Imperial College London

ProfessorDaniloMandic

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Professor of Signal Processing
 
 
 
//

Contact

 

+44 (0)20 7594 6271d.mandic Website

 
 
//

Assistant

 

Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267

 
//

Location

 

813Electrical EngineeringSouth Kensington Campus

//

Summary

 

Publications

Publication Type
Year
to

574 results found

Li Z, Xia Y, Pei W, Mandic DPet al., 2019, A cost-effective nonlinear self-interference canceller in full-duplex direct-conversion transceivers, SIGNAL PROCESSING, Vol: 158, Pages: 4-14, ISSN: 0165-1684

JOURNAL ARTICLE

Cheng H, Xia Y, Huang Y, Yang L, Mandic DPet al., 2019, Joint Channel Estimation and Tx/Rx I/Q Imbalance Compensation for GFDM Systems, IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, Vol: 18, Pages: 1304-1317, ISSN: 1536-1276

JOURNAL ARTICLE

Powezka K, Adjei T, von Rosenberg W, Normahani P, Goverdovsky V, Standfield NJ, Mandic DP, Jaffer Uet al., 2019, A pilot study of preoperative heart rate variability predicting pain during local anesthetic varicose vein surgery., J Vasc Surg Venous Lymphat Disord

OBJECTIVE: Local anesthetic endovenous procedures were shown to reduce recovery time, to decrease postoperative pain, and to more quickly return the patient to baseline activities. However, a substantial number of patients experience pain during these procedures. The autonomic nervous system modulates pain perception, and its influence on stress response can be noninvasively quantified using heart rate variability (HRV) indices. The aim of our study was to evaluate whether preoperative baseline HRV can predict intraoperative pain during local anesthetic varicose vein surgery. METHODS: Patients scheduled for radiofrequency ablation were included in the study. They had their electrocardiograms recorded from a single channel of a custom-made amplifier. Each patient preoperatively filled in forms Y-1 and Y-2 of Spielberger's State and Trait Anxiety Inventory, completed the Aberdeen Varicose Vein Questionnaire, and rated anxiety level on a numeric scale. Postoperatively, patients filled in the pain they felt during the procedure on the numeric pain intensity scale. MATLAB software (MathWorks, Natick, Mass) was used to extract R waves and to generate HRV signals, and a mathematical model was created to predict the pain score for each patient. RESULTS: In multivariable analysis, we looked into correlation between reported patient's pain score (rPPS) and Aberdeen Varicose Vein Questionnaire score, preoperative forms Y-1 and Y-2, preoperative anxiety level, and predicted patient's pain (pPPS) score. Multivariable analysis found association only between rPPS and pPPS. The pPPS was significantly correlated with rPPS (R = 0.807; P < .001) with accuracy of prediction of 65.2%, which was calculated from R2 on a linear regression model. CONCLUSIONS: This preliminary study shows that preoperative HRV can accurately predict patients' pain, allowing patients with higher predicted score to have the procedure under general anesthesia.

JOURNAL ARTICLE

Xiang M, Dees BS, Mandic DP, 2019, Multiple-Model Adaptive Estimation for 3-D and 4-D Signals: A Widely Linear Quaternion Approach, IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, Vol: 30, Pages: 72-84, ISSN: 2162-237X

JOURNAL ARTICLE

Oliveira V, Martins R, Liow N, Teiserskas J, von Rosenberg W, Adjei T, Shivamurthappa V, Lally PJ, Mandic D, Thayyil Set al., 2019, Prognostic Accuracy of Heart Rate Variability Analysis in Neonatal Encephalopathy: A Systematic Review, NEONATOLOGY, Vol: 115, Pages: 59-67, ISSN: 1661-7800

JOURNAL ARTICLE

Adjei T, Xue J, Mandic DP, 2018, The Female Heart: Sex Differences in the Dynamics of ECG in Response to Stress, FRONTIERS IN PHYSIOLOGY, Vol: 9, ISSN: 1664-042X

JOURNAL ARTICLE

Stott AE, Kanna S, Mandic DP, 2018, Widely linear complex partial least squares for latent subspace regression, SIGNAL PROCESSING, Vol: 152, Pages: 350-362, ISSN: 0165-1684

JOURNAL ARTICLE

Nakamura T, Alqurashi YD, Morrell MJ, Mandic DPet al., 2018, Automatic detection of drowsiness using in-ear EEG

© 2018 IEEE. Sleep monitoring with wearable electroencephalography (EEG) has recently been validated and reported in the research community. One such device is our ultra-wearable, unobtrusive, and inconspicuous in-ear EEG system, which has already been demonstrated to be next-generation solution for out-of-clinic sleep monitoring. We here provide a further proof of concept of the utility of ear-EEG in day time drowsiness monitoring in the real-world. For rigour, hypnograms are obtained from manually scored daytime nap recordings from twentythree subjects, while a complexity science feature-structural complexity extracted from scalp- and ear-EEG recordings - is used in the classification stage, in conjunction with a binary-class support vector machine (SVM). The achieved drowsiness classification accuracies range from 80.0% to 82.9% for ear-EEG, with the corresponding accuracies for scalp-EEG ranging from 86.8 % to 88.8 %. Given the notoriously difficult to classify drowsiness related changes in EEG (similar to the issues with the NREM Stage 1), this conclusively confirms the feasibility of in-ear EEG for automatic light sleep classification. This also promises a key stepping stone towards continuous, discreet, and user-friendly wearable out-of-clinic drowsiness monitoring in the real-world, with numerous applications in the monitoring the state of body and mind of pilots, train drivers, and tele-operators.

CONFERENCE PAPER

Talebi SP, Werner S, Mandic DP, 2018, Distributed Adaptive Filtering of alpha-Stable Signals, IEEE SIGNAL PROCESSING LETTERS, Vol: 25, Pages: 1450-1454, ISSN: 1070-9908

JOURNAL ARTICLE

Cheng H, Xia Y, Huang Y, Yang L, Mandic DPet al., 2018, A Normalized Complex LMS Based Blind I/Q Imbalance Compensator for GFDM Receivers and Its Full Second-Order Performance Analysis, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 66, Pages: 4701-4712, ISSN: 1053-587X

JOURNAL ARTICLE

Xia Y, Douglas SC, Mandic DP, 2018, A perspective on CLMS as a deficient length augmented CLMS: Dealing with second order noncircularity, SIGNAL PROCESSING, Vol: 149, Pages: 236-245, ISSN: 0165-1684

JOURNAL ARTICLE

Li Z, Xia Y, Pei W, Wang K, Mandic DPet al., 2018, An Augmented Nonlinear LMS for Digital Self-Interference Cancellation in Full-Duplex Direct-Conversion Transceivers, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 66, Pages: 4065-4078, ISSN: 1053-587X

JOURNAL ARTICLE

Brajović M, Stanković L, Daković M, Mandić Det al., 2018, Additive noise influence on the bivariate two-component signal decomposition, Pages: 1-4

© 2018 IEEE. Decomposition of multicomponent signals overlapping in the time-frequency domain is a challenging research topic. To solve this problem, many approaches have been proposed so far, but only to be efficient for some particular signal classes. Recently, we have proposed a decomposition approach for multivariate multicomponent signals, based on the time-frequency signal analysis and concentration measures. The proposed solution is efficient for multivariate signals partially overlapped in the time-frequency plane regardless of the non-stationarity type of particular signal components. This decomposition approach is shown to be also efficient in noisy environments. In this paper, we investigate the limits of the decomposition efficiency subject to the signal-to-noise ratio and initial phase differences between the signals from different channels. The paper is focused on the decomposition of bivariate two-component signals.

CONFERENCE PAPER

Constantinescu MAM, Lee S-L, Ernst S, Hemakom A, Mandic D, Yang G-Zet al., 2018, Probabilistic guidance for catheter tip motion in cardiac ablation procedures, MEDICAL IMAGE ANALYSIS, Vol: 47, Pages: 1-14, ISSN: 1361-8415

JOURNAL ARTICLE

Xiang M, Enshaeifar S, Stott AE, Took CC, Xia Y, Kanna S, Mandic DPet al., 2018, Simultaneous diagonalisation of the covariance and complementary covariance matrices in quaternion widely linear signal processing, SIGNAL PROCESSING, Vol: 148, Pages: 193-204, ISSN: 0165-1684

JOURNAL ARTICLE

Kanna S, von Rosenberg W, Goverdovsky V, Constantinides AG, Mandic DPet al., 2018, Bringing Wearable Sensors into the Classroom: A Participatory Approach, IEEE SIGNAL PROCESSING MAGAZINE, Vol: 35, Pages: 110-+, ISSN: 1053-5888

JOURNAL ARTICLE

Normahani P, Makwana N, von Rosenberg W, Syed S, Mandic DP, Goverdovsky V, Standfield NJ, Jaffer Uet al., 2018, Self-assessment of surgical ward crisis management using video replay augmented with stress biofeedback, PATIENT SAFETY IN SURGERY, Vol: 12, ISSN: 1754-9493

JOURNAL ARTICLE

Xiang M, Kanna S, Mandic DP, 2018, Performance Analysis of Quaternion-Valued Adaptive Filters in Nonstationary Environments, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 66, Pages: 1566-1579, ISSN: 1053-587X

JOURNAL ARTICLE

Xia Y, Douglas SC, Mandic DP, 2018, Performance analysis of the deficient length augmented CLMS algorithm for second order noncircular complex signals, SIGNAL PROCESSING, Vol: 144, Pages: 214-225, ISSN: 0165-1684

JOURNAL ARTICLE

Xia Y, Kanna S, Mandic DP, 2018, Maximum Likelihood Parameter Estimation of Unbalanced Three-Phase Power Signals, IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, Vol: 67, Pages: 569-581, ISSN: 0018-9456

JOURNAL ARTICLE

Nakamura T, Goverdovsky V, Mandic DP, 2018, In-Ear EEG Biometrics for Feasible and Readily Collectable Real-World Person Authentication, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, Vol: 13, Pages: 648-661, ISSN: 1556-6013

JOURNAL ARTICLE

Looney D, Adjei T, Mandic DP, 2018, A Novel Multivariate Sample Entropy Algorithm for Modeling Time Series Synchronization, ENTROPY, Vol: 20, ISSN: 1099-4300

JOURNAL ARTICLE

Xia Y, Mandic DP, 2018, Augmented Performance Bounds on Strictly Linear and Widely Linear Estimators With Complex Data, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 66, Pages: 507-514, ISSN: 1053-587X

JOURNAL ARTICLE

Hemakom A, Goverdovsky V, Mandic DP, 2018, EAR-EEG FOR DETECTING INTER-BRAIN SYNCHRONISATION IN CONTINUOUS COOPERATIVE MULTI-PERSON SCENARIOS, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 911-915

CONFERENCE PAPER

Douglas SC, Mandic DP, 2018, AFFINE-PROJECTION LEAST-MEAN-MAGNITUDE-PHASE ALGORITHMS USING A POSTERIORI UPDATES, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 4154-4158

CONFERENCE PAPER

Kisil I, Calvi GG, Cichocki A, Mandic DPet al., 2018, COMMON AND INDIVIDUAL FEATURE EXTRACTION USING TENSOR DECOMPOSITIONS: A REMEDY FOR THE CURSE OF DIMENSIONALITY?, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 6299-6303

CONFERENCE PAPER

Stankovic L, Mandic D, Dakovic M, Brajovic Met al., 2018, Time-frequency decomposition of multivariate multicomponent signals, SIGNAL PROCESSING, Vol: 142, Pages: 468-479, ISSN: 0165-1684

JOURNAL ARTICLE

Alqurashi YD, Nakamura T, Goverdovsky V, Moss J, Polkey MI, Mandic DP, Morrell MJet al., 2018, A novel in-ear sensor to determine sleep latency during the Multiple Sleep Latency Test in healthy adults with and without sleep restriction, NATURE AND SCIENCE OF SLEEP, Vol: 10, Pages: 385-396, ISSN: 1179-1608

JOURNAL ARTICLE

Calvi GG, Kisil I, Mandic DP, 2018, Feature Fusion via Tensor Network Summation, European Signal Processing Conference (EUSIPCO), Publisher: IEEE COMPUTER SOC, Pages: 2623-2627, ISSN: 2076-1465

CONFERENCE PAPER

Li Z, Deng W, Pei W, Xia Y, Mandic DPet al., 2018, Refreshing Digital Communications Curriculum with RFID Technology: A Participatory Approach, 23rd IEEE International Conference on Digital Signal Processing (DSP), Publisher: IEEE, ISSN: 1546-1874

CONFERENCE PAPER

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: http://wlsprd.imperial.ac.uk:80/respub/WEB-INF/jsp/search-html.jsp Request URI: /respub/WEB-INF/jsp/search-html.jsp Query String: respub-action=search.html&id=00168709&limit=30&person=true