UCLA Campus    |   UCLA Health    |   School of Medicine Translate:
UCLA Health It Begins With U

UCLA Neurosurgery

Subscribe
Print
Email
Share

UCLA Neurosurgery Neural Systems and Dynamics Laboratory (NSDL)

NSDL was established in 2006 at UCLA. Dr Xiao Hu is moving to UCSF School of Nursing to start a new phase of his career at the end 08/2013. He will continue to collaborate with the clinical investigators of the NSDL who remain at UCLA to develop, assess, and deploy translational biomedical informatics algorithms and software systems to support the realization of precision medicine.

 

Members

 
  Principal Investigators Xiao Hu, Ph.D.
  Marvin Bergsneider, M.D.
  Paul Vespa, M.D.
   
  Full Time Members Mark Connolly, BS, Research Associate
 
  Post Graduate Research Fellows  
  Graduate Students Robert Hamilton (BME)
  Mahsa Malekmohammadi (BME)
  Yong Bai (BME)
   
 Undergraduate Students
   
 Lab Alumni Peng Xu, Ph.D.
  Kyle Tsai
  Magdalena Kasprowicz, Ph.D.
  Mingxi Zhao, M.S.
  Shaozhi Wu, M.S.
  Jessica Lu (BME), with Amgen
  Sunghan Kim Ph.D.   Assistant professor, East Carolina University
  Shadnaz Asgari, Ph.D. Assistant professor, Cal State University, Long Beach
  Peter Honching Li,M.SSenior Software Engineer, LoopNet.com
  Fabien Scalzo, Ph.D.Assistant professor, UCLA Neurology

 

Active Extramural Grants

  1. "ICP Elevation Alerting Based on a Predictive Model Hosting Platform"; NINDS; 2012-2016; PI: Xiao Hu

Publications

2013

  1. S.Asgari, P.Vespa, X.Hu. Is There any Association Between Cerebral Vasoconstriction/Vasodilatation and Microdialysis Lactate to Pyruvate Ratio Increase? Neurocritical Care (in Press)
  2. C.Tsiokos, X.Hu, N.Pouratian. 200-300 Hz Movement Modulated Oscillations in the Internal Globus Pallidus of Patients with Parkinson's Disease. Neurobiology of Disease (in Press)
  3. F. Scalzo, X. Hu. Semi-Supervised Detection of Intracranial Pressure Alarms using Waveform Dynamics. Physiological Measurement (in Press)
  4. F. Scalzo, J. Alger, X. Hu, K. Danic, K. Muirc, A. Demchuk, S. Coutts, M. Luby, S. Warach, D. Liebeskind. Multi-Center Prediction of Hemorrhagic Transformation in Acute Ischemic Stroke using Permeability Imaging Features. Magnetic Resonance Imaging(in Press)
  5. X.Hu, D.Do, Y.Bai, N.Boyle. A Case-Cotrol Sstudy of Non-Monitored ECG Metrics Preceding In-Hospital Bradyasystolic Cardiac Arrest: Implication for Predictive Monitor Alarms. Journal of Electrocardiology (In Press).
  6. S. Kim, F. Scalzo, D. Telesca, X. Hu. Ensemble of Sparse Classifiers for High-Dimensional Biological Data. Internatinal Journal of Data Mining and Bioinformatics.(In Press)
  7. P.Xu, X.Hu, DZ.Yao. Improved wavelet entropy calculation with window functions and its preliminary application to study intracranial pressure. Computers in Biology and Medicine. Vol 43, Issue 5, 2013, P425–433

2012

  1. X. Hu, M.Sapo, V.Nenov, T. Barry, S.Kim, D. Do, N.Boyle, N. Marin. Predictive Combinations of Monitor Alarms Preceding In-Hospital Code Blue Events. Journal of Biomedical Informatics (in Press)
  2. F. Scalzo, M. Bergsneider, P. Vespa, N. Martin, and X. Hu. Intracranial Pressure Signal Morphology: real-time tracking. IEEE pulse. 3(2):49-52. 2012.
  3. F. Scalzo, Q. Hao, X. Hu, D. Liebeskind. Regional Prediction of Tissue Fate in Acute Ischemic Stroke. Annals of Biomedical Engineering (in press). 
  4. F. Scalzo, D. Liebeskind, and X. Hu. Reducing False Intracranial Pressure Alarms using Morphological Waveform Features.  IEEE Trans Biomed Eng. (in press), 2012.
  5. R. Hamilton, K. Baldwin, J.Fuller, P. Vespa, X. Hu, and M.Bergsneider. Intracranial Pressure Pulse Waveform Correlate with Aqueductal Cerebraospinal Fluid Stroke Volume. Journal of Applied Physiology (in press), 2012.
  6. J. Lu, W.Spier, X.Hu, and N.Pouratian.  The Effects of Stimulus Timing Features on P300 Speller Performance. Clinical Neurophysiology (in press), 2012
  7. N. Gonzalez, R.Hamilton, A. Freiert, J. Dusick, P.Vespa, X.Hu, S. Asgarid. Cerebral Hemodynamic and Metabolic Effects of Remote Ischemic Preconditioning in Patients with Subarachnoid Hemorrhage. Acta Neurochirurgica Supplementum, Vol 115 (2012)
  8. X. Hu, N. Gonzalez, M.Bergsneider. Steady-State Indicator of Intracranial Pressure Dynamic System using Geodesic Distance of ICP Pulse Waveform. Physiological Measurement. (Accepted 10/2012)
  9. Kim S, Hamilton R, Pineles S, Bergsneider M, Vespa P, Martin N, Hu X. Noninvasive Intracranial Hypertension Detection Utilizing Semi-Supervised Learning IEEE Transactions on Biomedical Engineering. (Accepted 10/2012)
  10. Asgari S, Gonzalez N, Subduhi A, Hamilton R, Bergsneider M, Vespa P, Hu X. Continuous Detection of Cerebral Vasodilatation and Vasoconstriction Using Intracranial Pulse Morphological Template Matching. PLoS One (Accepted 10/2012)

2011

  1. S. Kim, M. Bergsneider, and X. Hu, "A systematic study of linear dynamic modeling of intracranial pressure dynamics," Physiol Meas, vol. 32, pp. 319-336, Feb 1, 2011.
  2. S. Asgari, A. Subudhi,R. Roach,D. Liebeskind, M. Bergsneider,X. Hu. An Extended Model of Intracranial Latency Facilitates Non-Invasive Detection of Cerebrovascular Changes. Journal of Neuroscience Methods, 197(1):171-9, Feb 15, 2011.
  3. S. Asgari, P. Vespa, M. Bergsneider,X.  Hu.  Lack of Consistent Intracranial Pressure Pulse Morphological Changes during  Episodes of Microdialysis Lactate/Pyruvate Ratio Increase. Physiol Meas, vol. 32(10), pp.1639-1651, Sep 9, 2011.
  4. F. Scalzo, S. Asgari,S. Kim, M. Bergsneider, X. Hu. Bayesian tracking of intracranial pressure signal morphology. Artificial Intelligence in Medicine. in press, 2011.
  5. F. Scalzo,R. Hamilton,S. Asgari, S. Kim,X. Hu. Intracranial Hypertension Prediction using Extremely Randomized Decision Trees. Medical Engineering and Physics. in press, 2011.
  6. S. Asgari, P. Vespa, M. Bergsneider, X. Hu.  Latency Relationship Between Cerebral Blood Flow Velocity and Intracarnial Pressure. Acta Neurochir Suppl, vol. 114,  In press, 2011.
  7. M. Kasprowicz, M. Bergsneider,M. Czosnyka,X. Hu. Association between ICP Pulse Waveform Morphology and ICP B Waves.Acta Neurochir Suppl, vol. 114,  In press, 2011.
  8. X. Hu, R. Hamilton, K. Baldwin, P. Vespa, M. Bergsneider. Automated Extraction of Decision Rules for Predicting Lumbar Drain Outcome by Analyzing Overnight Intracranial Pressure. Acta Neurochir Suppl, vol. 114,  In press, 2011.

2010

  1. S. Asgari, M. Bergsneider, and X. Hu, "A robust approach toward recognizing valid arterial-blood-pressure pulses," IEEE Trans Inf Technol Biomed, vol. 14, pp. 166-72, Jan 2010.
  2. X. Hu, P. Xu, S. Asgari, P. Vespa, and M. Bergsneider, "Forecasting ICP elevation based on prescient changes of intracranial pressure waveform morphology," IEEE Trans Biomed Eng, vol. 57, pp. 1070-8, May 2010.
  3. X. Hu, P. Xu, S. Wu, S. Asgari, and M. Bergsneider, "A data mining framework for time series estimation," Journal of Biomedical Informatics, vol. 43, pp. 190-9, Apr 2010.
  4. X. Hu, T. Glenn, F. Scalzo, M. Bergsneider, C. Sarkiss, N. Martin, and P. Vespa, "Intracranial pressure pulse morphological features improved detection of decreased cerebral blood flow," Physiol Meas, vol. 31, pp. 679-95, May 2010.
  5. M. Kasprowicz, S. Asgari, M. Bergsneider, M. Czosnyka, R. Hamilton, and X. Hu, "Pattern recognition of overnight intracranial pressure slow waves using morphological features of intracranial pressure pulse," J Neurosci Methods, vol. 190, pp. 310-8, Jul 15.
  6. S. Asgari, M. Bergsneider, R. Hamilton, P. Vespa, and X. Hu, "Consistent Changes in Intracranial Pressure Waveform Morphology Induced by Acute Hypercapnic Cerebral Vasodilatation," Neurocrit Care, Oct 29.
  7. F. Scalzo, S. Asgari, S. Kim, M. Bergsneider, and X. Hu, Robust peak recognition in intracranial pressure signals, Biomed Eng Online, vol. 9, p. 61.
  8. S. Kim, X. Hu, D. McArthur, R. Hamilton, M. Bergsneider, T. Glenn, N. Martin, and P. Vespa, "Inter-Subject Correlation Exists Between Morphological Metrics of Cerebral Blood Flow Velocity and Intracranial Pressure Pulses," Neurocrit Care, Dec 7 2010.
  9. S. Kim, F. Scalzo, M. Bergsneider, P. Vespa, N. Martin, and X. Hu, "Noninvasive Intracranial Pressure Assessment based on Data Mining Approach using Nonlinear Mapping Function," IEEE Trans Biomed Eng, Nov 22, 2010.
  10. F. Scalzo, Q. Hao, J. Alger, X. Hu, D. Liebeskind. Tissue Fate Prediction in Acute Ischemic Stroke using Cuboid Models. Lecture Notes in Computer Science, vol.  6454, pp. 292-301, Springer, 2010.
  11. F. Scalzo, Q. Hao, A. Walczak, X. Hu, Y. Hoi, K. Hoffmann, D. Liebeskind. Computational Hemodynamics in Intracranial Vessels Reconstructed from Biplane AngiogramsLecture Notes in Computer Science, vol. 6455, pp. 359-367, Springer, 2010.

2009

  1. P. Xu, M. Bergsneider, and X. Hu, "Pulse onset detection using neighbor pulse-based signal enhancement," Med Eng Phys, vol. 31, pp. 337-45, Apr 2009.
  2. X. Hu, A. W. Subudhi, P. Xu, S. Asgari, R. C. Roach, and M. Bergsneider, "Inferring cerebrovascular changes from latencies of systemic and intracranial pulses: a model-based latency subtraction algorithm," J Cereb Blood Flow Metab, vol. 29, pp. 688-97, Apr 2009.
  3. X. Hu, P. Xu, F. Scalzo, P. Vespa, and M. Bergsneider, "Morphological clustering and analysis of continuous intracranial pressure," IEEE Trans Biomed Eng, vol. 56, pp. 696-705, Mar 2009.
  4. F. Scalzo, P. Xu, S. Asgari, M. Bergsneider, and X. Hu, "Regression analysis for peak designation in pulsatile pressure signals," Med Biol Eng Comput, vol. 47, pp. 967-77, Sep 2009. 
  5. P. Xu, M. Kasprowicz, M. Bergsneider, and X. Hu, "Improved noninvasive intracranial pressure assessment with nonlinear kernel regression," IEEE Trans Inf Technol Biomed, vol. 14, pp. 971-8, Jul 2009.
  6. M. Sapo, S. Wu, S. Asgari, N. McNair, F. Buxey, N. Martin, and X. Hu, "A comparison of vital signs charted by nurses with automated acquired values using waveform quality indices," J Clin Monit Comput, vol. 23, pp. 263-71, Oct 2009.
  7. S. Asgari, P. Xu, M. Bergsneider, and X. Hu, "A subspace decomposition approach toward recognizing valid pulsatile signals," Physiol Meas, vol. 30, pp. 1211-25, Nov 2009.

2008

  1. X. Hu, C. Miller, P. Vespa, and M. Bergsneider, "Adaptive computation of approximate entropy and its application in integrative analysis of irregularity of heart rate variability and intracranial pressure signals," Med Eng Phys, vol. 30, pp. 631-9, Jun 2008.
  2. X. Hu, P. Xu, D. J. Lee, P. Vespa, K. Baldwin, and M. Bergsneider, "An algorithm for extracting intracranial pressure latency relative to electrocardiogram R wave," Physiol Meas, vol. 29, pp. 459-71, Apr 2008.
  3. X. Hu, P. Xu, D. J. Lee, V. Paul, and M. Bergsneider, "Morphological changes of intracranial pressure pulses are correlated with acute dilatation of ventricles," Acta Neurochir Suppl, vol. 102, pp. 131-6, 2008.
  4. F. S. Cattivelli, A. H. Sayed, X. Hu, D. Lee, and P. Vespa, "Mathematical models of cerebral hemodynamics for detection of vasospasm in major cerebral arteries," Acta Neurochir Suppl, vol. 102, pp. 63-9, 2008.
  5. M. Bergsneider, C. Miller, P. M. Vespa, and X. Hu, "Surgical management of adult hydrocephalus," Neurosurgery, vol. 62 Suppl 2, pp. 643-59; discussion 659-60, Feb 2008.

2007

  1. X. Hu, V. Nenov, M. Bergsneider, T. C. Glenn, P. Vespa, and N. Martin, "Estimation of hidden state variables of the Intracranial system using constrained nonlinear Kalman filters," IEEE Trans Biomed Eng, vol. 54, pp. 597-610, Apr 2007.
  2. X. Hu, V. Nenov, P. Vespa, and M. Bergsneider, "Characterization of interdependency between intracranial pressure and heart variability signals: a causal spectral measure and a generalized synchronization measure," IEEE Trans Biomed Eng, vol. 54, pp. 1407-17, Aug 2007.
  3. P. M. Vespa, C. Miller, X. Hu, V. Nenov, F. Buxey, and N. A. Martin, "Intensive care unit robotic telepresence facilitates rapid physician response to unstable patients and decreased cost in neurointensive care," Surg Neurol, vol. 67, pp. 331-7, Apr 2007.

2006

  1. X. Hu and V. Nenov, "A single-lead ECG enhancement algorithm using a regularized data-driven filter," IEEE Trans Biomed Eng, vol. 53, pp. 347-51, Feb 2006.
  2. X. Hu, V. Nenov, T. Glenn, M. Bergsneider, and N. Martin, "A Framework of Noninvasive Intracranial Pressure Assessment via Data Mining of Cerebral Hemodynamic Signals," Biomedical Signal Processing & Control, vol. 1, pp. 64-77, 2006.
  3. X. Hu, V. Nenov, T. C. Glenn, L. A. Steiner, M. Czosnyka, M. Bergsneider, and N. Martin, "Nonlinear analysis of cerebral hemodynamic and intracranial pressure signals for characterization of autoregulation," IEEE Trans Biomed Eng, vol. 53, pp. 195-209, Feb 2006.
  4. X. Hu, A. A. Alwan, E. H. Rubinstein, and M. Bergsneider, "Reduction of compartment compliance increases venous flow pulsatility and lowers apparent vascular compliance: implications for cerebral blood flow hemodynamics," Med Eng Phys, vol. 28, pp. 304-14, May 2006.

Book Chapters

  • F. S. Cattivelli, S. Asgari, P. Vespa, A. H. Sayed, M. Bergsneider, and X. Hu, "Use of Constrained Nonlinear Kalman Filtering to Detect Pathological Constriction of Cerebral Arterial Blood Vessels," in Application of Kalman Filter: I-Tech Education and Publishing, 2009, pp. 143-162.
  • F. Scalzo, R. Hamilton, and X. Hu. Real-time analysis of intracranial pressure waveform morphology, in Neurological Disorders:I-Tech Education and Publishing, 2011, ISBN978-953-307-799-4
  • F. Scalzo, X. Hu, and D. Liebeskind. Tissue Fate Prediction from Regional Imaging Features in Acute Ischemic Stroke.  in Neuroimaging - Methods, ISBN 978-953-51-0097-3, 2012.

Pending and Granted Patents

  1. “Clinical information system”, with Nenov V et al.f
  2. “Multi Automated Severity Scoring”, with Martin N et al.
  3. “Data mining based Noninvasive Intracranial Pressure Assessment”, with Nenov V et al.
  4. Morphological Clustering and Analysis of Intracranial Pressure”, with Bergsneider M

 

25 Keywords Describing our Research:

Biomedical Informatics, Clinical Translational Science, Critical Care, Brain Injury, Stroke, Hydrocephalus, Ischemia, Subarachnoid Hemorrhage, Cerebral Ischemia, Seizure, Intracranial Pressure, EEG, ECG, Metabolomics, Proteomics, CT Perfusion Imaging, MR Perfusion Imaging, Clinical Forecasting, Multimodality Monitoring, Noninvasive, Data Mining, System Identification, Mathematical Model, HRV, Pulse Wave

Related Links

UCLA Hydrocephalus Program
UCLA Neurocritical Care Program
UCLA BIRC
UCLA EE Adaptive Systems Lab
Physionet
NINDS

UCLA Rated One of the Top Hospitals in the Nation