Pub Date : 2024-09-16DOI: 10.1088/1361-6579/ad74d7
Xavier Navarro-Sune, Mathieu Raux, Anna L Hudson, Thomas Similowski, Mario Chavez
Objective. Time-frequency (T-F) analysis of electroencephalographic (EEG) is a common technique to characterise spectral changes in neural activity. This study explores the limitations of utilizing conventional spectral techniques in examining cyclic event-related cortical activities due to challenges, including high inter-trial variability.Approach. Introducing the cycle-frequency (C-F) analysis, we aim to enhance the evaluation of cycle-locked respiratory events. For synthetic EEG that mimicked cycle-locked pre-motor activity, C-F had more accurate frequency and time localization compared to conventional T-F analysis, even for a significantly reduced number of trials and a variability of breathing rhythm.Main results. Preliminary validations using real EEG data during both unloaded breathing and loaded breathing (that evokes pre-motor activity) suggest potential benefits of using the C-F method, particularly in normalizing time units to cyclic activity phases and refining baseline placement and duration.Significance. The proposed approach could provide new insights for the study of rhythmic neural activities, complementing T-F analysis.
{"title":"Cycle-frequency content EEG analysis improves the assessment of respiratory-related cortical activity.","authors":"Xavier Navarro-Sune, Mathieu Raux, Anna L Hudson, Thomas Similowski, Mario Chavez","doi":"10.1088/1361-6579/ad74d7","DOIUrl":"10.1088/1361-6579/ad74d7","url":null,"abstract":"<p><p><i>Objective</i>. Time-frequency (T-F) analysis of electroencephalographic (EEG) is a common technique to characterise spectral changes in neural activity. This study explores the limitations of utilizing conventional spectral techniques in examining cyclic event-related cortical activities due to challenges, including high inter-trial variability.<i>Approach</i>. Introducing the cycle-frequency (C-F) analysis, we aim to enhance the evaluation of cycle-locked respiratory events. For synthetic EEG that mimicked cycle-locked pre-motor activity, C-F had more accurate frequency and time localization compared to conventional T-F analysis, even for a significantly reduced number of trials and a variability of breathing rhythm.<i>Main results</i>. Preliminary validations using real EEG data during both unloaded breathing and loaded breathing (that evokes pre-motor activity) suggest potential benefits of using the C-F method, particularly in normalizing time units to cyclic activity phases and refining baseline placement and duration.<i>Significance</i>. The proposed approach could provide new insights for the study of rhythmic neural activities, complementing T-F analysis.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142093678","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}
Pub Date : 2024-09-13DOI: 10.1088/1361-6579/ad7ad2
Hannah J Coyle-Asbil,Lukas Burk,Mirko Brandes,Berit Brandes,Christoph Buck,Marvin N Wright,Lori Ann Vallis
This study aimed to develop convolutional neural networks (CNN) models to predict the energy expenditure (EE) of children from raw accelerometer data. Additionally, this study sought to external validation of the CNN models in addition to the linear regression (LM), random forest (RF), and full connected neural network (FcNN) models published inet al (2019).
Approach:
Included in this study were 41 German children (3.0 to 6.99 years) for the training and internal validation who were equipped with GENEActiv, GT3X+, and activPAL accelerometers. The external validation dataset consisted of 39 Canadian children (3.0 to 5.99 years) that were equipped with OPAL, GT9X, GENEActiv, and GT3X+ accelerometers. EE was recorded simultaneously in both datasets using a portable metabolic unit. The protocols consisted of a semi-structured activities ranging from low to high intensities. The root mean square error (RMSE) values were calculated and used to evaluate model performances.
Main results:
1) The CNNs outperformed the LM (13.17% to 23.81% lower mean RMSE values), FcNN (8.13% to 27.27% lower RMSE values) and the RF models (3.59% to 18.84% lower RMSE values) in the internal dataset. 2) In contrast, it was found that when applied to the external Canadian dataset, the CNN models had consistently higher RMSE values compared to the LM, FcNN, and RF.
Significance:
Although CNNs can enhance EE prediction accuracy, their ability to generalize to new datasets and accelerometer brands/models, is more limited compared to LM, RF, and FcNN models.
.
{"title":"Energy expenditure prediction in preschool children: a machine learning approach using accelerometry and external validation.","authors":"Hannah J Coyle-Asbil,Lukas Burk,Mirko Brandes,Berit Brandes,Christoph Buck,Marvin N Wright,Lori Ann Vallis","doi":"10.1088/1361-6579/ad7ad2","DOIUrl":"https://doi.org/10.1088/1361-6579/ad7ad2","url":null,"abstract":"
This study aimed to develop convolutional neural networks (CNN) models to predict the energy expenditure (EE) of children from raw accelerometer data. Additionally, this study sought to external validation of the CNN models in addition to the linear regression (LM), random forest (RF), and full connected neural network (FcNN) models published inet al (2019).
Approach:
Included in this study were 41 German children (3.0 to 6.99 years) for the training and internal validation who were equipped with GENEActiv, GT3X+, and activPAL accelerometers. The external validation dataset consisted of 39 Canadian children (3.0 to 5.99 years) that were equipped with OPAL, GT9X, GENEActiv, and GT3X+ accelerometers. EE was recorded simultaneously in both datasets using a portable metabolic unit. The protocols consisted of a semi-structured activities ranging from low to high intensities. The root mean square error (RMSE) values were calculated and used to evaluate model performances.
Main results:
1) The CNNs outperformed the LM (13.17% to 23.81% lower mean RMSE values), FcNN (8.13% to 27.27% lower RMSE values) and the RF models (3.59% to 18.84% lower RMSE values) in the internal dataset. 2) In contrast, it was found that when applied to the external Canadian dataset, the CNN models had consistently higher RMSE values compared to the LM, FcNN, and RF.
Significance:
Although CNNs can enhance EE prediction accuracy, their ability to generalize to new datasets and accelerometer brands/models, is more limited compared to LM, RF, and FcNN models.
.","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"42 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252826","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}
Pub Date : 2024-09-13DOI: 10.1088/1361-6579/ad7ad3
Lukas Verderber,Willian da Silva,Inmaculada Aparicio,Andresa M C Germano,Felipe Carpes,Jose Ignacio Priego Quesada
The association between muscle damage and skin temperature is controversial. We hypothesize that including metrics that are more sensitive to individual responses by considering variability and regions representative of higher temperature could influence skin temperature outcomes. Here, the objective of the study was to determine whether using alternative metrics (TMAX, entropy, and pixelgraphy) leads to different results than mean, maximum, minimum, and standard deviation skin temperature when addressing muscle damage using infrared thermography.
Approach: Thermal images from four previous investigations measuring skin temperature before and after muscle damage in the anterior thigh and the posterior lower leg were used. The TMAX, entropy, and pixelgraphy (percentage of pixels above 33ºC) metrics were applied.
Main results: On 48h after running a marathon or half-marathon, no differences were found in skin temperature when applying any metric. Mean, minimum, maximum, TMAX, and pixelgraphy were lower 48h after than at basal condition following quadriceps muscle damage (p<0.05). Maximum skin temperature and pixelgraphy were lower 48h after than the basal condition following muscle damage to the triceps sural (p<0.05). Overall, TMAX strongly correlated with mean (r=0.85) and maximum temperatures (r=0.99) and moderately with minimum (r=0.66) and pixelgraphy parameter (r=0.64). Entropy strongly correlates with standard deviation (r=0.94) and inversely moderately with minimum temperature (r=-0.53). The pixelgraphy moderately correlated with mean (r=0.68), maximum (r=0.62), minimum (r=0.58), and TMAX (r=0.64).
Significance: Using alternative metrics does not change skin temperature outcomes following muscle damage of lower extremity muscle groups.
{"title":"Assessment of alternative metrics in the application of infrared thermography to detect muscle damage in sports.","authors":"Lukas Verderber,Willian da Silva,Inmaculada Aparicio,Andresa M C Germano,Felipe Carpes,Jose Ignacio Priego Quesada","doi":"10.1088/1361-6579/ad7ad3","DOIUrl":"https://doi.org/10.1088/1361-6579/ad7ad3","url":null,"abstract":"
The association between muscle damage and skin temperature is controversial. We hypothesize that including metrics that are more sensitive to individual responses by considering variability and regions representative of higher temperature could influence skin temperature outcomes. Here, the objective of the study was to determine whether using alternative metrics (TMAX, entropy, and pixelgraphy) leads to different results than mean, maximum, minimum, and standard deviation skin temperature when addressing muscle damage using infrared thermography. 
Approach: Thermal images from four previous investigations measuring skin temperature before and after muscle damage in the anterior thigh and the posterior lower leg were used. The TMAX, entropy, and pixelgraphy (percentage of pixels above 33ºC) metrics were applied. 
Main results: On 48h after running a marathon or half-marathon, no differences were found in skin temperature when applying any metric. Mean, minimum, maximum, TMAX, and pixelgraphy were lower 48h after than at basal condition following quadriceps muscle damage (p<0.05). Maximum skin temperature and pixelgraphy were lower 48h after than the basal condition following muscle damage to the triceps sural (p<0.05). Overall, TMAX strongly correlated with mean (r=0.85) and maximum temperatures (r=0.99) and moderately with minimum (r=0.66) and pixelgraphy parameter (r=0.64). Entropy strongly correlates with standard deviation (r=0.94) and inversely moderately with minimum temperature (r=-0.53). The pixelgraphy moderately correlated with mean (r=0.68), maximum (r=0.62), minimum (r=0.58), and TMAX (r=0.64). 
Significance: Using alternative metrics does not change skin temperature outcomes following muscle damage of lower extremity muscle groups.","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"9 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252825","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}
Pub Date : 2024-09-13DOI: 10.1088/1361-6579/ad7ad4
Wenjing Liu,Li Yan,Yangcheng Huang,Ziyi Yin,Mingjie Wang,Wenjie Cai
OBJECTIVEThis paper tackles the challenge of accurately detecting second-degree and third-degree atrioventricular block AVB) in electrocardiogram (ECG) signals through automated algorithms. The inaccurate detection of P-waves poses a difficulty in this process. To address this limitation, we propose a reliable method that significantly improves the performances of AVB detection by precisely localizing P-waves.APPROACHOur proposed P-WaveNet utilized an attention mechanism to extract spatial and temporal features, and employs a BiLSTM module to capture inter-temporal dependencies within the ECG signal. To overcome the scarcity of data for second-degree and third-degree AVB (2AVB,3AVB), a mathematical approach was employed to synthesize pseudo-data. By combining P-wave positions identified by the P-WaveNet with key medical features such as RR interval rhythm and PR intervals, we established a classification rule enabling automatic AVB detection.MAIN RESULTSThe P-WaveNet achieved an F1 score of 93.62% and 91.42% for P-wave localization on the QTDB and LUDB datasets, respectively. In the BUTPDB dataset, the F1 scores for P-wave localization in ECG signals with 2AVB and 3AVB were 98.29% and 62.65%, respectively. Across two independent datasets, the AVB detection algorithm achieved F1 scores of 83.33% and 84.15% for 2AVB and 3AVB, respectively.SIGNIFICANCEOur proposed P-WaveNet demonstrates accurate identification of P-waves in complex ECGs, significantly enhancing AVB detection efficacy. This paper's contributions stem from the fusion of medical expertise with data augmentation techniques and ECG classification. The proposed P-WaveNet demonstrates potential clinical applicability.
目的 本文探讨了如何通过自动算法准确检测心电图（ECG）信号中的二度和三度房室传导阻滞（AVB）。在这一过程中，P 波检测不准确是一个难题。针对这一局限性，我们提出了一种可靠的方法，通过精确定位 P 波来显著提高 AVB 检测的性能。我们提出的 P 波网利用注意力机制来提取空间和时间特征，并采用 BiLSTM 模块来捕捉心电信号中的时际依赖性。为了克服二度和三度 AVB（2AVB,3AVB）数据稀缺的问题，我们采用了一种数学方法来合成伪数据。通过将 P-WaveNet识别的P波位置与RR间期节律和PR间期等关键医学特征相结合，我们建立了一种能够自动检测房室传导阻滞的分类规则。主要结果P-WaveNet在QTDB和LUDB数据集上的P波定位F1得分率分别达到了93.62%和91.42%。在 BUTPDB 数据集中，使用 2AVB 和 3AVB 对心电图信号进行 P 波定位的 F1 分数分别为 98.29% 和 62.65%。在两个独立的数据集中，AVB 检测算法对 2AVB 和 3AVB 的 F1 分数分别达到 83.33% 和 84.15%。本文的贡献在于将医学专业知识与数据增强技术和心电图分类相结合。所提出的 P-WaveNet 具有潜在的临床适用性。
{"title":"Enhancing P-wave localization for accurate detection of second-degree and third-degree atrioventricular conduction blocks.","authors":"Wenjing Liu,Li Yan,Yangcheng Huang,Ziyi Yin,Mingjie Wang,Wenjie Cai","doi":"10.1088/1361-6579/ad7ad4","DOIUrl":"https://doi.org/10.1088/1361-6579/ad7ad4","url":null,"abstract":"OBJECTIVEThis paper tackles the challenge of accurately detecting second-degree and third-degree atrioventricular block AVB) in electrocardiogram (ECG) signals through automated algorithms. The inaccurate detection of P-waves poses a difficulty in this process. To address this limitation, we propose a reliable method that significantly improves the performances of AVB detection by precisely localizing P-waves.APPROACHOur proposed P-WaveNet utilized an attention mechanism to extract spatial and temporal features, and employs a BiLSTM module to capture inter-temporal dependencies within the ECG signal. To overcome the scarcity of data for second-degree and third-degree AVB (2AVB,3AVB), a mathematical approach was employed to synthesize pseudo-data. By combining P-wave positions identified by the P-WaveNet with key medical features such as RR interval rhythm and PR intervals, we established a classification rule enabling automatic AVB detection.MAIN RESULTSThe P-WaveNet achieved an F1 score of 93.62% and 91.42% for P-wave localization on the QTDB and LUDB datasets, respectively. In the BUTPDB dataset, the F1 scores for P-wave localization in ECG signals with 2AVB and 3AVB were 98.29% and 62.65%, respectively. Across two independent datasets, the AVB detection algorithm achieved F1 scores of 83.33% and 84.15% for 2AVB and 3AVB, respectively.SIGNIFICANCEOur proposed P-WaveNet demonstrates accurate identification of P-waves in complex ECGs, significantly enhancing AVB detection efficacy. This paper's contributions stem from the fusion of medical expertise with data augmentation techniques and ECG classification. The proposed P-WaveNet demonstrates potential clinical applicability.","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"11 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142252827","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}
Despite the growing interest in understanding the role of triggers in paroxysmal atrial fibrillation (AF), solutions beyond questionnaires to identify a broader range of triggers remain lacking. This study aims to investigate the relation between triggers detected in wearable-based physiological signals and the occurrence of AF episodes.
Methods: Week-long physiological signals were collected during everyday activities from 35 patients with paroxysmal AF, employing an ECG patch attached to the chest and a photoplethysmogram (PPG)-based wrist-worn device. The signals acquired by the patch were used for detecting triggers of physical exertion, psychophysiological stress, lying on the left side, and sleep disturbances, as well as to annotate AF episodes. To assess the relation between detected triggers and the occurrence of AF episodes, a measure of relational strength is employed accounting for pre- and post-trigger AF burden. The utility of ECG- and PPG-based AF detectors in determining AF burden and assessing the relational strength is also analyzed.
Results: Physical exertion emerged as the trigger associated with the largest increase in relational strength for the largest number of patients (p< 0.01). On the other hand, no significant difference was observed for psychophysiological stress and sleep disorders. When AF episodes are captured using AF detectors, the relational strength exhibits a moderate correlation with the relational strength of the annotated AF, withr= 0.66 for ECG-based AF detection andr= 0.62 for PPG-based AF detection.
Conclusions: The findings indicate a patient-specific increase in relational strength for all four types of triggers.
Significance: The proposed approach has the potential to facilitate the implementation of longitudinal studies and can serve as a less biased alternative to questionnaire-based AF trigger detection.
{"title":"Assessment of the relational strength between triggers detected in physiological signals and the occurrence of atrial fibrillation episodes.","authors":"Vilma Pluščiauskaitė,Andrius Sološenko,Karolina Jančiulevičiūtė,Vaidotas Marozas,Leif Sörnmo,Andrius Petrėnas","doi":"10.1088/1361-6579/ad79b3","DOIUrl":"https://doi.org/10.1088/1361-6579/ad79b3","url":null,"abstract":"Despite the growing interest in understanding the role of triggers in paroxysmal atrial fibrillation (AF), solutions beyond questionnaires to identify a broader range of triggers remain lacking. This study aims to investigate the relation between triggers detected in wearable-based physiological signals and the occurrence of AF episodes.
 
Methods: Week-long physiological signals were collected during everyday activities from 35 patients with paroxysmal AF, employing an ECG patch attached to the chest and a photoplethysmogram (PPG)-based wrist-worn device. The signals acquired by the patch were used for detecting triggers of physical exertion, psychophysiological stress, lying on the left side, and sleep disturbances, as well as to annotate AF episodes. To assess the relation between detected triggers and the occurrence of AF episodes, a measure of relational strength is employed accounting for pre- and post-trigger AF burden. The utility of ECG- and PPG-based AF detectors in determining AF burden and assessing the relational strength is also analyzed.
 
Results: Physical exertion emerged as the trigger associated with the largest increase in relational strength for the largest number of patients (p< 0.01). On the other hand, no significant difference was observed for psychophysiological stress and sleep disorders. When AF episodes are captured using AF detectors, the relational strength exhibits a moderate correlation with the relational strength of the annotated AF, withr= 0.66 for ECG-based AF detection andr= 0.62 for PPG-based AF detection.
 
Conclusions: The findings indicate a patient-specific increase in relational strength for all four types of triggers.
 
Significance: The proposed approach has the potential to facilitate the implementation of longitudinal studies and can serve as a less biased alternative to questionnaire-based AF trigger detection.","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"9 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178633","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}
Background and Objective Obstructive sleep apnoea (OSA) affects an estimated 936 million people worldwide, yet only 15% receive a definitive diagnosis. Diagnosis of OSA poses challenges due to the dynamic nature of physiological signals such as oxygen saturation (SpO2) and heart rate variability (HRV). Linear analysis methods may not fully capture the irregularities present in these signals. The application of entropy of routine physiological signals offers a promising method to better measure variabilities in dynamic biological data. This review aims to explore entropy changes in physiological signals among individuals with OSA.
Methods Keyword and title searches were performed on Medline, Embase, Scopus, and CINAHL databases. Studies had to analyse physiological signals in OSA using entropy. Quality assessment used the Newcastle-Ottawa Scale. Evidence was qualitatively synthesized, considering entropy signals, entropy type, and time-series length.
Main results Twenty-two studies were included. Multiple physiological signals related to OSA, including SpO2, HRV, and the oxygen desaturation index (ODI), have been investigated using entropy. Results revealed a significant decrease in HRV entropy in those with OSA compared to control groups. Conversely, SpO2 and ODI entropy values were increased in OSA. Despite variations in entropy types, time scales, and data extraction devices, studies using receiver operating characteristic (ROC) curves demonstrated a high discriminative accuracy (>80% AUC) in distinguishing OSA patients from control groups.
Conclusions This review highlights the potential of SpO2 entropy analysis in developing new diagnostic indices for patients with OSA. Further investigation is needed before applying this technique clinically.
.
背景和目的 据估计，全球有 9.36 亿人患有阻塞性睡眠呼吸暂停（OSA），但只有 15%的人得到明确诊断。由于血氧饱和度（SpO2）和心率变异性（HRV）等生理信号的动态性质，OSA 的诊断面临挑战。线性分析方法可能无法完全捕捉到这些信号中存在的不规则性。常规生理信号熵的应用为更好地测量动态生物数据中的变异性提供了一种很有前景的方法。本综述旨在探讨 OSA 患者生理信号的熵变化。方法 在 Medline、Embase、Scopus 和 CINAHL 数据库中进行关键词和标题检索。研究必须使用熵分析 OSA 的生理信号。采用纽卡斯尔-渥太华量表进行质量评估。考虑到熵信号、熵类型和时间序列长度，对证据进行了定性综合。使用熵对与 OSA 相关的多种生理信号进行了研究，包括 SpO2、心率变异和氧饱和度指数 (ODI)。结果显示，与对照组相比，OSA 患者的心率变异熵明显下降。相反，SpO2 和 ODI 的熵值在 OSA 患者中有所增加。尽管熵的类型、时间尺度和数据提取设备各不相同，但使用接收器操作特征曲线（ROC）进行的研究表明，在区分 OSA 患者和对照组时，熵的鉴别准确率很高（AUC >80%）。在将此技术应用于临床之前，还需要进一步的研究。
{"title":"Changes in physiological signal entropy in patients with obstructive sleep apnoea: a systematic review.","authors":"Nawal Ziyad Alotaibi,Maggie Cheung,Amar Shah,John Hurst,Alireza Mani,Swapna Mandal","doi":"10.1088/1361-6579/ad79b4","DOIUrl":"https://doi.org/10.1088/1361-6579/ad79b4","url":null,"abstract":"Background and Objective Obstructive sleep apnoea (OSA) affects an estimated 936 million people worldwide, yet only 15% receive a definitive diagnosis. Diagnosis of OSA poses challenges due to the dynamic nature of physiological signals such as oxygen saturation (SpO2) and heart rate variability (HRV). Linear analysis methods may not fully capture the irregularities present in these signals. The application of entropy of routine physiological signals offers a promising method to better measure variabilities in dynamic biological data. This review aims to explore entropy changes in physiological signals among individuals with OSA.
Methods Keyword and title searches were performed on Medline, Embase, Scopus, and CINAHL databases. Studies had to analyse physiological signals in OSA using entropy. Quality assessment used the Newcastle-Ottawa Scale. Evidence was qualitatively synthesized, considering entropy signals, entropy type, and time-series length.
Main results Twenty-two studies were included. Multiple physiological signals related to OSA, including SpO2, HRV, and the oxygen desaturation index (ODI), have been investigated using entropy. Results revealed a significant decrease in HRV entropy in those with OSA compared to control groups. Conversely, SpO2 and ODI entropy values were increased in OSA. Despite variations in entropy types, time scales, and data extraction devices, studies using receiver operating characteristic (ROC) curves demonstrated a high discriminative accuracy (>80% AUC) in distinguishing OSA patients from control groups. 
Conclusions This review highlights the potential of SpO2 entropy analysis in developing new diagnostic indices for patients with OSA. Further investigation is needed before applying this technique clinically.

.","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"152 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178611","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}
Pub Date : 2024-09-10DOI: 10.1088/1361-6579/ad7931
Julia Louise Nelson,Connor Cobb,Joshua L Keller,Miranda K Traylor,David Arthur Nelson,Christopher Michael Francis
OBJECTIVEPeripheral Artery Disease (PAD) is a progressive cardiovascular condition affecting 8-10 million adults in the United States. PAD elevates the risk of cardiovascular events, but up to 50% of people with PAD are asymptomatic and undiagnosed. In this study, we tested the ability of a device, REFLO (Rapid Electromagnetic FLOw), to identify low blood flow using electromagnetic radiation and dynamic thermography toward a non-invasive PAD diagnostic.APPROACHDuring REFLO radio frequency (RF) irradiation, the rate of temperature increase is a function of the rate of energy absorption and blood flow to the irradiated tissue. For a given rate of RF energy absorption, a slow rate of temperature increase implies a large blood flow rate to the tissue. This is due to the cooling effect of the blood. Post-irradiation, a slow rate of temperature decrease is associated with a low rate of blood flow to the tissue. Here, we performed two cohorts of controlled flow experiments on human calves during baseline, occluded, and post-occluded conditions. Nonlinear regression was used to fit temperature data and obtain the rate constant, which was used as a metric for blood flow.MAIN RESULTSIn the pilot study, (N = 7) REFLO distinguished between baseline and post-occlusion during the irradiation phase, and between baseline and occlusion in the post-irradiation phase. In the reliability study, (N = 5 with 3 visits each), two-way ANOVA revealed that flow and subject significantly affected skin heating and cooling rates, while visit did not.SIGNIFICANCEResults suggest that MMW irradiation can be used to distinguish between blood flow rates in humans. Utilizing the rate of skin cooling rather than heating is more consistent for distinguishing flow. Future modifications and clinical testing will aim to improve REFLO's ability to distinguish between flow rates and evaluate its ability to accurately identify PAD.
目的外周动脉疾病（PAD）是一种渐进性心血管疾病，影响着美国 800 万到 1000 万成年人。PAD 会增加心血管事件的风险，但多达 50% 的 PAD 患者没有症状，也未得到诊断。在这项研究中，我们测试了一种名为 REFLO（Rapid Electromagnetic FLOw）的设备利用电磁辐射和动态热成像技术识别低血流量的能力，以实现对 PAD 的无创诊断。对于给定的射频能量吸收率，温度上升速度慢意味着组织的血流量大。这是由于血液的冷却作用。辐照后，温度下降速度慢则组织血流量低。在此，我们对基线、闭塞和闭塞后条件下的人类小腿进行了两组受控血流实验。主要结果在试验研究中，（N = 7）REFLO 在辐照阶段区分了基线和闭塞后，在辐照后阶段区分了基线和闭塞后。在可靠性研究（5 人，每人 3 次）中，双向方差分析显示，血流和受试者对皮肤加热和冷却速率有显著影响，而访问则没有影响。利用皮肤冷却率而不是加热率来区分血流速度更为一致。未来的修改和临床测试将旨在提高 REFLO 区分血流速度的能力，并评估其准确识别 PAD 的能力。
{"title":"Millimeter wave radiation to measure blood flow in healthy human subjects.","authors":"Julia Louise Nelson,Connor Cobb,Joshua L Keller,Miranda K Traylor,David Arthur Nelson,Christopher Michael Francis","doi":"10.1088/1361-6579/ad7931","DOIUrl":"https://doi.org/10.1088/1361-6579/ad7931","url":null,"abstract":"OBJECTIVEPeripheral Artery Disease (PAD) is a progressive cardiovascular condition affecting 8-10 million adults in the United States. PAD elevates the risk of cardiovascular events, but up to 50% of people with PAD are asymptomatic and undiagnosed. In this study, we tested the ability of a device, REFLO (Rapid Electromagnetic FLOw), to identify low blood flow using electromagnetic radiation and dynamic thermography toward a non-invasive PAD diagnostic.APPROACHDuring REFLO radio frequency (RF) irradiation, the rate of temperature increase is a function of the rate of energy absorption and blood flow to the irradiated tissue. For a given rate of RF energy absorption, a slow rate of temperature increase implies a large blood flow rate to the tissue. This is due to the cooling effect of the blood. Post-irradiation, a slow rate of temperature decrease is associated with a low rate of blood flow to the tissue. Here, we performed two cohorts of controlled flow experiments on human calves during baseline, occluded, and post-occluded conditions. Nonlinear regression was used to fit temperature data and obtain the rate constant, which was used as a metric for blood flow.MAIN RESULTSIn the pilot study, (N = 7) REFLO distinguished between baseline and post-occlusion during the irradiation phase, and between baseline and occlusion in the post-irradiation phase. In the reliability study, (N = 5 with 3 visits each), two-way ANOVA revealed that flow and subject significantly affected skin heating and cooling rates, while visit did not.SIGNIFICANCEResults suggest that MMW irradiation can be used to distinguish between blood flow rates in humans. Utilizing the rate of skin cooling rather than heating is more consistent for distinguishing flow. Future modifications and clinical testing will aim to improve REFLO's ability to distinguish between flow rates and evaluate its ability to accurately identify PAD.","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"11 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178612","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}
BACKGROUNDSleepiness assessment tools were mostly developed for detection of an elevated sleepiness level in the condition of sleep deprivation and several medical conditions. However, sleepiness occurs in various other conditions including the transition from wakefulness to sleep during an everyday attempt to get sleep.OBJECTIVEWe examined whether objective sleepiness indexes can be implicated in detection of fluctuations in sleepiness level during the polysomnographically-monitored attempt to sleep, i.e., in the absence of self-reports on perceived sleepiness level throughout such an attempt.APPROACHThe polysomnographic signals were recorded in the afternoon throughout 106 90-min napping attempts of 53 university students (28 females). To calculate two objective sleepiness indexes, the electroencephalographic (EEG) spectra were averaged on 30-s epochs of each record, assigned to one of 5 sleep-wake stages, and scored using either the frequency weighting curve for sleepiness substate of wake state or loadings of each frequency on the 2nd principal component of variation in the EEG spectrum (either sleepiness score or PC2 score, respectively).MAIN RESULTSWe showed that statistically significant fluctuations in these two objective sleepiness indexes during epochs assigned to wake stage can be described in terms of the changes in verbally anchored levels of subjective sleepiness assessed by scoring on the 9-step Karolinska Sleepiness Scale.SIGNIFICANCEThe results afford new opportunities to elaborate importance of intermediate substates between wake and sleep states for sleep-wake dynamics in healthy individuals and patients with disturbed sleep.
{"title":"How to quantify sleepiness during an attempt to sleep?","authors":"Arcady Putilov,Dmitry Sveshnikov,Elena Yakunina,Olga Mankaeva,Alexandra Puchkova,Dmitry Shumov,Eugenia Gandina,Anton Taranov,Natalya Ligun,Olga Donskaya,Evgeniy Verevkin,Vladimir Dorokhov","doi":"10.1088/1361-6579/ad7930","DOIUrl":"https://doi.org/10.1088/1361-6579/ad7930","url":null,"abstract":"BACKGROUNDSleepiness assessment tools were mostly developed for detection of an elevated sleepiness level in the condition of sleep deprivation and several medical conditions. However, sleepiness occurs in various other conditions including the transition from wakefulness to sleep during an everyday attempt to get sleep.OBJECTIVEWe examined whether objective sleepiness indexes can be implicated in detection of fluctuations in sleepiness level during the polysomnographically-monitored attempt to sleep, i.e., in the absence of self-reports on perceived sleepiness level throughout such an attempt.APPROACHThe polysomnographic signals were recorded in the afternoon throughout 106 90-min napping attempts of 53 university students (28 females). To calculate two objective sleepiness indexes, the electroencephalographic (EEG) spectra were averaged on 30-s epochs of each record, assigned to one of 5 sleep-wake stages, and scored using either the frequency weighting curve for sleepiness substate of wake state or loadings of each frequency on the 2nd principal component of variation in the EEG spectrum (either sleepiness score or PC2 score, respectively).MAIN RESULTSWe showed that statistically significant fluctuations in these two objective sleepiness indexes during epochs assigned to wake stage can be described in terms of the changes in verbally anchored levels of subjective sleepiness assessed by scoring on the 9-step Karolinska Sleepiness Scale.SIGNIFICANCEThe results afford new opportunities to elaborate importance of intermediate substates between wake and sleep states for sleep-wake dynamics in healthy individuals and patients with disturbed sleep.","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"38 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178613","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}
Pub Date : 2024-09-09DOI: 10.1088/1361-6579/ad78a3
Luis Mercado,Sallie Oliphant,Diana Escalona-Vargas,Eric R Siegel,Heather Moody,Hari Eswaran
Levator ani muscles undergo significant stretching and micro-trauma at childbirth. The goal was to assess the neuromuscular integrity of this muscle group by means of magnetomyography and correlate with Brink score - a commonly used digital assessment of pelvic floor muscle strength.
Methods:
Non-invasive magnetomyography (MMG) data was collected on 22 pregnant women during rest and voluntary contraction of the pelvic-floor muscles (Kegels). The mean amplitude and power spectral density (PSD) of the Kegels were correlated to Brink pressure score.
Results:
The Brink's scores demonstrated medium correlations (≥0.3) with MMG amplitude and PSD with the average Kegel of medium intensity and rest. Data showed that the "resting state" of the pelvic floor is, in actuality, quite dynamic and may have implications for pelvic floor disorder propensity postpartum.
Conclusion:
These results confirm the ability of non-invasive magnetomyography to reliably capture pelvic floor contraction as these signals correlate with clinical measure.
.
{"title":"Comparison of non-invasive magnetomyography to Brink score for assessment of pelvic floor muscle strength.","authors":"Luis Mercado,Sallie Oliphant,Diana Escalona-Vargas,Eric R Siegel,Heather Moody,Hari Eswaran","doi":"10.1088/1361-6579/ad78a3","DOIUrl":"https://doi.org/10.1088/1361-6579/ad78a3","url":null,"abstract":"
Levator ani muscles undergo significant stretching and micro-trauma at childbirth. The goal was to assess the neuromuscular integrity of this muscle group by means of magnetomyography and correlate with Brink score - a commonly used digital assessment of pelvic floor muscle strength.
Methods:
Non-invasive magnetomyography (MMG) data was collected on 22 pregnant women during rest and voluntary contraction of the pelvic-floor muscles (Kegels). The mean amplitude and power spectral density (PSD) of the Kegels were correlated to Brink pressure score.
Results:
The Brink's scores demonstrated medium correlations (≥0.3) with MMG amplitude and PSD with the average Kegel of medium intensity and rest. Data showed that the \"resting state\" of the pelvic floor is, in actuality, quite dynamic and may have implications for pelvic floor disorder propensity postpartum.
Conclusion:
These results confirm the ability of non-invasive magnetomyography to reliably capture pelvic floor contraction as these signals correlate with clinical measure.
.","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":"36 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178614","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}
Pub Date : 2024-09-06DOI: 10.1088/1361-6579/ad74d5
Buket Sonbas Cobb, Stephen J Kolb, Seward B Rutkove
Objective.To evaluate electrical impedance myography (EIM) in conjunction with machine learning (ML) to detect infantile spinal muscular atrophy (SMA) and disease progression.Approach. Twenty-six infants with SMA and twenty-seven healthy infants had been enrolled and assessed with EIM as part of the NeuroNEXT SMA biomarker study. We applied a variety of modern, supervised ML approaches to this data, first seeking to differentiate healthy from SMA muscle, and then, using the best method, to track SMA progression.Main Results.Several of the ML algorithms worked well, but linear discriminant analysis (LDA) achieved 88.6% accuracy on subject muscles studied. This contrasts with a maximum of 60% accuracy that could be achieved using the single or multifrequency assessment approaches available at the time. LDA scores were also able to track progression effectively, although a multifrequency reactance-based measure also performed very well in this context.Significance.EIM enhanced with ML promises to be effective for providing effective diagnosis and tracking children and adults with SMA treated with currently available therapies. The normative trends identified here may also inform future applications of the technology in very young children. The basic analyses applied here could also likely be applied to other neuromuscular disorders characterized by muscle atrophy.
目的：
评估电阻抗肌电图（EIM）与机器学习相结合检测小儿脊髓性肌萎缩症（SMA）和疾病进展的效果
方法：
作为 NeuroNEXT SMA 生物标记物研究的一部分，我们对 26 名 SMA 婴儿和 27 名健康婴儿进行了登记和 EIM 评估。我们对这些数据采用了多种现代、有监督的机器学习方法，首先寻求区分健康和 SMA 肌肉，然后使用最佳方法跟踪 SMA 的进展。这与当时使用单频或多频评估方法达到的最高 66% 的准确率形成了鲜明对比。尽管基于多频反应的测量方法在这方面也表现出色，但 LDA 分数也能有效跟踪病情进展。这里确定的标准值和趋势对该技术的其他儿科应用也很有价值。这里应用的基本分析方法也可能适用于其他以肌肉萎缩为特征的神经肌肉疾病。
{"title":"Machine learning-enhanced electrical impedance myography to diagnose and track spinal muscular atrophy progression.","authors":"Buket Sonbas Cobb, Stephen J Kolb, Seward B Rutkove","doi":"10.1088/1361-6579/ad74d5","DOIUrl":"10.1088/1361-6579/ad74d5","url":null,"abstract":"<p><p><i>Objective.</i>To evaluate electrical impedance myography (EIM) in conjunction with machine learning (ML) to detect infantile spinal muscular atrophy (SMA) and disease progression.<i>Approach</i>. Twenty-six infants with SMA and twenty-seven healthy infants had been enrolled and assessed with EIM as part of the NeuroNEXT SMA biomarker study. We applied a variety of modern, supervised ML approaches to this data, first seeking to differentiate healthy from SMA muscle, and then, using the best method, to track SMA progression.<i>Main Results.</i>Several of the ML algorithms worked well, but linear discriminant analysis (LDA) achieved 88.6% accuracy on subject muscles studied. This contrasts with a maximum of 60% accuracy that could be achieved using the single or multifrequency assessment approaches available at the time. LDA scores were also able to track progression effectively, although a multifrequency reactance-based measure also performed very well in this context.<i>Significance.</i>EIM enhanced with ML promises to be effective for providing effective diagnosis and tracking children and adults with SMA treated with currently available therapies. The normative trends identified here may also inform future applications of the technology in very young children. The basic analyses applied here could also likely be applied to other neuromuscular disorders characterized by muscle atrophy.</p>","PeriodicalId":20047,"journal":{"name":"Physiological measurement","volume":" ","pages":""},"PeriodicalIF":2.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11446569/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142093680","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}
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