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Sun T, Jin B, Wu Y, Bao J. A study of the attenuation stage of a global infectious disease. Front Public Health 2024; 12:1379481. [PMID: 38645440 PMCID: PMC11026565 DOI: 10.3389/fpubh.2024.1379481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 03/14/2024] [Indexed: 04/23/2024] Open
Abstract
Introduction Differences in control measures and response speeds between regions may be responsible for the differences in the number of infections of global infectious diseases. Therefore, this article aims to examine the decay stage of global infectious diseases. We demonstrate our method by considering the first wave of the COVID-19 epidemic in 2020. Methods We introduce the concept of the attenuation rate into the varying coefficient SEIR model to measure the effect of different cities on epidemic control, and make inferences through the integrated adjusted Kalman filter algorithm. Results We applied the varying coefficient SEIR model to 136 cities in China where the total number of confirmed cases exceeded 20 after the implementation of control measures and analyzed the relationship between the estimated attenuation rate and local factors. Subsequent analysis and inference results show that the attenuation rate is significantly related to the local annual GDP and the longitude and latitude of a city or a region. We also apply the varying coefficient SEIR model to other regions outside China. We find that the fitting curve of the average daily number of new confirmed cases simulated by the variable coefficient SEIR model is consistent with the real data. Discussion The results show that the cities with better economic development are able to control the epidemic more effectively to a certain extent. On the other hand, geographical location also affected the effectiveness of regional epidemic control. In addition, through the results of attenuation rate analysis, we conclude that China and South Korea have achieved good results in controlling the epidemic in 2020.
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Affiliation(s)
- Tianyi Sun
- Department of Statistics and Finance, University of Science and Technology of China, Hefei, China
| | - Baisuo Jin
- Department of Statistics and Finance, University of Science and Technology of China, Hefei, China
| | - Yuehua Wu
- Department of Mathematics and Statistics, York University, Toronto, ON, Canada
| | - Junjun Bao
- Endoscopy Center, The First Affiliated Hospital of Anhui Medical University, Hefei, China
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2
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Huang B, Yan J, Morris M, Sinnett V, Somaiah N, Tang MX. Acceleration-Based Kalman Tracking for Super-Resolution Ultrasound Imaging In Vivo. IEEE Trans Ultrason Ferroelectr Freq Control 2023; 70:1739-1748. [PMID: 37871098 PMCID: PMC7615377 DOI: 10.1109/tuffc.2023.3326863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Super-resolution ultrasound (SRUS) can image microvascular structure and flow at subwave-diffraction resolution based on localizing and tracking microbubbles (MBs). Currently, tracking MBs accurately under limited imaging frame rates and high MB concentrations remains a challenge, especially under the effect of cardiac pulsatility and in highly curved vessels. In this study, an acceleration-incorporated MB motion model is introduced into a Kalman tracking framework. The tracking performance was evaluated using simulated microvasculature with different MB motion parameters, concentrations, and acquisition frame rates, and in vivo human breast tumor US datasets. The simulation results show that the acceleration-based method outperformed the nonacceleration-based method at different levels of acceleration and acquisition frame rates and achieved significant improvement in true positive rate (TPR; up to 11.3%) and false negative rate (FNR; up to 13.2%). The proposed method can also reduce errors in vasculature reconstruction via the acceleration-based nonlinear interpolation, compared with linear interpolation (up to [Formula: see text]). The tracking results from temporally downsampled low frame rate in vivo datasets from human breast tumors show that the proposed method has better MB tracking performance than the baseline method, if using results from the initial high frame data as a reference. Finally, the acceleration estimated from tracking results also provides a spatial speed gradient map that may contain extra valuable diagnostic information.
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Affiliation(s)
- Biao Huang
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK, SW7 2AZ
| | - Jipeng Yan
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK, SW7 2AZ
| | - Megan Morris
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK, SW7 2AZ
| | | | - Navita Somaiah
- Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, UK, SM2 5NG
| | - Meng-Xing Tang
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK, SW7 2AZ
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3
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Tian H, Cai W, Ding W, Liang P, Yu J, Huang Q. Long-term liver lesion tracking in contrast-enhanced ultrasound videos via a siamese network with temporal motion attention. Front Physiol 2023; 14:1180713. [PMID: 37435311 PMCID: PMC10330811 DOI: 10.3389/fphys.2023.1180713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 05/31/2023] [Indexed: 07/13/2023] Open
Abstract
Propose: Contrast-enhanced ultrasound has shown great promises for diagnosis and monitoring in a wide range of clinical conditions. Meanwhile, to obtain accurate and effective location of lesion in contrast-enhanced ultrasound videos is the basis for subsequent diagnosis and qualitative treatment, which is a challenging task nowadays. Methods: We propose to upgrade a siamese architecture-based neural network for robust and accurate landmark tracking in contrast-enhanced ultrasound videos. Due to few researches on it, the general inherent assumptions of the constant position model and the missing motion model remain unaddressed limitations. In our proposed model, we overcome these limitations by introducing two modules into the original architecture. We use a temporal motion attention based on Lucas Kanade optic flow and Karman filter to model the regular movement and better instruct location prediction. Moreover, we design a pipeline of template update to ensure timely adaptation to feature changes. Results: Eventually, the whole framework was performed on our collected datasets. It has achieved the average mean IoU values of 86.43% on 33 labeled videos with a total of 37,549 frames. In terms of tracking stability, our model has smaller TE of 19.2 pixels and RMSE of 27.6 with the FPS of 8.36 ± 3.23 compared to other classical tracking models. Conclusion: We designed and implemented a pipeline for tracking focal areas in contrast-enhanced ultrasound videos, which takes the siamese network as the backbone and uses optical flow and Kalman filter algorithm to provide position prior information. It turns out that these two additional modules are helpful for the analysis of CEUS videos. We hope that our work can provide an idea for the analysis of CEUS videos.
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Affiliation(s)
- Haozhe Tian
- School of Computer Science, Northwestern Polytechnical University, Xi’an, China
| | - Wenjia Cai
- Department of Interventional Ultrasound, Chinese PLA General Hospital Fifth Medical Center, Beijing, China
| | - Wenzhen Ding
- Department of Interventional Ultrasound, Chinese PLA General Hospital Fifth Medical Center, Beijing, China
| | - Ping Liang
- Department of Interventional Ultrasound, Chinese PLA General Hospital Fifth Medical Center, Beijing, China
| | - Jie Yu
- Department of Interventional Ultrasound, Chinese PLA General Hospital Fifth Medical Center, Beijing, China
| | - Qinghua Huang
- School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China
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Das A, Hameed M, Prather R, Farias M, Divo E, Kassab A, Nykanen D, DeCampli W. In-Silico and In-Vitro Analysis of the Novel Hybrid Comprehensive Stage II Operation for Single Ventricle Circulation. Bioengineering (Basel) 2023; 10:bioengineering10020135. [PMID: 36829630 PMCID: PMC9952694 DOI: 10.3390/bioengineering10020135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 12/22/2022] [Accepted: 01/05/2023] [Indexed: 01/20/2023] Open
Abstract
Single ventricle (SV) anomalies account for one-fourth of all congenital heart disease cases. The existing palliative treatment for this anomaly achieves a survival rate of only 50%. To reduce the trauma associated with surgical management, the hybrid comprehensive stage II (HCSII) operation was designed as an alternative for a select subset of SV patients with the adequate antegrade aortic flow. This study aims to provide better insight into the hemodynamics of HCSII patients utilizing a multiscale Computational Fluid Dynamics (CFD) model and a mock flow loop (MFL). Both 3D-0D loosely coupled CFD and MFL models have been tuned to match baseline hemodynamic parameters obtained from patient-specific catheterization data. The hemodynamic findings from clinical data closely match the in-vitro and in-silico measurements and show a strong correlation (r = 0.9). The geometrical modification applied to the models had little effect on the oxygen delivery. Similarly, the particle residence time study reveals that particles injected in the main pulmonary artery (MPA) have successfully ejected within one cardiac cycle, and no pathological flows were observed.
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Affiliation(s)
- Arka Das
- Department of Mechanical Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA
- Correspondence: ; Tel.: +1-386-241-1457
| | - Marwan Hameed
- Department of Mechanical Engineering, American University of Bahrain, Riffa 942, Bahrain
| | - Ray Prather
- Department of Mechanical Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA
- Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL 32816, USA
- The Heart Center at Orlando Health Arnold Palmer Hospital for Children, Orlando, FL 32806, USA
| | - Michael Farias
- The Heart Center at Orlando Health Arnold Palmer Hospital for Children, Orlando, FL 32806, USA
- Department of Clinical Sciences, College of Medicine, University of Central Florida, Orlando, FL 32816, USA
| | - Eduardo Divo
- Department of Mechanical Engineering, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA
| | - Alain Kassab
- Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL 32816, USA
| | - David Nykanen
- The Heart Center at Orlando Health Arnold Palmer Hospital for Children, Orlando, FL 32806, USA
- Department of Clinical Sciences, College of Medicine, University of Central Florida, Orlando, FL 32816, USA
| | - William DeCampli
- The Heart Center at Orlando Health Arnold Palmer Hospital for Children, Orlando, FL 32806, USA
- Department of Clinical Sciences, College of Medicine, University of Central Florida, Orlando, FL 32816, USA
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Muhammad Naeem, Wali Khan Mashwani, Mohammad ABIAD, Habib Shah, Zardad Khan, Muhammad Aamir. Soft computing techniques for forecasting of COVID-19 in Pakistan. Alexandria Engineering Journal 2023; 63. [ DOI: 10.1016/j.aej.2022.07.029] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 07/16/2022] [Accepted: 07/18/2022] [Indexed: 12/01/2023]
Abstract
Novel Pandemic COVID-19 led globally to severe health barriers and financial issues in different parts of the world. The forecast on COVID-19 infections is significant. Demeanor vital data will help in executing policies to reduce the number of cases efficiently. Filtering techniques are appropriate for dynamic model structures as it provide reasonable estimates over the recursive Bayesian updates. Kalman Filters, used for controlling epidemics, are valuable in knowing contagious infections. Artificial Neural Networks (ANN) have generally been used for classification and forecasting problems. ANN models show an essential role in several successful applications of neural networks and are commonly used in economic and business studies. Long short-term memory (LSTM) model is one of the most popular technique used in time series analysis. This paper aims to forecast COVID-19 on the basis of ANN, KF, LSTM and SVM methods. We applied ANN, KF, LSTM and SVM for the COVID-19 data in Pakistan to find the number of deaths, confirm cases, and cases of recovery. The three methods were used for prediction, and the results showed the performance of LSTM to be better than that of ANN and KF method. ANN, KF, LSTM and SVM endorsed the COVID-19 data in closely all three scenarios. LSTM, ANN and KF followed the fluctuations of the original data and made close COVID-19 predictions. The results of the three methods helped significantly in the decision-making direction for short term strategies and in the control of the COVID-19 outbreak.
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Zhang J, Sui W, Zhang Q, Chen T, Yang C. Towards Accurate Ground Plane Normal Estimation from Ego-Motion. Sensors (Basel) 2022; 22:9375. [PMID: 36502078 PMCID: PMC9741436 DOI: 10.3390/s22239375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/26/2022] [Accepted: 11/29/2022] [Indexed: 06/17/2023]
Abstract
In this paper, we introduce a novel approach for ground plane normal estimation of wheeled vehicles. In practice, the ground plane is dynamically changed due to braking and unstable road surface. As a result, the vehicle pose, especially the pitch angle, is oscillating from subtle to obvious. Thus, estimating ground plane normal is meaningful since it can be encoded to improve the robustness of various autonomous driving tasks (e.g., 3D object detection, road surface reconstruction, and trajectory planning). Our proposed method only uses odometry as input and estimates accurate ground plane normal vectors in real time. Particularly, it fully utilizes the underlying connection between the ego pose odometry (ego-motion) and its nearby ground plane. Built on that, an Invariant Extended Kalman Filter (IEKF) is designed to estimate the normal vector in the sensor's coordinate. Thus, our proposed method is simple yet efficient and supports both camera- and inertial-based odometry algorithms. Its usability and the marked improvement of robustness are validated through multiple experiments on public datasets. For instance, we achieve state-of-the-art accuracy on KITTI dataset with the estimated vector error of 0.39°.
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Affiliation(s)
- Jiaxin Zhang
- Horizon Robotics, No. 9, FengHao East Road, Beijing 100094, China; (J.Z.); (W.S.); (Q.Z.)
| | - Wei Sui
- Horizon Robotics, No. 9, FengHao East Road, Beijing 100094, China; (J.Z.); (W.S.); (Q.Z.)
| | - Qian Zhang
- Horizon Robotics, No. 9, FengHao East Road, Beijing 100094, China; (J.Z.); (W.S.); (Q.Z.)
| | - Tao Chen
- School of Future Science and Engineering, Soochow University, Suzhou 215222, China;
| | - Cong Yang
- School of Future Science and Engineering, Soochow University, Suzhou 215222, China;
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7
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Yan J, Zhang T, Broughton-Venner J, Huang P, Tang MX. Super-Resolution Ultrasound Through Sparsity-Based Deconvolution and Multi-Feature Tracking. IEEE Trans Med Imaging 2022; 41:1938-1947. [PMID: 35171767 PMCID: PMC7614417 DOI: 10.1109/tmi.2022.3152396] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Ultrasound super-resolution imaging through localisation and tracking of microbubbles can achieve sub-wave-diffraction resolution in mapping both micro-vascular structure and flow dynamics in deep tissue in vivo. Currently, it is still challenging to achieve high accuracy in localisation and tracking particularly with limited imaging frame rates and in the presence of high bubble concentrations. This study introduces microbubble image features into a Kalman tracking framework, and makes the framework compatible with sparsity-based deconvolution to address these key challenges. The performance of the method is evaluated on both simulations using individual bubble signals segmented from in vivo data and experiments on a mouse brain and a human lymph node. The simulation results show that the deconvolution not only significantly improves the accuracy of isolating overlapping bubbles, but also preserves some image features of the bubbles. The combination of such features with Kalman motion model can achieve a significant improvement in tracking precision at a low frame rate over that using the distance measure, while the improvement is not significant at the highest frame rate. The in vivo results show that the proposed framework generates SR images that are significantly different from the current methods with visual improvement, and is more robust to high bubble concentrations and low frame rates.
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Affiliation(s)
- Jipeng Yan
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK, SW7 2AZ
| | - Tao Zhang
- Second Affiliate Hospital, Zhejiang University, Hangzhou, China, 313000
| | - Jacob Broughton-Venner
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK, SW7 2AZ
| | - Pintong Huang
- Second Affiliate Hospital, Zhejiang University, Hangzhou, China, 313000
| | - Meng-Xing Tang
- Ultrasound Lab for Imaging and Sensing, Department of Bioengineering, Imperial College London, London, UK, SW7 2AZ
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8
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Chang CW, Lo LY, Cheung HC, Feng Y, Yang AS, Wen CY, Zhou W. Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-Inertial Approach. Sensors (Basel) 2022; 22:404. [PMID: 35009946 PMCID: PMC8749553 DOI: 10.3390/s22010404] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 12/27/2021] [Accepted: 01/01/2022] [Indexed: 12/29/2022]
Abstract
This work aimed to develop an autonomous system for unmanned aerial vehicles (UAVs) to land on moving platforms such as an automobile or a marine vessel, providing a promising solution for a long-endurance flight operation, a large mission coverage range, and a convenient recharging ground station. Unlike most state-of-the-art UAV landing frameworks that rely on UAV onboard computers and sensors, the proposed system fully depends on the computation unit situated on the ground vehicle/marine vessel to serve as a landing guidance system. Such a novel configuration can therefore lighten the burden of the UAV, and the computation power of the ground vehicle/marine vessel can be enhanced. In particular, we exploit a sensor fusion-based algorithm for the guidance system to perform UAV localization, whilst a control method based upon trajectory optimization is integrated. Indoor and outdoor experiments are conducted, and the results show that precise autonomous landing on a 43 cm × 43 cm platform can be performed.
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Affiliation(s)
- Ching-Wei Chang
- Department of Mechanical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong; (C.-W.C.); (H.C.C.)
| | - Li-Yu Lo
- Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong; (L.-Y.L.); (Y.F.); (C.-Y.W.)
| | - Hiu Ching Cheung
- Department of Mechanical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong; (C.-W.C.); (H.C.C.)
| | - Yurong Feng
- Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong; (L.-Y.L.); (Y.F.); (C.-Y.W.)
| | - An-Shik Yang
- Department of Energy and Refrigerating Air-Conditioning Engineering, National Taipei University of Technology, Taipei 10608, Taiwan;
| | - Chih-Yung Wen
- Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong; (L.-Y.L.); (Y.F.); (C.-Y.W.)
| | - Weifeng Zhou
- School of Professional Education and Executive Development, The Hong Kong Polytechnic University, Kowloon, Hong Kong
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Zheng J, Li S, Liu S, Guan B, Wei D, Fu Q. Research on the Shearer Positioning Method Based on the MEMS Inertial Sensors/Odometer Integrated Navigation System and RTS Smoother. Micromachines (Basel) 2021; 12:mi12121527. [PMID: 34945378 PMCID: PMC8707076 DOI: 10.3390/mi12121527] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 12/07/2021] [Accepted: 12/07/2021] [Indexed: 11/16/2022]
Abstract
The shearer positioning method with an inertial measurement unit and the odometer is feasible in the longwall coal-mining process. However, the positioning accuracy will continue to decrease, especially for the micro-electromechanical inertial measurement unit (MIMU). In order to further improve the positioning accuracy of the shearer without adding other external sensors, the positioning method of the Rauch-Tung-Striebel (RTS) smoother-aided MIMU and odometer is proposed. A Kalman filter (KF) with the velocity and position measurements, which are provided by the odometer and closing path optimal estimation model (CPOEM), respectively, is established. The observability analysis is discussed to study the possible conditions under which the error states of KF can be estimated. A RTS smoother with the above-mentioned KF as the forward filter is built. Finally, the experiments of simulating the movement of the shearer through a mobile carrier were carried out, with a longitudinal movement distance of 44.6 m and a lateral advance distance of 1.2 m. The results show that the proposed method can effectively improve the positioning accuracy. In addition, the odometer scale factor and mounting angles can be estimated in real time.
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Caruso M, Sabatini AM, Knaflitz M, Della Croce U, Cereatti A. Extension of the Rigid-Constraint Method for the Heuristic Suboptimal Parameter Tuning to Ten Sensor Fusion Algorithms Using Inertial and Magnetic Sensing. Sensors (Basel) 2021; 21:s21186307. [PMID: 34577514 PMCID: PMC8473403 DOI: 10.3390/s21186307] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 09/10/2021] [Accepted: 09/17/2021] [Indexed: 11/23/2022]
Abstract
The orientation of a magneto-inertial measurement unit can be estimated using a sensor fusion algorithm (SFA). However, orientation accuracy is greatly affected by the choice of the SFA parameter values which represents one of the most critical steps. A commonly adopted approach is to fine-tune parameter values to minimize the difference between estimated and true orientation. However, this can only be implemented within the laboratory setting by requiring the use of a concurrent gold-standard technology. To overcome this limitation, a Rigid-Constraint Method (RCM) was proposed to estimate suboptimal parameter values without relying on any orientation reference. The RCM method effectiveness was successfully tested on a single-parameter SFA, with an average error increase with respect to the optimal of 1.5 deg. In this work, the applicability of the RCM was evaluated on 10 popular SFAs with multiple parameters under different experimental scenarios. The average residual between the optimal and suboptimal errors amounted to 0.6 deg with a maximum of 3.7 deg. These encouraging results suggest the possibility to properly tune a generic SFA on different scenarios without using any reference. The synchronized dataset also including the optical data and the SFA codes are available online.
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Affiliation(s)
- Marco Caruso
- PolitoBIOMed Lab—Biomedical Engineering Lab, Politecnico di Torino, 10129 Torino, Italy;
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy;
- Correspondence:
| | - Angelo Maria Sabatini
- Department of Excellence in Robotics & AI, The BioRobotics Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy;
| | - Marco Knaflitz
- PolitoBIOMed Lab—Biomedical Engineering Lab, Politecnico di Torino, 10129 Torino, Italy;
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy;
| | - Ugo Della Croce
- Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy;
| | - Andrea Cereatti
- Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy;
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Abstract
Electronic olfaction can help detect and localize harmful gases and pollutants, but the turbulence of the natural environment presents a particular challenge: odor encounters are intermittent, and an effective electronic nose must therefore be able to resolve short odor pulses. The slow responses of the widely used metal oxide (MOX) gas sensors complicate the task. Here, we combine high-resolution data acquisition with a processing method based on Kalman filtering and absolute-deadband sampling to extract fast onset events. We find that our system can resolve the onset time of odor encounters with enough precision for source direction estimation with a pair of MOX sensors in a stereo-osmic configuration.
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Affiliation(s)
- Damien Drix
- Biocomputation group, Department of Computer Science, University of Hertfordshire, Hatfield AL10 9AB, United Kingdom
| | - Michael Schmuker
- Biocomputation group, Department of Computer Science, University of Hertfordshire, Hatfield AL10 9AB, United Kingdom
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12
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Lee Y, Ahn T, Lee C, Kim S, Park K. A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication. Sensors (Basel) 2020; 20:E7022. [PMID: 33302467 DOI: 10.3390/s20247022] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 12/04/2020] [Accepted: 12/07/2020] [Indexed: 11/24/2022]
Abstract
In truck platooning, the leading vehicle is driven manually, and the following vehicles run by autonomous driving, with the short inter-vehicle distance between trucks. To successfully perform platooning in various situations, each truck must maintain dynamic stability, and furthermore, the whole system must maintain string stability. Due to the short front-view range, however, the following vehicles’ path planning capabilities become significantly impaired. In addition, in platooning with articulated cargo trucks, the off-tracking phenomenon occurring on a curved road makes it hard for the following vehicle to track the trajectory of the preceding truck. In addition, without knowledge of the global coordinate system, it is difficult to correlate the local coordinate systems that each truck relies on for sensing environment and dynamic signals. In this paper, in order to solve these problems, a path planning algorithm for platooning of articulated cargo trucks has been developed. Using the Kalman filter, V2V (Vehicle-to-Vehicle) communication, and a novel update-and-conversion method, each following vehicle can accurately compute the trajectory of the leading vehicle’s front part for using it as a target path. The path planning algorithm of this paper was validated by simulations on severe driving scenarios and by tests on an actual road. The results demonstrated that the algorithm could provide lateral string stability and robustness for truck platooning.
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Keskinoğlu C, Aydın A. Wearable wireless low-cost electrogoniometer design with Kalman filter for joint range of motion measurement and 3D modeling of joint movements. Proc Inst Mech Eng H 2020; 235:222-231. [PMID: 33183138 DOI: 10.1177/0954411920971398] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Joint movements are the key factor for the mobility of the people during daily activities. The evaluation of the joint movements is determined by the range of motion (ROM) parameters. The ROM might change due to age, gender, and some diseases. Therefore, it is essential to measure ROM accurately and compare it with the normal values of the healthy people. In this study, a low-cost, wireless, and wearable electrogoniometer was designed for highly precise and accurate measurements. The stability of the measurements is guaranteed with the quaternion based Kalman filter. The measurements of the developed system are compared with the traditional goniometer. The concordance correlation coefficient is calculated as a similarity metric, and the result is obtained as 1. In addition, a GUI was prepared to present 3D visualization of the movements in real-time with the ROM measurements and give visual feedback to the physiotherapists during physical examinations and to the patient during the home therapy sessions. The measurements also can be recorded using the GUI for retrospective analysis.
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Affiliation(s)
- Cemil Keskinoğlu
- Department of Biomedical Engineering, Cukurova University, Adana, Turkey
| | - Ahmet Aydın
- Department of Biomedical Engineering, Cukurova University, Adana, Turkey
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Changalvala R, Fedoruk B, Malik H. Radar Data Integrity Verification Using 2D QIM-Based Data Hiding. Sensors (Basel) 2020; 20:E5530. [PMID: 32992543 DOI: 10.3390/s20195530] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Revised: 09/17/2020] [Accepted: 09/22/2020] [Indexed: 11/16/2022]
Abstract
The modern-day vehicle is evolved in a cyber-physical system with internal networks (controller area network (CAN), Ethernet, etc.) connecting hundreds of micro-controllers. From the traditional core vehicle functions, such as vehicle controls, infotainment, and power-train management, to the latest developments, such as advanced driver assistance systems (ADAS) and automated driving features, each one of them uses CAN as their communication network backbone. Automated driving and ADAS features rely on data transferred over the CAN network from multiple sensors mounted on the vehicle. Verifying the integrity of the sensor data is essential for the safety and security of occupants and the proper functionality of these applications. Though the CAN interface ensures reliable data transfer, it lacks basic security features, including message authentication, which makes it vulnerable to a wide array of attacks, including spoofing, replay, DoS, etc. Using traditional cryptography-based methods to verify the integrity of data transmitted over CAN interfaces is expected to increase the computational complexity, latency, and overall cost of the system. In this paper, we propose a light-weight alternative to verify the sensor data's integrity for vehicle applications that use CAN networks for data transfers. To this end, a framework for 2-dimensional quantization index modulation (2D QIM)-based data hiding is proposed to achieve this goal. Using a typical radar sensor data transmission scenario in an autonomous vehicle application, we analyzed the performance of the proposed framework regarding detecting and localizing the sensor data tampering. The effects of embedding-induced distortion on the applications using the radar data were studied through a sensor fusion algorithm. It was observed that the proposed framework offers the much-needed data integrity verification without compromising on the quality of sensor fusion data and is implemented with low overall design complexity. This proposed framework can also be used on any physical network interface other than CAN, and it offers traceability to in-vehicle data beyond the scope of the in-vehicle applications.
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Tang S, Song P, Trzasko JD, Lowerison M, Huang C, Gong P, Lok UW, Manduca A, Chen S. Kalman Filter-Based Microbubble Tracking for Robust Super-Resolution Ultrasound Microvessel Imaging. IEEE Trans Ultrason Ferroelectr Freq Control 2020; 67:1738-1751. [PMID: 32248099 PMCID: PMC7485263 DOI: 10.1109/tuffc.2020.2984384] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Contrast microbubble (MB)-based super-resolution ultrasound microvessel imaging (SR-UMI) overcomes the compromise in conventional ultrasound imaging between spatial resolution and penetration depth and has been successfully applied to a wide range of clinical applications. However, clinical translation of SR-UMI remains challenging due to the limited number of MBs detected within a given accumulation time. Here, we propose a Kalman filter-based method for robust MB tracking and improved blood flow speed measurement with reduced numbers of MBs. An acceleration constraint and a direction constraint for MB movement were developed to control the quality of the estimated MB trajectory. An adaptive interpolation approach was developed to inpaint the missing microvessel signal based on the estimated local blood flow speed, facilitating more robust depiction of microvasculature with a limited amount of MBs. The proposed method was validated on an ex ovo chorioallantoic membrane and an in vivo rabbit kidney. Results demonstrated improved imaging performance on both microvessel density maps and blood flow speed maps. With the proposed method, the percentage of microvessel filling in a selected blood vessel at a given accumulation period was increased from 28.17% to 74.45%. A similar SR-UMI performance was achieved with MB numbers reduced by 85.96%, compared to that with the original MB number. The results indicate that the proposed method substantially improves the robustness of SR-UMI under a clinically relevant imaging scenario where SR-UMI is challenged by a limited MB accumulation time, reduced number of MBs, lowered imaging frame rate, and degraded signal-to-noise ratio.
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Affiliation(s)
- Shanshan Tang
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905
| | - Pengfei Song
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801
| | - Joshua D. Trzasko
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905
| | - Matthew Lowerison
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801
| | - Chengwu Huang
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905
| | - Ping Gong
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905
| | - U-Wai Lok
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905
| | - Armando Manduca
- Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, MN 55905
| | - Shigao Chen
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905
- Corresponding Author: Shigao Chen ()
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Wang S, Zhan X, Zhai Y, Liu B. Fault Detection and Exclusion for Tightly Coupled GNSS/INS System Considering Fault in State Prediction. Sensors (Basel) 2020; 20:E590. [PMID: 31973136 DOI: 10.3390/s20030590] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 01/14/2020] [Accepted: 01/18/2020] [Indexed: 11/17/2022]
Abstract
To ensure navigation integrity for safety-critical applications, this paper proposes an efficient Fault Detection and Exclusion (FDE) scheme for tightly coupled navigation system of Global Navigation Satellite Systems (GNSS) and Inertial Navigation System (INS). Special emphasis is placed on the potential faults in the Kalman Filter state prediction step (defined as "filter fault"), which could be caused by the undetected faults occurring previously or the Inertial Measurement Unit (IMU) failures. The integration model is derived first to capture the features and impacts of GNSS faults and filter fault. To accommodate various fault conditions, two independent detectors, which are respectively designated for GNSS fault and filter fault, are rigorously established based on hypothesis-test methods. Following a detection event, the newly-designed exclusion function enables (a) identifying and removing the faulty measurements and (b) eliminating the effect of filter fault through filter recovery. Moreover, we also attempt to avoid wrong exclusion events by analyzing the underlying causes and optimizing the decision strategy for GNSS fault exclusion accordingly. The FDE scheme is validated through multiple simulations, where high efficiency and effectiveness have been achieved in various fault scenarios.
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Bai YT, Wang XY, Jin XB, Zhao ZY, Zhang BH. A Neuron-Based Kalman Filter with Nonlinear Autoregressive Model. Sensors (Basel) 2020; 20:s20010299. [PMID: 31948060 PMCID: PMC6983156 DOI: 10.3390/s20010299] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 12/25/2019] [Accepted: 01/02/2020] [Indexed: 11/16/2022]
Abstract
The control effect of various intelligent terminals is affected by the data sensing precision. The filtering method has been the typical soft computing method used to promote the sensing level. Due to the difficult recognition of the practical system and the empirical parameter estimation in the traditional Kalman filter, a neuron-based Kalman filter was proposed in the paper. Firstly, the framework of the improved Kalman filter was designed, in which the neuro units were introduced. Secondly, the functions of the neuro units were excavated with the nonlinear autoregressive model. The neuro units optimized the filtering process to reduce the effect of the unpractical system model and hypothetical parameters. Thirdly, the adaptive filtering algorithm was proposed based on the new Kalman filter. Finally, the filter was verified with the simulation signals and practical measurements. The results proved that the filter was effective in noise elimination within the soft computing solution.
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Affiliation(s)
- Yu-ting Bai
- School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China; (Y.-t.B.); (Z.-y.Z.)
- Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China
| | - Xiao-yi Wang
- School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China; (Y.-t.B.); (Z.-y.Z.)
- Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China
- Correspondence: (X.-y.W.); (X.-b.J.)
| | - Xue-bo Jin
- School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China; (Y.-t.B.); (Z.-y.Z.)
- Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China
- Correspondence: (X.-y.W.); (X.-b.J.)
| | - Zhi-yao Zhao
- School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China; (Y.-t.B.); (Z.-y.Z.)
- Beijing Key Laboratory of Big Data Technology for Food Safety, Beijing Technology and Business University, Beijing 100048, China
| | - Bai-hai Zhang
- School of Automation, Beijing Institute of Technology, Beijing 100811, China;
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Brembeck J. A Physical Model-Based Observer Framework for Nonlinear Constrained State Estimation Applied to Battery State Estimation. Sensors (Basel) 2019; 19:E4402. [PMID: 31614570 DOI: 10.3390/s19204402] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Revised: 09/30/2019] [Accepted: 10/01/2019] [Indexed: 11/16/2022]
Abstract
Future electrified autonomous vehicles demand higly accurate knowledge of their system states to guarantee a high-fidelity and reliable control. This constitutes a challenging task—firstly, due to rising complexity and operational safeness, and secondly, due to the need for embedded service oriented architecture which demands a continuous development of new functionalities. Based on this, a novel model based Kalman filter framework is outlined in this publication, which enables the automatic incorporation of multiphysical Modelica models into discrete-time estimation algorithms. Additionally, these estimation algorithms are extended with nonlinear inequality constraint handling functionalities. The proposed framework is applied to a constrained nonlinear state of charge lithium-ion cell observer and is validated with experimental data.
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Mohebian MR, Marateb HR, Karimimehr S, Mañanas MA, Kranjec J, Holobar A. Non-invasive Decoding of the Motoneurons: A Guided Source Separation Method Based on Convolution Kernel Compensation With Clustered Initial Points. Front Comput Neurosci 2019; 13:14. [PMID: 31001100 PMCID: PMC6455215 DOI: 10.3389/fncom.2019.00014] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2018] [Accepted: 02/26/2019] [Indexed: 11/18/2022] Open
Abstract
Despite the progress in understanding of neural codes, the studies of the cortico-muscular coupling still largely rely on interferential electromyographic (EMG) signal or its rectification for the assessment of motor neuron pool behavior. This assessment is non-trivial and should be used with precaution. Direct analysis of neural codes by decomposing the EMG, also known as neural decoding, is an alternative to EMG amplitude estimation. In this study, we propose a fully-deterministic hybrid surface EMG (sEMG) decomposition approach that combines the advantages of both template-based and Blind Source Separation (BSS) decomposition approaches, a.k.a. guided source separation (GSS), to identify motor unit (MU) firing patterns. We use the single-pass density-based clustering algorithm to identify possible cluster representatives in different sEMG channels. These cluster representatives are then used as initial points of modified gradient Convolution Kernel Compensation (gCKC) algorithm. Afterwards, we use the Kalman filter to reduce the noise impact and increase convergence rate of MU filter identification by gCKC. Moreover, we designed an adaptive soft-thresholding method to identify MU firing times out of estimated MU spike trains. We tested the proposed algorithm on a set of synthetic sEMG signals with known MU firing patterns. A grid of 9 × 10 monopolar surface electrodes with 5-mm inter-electrode distances in both directions was simulated. Muscle excitation was set to 10, 30, and 50%. Colored Gaussian zero-mean noise with the signal-to-noise ratio (SNR) of 10, 20, and 30 dB, respectively, was added to 16 s long sEMG signals that were sampled at 4,096 Hz. Overall, 45 simulated signals were analyzed. Our decomposition approach was compared with gCKC algorithm. Overall, in our algorithm, the average numbers of identified MUs and Rate-of-Agreement (RoA) were 16.41 ± 4.18 MUs and 84.00 ± 0.06%, respectively, whereas the gCKC identified 12.10 ± 2.32 MUs with the average RoA of 90.78 ± 0.08%. Therefore, the proposed GSS method identified more MUs than the gCKC, with comparable performance. Its performance was dependent on the signal quality but not the signal complexity at different force levels. The proposed algorithm is a promising new offline tool in clinical neurophysiology.
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Affiliation(s)
- Mohammad Reza Mohebian
- The Biomedical Engineering Department, Engineering Faculty, University of Isfahan, Isfahan, Iran
| | - Hamid Reza Marateb
- The Biomedical Engineering Department, Engineering Faculty, University of Isfahan, Isfahan, Iran
| | - Saeed Karimimehr
- The Biomedical Engineering Department, Engineering Faculty, University of Isfahan, Isfahan, Iran
- Brain Engineering Research Center, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Miquel Angel Mañanas
- Department of Automatic Control, Biomedical Engineering Research Center, Universitat Politècnica de Catalunya BarcelonaTech, Barcelona, Spain
- Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain
| | - Jernej Kranjec
- Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
| | - Ales Holobar
- Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia
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20
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Aljoumani B, Sanchez-Espigares JA, Wessolek G. Estimating Pore Water Electrical Conductivity of Sandy Soil from Time Domain Reflectometry Records Using a Time-Varying Dynamic Linear Model. Sensors (Basel) 2018; 18:s18124403. [PMID: 30551566 PMCID: PMC6308429 DOI: 10.3390/s18124403] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 12/07/2018] [Accepted: 12/10/2018] [Indexed: 11/16/2022]
Abstract
Despite the importance of computing soil pore water electrical conductivity (σp) from soil bulk electrical conductivity (σb) in ecological and hydrological applications, a good method of doing so remains elusive. The Hilhorst concept offers a theoretical model describing a linear relationship between σb, and relative dielectric permittivity (εb) in moist soil. The reciprocal of pore water electrical conductivity (1/σp) appears as a slope of the Hilhorst model and the ordinary least squares (OLS) of this linear relationship yields a single estimate (1/σp^) of the regression parameter vector (σp) for the entire data. This study was carried out on a sandy soil under laboratory conditions. We used a time-varying dynamic linear model (DLM) and the Kalman filter (Kf) to estimate the evolution of σp over time. A time series of the relative dielectric permittivity (εb) and σb of the soil were measured using time domain reflectometry (TDR) at different depths in a soil column to transform the deterministic Hilhorst model into a stochastic model and evaluate the linear relationship between εb and σb in order to capture deterministic changes to (1/σp). Applying the Hilhorst model, strong positive autocorrelations between the residuals could be found. By using and modifying them to DLM, the observed and modeled data of εb obtain a much better match and the estimated evolution of σp converged to its true value. Moreover, the offset of this linear relation varies for each soil depth.
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Affiliation(s)
- Basem Aljoumani
- Department of Ecology, Ecohydrology and Landscape Evaluation, Technische Universität Berlin Ernst-Reuter Platz 1, 10587 Berlin, Germany.
| | - Jose A Sanchez-Espigares
- Department of Statistical and Operational Research, Universitat Politècnica de Catalunya (UPC), Jordi Girona, 31, 08034 Barcelona, Spain.
| | - Gerd Wessolek
- Department of Ecology, Technische Universität Berlin Ernst-Reuter Platz 1, 10587 Berlin, Germany.
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Culaclii S, Kim B, Lo YK, Li L, Liu W. Online Artifact Cancelation in Same-Electrode Neural Stimulation and Recording Using a Combined Hardware and Software Architecture. IEEE Trans Biomed Circuits Syst 2018; 12:601-613. [PMID: 29877823 PMCID: PMC6299268 DOI: 10.1109/tbcas.2018.2816464] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Advancing studies of neural network dynamics and developments of closed-loop neural interfaces requires the ability to simultaneously stimulate and record the neural cells. Recording adjacent to or at the stimulation site produces artifact signals that are orders of magnitude larger than the neural responses of interest. These signals often saturate the recording amplifier causing distortion or loss of short-latency evoked responses. This paper proposes a method to cancel the artifact in simultaneous neural recording and stimulation on the same electrode. By combining a novel hardware architecture with concurrent software processing, the design achieves neural signal recovery in a wide range of conditions. The proposed system uniquely demonstrates same-electrode stimulation and recording, with neural signal recovery in presence of stimulation artifact 100 dB larger in magnitude than the underlying signals. The system is tested both in vitro and in vivo, during concurrent stimulation and recording on the same electrode. In vivo results in a rodent model are compared to recordings made by a commercial neural amplifier system connected in parallel.
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Blumrosen G, Luttwak A. Human body parts tracking and kinematic features assessment based on RSSI and inertial sensor measurements. Sensors (Basel) 2013; 13:11289-313. [PMID: 23979481 PMCID: PMC3821292 DOI: 10.3390/s130911289] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/03/2013] [Revised: 08/05/2013] [Accepted: 08/10/2013] [Indexed: 11/28/2022]
Abstract
Acquisition of patient kinematics in different environments plays an important role in the detection of risk situations such as fall detection in elderly patients, in rehabilitation of patients with injuries, and in the design of treatment plans for patients with neurological diseases. Received Signal Strength Indicator (RSSI) measurements in a Body Area Network (BAN), capture the signal power on a radio link. The main aim of this paper is to demonstrate the potential of utilizing RSSI measurements in assessment of human kinematic features, and to give methods to determine these features. RSSI measurements can be used for tracking different body parts' displacements on scales of a few centimeters, for classifying motion and gait patterns instead of inertial sensors, and to serve as an additional reference to other sensors, in particular inertial sensors. Criteria and analytical methods for body part tracking, kinematic motion feature extraction, and a Kalman filter model for aggregation of RSSI and inertial sensor were derived. The methods were verified by a set of experiments performed in an indoor environment. In the future, the use of RSSI measurements can help in continuous assessment of various kinematic features of patients during their daily life activities and enhance medical diagnosis accuracy with lower costs.
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Affiliation(s)
- Gaddi Blumrosen
- School of Computer Science & Engineering, Hebrew University of Jerusalem, Jerusalem 91904, Israel.
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23
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Rosas-Cholula G, Ramirez-Cortes JM, Alarcon-Aquino V, Gomez-Gil P, Rangel-Magdaleno JDJ, Reyes-Garcia C. Gyroscope-driven mouse pointer with an EMOTIV® EEG headset and data analysis based on Empirical Mode Decomposition. Sensors (Basel) 2013; 13:10561-83. [PMID: 23948873 PMCID: PMC3812618 DOI: 10.3390/s130810561] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2013] [Revised: 08/02/2013] [Accepted: 08/06/2013] [Indexed: 11/17/2022]
Abstract
This paper presents a project on the development of a cursor control emulating the typical operations of a computer-mouse, using gyroscope and eye-blinking electromyographic signals which are obtained through a commercial 16-electrode wireless headset, recently released by Emotiv. The cursor position is controlled using information from a gyroscope included in the headset. The clicks are generated through the user's blinking with an adequate detection procedure based on the spectral-like technique called Empirical Mode Decomposition (EMD). EMD is proposed as a simple and quick computational tool, yet effective, aimed to artifact reduction from head movements as well as a method to detect blinking signals for mouse control. Kalman filter is used as state estimator for mouse position control and jitter removal. The detection rate obtained in average was 94.9%. Experimental setup and some obtained results are presented.
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Affiliation(s)
- Gerardo Rosas-Cholula
- Department of Electronics, National Institute of Astrophysics, Optics and Electronics, Luis Enrique Erro No. 1, Tonantzintla, Puebla 72760, Mexico; E-Mails: (G.R.-C.); (J.J.R.-M.)
| | - Juan Manuel Ramirez-Cortes
- Department of Electronics, National Institute of Astrophysics, Optics and Electronics, Luis Enrique Erro No. 1, Tonantzintla, Puebla 72760, Mexico; E-Mails: (G.R.-C.); (J.J.R.-M.)
- Author to whom correspondence should be addressed; E-Mail: ; Tel.: +52-222-266-3100; Fax: +52-222-247-2580
| | - Vicente Alarcon-Aquino
- Department of Electronics and Computer Science, Exhda. Sta. Catarina Martir, Cholula, University of the Americas, Puebla, Puebla 72720, Mexico; E-Mail:
| | - Pilar Gomez-Gil
- Department of Computer Science, National Institute of Astrophysics, Optics and Electronics, Luis Enrique Erro No. 1, Tonantzintla, Puebla 72760, Mexico; E-Mails: (P.G.-G.); (C.R.-G.)
| | - Jose de Jesus Rangel-Magdaleno
- Department of Electronics, National Institute of Astrophysics, Optics and Electronics, Luis Enrique Erro No. 1, Tonantzintla, Puebla 72760, Mexico; E-Mails: (G.R.-C.); (J.J.R.-M.)
| | - Carlos Reyes-Garcia
- Department of Computer Science, National Institute of Astrophysics, Optics and Electronics, Luis Enrique Erro No. 1, Tonantzintla, Puebla 72760, Mexico; E-Mails: (P.G.-G.); (C.R.-G.)
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Abstract
Influenza recurs seasonally in temperate regions of the world; however, our ability to predict the timing, duration, and magnitude of local seasonal outbreaks of influenza remains limited. Here we develop a framework for initializing real-time forecasts of seasonal influenza outbreaks, using a data assimilation technique commonly applied in numerical weather prediction. The availability of real-time, web-based estimates of local influenza infection rates makes this type of quantitative forecasting possible. Retrospective ensemble forecasts are generated on a weekly basis following assimilation of these web-based estimates for the 2003-2008 influenza seasons in New York City. The findings indicate that real-time skillful predictions of peak timing can be made more than 7 wk in advance of the actual peak. In addition, confidence in those predictions can be inferred from the spread of the forecast ensemble. This work represents an initial step in the development of a statistically rigorous system for real-time forecast of seasonal influenza.
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Affiliation(s)
- Jeffrey Shaman
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA.
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Cameron F, Wilson DM, Buckingham BA, Arzumanyan H, Clinton P, Chase HP, Lum J, Maahs DM, Calhoun PM, Bequette BW. Inpatient studies of a Kalman-filter-based predictive pump shutoff algorithm. J Diabetes Sci Technol 2012; 6:1142-7. [PMID: 23063041 PMCID: PMC3570849 DOI: 10.1177/193229681200600519] [Citation(s) in RCA: 50] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND An insulin pump shutoff system can prevent nocturnal hypoglycemia and is a first step on the pathway toward a closed-loop artificial pancreas. In previous pump shutoff studies using a voting algorithm and a 1 min continuous glucose monitor (CGM), 80% of induced hypoglycemic events were prevented. METHODS The pump shutoff algorithm used in previous studies was revised to a single Kalman filter to reduce complexity, incorporate CGMs with different sample times, handle sensor signal dropouts, and enforce safety constraints on the allowable pump shutoff time. RESULTS Retrospective testing of the new algorithm on previous clinical data sets indicated that, for the four cases where the previous algorithm failed (minimum reference glucose less than 60 mg/dl), the mean suspension start time was 30 min earlier than the previous algorithm. Inpatient studies of the new algorithm have been conducted on 16 subjects. The algorithm prevented hypoglycemia in 73% of subjects. Suspension-induced hyperglycemia is not assessed, because this study forced excessive basal insulin infusion rates. CONCLUSIONS The new algorithm functioned well and is flexible enough to handle variable sensor sample times and sensor dropouts. It also provides a framework for handling sensor signal attenuations, which can be challenging, particularly when they occur overnight.
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Affiliation(s)
- Fraser Cameron
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York, USA.
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Cheng R, Heinzelman W, Sturge-Apple M, Ignjatovic Z. A Motion-Tracking Ultrasonic Sensor Array for Behavioral Monitoring. IEEE Sens J 2011; PP:1. [PMID: 22081760 PMCID: PMC3211111 DOI: 10.1109/jsen.2011.2165942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
The application of Kalman filtering to track subjects' movements during a behavioral experiment is discussed. Specifically, an overhead array of wireless, ultrasound sensors automatically tracks the position of a parent, child, and stranger over a 4.45 m × 4.23 m observation area. This WiPsy (Wireless sensors for Psychology research) system provides accurate, real-time quantitative metrics for psychological evaluation in lieu of traditional qualitative manual coding. Moreover, tracking subjects using ultrasound sensors is less error-prone than existing methods that track based on human coding of video. In particular, the Kalman filter, which forms the core of this tracking system, can locate targets with a mean square error of about 1.3 m(2). Overall, WiPsy strives to streamline data acquisition, processing, and analysis by providing previously unavailable assessment parameters.
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Affiliation(s)
- Roland Cheng
- Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY 14627 USA
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27
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Hughes CS, Patek SD, Breton MD, Kovatchev BP. Hypoglycemia prevention via pump attenuation and red-yellow-green "traffic" lights using continuous glucose monitoring and insulin pump data. J Diabetes Sci Technol 2010; 4:1146-55. [PMID: 20920434 PMCID: PMC2956822 DOI: 10.1177/193229681000400513] [Citation(s) in RCA: 73] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND Hypoglycemia has been identified as a primary barrier to optimal management of diabetes. This observation, in conjunction with the introduction of continuous glucose monitoring (CGM) devices, has set the stage for achieving tight glycemic control with systems that adjust the insulin pump settings based on measured glucose concentrations. Because system safety and system reliability are key considerations, there is a need for algorithms that reduce the risk of hypoglycemia in closed-loop, open-loop, and advisory-mode systems. More specifically, the algorithm presented here is formulated as a component of the independent safety system module proposed in the modular control-to-range architecture. METHODS We developed two algorithms for attenuating insulin pump injections, which we refer to as Brakes and Power Brakes: Brakes is a pump attenuation function computed using CGM information only, while Power Brakes is an attenuation function in which a metabolic state observer with insulin input is used in addition to CGM information to inform the level of pump attenuation. These algorithms modulate the insulin pump delivery so that the insulin injection rate is dramatically reduced when the risk of hypoglycemia is high. Additionally, we combined these algorithms with an alert system that indicates a level of hypoglycemic risk to the user. RESULTS We demonstrated the effectiveness of Brakes and Power Brakes in reducing the incidence of hypoglycemia in two simulated scenarios: an elevated basal rate scenario and a scenario in which a bolus is delivered for a meal that is skipped. For these scenarios, the incidence of hypoglycemia using Power Brakes was reduced by 88 and 94%, respectively, where we defined hypoglycemia based on the American Diabetes Association guidelines for defining and reporting as 70 mg/dl. In the elevated basal rate scenario, no rebounds above 180 mg/dl (the desired upper limit of the control-to-range protocol) following hypoglycemia were shown to occur. We demonstrated the way the hypoglycemia alert system can trigger the intake of carbohydrates to reduce the incidence of hypoglycemia by 98%. CONCLUSIONS This article offers, for the first time, a method for smoothly reducing insulin delivery rate to prevent hypoglycemia in individuals with type 1 diabetes mellitus based on a mathematically formal assessment of hypoglycemic risk. In silico, we demonstrate the way this method can prevent hypoglycemia while avoiding hyperglycemia rebounds that exceed 180 mg/dl. In conjunction with the pump attenuation algorithms, this article also proposes a system for alerting an individual of their hypoglycemic risk that contains three "levels" of alerts in the form of a traffic light. This alert system can be used in an advisory mode setting to alert the user to take action when hypoglycemia is imminent ("red" light) or in a closed-loop setting where initiation of rescue action begins when the red light alert is triggered.
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Affiliation(s)
- Colleen S Hughes
- Department of Systems and Information Engineering, University of Virginia, Charlottesville, Virginia 22904, USA.
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Abstract
Modern model-based control theory has led to transformative improvements in our ability to track the nonlinear dynamics of systems that we observe, and to engineer control systems of unprecedented efficacy. In parallel with these developments, our ability to build computational models to embody our expanding knowledge of the biophysics of neurons and their networks is maturing at a rapid rate. In the treatment of human dynamical disease, our employment of deep brain stimulators for the treatment of Parkinson's disease is gaining increasing acceptance. Thus, the confluence of these three developments--control theory, computational neuroscience and deep brain stimulation--offers a unique opportunity to create novel approaches to the treatment of this disease. This paper explores the relevant state of the art of science, medicine and engineering, and proposes a strategy for model-based control of Parkinson's disease. We present a set of preliminary calculations employing basal ganglia computational models, structured within an unscented Kalman filter for tracking observations and prescribing control. Based upon these findings, we will offer suggestions for future research and development.
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Affiliation(s)
- Steven J Schiff
- Center for Neural Engineering, Department of Neurosurgery, Pennsylvania State University, University Park, PA 16802, USA.
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Daunizeau J, Friston K, Kiebel S. Variational Bayesian identification and prediction of stochastic nonlinear dynamic causal models. Physica D 2009; 238:2089-2118. [PMID: 19862351 PMCID: PMC2767160 DOI: 10.1016/j.physd.2009.08.002] [Citation(s) in RCA: 116] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2008] [Revised: 07/29/2009] [Accepted: 08/01/2009] [Indexed: 05/28/2023]
Abstract
In this paper, we describe a general variational Bayesian approach for approximate inference on nonlinear stochastic dynamic models. This scheme extends established approximate inference on hidden-states to cover: (i) nonlinear evolution and observation functions, (ii) unknown parameters and (precision) hyperparameters and (iii) model comparison and prediction under uncertainty. Model identification or inversion entails the estimation of the marginal likelihood or evidence of a model. This difficult integration problem can be finessed by optimising a free-energy bound on the evidence using results from variational calculus. This yields a deterministic update scheme that optimises an approximation to the posterior density on the unknown model variables. We derive such a variational Bayesian scheme in the context of nonlinear stochastic dynamic hierarchical models, for both model identification and time-series prediction. The computational complexity of the scheme is comparable to that of an extended Kalman filter, which is critical when inverting high dimensional models or long time-series. Using Monte-Carlo simulations, we assess the estimation efficiency of this variational Bayesian approach using three stochastic variants of chaotic dynamic systems. We also demonstrate the model comparison capabilities of the method, its self-consistency and its predictive power.
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Affiliation(s)
- J. Daunizeau
- Corresponding address: Wellcome Trust for Neuroimaging, Institute of Neurology, UCL, 12 Queen Square, London, WC1N 3BG, United Kingdom. Tel.: +44 207 833 7488; fax: +44 207 813 1445.
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Prerau MJ, Smith AC, Eden UT, Yanike M, Suzuki WA, Brown EN. A mixed filter algorithm for cognitive state estimation from simultaneously recorded continuous and binary measures of performance. Biol Cybern 2008; 99:1-14. [PMID: 18438683 PMCID: PMC2707852 DOI: 10.1007/s00422-008-0227-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2006] [Accepted: 12/10/2007] [Indexed: 05/26/2023]
Abstract
Continuous (reaction times) and binary (correct/ incorrect responses) measures of performance are routinely recorded to track the dynamics of a subject's cognitive state during a learning experiment. Current analyses of experimental data from learning studies do not consider the two performance measures together and do not use the concept of the cognitive state formally to design statistical methods. We develop a mixed filter algorithm to estimate the cognitive state modeled as a linear stochastic dynamical system from simultaneously recorded continuous and binary measures of performance. The mixed filter algorithm has the Kalman filter and the more recently developed recursive filtering algorithm for binary processes as special cases. In the analysis of a simulated learning experiment the mixed filter algorithm provided a more accurate and precise estimate of the cognitive state process than either the Kalman or binary filter alone. In the analysis of an actual learning experiment in which a monkey's performance was tracked by its series of reaction times, and correct and incorrect responses, the mixed filter gave a more complete description of the learning process than either the Kalman or binary filter. These results establish the feasibility of estimating cognitive state from simultaneously recorded continuous and binary performance measures and suggest a way to make practical use of concepts from learning theory in the design of statistical methods for the analysis of data from learning experiments.
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Affiliation(s)
- M. J. Prerau
- Program in Neuroscience at Boston University, Boston, MA 02215, USA, e-mail: , URL: http://people.bu.edu/prerau/
| | - A. C. Smith
- Department of Anesthesiology and Pain Medicine, University of California at Davis, Davis, CA 95616, USA e-mail:
| | - U. T. Eden
- Program in Neuroscience at Boston University, Boston, MA 02215, USA, e-mail: , URL: http://people.bu.edu/prerau/
| | - M. Yanike
- Center for Neural Science, New York University, New York, NY 10003, USA, e-mail:
| | - W. A. Suzuki
- Center for Neural Science, New York University, New York, NY 10003, USA, e-mail:
| | - E. N. Brown
- Neuroscience Statistics Research Laboratory, Department of Anesthesia and Critical Care, Massachusetts General Hospital, Boston, MA 02114, USA
- Department of Brain and Cognitive Sciences and the Massachusetts Institute of Technology/Harvard Division of Health, Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA, e-mail:
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Hu X, Nenov V, Bergsneider M, Glenn TC, Vespa P, Martin N. Estimation of hidden state variables of the intracranial system using constrained nonlinear Kalman filters. Conf Proc IEEE Eng Med Biol Soc 2007; 2005:5631-4. [PMID: 17281533 PMCID: PMC2148030 DOI: 10.1109/iembs.2005.1615763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
Impeded by the rigid skull, direct assessment of physiological variables of the intracranial system is difficult. A hidden state estimation approach is designed in the present work to facilitate the estimation of unobserved variables from available clinical measurements including intracranial pressure (ICP) and cerebral blood flow velocity (CBFV). The estimation algorithm is based on a modified nonlinear intracranial mathematical model, whose parameters are first identified in an offline stage using a nonlinear optimization paradigm. Following the offline stage, an online filtering process is performed using a nonlinear Kalman filter-like state estimator that is equipped with a new way of deriving the Kalman gain using the physiological constraints on the state variables. It is shown in the present work that changes of nominal radii of the proximal and distal cerebral arterial vascular beds could be tracked by using the proposed hidden state estimator.
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Affiliation(s)
- Xiao Hu
- X. Hu is with the Brain Monitoring and Modeling Laboratory, Division of Neurosurgery, University of California, Los Angeles, CA 90034 USA (e-mail: )
| | - Valeriy Nenov
- V. Nenov is with the Brain Monitoring and Modeling Laboratory, Division of Neurosurgery, University of California, Los Angeles, CA 90034 USA
| | - Marvin Bergsneider
- M. Bergnseider is with the Adult Hydrocephalous Program, Division of Neurosurgery, University of California, Los Angeles, CA 90034 USA
| | - Thomas C. Glenn
- T. C. Glenn and N. Martin are with the Cerebral Blood Flow Laboratory, Division of Neurosurgery, University of California, Los Angeles, CA 90034 USA
| | - Paul Vespa
- P. Vespa is with the Neurological Intensive Care Unit, Division of Neurosurgery, University of California, Los Angeles, CA 90034 USA
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Abstract
A dynamic complex impedance imaging technique is developed with the aid of the linearized Kalman filter (LKF) for real-time reconstruction of the human chest. The forward problem is solved by an analytical method based on the separation of variables and Fourier series. The inverse problem is treated as a state estimation problem. The nonlinear measurement equation is linearized about the best homogeneous impedivity value as an initial guess, and the impedivity distribution is estimated with the aid of the Kalman estimator. The Kalman gain matrix is pre-computed and stored off-line to minimize the on-line computational time. Simulation and phantom experiment are reported to illustrate the reconstruction performances in the sense of spatio-temporal resolution in a simplified geometry of the human chest.
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Affiliation(s)
- Bong Seok Kim
- Department of Electrical and Electronic Engineering, Cheju National University, Cheju 690-756, Korea.
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Büchel C, Friston KJ. Dynamic changes in effective connectivity characterized by variable parameter regression and Kalman filtering. Hum Brain Mapp 1998; 6:403-8. [PMID: 9788081 PMCID: PMC6873378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2023] Open
Abstract
Attention to visual motion can increase the responsiveness of the motion-selective cortical area V5 and the posterior parietal cortex. We addressed attentional modulation of effective connectivity using variable parameter regression and functional magnetic resonance imaging. We present data from a single subject scanned under identical stimulus conditions (visual motion) while varying only the attentional component of the task. Variable parameter regression of the influence of V5 on PP revealed increased effective connectivity during attention to visual motion. With this dynamic measure of effective connectivity we were able to make inferences about the source of modulation by looking for regions that predicted the observed changes in connectivity. Using an ordinary regression analysis, we showed that activity in the prefrontal cortex could explain these changes and was sufficient to account for these modulatory influences on connections in the dorsal visual pathway.
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Affiliation(s)
- C Büchel
- Leopold Müller Functional Imaging Laboratory, Wellcome Department of Cognitive Neurology, London, UK.
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