An empirical study of modified beat SQI based majority voting fusion method for heart-rate estimation in noisy multimodal cardiovascular signals
This study aims to: (i) propose a modified beat signal quality index-based majority voting fusion (MMVF) method to deal with extremely noisy cardiovascular signals; (ii) generate synthetic noise datasets from standard PhysioNet datasets by adding different types of ECG noises, i.e. baseline wander (bw), electrode motion (em), muscle artifact (ma), and realistic artificial ABP noises in clean or low-noise ECG and ABP signals, respectively; and (iii) analyze the effectiveness of the MMVF method for heart-rate estimation with different combinations of beat detectors. Approach. The modified beat signal quality index in the pro...
Source: Physiological Measurement - December 22, 2022 Category: Physiology Authors: Shalini A Rankawat Source Type: research
Lung volumes measurement using novel pressure derived method in participants with obstructive, restrictive and healthy lungs
Conclusions. Lung volumes measured by BP and CT had high concordance in the scenario of varied pulmonary conditions including lung bullae, restrictive and obstructive diseases. The new PDM device, had low intra-test variability, and was easy to perform, with a reasonable co ncordance with BP. (Source: Physiological Measurement)
Source: Physiological Measurement - December 20, 2022 Category: Physiology Authors: Jacob Zac, Salomon Zac, Rogelio P érez-Padilla, Arantxa Remigio-Luna, Nicolas Guzmán-Boulloud, Laura Gochicoa-Rangel, Carlos Guzmán-Valderrábano and Ireri Thirión-Romero Source Type: research
Seizure forecasting using machine learning models trained by seizure diaries
Objectives. People with refractory epilepsy are overwhelmed by the uncertainty of their next seizures. Accurate prediction of future seizures could greatly improve the quality of life for these patients. New evidence suggests that seizure occurrences can have cyclical patterns for some patients. Even though these cyclicalities are not intuitive, they can be identified by machine learning (ML), to identify patients with predictable vs unpredictable seizure patterns. Approach. Self-reported seizure logs of 153 patients from the Human Epilepsy Project with more than three reported seizures (totaling 8337 seizures) were used t...
Source: Physiological Measurement - December 14, 2022 Category: Physiology Authors: Ezequiel Gleichgerrcht, Mircea Dumitru, David A Hartmann, Brent C Munsell, Ruben Kuzniecky, Leonardo Bonilha and Reza Sameni Source Type: research
Application of Fourier-Bessel expansion and LSTM on multi-lead ECG for cardiac abnormalities identification
Objective. The availability of online electrocardiogram (ECG) repositories can aid researchers in developing automated cardiac abnormality diagnostic systems. Using such ECG repositories, this study aims to develop an algorithm that can assist physicians in diagnosing cardiac abnormalities. Approach. The PhysioNet/CinC 2021 Challenge has opened the venues for creating benchmark algorithms using standard and relatively diverse 12-lead ECG datasets. This work attempts to create a new machine learning approach for identifying common cardiac abnormalities using an ensemble-based classification with two models resulting from tw...
Source: Physiological Measurement - December 12, 2022 Category: Physiology Authors: Nidhi Kalidas Sawant and Shivnarayan Patidar Source Type: research
Multiscale entropy as a metric of brain maturation in a large cohort of typically developing children born preterm using longitudinal high-density EEG in the first two years of life
Objective. We aimed to analyze whether complexity of brain electrical activity (EEG) measured by multiscale entropy (MSE) increases with brain maturation during the first two years of life. We also aimed to investigate whether this complexity shows regional differences across the brain, and whether changes in complexity are influenced by extrauterine life experience duration. Approach. We measured MSE of EEG signals recorded longitudinally using a high-density setup (64 or 128 electrodes) in 84 typically developing infants born preterm (<32 weeks ’ gestation) from term age to two years. We analyzed the complexity inde...
Source: Physiological Measurement - December 7, 2022 Category: Physiology Authors: Karine Pelc, Aleksandra Gajewska, Natan Napi órkowski, Jonathan Dan, Caroline Verhoeven and Bernard Dan Source Type: research
Fast absolute 3D CGO-based electrical impedance tomography on experimental tank data
Objective. To present the first 3D CGO-based absolute EIT reconstructions from experimental tank data. Approach. CGO-based methods for absolute EIT imaging are compared to traditional TV regularized non-linear least squares reconstruction methods. Additional robustness testing is performed by considering incorrect modeling of domain shape. Main Results. The CGO-based methods are fast, and show strong robustness to incorrect domain modeling comparable to classic difference EIT imaging and fewer boundary artefacts than the TV regularized non-linear least squares reference reconstructions. Significance. This work is the first...
Source: Physiological Measurement - December 6, 2022 Category: Physiology Authors: S J Hamilton, P A Muller, D Isaacson, V Kolehmainen, J Newell, O Rajabi Shishvan, G Saulnier and J Toivanen Source Type: research
Changes of oscillogram envelope maximum with blood pressure and aging: a quantitative observation
This study experientially and theoretically concluded the BPs and aging are two important factors that influence the maximum value of the oscillogram envelope. (Source: Physiological Measurement)
Source: Physiological Measurement - December 1, 2022 Category: Physiology Authors: Fan Pan, Peiyu He, Yongjun Qian, Hu Gao, Fei Chen, Haipeng Liu and Dingchang Zheng Source Type: research
Agreement between standard and continuous wireless vital sign measurements after major abdominal surgery: a clinical comparison study
Objective. Continuous wireless monitoring outside the post-anesthesia or intensive care units may enable early detection of patient deterioration, but good accuracy of measurements is required. We aimed to assess the agreement between vital signs recorded by standard and novel wireless devices in postoperative patients. Approach. In 20 patients admitted to the post-anesthesia care unit, we compared heart rate (HR), respiratory rate (RR), peripheral oxygen saturation (SpO2), and systolic and diastolic blood pressure (SBP and DBP) as paired data. The primary outcome measure was the agreement between standard wired and wirele...
Source: Physiological Measurement - November 25, 2022 Category: Physiology Authors: Camilla Haahr-Raunkjaer, Magnus Skovbye, S øren M Rasmussen, Mikkel Elvekjaer, Helge B D Sørensen, Christian S Meyhoff and Eske K Aasvang Source Type: research
Pulse oximetry SpO
2 signal for automated identification of sleep apnea: a review and future trends
Sleep apnea (SA) is characterized by intermittent episodes of apnea or hypopnea paused or reduced breathing, respectively each lasting at least ten seconds that occur during sleep. SA has an estimated global prevalence of 200 million and is associated with medical comorbidity, and sufferers are also more likely to sustain traffic- and work-related injury due to daytime somnolence. SA is amenable to treatment if detected early. Polysomnography (PSG) involving multi-channel signal acquisition is the reference standard for diagnosing SA but is onerous and costly. For home-based detection of SA, single-channel SpO2 signal acqu...
Source: Physiological Measurement - November 25, 2022 Category: Physiology Authors: Manish Sharma, Kamlesh Kumar, Prince Kumar, Ru-San Tan and U Rajendra Acharya Source Type: research
Gas distribution by EIT during PEEP inflation: PEEP response and optimal PEEP with lowest trans-pulmonary driving pressure can be determined without esophageal pressure during a rapid PEEP trial in patients with acute respiratory failure
Objective. Protective ventilation should be based on lung mechanics and transpulmonary driving pressure ( ΔPTP), as this 'hits' the lung directly. Approach. The change in end-expiratory lung volume (ΔEELV) is determined by the size of the PEEP step and the elastic properties of the lung (EL), ΔEELV/ΔPEEP. Consequently, EL can be determined as ΔPEEP/ΔEELV. By calibration of tidal inspiratory impeda nce change with ventilator inspiratory tidal volume, end-expiratory lung impedance changes were converted to volume changes and lung P/V curves were obtained during a PEEP trial in ten patients with acute respiratory failur...
Source: Physiological Measurement - November 25, 2022 Category: Physiology Authors: Christina Grivans and Ola Stenqvist Source Type: research
Non-invasive blood pressure estimation combining deep neural networks with pre-training and partial fine-tuning
Objective. Daily blood pressure (BP) monitoring is essential since BP levels can reflect the functions of heart pumping and vasoconstriction. Although various neural network-based BP estimate approaches have been proposed, they have certain practical shortcomings, such as low estimation accuracy and poor model generalization. Based on the strategy of pre-training and partial fine-tuning, this work proposes a non-invasive method for BP estimation using the photoplethysmography (PPG) signal. Approach. To learn the PPG-BP relationship, the deep convolutional bidirectional recurrent neural network (DC-Bi-RNN) was pre-trained w...
Source: Physiological Measurement - November 11, 2022 Category: Physiology Authors: Ziyan Meng, Xuezhi Yang, Xuenan Liu, Dingliang Wang and Xuesong Han Source Type: research
A novel deep learning package for electrocardiography research
Objective. In recent years, deep learning has blossomed in the field of electrocardiography (ECG) processing, outperforming traditional signal processing methods in a number of typical tasks; for example, classification, QRS detection and wave delineation. Although many neural architectures have been proposed in the literature, there is a lack of systematic studies and open-source libraries for ECG deep learning. Approach. In this paper, we propose a deep learning package, named torch_ecg, which assembles a large number of neural networks, from existing and novel literature, for various ECG processing tasks. The models are...
Source: Physiological Measurement - November 4, 2022 Category: Physiology Authors: Hao Wen and Jingsu Kang Source Type: research
Contactless skin perfusion monitoring with video cameras: tracking pharmacological vasoconstriction and vasodilation using photoplethysmographic changes
We report relative pixel intensity changes from baseline, as absolute values are sensitive to environmental factors. The primary outcome was the pre- to peak- infusion green channel amplitude change in the pulsatile PPGi waveform component. Secondary outcomes were pre-to-peak changes in the photoplethysmographic imaging waveform baseline, skin colour hue and skin colour saturation. Main results. The 30 participants had a median age of 29 years (IQR 25 –34), sixteen (53%) were male. A 34.7% (p = 0.0001) mean decrease in the amplitude of the pulsatile photoplethysmographic imaging waveform occurred following phenylephrine ...
Source: Physiological Measurement - November 3, 2022 Category: Physiology Authors: M Harford, M Villarroel, J Jorge, O Redfern, E Finnegan, S Davidson, J D Young, L Tarassenko and P Watkinson Source Type: research
Postural control paradigm (BioVRSea): towards a neurophysiological signature
This study develops a neurophysiological reference during a complex postural control task. In particular, we found a strong localized activity associated with certain frequency bands during certain phases of the experiment. This is the first step towards a neurophysiological signature that can be used to identify pathological conditions lacking quantitative diagnostics assessment. (Source: Physiological Measurement)
Source: Physiological Measurement - November 3, 2022 Category: Physiology Authors: R Aubonnet, A Shoykhet, D Jacob, G Di Lorenzo, H Petersen and P Gargiulo Source Type: research
Deep learning-based remote-photoplethysmography measurement from short-time facial video
Objective. Efficient non-contact heart rate (HR) measurement from facial video has received much attention in health monitoring. Past methods relied on prior knowledge and an unproven hypothesis to extract remote photoplethysmography (rPPG) signals, e.g. manually designed regions of interest (ROIs) and the skin reflection model. Approach. This paper presents a short-time end to end HR estimation framework based on facial features and temporal relationships of video frames. In the proposed method, a deep 3D multi-scale network with cross-layer residual structure is designed to construct an autoencoder and extract robust rPP...
Source: Physiological Measurement - November 3, 2022 Category: Physiology Authors: Bin Li, Wei Jiang, Jinye Peng and Xiaobai Li Source Type: research
