Physiological measurement最新文献

{"title":"Early impairment of two arms of the baroreflex response in young normotensive patients with obesity.","authors":"Jana Cernanova Krohova, Barbora Czippelova, Zuzana Turianikova, Miriam Kuricova, Jana Tuzakova, Daniel Cierny, Luca Faes, Michal Javorka","doi":"10.1088/1361-6579/adea0a","DOIUrl":"10.1088/1361-6579/adea0a","url":null,"abstract":"<p><p><i>Objective</i>. Hypertension increasingly affects younger populations alongside rising obesity rates, and impaired baroreflex (BR) function could contribute to its development. This study investigated changes in BR control of the cardiac chronotropic (ccBR) and vascular resistance (vrBR) arms in young normotensive patients with obesity and explored associations with sex- and age-independent anthropometric measures (body mass index (iso-BMI) and waist to hip ratio (OSS of WHR)), insulin resistance (HOMA_IR), and arterial stiffness index CAVI₀.<i>Approach.</i>Twenty-three normotensive adolescents and young adults with obesity (17 females, median age: 17.1 years) and twenty-two sex- and age-matched healthy lean participants (16 females, median age: 17.4 years) were examined during four phases: supine rest, head-up-tilt (HUT), supine recovery, and mental arithmetics task (MA). The causal coupling and gain in the frequency-domain of the ccBR and vrBR arms were assessed non-invasively from the spontaneous variability series of arterial pressure, heart period, and peripheral vascular resistance using a partial spectral decomposition method in the low frequency band (0.04-0.15 Hz).<i>Main results.</i>Patients with obesity showed lower ccBR gain during HUT and persistently lower vrBR gain during supine rest and HUT. No significant associations were found between iso-BMI, OSS of WHR, HOMA_IR, CAVI₀, and spectral parameters during supine rest, except for a significant negative correlation between iso-BMI and changes in ccBR spectral gain as a response to MA.<i>Significance.</i>Advanced non-invasive methods accounting for causality in evaluating two BR arms revealed early BR impairment in young participants with obesity, affecting both the ccBR arm and the less-explored vrBR arm.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144529232","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":"ModelS4Apnea: leveraging structured state space models for efficient sleep apnea detection from ECG signals.","authors":"Hasan Zan","doi":"10.1088/1361-6579/adebdd","DOIUrl":"10.1088/1361-6579/adebdd","url":null,"abstract":"<p><p><i>Objective</i>. Sleep apnea is a common sleep disorder associated with severe health risks, necessitating accurate and efficient detection methods.<i>Approach</i>. This study proposes ModelS4Apnea, a deep learning framework for sleep apnea detection from electrocardiogram (ECG) spectrograms, integrating structured state space models (S4) for temporal modeling. The framework consists of a convolutional neural network module for local feature extraction, an S4 module for capturing long-range dependencies, and a classification module for final predictions.<i>Main results</i>. The model was trained and evaluated on the Apnea-ECG dataset, achieving an accuracy of 0.933, an<i>F</i>1-score of 0.912, a sensitivity of 0.916, and a specificity of 0.944, outperforming most prior studies while maintaining computational efficiency.<i>Significance</i>. Compared to existing methods, ModelS4Apnea provides high classification performance with significantly fewer trainable parameters than long short-term memory-based models, reducing training time and memory consumption. The model's ability to aggregate segment-level predictions enabled perfect per-recording classification, demonstrating its robustness in diagnosing sleep apnea across entire recordings. Moreover, its low memory footprint and fast inference speed make it well-suited for wearable devices, home-based monitoring, and clinical applications, offering a scalable and efficient solution for automated sleep apnea detection. Future work may explore multi-modal data integration, real-world deployment, and further optimizations to enhance its clinical applicability and reliability.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144560775","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":"Automated detection of air trapping from mechanical ventilation waveform through interpretable dual-channel 1D convolutional neural network.","authors":"Chengxuan Zhang, Lifeng Gu, Weimin Shen, Kai Wang, Xiaoli Qian, Yuejia Ding, Lingwei Zhang, Fei Lu, Yuanjing Feng, Luping Fang, Huiqing Ge, Qing Pan","doi":"10.1088/1361-6579/adea2c","DOIUrl":"10.1088/1361-6579/adea2c","url":null,"abstract":"<p><p><i>Objective</i>. Air trapping is a major symptom of respiratory diseases like chronic obstructive pulmonary disease and asthma, and has always been a significant problem in treating patients using mechanical ventilation. If not handled timely, it can pose risk of severe respiratory dysfunction and potential life-threatening complications. Currently, the assessment of air trapping for ventilated patients largely relies on clinical experience of medical staffs.<i>Approach</i>. We introduced an interpretable dual-channel one-dimensional convolutional neural network (DC-1DCNN) with a simple structure, which enables fast inference. This model is designed to classify whether a respiratory waveform is indicative of air trapping. A global average pooling layer was integrated into the DC-1DCNN model to highlight the segments of the respiratory waveform that the model focused on when making a classification. An air trapping index (ATI) was introduced to quantify the condition of air trapping in the ventilated patients and to evaluate the effectiveness of bronchodilator nebulized treatments.<i>Main results</i>. The results demonstrate a satisfactory accuracy of 96.4% in identifying air trapping breath cycles, with highlighted critical sections in breath cycles that match the understanding of clinical experts for air trapping. The efficacy of bronchodilators can be well assessed by the ATI.<i>Significance</i>. The findings suggest that the proposed DC-1DCNN can help detect air trapping in real-time, and help the clinicians better monitor the airway condition of the ventilated patients.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144529231","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":"Dynamic response of Bluetooth wearable heart rate monitors during rapid changes in heart rate.","authors":"Mariah Sabioni, Jonas Willén, Seraina Anne Dual, Martin Jacobsson","doi":"10.1088/1361-6579/adece4","DOIUrl":"https://doi.org/10.1088/1361-6579/adece4","url":null,"abstract":"<p><strong>Objectives: </strong>To quantify and evaluate the dynamic response of RR intervals (RRI) and heart rate (HR) measurements of commercially available Bluetooth chest-worn HR monitors during induced rapid changes in HR.&#xD;Approach. An arbitrary function generator created synthetic ECG signals simulating the heart activity. Different scenarios of rapid changes in HR were simulated several times using: (1) step responses; (2) exercise data; and (3) intermittent exercise data. RRI and HR were recorded using the standard Bluetooth HR service for four wearable monitors: Garmin HRM-Dual, Movesense Active, Polar H10, and Wahoo TRACKR. RRI latency, HR latency, and agreement were evaluated from the reference signal.&#xD;Main Results. RRI latency (median and IQR) was 0.7(0.5,0.7) s for Garmin, 0.4(0.2,0.5) s for Movesense, 2.6(2.2,2.8) s for Polar, and 2.1(1.9,2.4) s for Wahoo, where results did not differ greatly between tests. HR response latency was different between devices and tests. During intermittent exercise tests, HR latency was 3.3(3.0, 3.3) s for Garmin, 1.0(1.0,1.0) s for Movesense, 2.3(2.3,2.3) s for Polar, and 2.2(2.2,2.3) s for Wahoo, where all devices consistently underestimated HR peaks and overestimated HR valleys, with a greater discrepancy in HR valleys.&#xD;Significance. Most validation protocols of RRI and HR measured by wearable monitors neglect their dynamic characteristics. The present study demonstrated that manufacturers implemented different digital filters to compute the HR values, limiting the devices' ability to capture rapid HR changes. Open documentation of the processing steps is advised, and use cases involving sharp HR changes - such as intermittent high-intensity training - should rely on beat-to-beat RRI recordings.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144584545","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":"Photoplethysmography imaging to assess facial perfusion under simulated hypovolemia.","authors":"Stefan Borik, Marguerite L Gilmore, Antonio Gonzalez-Fiol, James W Biondi, Hau-Tieng Wu, Kirk H Shelley, Aymen Awad Alian","doi":"10.1088/1361-6579/adece3","DOIUrl":"https://doi.org/10.1088/1361-6579/adece3","url":null,"abstract":"<p><strong>Objective: </strong>This study evaluates the potential of photoplethysmography imaging (PPGI) with automated facial tracking for detecting hemodynamic and autonomic changes induced by lower-body negative pressure (LBNP). The goal is to assess whether PPGI-derived facial perfusion variations are related with stroke volume (SV), systemic vascular resistance (SVR), heart rate variability (HRV), and autonomic responses to progressive hypovolemia.&#xD;Approach: Twenty-four healthy adults (8 females, 16 males; aged 28.7 ± 3.5 years) underwent a seven-stage LBNP protocol (-15 to -60 mmHg, recovery). Facial perfusion was recorded using cross-polarized PPGI, along with SV, SVR, heart rate (HR), and mean arterial pressure (MAP). Facial landmark tracking (MediaPipe) was used to extract region-specific PPGI signals. Wavelet synchrosqueezing transform enabled spectral analysis, and HRV was assessed with NeuroKit2.&#xD;Main Results: At -60 mmHg, the LBNP-intolerant group showed a 25.2% decrease in SV (p < 0.0001) and a 19% increase in SVR (p = 0.041). At -30 mmHg recovery, SV remained reduced by 21% (p < 0.001), with SVR elevated by 30.1% (p = 0.002). In contrast, the tolerant group exhibited SV increases of 12% and 18% at these stages (both p < 0.0001), and a HR reduction of up to 5% (p < 0.05), with a decreasing SVR trend. HRV analysis indicated greater sympathetic activation in the intolerant group, with reduced HF power (p = 0.037) and increased LF/HF ratio (3.5 at -60 mmHg, p = 0.020). First harmonic PPGI amplitudes significantly declined in the intolerant group, most notably in the cheeks (-44.2%, p = 0.005).&#xD;Significance: These findings suggests that PPGI, combined with AI-based face tracking and wavelet analysis, enables non-invasive, spatially resolved monitoring of vascular and autonomic responses. PPGI differentiates tolerant and intolerant groups, supporting its potential for real-time cardiovascular assessment in critical care and emergency settings.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144584547","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":"Hemodynamics and contact simulation investigation of coronary artery stents after interventional surgery.","authors":"Miaoxian Xu, Ning Dang, Hui Tang, Hao Wei, Shikun Zhang, Yinghong Zhao","doi":"10.1088/1361-6579/ade652","DOIUrl":"https://doi.org/10.1088/1361-6579/ade652","url":null,"abstract":"<p><p><i>Objective.</i>Interventional therapy represents a primary treatment modality for moderate to severe coronary atherosclerosis. However, potential complications following stent implantation can pose significant risks to patients. This study aims to explore the relationship between aberrant hemodynamic patterns and the incidence of post-stent implantation complications.<i>Approach.</i>By creating models of three distinct types of coronary artery stents and utilizing clinical fractional flow reserve data, this research employs fluid-structure interaction analyses to simulate the hemodynamic alterations and vascular wall responses post-stent implantation.<i>Main results.</i>It is indicated that implantation of stents can induce complex hemodynamic modifications in the vicinity of the stent, particularly at the juncture where the stent contacts the vascular wall. While the hemodynamic profiles of the three stent types exhibit general consistency, distinctions in local hemodynamics arise from the varied pore densities inherent to each stent design. Notably, the B-type stent, characterized by their moderate pore density, demonstrates comparatively stable hemodynamics relative to the other stent types. Additionally, stent implantation impacts areas of the vascular wall not covered by the stent, with notable hemodynamic changes also manifesting in these regions.<i>Significance.</i>The implantation of stents has a significant impact on the hemodynamics inside the blood vessels. Specifically, abnormal hemodynamic changes near the stents can inflict damage to the blood vessel wall, thus accelerating the occurrence of complications. Moreover, the hemodynamic changes elicited by different stents vary significantly, and it has been observed that stents with moderate grid spacing exhibit superior performance in mitigating adverse hemodynamic effects.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"46 6","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144507527","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":"Research on nighttime IPPG algorithm based on ROI delay expansion and fundamental frequency constrained FastICA.","authors":"Jiang Wu, Jian Qiu, Li Peng, Peng Han, Kaiqing Luo, Dongmei Liu, Miao Chen","doi":"10.1088/1361-6579/ade653","DOIUrl":"https://doi.org/10.1088/1361-6579/ade653","url":null,"abstract":"&lt;p&gt;&lt;p&gt;&lt;i&gt;Objective.&lt;/i&gt;This study aims to enhance the accuracy and reliability of imaging photoplethysmography (IPPG) for heart rate (HR) measurements during nighttime by introducing an innovative approach that combines fast independent component analysis (FastICA) with a&lt;b&gt;T&lt;/b&gt;ime-&lt;b&gt;D&lt;/b&gt;elayed&lt;b&gt;M&lt;/b&gt;ulti-&lt;b&gt;D&lt;/b&gt;imensional&lt;b&gt;E&lt;/b&gt;xtended&lt;b&gt;R&lt;/b&gt;egions&lt;b&gt;o&lt;/b&gt;f&lt;b&gt;I&lt;/b&gt;nterest&lt;b&gt;Ex&lt;/b&gt;traction (&lt;b&gt;TDMDE-ROI-Ex&lt;/b&gt;) technique, specifically tailored to overcome the challenges posed by motion artefacts and the difficulty in identifying regions of interest (ROIs).&lt;i&gt;Approach.&lt;/i&gt;This research employs a dual-method strategy for the precise extraction of ROIs and robust processing of HR signals in nighttime IPPG scenarios. Initially, a face detection algorithm is integrated with a grayscale clustering technique to pinpoint optimal ROIs. This is followed by the application of the mutual information delay method to synthesize multi-channel IPPG signals. Concurrently, the&lt;b&gt;HR&lt;/b&gt;'s&lt;b&gt;F&lt;/b&gt;undamental&lt;b&gt;F&lt;/b&gt;requency is leveraged as a prior&lt;b&gt;C&lt;/b&gt;onstraint within the iterative process of&lt;b&gt;FastICA&lt;/b&gt;(&lt;b&gt;HRFFC-FastICA&lt;/b&gt;), mitigating the susceptibility to initial value fluctuations inherent in FastICA. The synergistic application of these methodologies substantially bolsters the stability and robustness of nighttime HR measurements, particularly in conditions characterized by significant motion.&lt;i&gt;Main results.&lt;/i&gt;The efficacy of the proposed method, which incorporates HRFFC-FastICA, is initially validated through performance testing using the MR-NIRP dataset. This step serves to assess the practicality of the approach for nighttime IPPG HR measurements. Following this, a series of modular ablation studies and comparative evaluations against current nighttime IPPG algorithms are executed. The statistical outcomes demonstrate that our method achieves a mean absolute error (MAE) of 4.57 beats per minute (bpm) and a root mean squared error (RMSE) of 5.95 bpm. In direct comparison with prominent algorithms such as SparsePPG and PhysNet, the method exhibits a notable enhancement in MAE by up to 8.39 bpm and a significant decrease in RMSE by 17.83 bpm. The 95% confidence interval of the Bland-Altman graph of this method is between 9.5 and -12.8 bpm. Compared to other comparable methods, this interval is significantly narrower, with a width nearly half that of alternative approaches, indicating superior precision and reliability.&lt;i&gt;Significance.&lt;/i&gt;The significance of this research is highlighted by the experimental outcomes that demonstrate the considerable advantages of the TDMDE-ROI-Ex method. This technique significantly reduces reliance on facial motion, which is crucial for accurately identifying facial skin colour regions of interest. Moreover, integrating the HRFFC-FastICA method effectively counteracts the effects of motion artefacts and the initial value sensitivity inherent in the FastICA process. The introduction of this methodology into nighttim","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"46 6","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144507528","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":"Quantification electroencephalography response to procedural pain during heel puncture in preterm infants.","authors":"Nusreena Hohsoh, Osuke Iwata, Tomoko Suzuki, Chinami Hanai, Ming Huang, Kiyoko Yokoyama","doi":"10.1088/1361-6579/addfa9","DOIUrl":"10.1088/1361-6579/addfa9","url":null,"abstract":"<p><p><i>Objective</i>. Pain assessment in preterm infants is often based on subjective observations, which may lack objectivity and are labor-intensive. Non-invasive EEG can serve as an objective assessment tool. However, no specific EEG feature within a particular frequency band and brain region has been reported for pain detection in the objective pain assessment of preterm infants. This study quantified electroencephalography (EEG) responses to procedural pain during a puncture in preterm infants, specifically analyzing three EEG parameters.<i>Approach</i>. Fifty-seven EEG datasets from forty-two preterm infants were analyzed across eight EEG channels. The differences between the upper and lower margins (UM-LM) of amplitude-integrated EEG (aEEG), as well as the five frequency bands (low delta, high delta, theta, alpha, and beta) of frequency power and time-frequency power, were used to characterize the response of the brain to pain during specific periods: before, during, and after the puncture.<i>Main results</i>. The Fp1 and Fp2 exhibited the most significant differences in the UM-LM aEEG differences between before vs during (Fp1:<i>p</i>= 0.0060, Fp2:<i>p</i>= 0.0031), before vs after (<i>p</i>< 0.0001), and during vs after (Fp1:<i>p</i>= 0.0427, Fp2:<i>p</i>= 0.025) the puncture. The C3 and C4 responded significantly to pain during the puncture in the frequency and time-frequency power, notably the time-frequency power in the low delta, which showed the most significant differences between the periods before vs during (<i>p</i>< 0.0001), before vs after (<i>p</i>< 0.0001), and during vs after (<i>p</i>= 0.0002) the puncture.<i>Significance</i>. The central brain region responds significantly to procedural pain in preterm infants, which is prominently detected in the low delta of time-frequency power. These findings support the use of EEG application as an objective and non-invasive method to identify and detect pain in nonverbal populations, focusing on specific critical channels and frequency bands.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144209151","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":"An exploratory study on maternal-fetal heart rate variability during normal and operative vaginal delivery: physiopathological, behavioral and clinical perspectives.","authors":"Hernâni Gonçalves, Beatriz Ferro, Paula Pinto, João Bernardes","doi":"10.1088/1361-6579/ade113","DOIUrl":"10.1088/1361-6579/ade113","url":null,"abstract":"<p><p><i>Objective</i>. Operative vaginal delivery (OVD) is a major obstetrical issue in developed countries. In this study, we analyzed simultaneous maternal (MHR) and fetal heart rate (FHR) variabilities, as markers of maternal and fetal autonomous nervous systems activity, in relation with OVD.<i>Approach</i>. A set of 44 simultaneous MHR and FHR recordings were obtained from distinct singleton term pregnancies in normal (<i>n</i>= 27) and OVD (<i>n</i>= 17) in the last two hours of labor (H₁and H₂), and were analyzed using linear and nonlinear indices of heart rate variability analysis. Interaction between MHR and FHR was assessed through their differences and cross-sample entropy analysis.<i>Main results</i>. With progression of labor, there was an increase in most MHR and FHR linear indices, a decrease of entropy indices and an increase of MHR and FHR synchrony/regularity, whereas the sympatho-vagal balance (LF/HF) increased in the mother but decreased in the fetus. Mean MHR, predominance of low frequencies (LF_norm) and LF/HF were significantly higher in the OVD group, while the opposite occurred with the high frequencies (HF) and entropy. The synchronization/regularity between MHR and FHR was significantly higher in OVD. A sensitivity and specificity of 94.1% and 70.4%, respectively, were achieved in the classification of OVD cases using an univariate linear discriminant.<i>Significance</i>. Maternal-FHR variability analysis adds information regarding intrapartum physiology and maternal-fetal behavior and might be considered in prediction models.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144226281","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":"GPT-PPG: a GPT-based foundation model for photoplethysmography signals.","authors":"Zhaoliang Chen, Cheng Ding, Saurabh Kataria, Runze Yan, Minxiao Wang, Randall Lee, Xiao Hu","doi":"10.1088/1361-6579/add988","DOIUrl":"10.1088/1361-6579/add988","url":null,"abstract":"<p><p><i>Objective</i>. This study aims to introduce a novel generative pre-trained transformer (GPT)-based foundation model specifically tailored to photoplethysmography (PPG) signals, enabling effective adaptation to various downstream biomedical tasks.<i>Approach</i>. We adapted the standard GPT architecture to handle the continuous characteristics of PPG signals, leveraging extensive pre-training on a large dataset comprising over 200 million 30 s PPG samples, followed by supervised fine-tuning strategies for task-specific optimization.<i>Main results</i>. Our approach achieves performance comparable to or exceeding current state-of-the-art methods on various downstream tasks, notably atrial fibrillation detection, and demonstrates a unique generative capability, such as effective signal denoising, inherently available without additional fine-tuning.<i>Significance</i>. The successful adaptation of GPT to PPG signals underscores the potential of generative transformer frameworks as versatile foundation models in biomedical signal processing, highlighting their dual role in predictive and generative tasks.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144079550","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}