat strain. The PVT response times were higher on the hotter day, reflecting increased cognitive strain due to heat exposure. The study highlights the critical impact of heat stress on TWs, with statistically significant increases in physiological and cognitive strain under higher temperatures. Future research should focus on real-world applications of heat strain monitoring.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142710902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A skewed-Gaussian model for pulse decomposition analysis of photoplethysmography signals.","authors":"Giulio Basso, Reinder Haakma, Rik Vullings","doi":"10.1088/1361-6579/ad9662","DOIUrl":"10.1088/1361-6579/ad9662","url":null,"abstract":"<p><p><i>Objective.</i>Pulse decomposition analysis (PDA) has been proposed to extract reliable information from photoplethysmography (PPG) morphology by decomposing the signal in its physiological sub-waves. The Gaussian model has been widely used in the literature, even though it often underperforms because it is limited to symmetric morphologies. More advanced asymmetric models, such as the Gamma model, have been proposed to achieve improved accuracy. However, the physiological interpretation of the Gamma model is less effective than the Gaussian model, challenging the assessment of the clinical relevance of the outcomes. This paper aims to design an asymmetric PDA model with improved accuracy and effective physiological interpretability.<i>Approach.</i>We implemented a novel PDA model called the skewed-Gaussian model and tested it on 8000 PPG pulses from the MIMIC-III Waveform Database. The performances were compared with the reference Gamma-Gaussian model. Models' accuracies were assessed using the residual sum of squares, while Bland-Altman plots were used to evaluate biases. Lastly, the sensitivity and robustness of the models to the initial values' choice were evaluated using random initial values.<i>Main results.</i>Our model achieved significantly higher accuracy than the reference model. The analysis with random initial values suggested that the model was less sensitive and consistently more robust. Finally, we highlighted the physiological interpretation of the model.<i>Significance.</i>The proposed model may help to establish a link between alterations in cardiovascular functions and variations detectable in the PPG signal, as well as opening up new avenues for PPG-based remote patient monitoring.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142693064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Amplitude spectrum area is dependent on the electrocardiogram magnitude: evaluation of different normalization approaches.","authors":"Luiz E V Silva, Hunter A Gaudio, Nicholas J Widmann, Rodrigo M Forti, Viveknarayanan Padmanabhan, Kumaran Senthil, Julia C Slovis, Constantine D Mavroudis, Yuxi Lin, Lingyun Shi, Wesley B Baker, Ryan W Morgan, Todd J Kilbaugh, Fuchiang Rich Tsui, Tiffany S Ko","doi":"10.1088/1361-6579/ad9233","DOIUrl":"10.1088/1361-6579/ad9233","url":null,"abstract":"<p><p><i>Objective.</i>Amplitude Spectrum Area (AMSA) of the electrocardiogram (ECG) waveform during ventricular fibrillation (VF) has shown promise as a predictor of defibrillation success during cardiopulmonary resuscitation (CPR). However, AMSA relies on the magnitude of the ECG waveform, raising concerns about reproducibility across different settings that may introduce magnitude bias. This study aimed to evaluate different AMSA normalization approaches and their impact on removing bias while preserving predictive value.<i>Approach.</i>ECG were recorded in 118 piglets (1-2 months old) during a model of asphyxia-associated VF cardiac arrest and CPR. An initial subset (91/118) was recorded using one device (Device 1), and the remaining piglets were recorded in the second device (Device 2). Raw AMSA and three ECG magnitude metrics were estimated to assess magnitude-related bias between devices. Five AMSA normalization approaches were assessed for their ability to remove detected bias and to classify defibrillation success.<i>Main results.</i>Device 2 showed significantly lower ECG magnitude and raw AMSA compared to Device 1. CPR-based AMSA normalization approaches mitigated device-associated bias. Raw AMSA normalized by the average AMSA in the 1st minute of CPR (AMSA_1m-cpr) exhibited the best sensitivity and specificity for classification of successful and unsuccessful defibrillation. While the optimal AMSA_1m-cprthresholds for balanced sensitivity and specificity were consistent across both devices, the optimal raw AMSA thresholds varied between the two devices. The area under the receiver operating characteristic curve for AMSA_1m-cprdid not significantly differ from raw AMSA for both devices (Device 1: 0.74 vs. 0.88,<i>P</i>= 0.14; Device 2: 0.56 vs. 0.59,<i>P</i>= 0.81).<i>Significance.</i>Unlike raw AMSA, AMSA_1m-cprdemonstrated consistent results across different devices while maintaining predictive value for defibrillation success. This consistency has important implications for the widespread use of AMSA and the development of future guidelines on optimal AMSA thresholds for successful defibrillation.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11653958/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142625819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of automatic and physiologically-based feature selection methods for classifying physiological stress using heart rate and pulse rate variability indices.","authors":"Marta Iovino, Ivan Lazic, Tatjana Loncar-Turukalo, Michal Javorka, Riccardo Pernice, Luca Faes","doi":"10.1088/1361-6579/ad9234","DOIUrl":"10.1088/1361-6579/ad9234","url":null,"abstract":"<p><p><i>Objective.</i>This study evaluates the effectiveness of four machine learning algorithms in classifying physiological stress using heart rate variability (HRV) and pulse rate variability (PRV) time series, comparing an automatic feature selection based on Akaike's criterion to a physiologically-based feature selection approach.<i>Approach.</i>Linear discriminant analysis, support vector machines,<i>K</i>-nearest neighbors and random forest were applied on ten HRV and PRV indices from time, frequency and information domains, selected with the two feature selection approaches. Data were collected from 127 healthy individuals during different stress conditions (rest, postural and mental stress).<i>Main results.</i>Our results highlight that, while specific stress classification is feasible, distinguishing between postural and mental stress remains challenging. The used classifiers exhibited similar performance, with automatic Akaike Information Criterion-based feature selection proving overall better than the physiology-driven approach. Additionally, PRV-based features performed comparably to HRV-based ones, indicating their potential in outpatient monitoring using wearable devices.<i>Significance.</i>The obtained findings help to determine the most relevant HRV/PRV features for stress classification, potentially useful to highlight different physiological mechanisms involved during both challenges accompanied by a shift in the sympathovagal balance. The proposed approach may have implications for advancing stress assessment methodologies in clinical settings and real-world contexts for well-being evaluation.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142625822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interhemispheric asynchrony of NREM EEG at the beginning and end of sleep describes evening vigilance performance in patients undergoing diagnostic polysomnography.","authors":"Karen McCloy, Brett Duce, Nadeeka Dissanayaka, Craig Hukins, Udantha Abeyratne","doi":"10.1088/1361-6579/ad8f8f","DOIUrl":"10.1088/1361-6579/ad8f8f","url":null,"abstract":"<p><p><i>Objective.</i>Obstructive sleep apnea (OSA) is associated with deficits in vigilance. This work explored the temporal patterns of OSA-related events during sleep and vigilance levels measured by the psychomotor vigilance test (PVT) in patients undergoing polysomnography (PSG) for suspected OSA.<i>Approach.</i>The PVT was conducted prior to in-laboratory PSG for 80 patients suspected of having OSA. Three groups were formed based on PVT-RT-outcomes and participants were randomly allocated into Training (<i>n</i>= 55) and Test (<i>n</i>= 25) samples. Sleep epochs of non-rapid-eye movement (NREM) electroencephalographic (EEG) asynchrony data, and REM and NREM data for respiratory, arousal, limb movement and desaturation events were analysed. The data were segmented by sleep stage, by sleep blocks (SB) of stable Stage N2, Stage N3, mixed-stage NREM sleep (NXL), and, by Time of Night (TN) across sleep. Models associating this data with PVT groups were developed and tested.<i>Main Results.</i><b>A</b>model using NREM EEG asynchrony data segmented by SB and TN achieved 81.9% accuracy in the Test Cohort. Models based on interhemispheric asynchrony SB data and OSA data segmented by TN achieved 80.6% and 79.5% respectively.<i>Significance.</i>Novel data segmentation methods via blocks of NXL and TN have improved our understanding of the relationship between sleep, OSA and vigilance.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142591181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of arteriosclerosis based on lognormal fitting.","authors":"Hao Tang, Yumin Li, Lulu Zhao, Tenghui Xiang, Ziqi Zhang, Jianqing Li, Chengyu Liu","doi":"10.1088/1361-6579/ad8f29","DOIUrl":"10.1088/1361-6579/ad8f29","url":null,"abstract":"<p><p><i>Objective</i>. Pulse pressure waves contain information about human physiology. There is a need for a simple, accurate way to know cardiovascular health in the clinic, so as to realize the implementation of convenient and effective early health monitoring for patients with arteriosclerosis.<i>Approach</i>. This study proposes an arteriosclerosis assessment method based on fitting a lognormal function, along with improving a conventional electronic sphygmomanometer. During the deflation phase of blood pressure measurement, the cuff pressure was kept constant (40 mmHg) and an additional 10 s of pulse signal was acquired. To derive the pulse pressure waveforms for a single cycle, the acquired pulse data of 101 cases were preprocessed in this study, including filtering for noise removal, onset point identification, removal of baseline drift, and normalization. In this study, an improved pulse resolution algorithm is proposed for the multimodal problem of the pulse wave, combining waveform matching and threshold setting, and finally obtaining the resolution parameters of the lognormal function with an average error less than 1.5%.<i>Main results</i>. According to the correlation analysis, the resolved parameters<i>A</i>₁,<i>W</i>₂,<i>C</i>₂,<i>W</i>₃, and<i>C</i>₃were significantly correlated with brachial-ankle Pulse Wave Velocity, and the absolute correlation range in 0.17-0.53, which can be used as a reference index for arteriosclerosis. An arteriosclerosis assessment model was constructed based on the support vector mechanism, and the prediction accuracy was 91.1%.<i>Significance</i>. This study provides a new solution idea for the arteriosclerosis assessment method as well as the pulse resolution algorithm, which has a greater reference value.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142584056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sulfur hexafluoride multiple breath washin and washout outcomes in infants are not interchangeable.","authors":"Anne-Christianne Kentgens, Florian Wyler, Marc-Alexander Oestreich, Philipp Latzin, Sophie Yammine","doi":"10.1088/1361-6579/ad8da4","DOIUrl":"10.1088/1361-6579/ad8da4","url":null,"abstract":"<p><p><i>Objective.</i>Sulfur hexafluoride (SF₆) multiple-breath washout (MBW) assesses ventilation inhomogeneity, as an early marker of obstructive respiratory diseases. Primary outcomes are customarily washout-derived, and it is unclear whether the preceding SF₆-washin can provide similar estimates. We aimed to assess comparability of primary SF₆-MBW outcomes between washin and washout phases of infant SF₆-MBW data measured with the WBreath (ndd Medizintechnik AG, Zurich, Switzerland) and Spiroware (Eco Medics AG, Duernten, Switzerland) MBW-setups, respectively.<i>Approach.</i>We assessed mean relative differences in lung clearance index (LCI) and functional residual capacity (FRC) between the washin and washout of existing SF₆-MBW data from healthy infants and infants with cystic fibrosis (CF). We assessed whether these differences exceeded the mean relative within-test between-trial differences of washout-derived outcomes, which can be attributed to natural variability. We also explored non-physiological factors using a pediatric lung simulator.<i>Main results.</i>LCI and FRC from washin and washout were not comparable, for both setups. The mean difference (SD) in LCI between washin and washout was 2.3(10.8)% for WBreath and -9.7(8.0)% for Spiroware, while in FRC it was -4.7(8.4)% for WBreath and -2.3(9.7)% for Spiroware. These differences exceeded the within-test between-trial differences in washout-derived outcomes. Outcomes from washin and washout were also not comparable in a pediatric lung simulator.<i>Significance.</i>Outcomes of the washin and washout were not comparable due to an interplay of physiological and non-physiological factors, and cannot be used interchangeably.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142558389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fraction of reverse impedance change (FRIC): a quantitative electrical impedance tomography measure of intrapulmonary pendelluft.","authors":"Andy Adler, Tobias Becher, Claas Händel, Inéz Frerichs","doi":"10.1088/1361-6579/ad7fca","DOIUrl":"10.1088/1361-6579/ad7fca","url":null,"abstract":"<p><p><i>Objective</i>. Pendelluft is the movement of air between lung regions, and electrical impedance tomography (EIT) has shown an ability to detect and monitor it.<i>Approach.</i>In this note, we propose a functional EIT measure which quantifies the reverse airflow seen in pendelluft: the<i>Fraction of Reverse Impedance Change</i>(FRIC).<i>Main</i><i>Results</i>. FRIC measures the fraction of reverse flow in each pixel waveform (as an image) or globally (as a single parameter).<i>Significance</i>. Such a measure is designed to be a more specific measure than previous approaches, to enable comparative studies of the pendelluft, and to help clarify the effect of ventilation strategies.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142351970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}