Liu Yang

All Publications

• Sequential Detection of Anomalies in Noisy Outputs of an Unknown Function Using Gaussian and Yule-Simon Processes ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Yang, L., Butler, K., Djurić, P. M. 2024: 7205-7209

  View details for DOI 10.1109/ICASSP48485.2024.10446227

• A quantitative model of the cerebral windkessel and its relevance to disorders of intracranial dynamics Journal of Neurosurgery: Pediatrics Egnor, M., Yang, L., Mani, R. M., Fiore, S. M., Djurić, P. M. 2023; 32 (3): 302–311
• Why don't ventricles dilate in pseudotumor cerebri? A circuit model of the cerebral windkessel. Journal of neurosurgery. Pediatrics Wang, Z., Yang, L., Djurić, P. M., Egnor, M. R. 2022; 29 (6): 719-726

  Abstract

  Pseudotumor cerebri is a disorder of intracranial dynamics characterized by elevated intracranial pressure (ICP) and chronic cerebral venous hypertension without structural abnormalities. A perplexing feature of pseudotumor is the absence of the ventriculomegaly found in obstructive hydrocephalus, although both diseases are associated with increased resistance to cerebrospinal fluid (CSF) resorption. Traditionally, the pathophysiology of ventricular dilation and obstructive hydrocephalus has been attributed to the backup of CSF due to impaired absorption, and it is unclear why backup of CSF with resulting ventriculomegaly would not occur in pseudotumor. In this study, the authors used an electrical circuit model to simulate the cerebral windkessel effect and explain the presence of ventriculomegaly in obstructive hydrocephalus but not in pseudotumor cerebri.The cerebral windkessel is a band-stop filter that dampens the arterial blood pressure pulse in the cranium. The authors used a tank circuit with parallel inductance and capacitance to model the windkessel. The authors distinguished the smooth flow of blood and CSF and the pulsatile flow of blood and CSF by using direct current (DC) and alternating current (AC) sources, respectively. The authors measured the dampening notch from ABP to ICP as the band-stop filter of the windkessel.In obstructive hydrocephalus, loss of CSF pathway volume impaired the flow of AC power in the cranium and caused windkessel impairment, to which ventriculomegaly is an adaptation. In pseudotumor, venous hypertension affected DC power flow in the capillaries but did not affect AC power or the windkessel, therefore obviating the need for adaptive ventriculomegaly.In pseudotumor, the CSF spaces are unaffected and the windkessel remains effective. Therefore, ventricles remain normal in size. In hydrocephalus, the windkessel, which depends on the flow of AC power in patent CSF spaces, is impaired, and the ventricles dilate as an adaptive process to restore CSF pathway volume. The windkessel model explains both ventriculomegaly in obstructive hydrocephalus and the lack of ventriculomegaly in pseudotumor. This model provides a novel understanding of the pathophysiology of disorders of CSF dynamics and has significant implications in clinical management.

  View details for DOI 10.3171/2022.1.PEDS21527

  View details for PubMedID 35303694

• UNSUPERVISED CLUSTERING AND ANALYSIS OF CONTRACTION-DEPENDENT FETAL HEART RATE SEGMENTS. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) Yang, L., Heiselman, C., Quirk, J. G., Djurić, P. M. 2022; 2022

  Abstract

  The computer-aided interpretation of fetal heart rate (FHR) and uterine contraction (UC) has not been developed well enough for wide use in delivery rooms. The main challenges still lie in the lack of unclear and nonstandard labels for cardiotocography (CTG) recordings, and the timely prediction of fetal state during monitoring. Rather than traditional supervised approaches to FHR classification, this paper demonstrates a way to understand the UC-dependent FHR responses in an unsupervised manner. In this work, we provide a complete method for FHR-UC segment clustering and analysis via the Gaussian process latent variable model, and density-based spatial clustering. We map the UC-dependent FHR segments into a space with a visual dimension and propose a trajectory-based FHR interpretation method. Three metrics of FHR trajectory are defined and an open-access CTG database is used for testing the proposed method.

  View details for DOI 10.1109/icassp43922.2022.9747598

  View details for PubMedID 36035504

  View details for PubMedCentralID PMC9415917

• Unsupervised Detection of Anomalies in Fetal Heart Rate Tracings using Phase Space Reconstruction. Proceedings of the ... European Signal Processing Conference (EUSIPCO). EUSIPCO (Conference) Yang, L., Ajirak, M., Heiselman, C., Quirk, J. G., Djurić, P. M. 2021; 2021: 1321-1325

  Abstract

  Detection of anomalies in time series is still a challenging problem. In this paper, we provide a new approach to unsupervised detection of anomalies in time series based on the concept of phase space reconstruction and manifolds. We propose a rotation-insensitive metric for quantifying the similarity of manifolds and a method that uses it for estimating the probability of an outlier. The proposed method does not rely on any features and can be used for signals with variable lengths. We tested it on both synthetic signals and real fetal heart rate tracings. The method has promising performance and can be used for interpreting the severity of fetal asphyxia.

  View details for DOI 10.23919/eusipco54536.2021.9616264

  View details for PubMedID 35233348

  View details for PubMedCentralID PMC8884191

• IDENTIFICATION OF UTERINE CONTRACTIONS BY AN ENSEMBLE OF GAUSSIAN PROCESSES. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) Yang, L., Heiselman, C., Quirk, J. G., Djurić, P. M. 2021; 2021

  Abstract

  Identifying uterine contractions with the aid of machine learning methods is necessary vis-á-vis their use in combination with fetal heart rates and other clinical data for the assessment of a fetus wellbeing. In this paper, we study contraction identification by processing noisy signals due to uterine activities. We propose a complete four-step method where we address the imbalanced classification problem with an ensemble Gaussian process classifier, where the Gaussian process latent variable model is used as a decision-maker. The results of both simulation and real data show promising performance compared to existing methods.

  View details for DOI 10.1109/icassp39728.2021.9414041

  View details for PubMedID 34712103

  View details for PubMedCentralID PMC8547336

• CLASS-IMBALANCED CLASSIFIERS USING ENSEMBLES OF GAUSSIAN PROCESSES AND GAUSSIAN PROCESS LATENT VARIABLE MODELS. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) Yang, L., Heiselman, C., Quirk, J. G., Djurić, P. M. 2021; 2021

  Abstract

  Classification with imbalanced data is a common and challenging problem in many practical machine learning problems. Ensemble learning is a popular solution where the results from multiple base classifiers are synthesized to reduce the effect of a possibly skewed distribution of the training set. In this paper, binary classifiers based on Gaussian processes are chosen as bases for inferring the predictive distributions of test latent variables. We apply a Gaussian process latent variable model where the outputs of the Gaussian processes are used for making the final decision. The tests of the new method in both synthetic and real data sets show improved performance over standard approaches.

  View details for DOI 10.1109/icassp39728.2021.9414754

  View details for PubMedID 34712104

  View details for PubMedCentralID PMC8547341

• Particle Filtering Under General Regime Switching El-Laham, Y., Yang, L., Djuric, P. M., Bugallo, M. F., IEEE IEEE. 2021: 2378-2382

  View details for Web of Science ID 000632622300479

• PARTICLE GIBBS SAMPLING FOR REGIME-SWITCHING STATE-SPACE MODELS El-Laham, Y., Yang, L., Lynch, H. J., Djuric, P. M., Bugallo, M. F., IEEE IEEE. 2021: 5579-5583

  View details for DOI 10.1109/ICASSP39728.2021.9414875

  View details for Web of Science ID 000704288405169

• INDOOR ALTITUDE ESTIMATION OF UNMANNED AERIAL VEHICLES USING A BANK OF KALMAN FILTERS Yang, L., Wang, H., El-Laham, Y., Lamas Fonte, J., Perez, D., Bugallo, M. F., IEEE IEEE. 2020: 5455-5459

  View details for DOI 10.1109/icassp40776.2020.9054203

  View details for Web of Science ID 000615970405143

• MOVING TARGET LOCALIZATION IN MULTISTATIC SONAR USING TIME DELAYS, DOPPLER SHIFTS AND ARRIVAL ANGLES Yang, L., Yang, L., Ho, K. C., IEEE IEEE. 2017: 3399-3403

  View details for Web of Science ID 000414286203113

• TDOA-FDOA source geolocation using moving horizon estimation with satellite location errors 2017 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (PACRIM) Shan, C., Yang, L., Yang, L., Li, X., Li, W. 2017

  View details for DOI 10.1109/PACRIM.2017.8121932

• Moving Target Localization in Multistatic Sonar by Differential Delays and Doppler Shifts IEEE SIGNAL PROCESSING LETTERS Yang, L., Yang, L., Ho, K. C. 2016; 23 (9): 1160-1164

  View details for DOI 10.1109/LSP.2016.2582043

  View details for Web of Science ID 000381454400002