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  • JOURNAL ARTICLE
    Imtiaz SA, Mardell J, Saremi-Yarahmadi S, Rodriguez-Villegas Eet al., 2016,

    ECG artefact identification and removal in mHealth systems for continuous patient monitoring

    , HEALTHCARE TECHNOLOGY LETTERS, Vol: 3, Pages: 171-176, ISSN: 2053-3713
  • JOURNAL ARTICLE
    Pramono RXA, Imtiaz SA, Rodriguez-Villegas E, 2016,

    A Cough-Based Algorithm for Automatic Diagnosis of Pertussis

    , PLOS ONE, Vol: 11, ISSN: 1932-6203
  • CONFERENCE PAPER
    Patrick KCA, Imtiaz SA, Bowyer S, Rodriguez-Villegas Eet al., 2016,

    An Algorithm for Automatic Detection of Drowsiness for Use in Wearable EEG Systems

    , 38th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Publisher: IEEE, Pages: 3523-3526, ISSN: 1557-170X
  • JOURNAL ARTICLE
    Imtiaz SA, Logesparan L, Rodriguez-Villegas E, 2015,

    Performance-Power Consumption Tradeoff in Wearable Epilepsy Monitoring Systems

    , IEEE Journal of Biomedical and Health Informatics, Vol: 19, Pages: 1019-1028, ISSN: 2168-2208

    Automated seizure detection methods can be used to reduce time and costs associated with analyzing large volumes of ambulatory EEG recordings. These methods however have to rely on very complex, power hungry algorithms, implemented on the system backend, in order to achieve acceptable levels of accuracy. In size, and therefore power-constrained EEG systems, an alternative approach to the problem of data reduction is online data selection, in which simpler algorithms select potential epileptiform activity for discontinuous recording but accurate analysis is still left to a medical practitioner. Such a diagnostic decision support system would still provide doctors with information relevant for diagnosis while reducing the time taken to analyze the EEG. For wearable systems with limited power budgets, data selection algorithm must be of sufficiently low complexity in order to reduce the amount of data transmitted and the overall power consumption. In this paper, we present a low-power hardware implementation of an online epileptic seizure data selection algorithm with encryption and data transmission and demonstrate the tradeoffs between its accuracy and the overall system power consumption. We demonstrate that overall power savings by data selection can be achieved by transmitting less than 40% of the data. We also show a 29% power reduction when selecting and transmitting 94% of all seizure events and only 10% of background EEG.
  • JOURNAL ARTICLE
    Chen G, Imtiaz SA, Aguilar-Pelaez E, Rodriguez-Villegas Eet al., 2015,

    Algorithm for heart rate extraction in a novel wearable acoustic sensor

    , HEALTHCARE TECHNOLOGY LETTERS, Vol: 2, Pages: 28-33, ISSN: 2053-3713
  • CONFERENCE PAPER
    Imtiaz SA, Rodriguez-Villegas E, 2015,

    An Open-source Toolbox For Standardized Use Of PhysioNet Sleep EDF Expanded Database

    , 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEE, Pages: 6014-6017, ISSN: 1557-170X
  • CONFERENCE PAPER
    Imtiaz SA, Rodriguez-Villegas E, 2015,

    Automatic Sleep Staging Using State Machine-controlled Decision Trees

    , 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEE, Pages: 378-381, ISSN: 1557-170X
  • JOURNAL ARTICLE
    Imtiaz SA, Rodriguez-Villegas E, 2014,

    A low computational cost algorithm for REM sleep detection using single channel EEG.

    , Ann Biomed Eng, Vol: 42, Pages: 2344-2359

    The push towards low-power and wearable sleep systems requires using minimum number of recording channels to enhance battery life, keep processing load small and be more comfortable for the user. Since most sleep stages can be identified using EEG traces, enormous power savings could be achieved by using a single channel of EEG. However, detection of REM sleep from one channel EEG is challenging due to its electroencephalographic similarities with N1 and Wake stages. In this paper we investigate a novel feature in sleep EEG that demonstrates high discriminatory ability for detecting REM phases. We then use this feature, that is based on spectral edge frequency (SEF) in the 8-16 Hz frequency band, together with the absolute power and the relative power of the signal, to develop a simple REM detection algorithm. We evaluate the performance of this proposed algorithm with overnight single channel EEG recordings of 5 training and 15 independent test subjects. Our algorithm achieved sensitivity of 83%, specificity of 89% and selectivity of 61% on a test database consisting of 2221 REM epochs. It also achieved sensitivity and selectivity of 81 and 75% on PhysioNet Sleep-EDF database consisting of 8 subjects. These results demonstrate that SEF can be a useful feature for automatic detection of REM stages of sleep from a single channel EEG.
  • CONFERENCE PAPER
    Imtiaz SA, Rodriguez-Villegas E, 2014,

    Recommendations for Performance Assessment of Automatic Sleep Staging Algorithms

    , 36th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Publisher: IEEE, Pages: 5044-5047, ISSN: 1557-170X

    A number of automatic sleep scoring algorithms have been published in the last few years. These can potentially help save time and reduce costs in sleep monitoring. However, the use of both R&K and AASM classification, different databases and varying performance metrics makes it extremely difficult to compare these algorithms. In this paper, we describe some readily available polysomnography databases and propose a set of recommendations and performance metrics to promote uniform testing and direct comparison of different algorithms. We use two different polysomnography databases with a simple sleep staging algorithm to demonstrate the usage of all recommendations and presentation of performance results. We also illustrate how seemingly similar results using two different databases can have contrasting accuracies in different sleep stages. Finally, we show how selection of different training and test subjects from the same database can alter the final performance results.
  • JOURNAL ARTICLE
    Rodriguez-Villegas E, Logesparan L, Casson AJ, 2014,

    A Low Power Linear Phase Programmable Long Delay Circuit

    , IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS, Vol: 8, Pages: 432-441, ISSN: 1932-4545
  • JOURNAL ARTICLE
    Imtiaz SA, Casson AJ, Rodriguez-Villegas E, 2014,

    Compression in Wearable Sensor Nodes: Impacts of Node Topology

    , IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 61, Pages: 1080-1090, ISSN: 0018-9294
  • JOURNAL ARTICLE
    Casson AJ, Rodriguez-Villegas E, 2014,

    Nanowatt multi-scale continuous wavelet transform chip

    , ELECTRONICS LETTERS, Vol: 50, Pages: 153-154, ISSN: 0013-5194
  • CONFERENCE PAPER
    Saraswat R, Rodriguez-Villegas E, 2014,

    Chaotic Inductively Coupled Non-PLL Low Emission Transmitter for Implanted Devices

    , IEEE 5th Latin American Symposium on Circuits and Systems (LASCAS), Publisher: IEEE, ISSN: 2330-9954
  • JOURNAL ARTICLE
    Rodriguez-Villegas E, Chen G, Radcliffe J, Duncan Jet al., 2014,

    A pilot study of a wearable apnoea detection device

    , BMJ OPEN, Vol: 4, ISSN: 2044-6055
  • CONFERENCE PAPER
    Hizon JRE, Rodriguez-Villegas E, 2014,

    A Reconfigurable FGMOS based OTA-C Filter

    , IEEE International Symposium on Circuits and Systems (ISCAS), Publisher: IEEE, Pages: 2093-2096, ISSN: 0271-4302
  • CONFERENCE PAPER
    Imtiaz SA, Rodriguez-Villegas E, 2014,

    Evaluating the use of line length for automatic sleep spindle detection

    , 36th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Publisher: IEEE, Pages: 5024-5027, ISSN: 1557-170X
  • JOURNAL ARTICLE
    Saraswat R, Rodriguez-Villegas E, 2014,

    Low Power EMI Mitigation Strategies Utilizing Non-PLL Based Periodic and Chaotic SSC Profiles for Implanted Devices

    , 2014 8TH INTERNATIONAL SYMPOSIUM ON MEDICAL INFORMATION AND COMMUNICATION TECHNOLOGY (ISMICT), ISSN: 2326-828X
  • CONFERENCE PAPER
    Imtiaz SA, Saremi-Yarahmadi S, Rodriguez-Villegas E, 2013,

    Automatic detection of sleep spindles using Teager energy and spectral edge frequency

    , IEEE Biomedical Circuits and Systems Conference (BioCAS), Publisher: IEEE, Pages: 262-265

    Sleep spindles are the hallmark of N2 stage of sleep. They are transient waveforms observed on sleep electroencephalogram and their identification is required for sleep staging. Due to the large number of sleep spindles appearing on an overnight sleep EEG, automating the detection of sleep spindles would be desirable, not only to save specialist time but also for fully automated sleep staging systems. A simple algorithm for automatic sleep spindle detection is presented in this paper using only one channel of EEG input. This algorithm uses Teager energy and spectral edge frequency to mark sleep spindles and results in a sensitivity of 80% and specificity of about 98%. It is also shown that more than 91% of spindles detected by the algorithm were in N2 and N3 stages combined.
  • CONFERENCE PAPER
    Logesparan L, Casson AJ, Imtiaz SA, Rodriguez-Villegas Eet al., 2013,

    Discriminating between best performing features for seizure detection and data selection

    , 35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Publisher: IEEE, Pages: 1692-1695, ISSN: 1557-170X

    Seizure detection algorithms have been developed to solve specific problems, such as seizure onset detection, occurrence detection, termination detection and data selection. It is thus inherent that each type of seizure detection algorithm would detect a different EEG characteristic (feature). However most feature comparison studies do not specify the seizure detection problem for which their respective features have been evaluated. This paper shows that the best features/algorithm bases are not the same for all types of algorithms but depend on the type of seizure detection algorithm wanted. To demonstrate this, 65 features previously evaluated for online seizure data selection are re-evaluated here for seizure occurrence detection, using performance metrics pertinent to each seizure detection type whilst keeping the testing methodology the same. The results show that the best performing features/algorithm bases for data selection and occurrence detection algorithms are different and that it is more challenging to achieve high detection accuracy for the former seizure detection type. This paper also provides a comprehensive evaluation of the performance of 65 features for seizure occurrence detection to aid future researchers in choosing the best performing feature(s) to improve seizure detection accuracy.
  • JOURNAL ARTICLE
    Pinuela M, Yates DC, Lucyszyn S, Mitcheson PDet al., 2013,

    Maximizing DC-to-Load Efficiency for Inductive Power Transfer

    , IEEE TRANSACTIONS ON POWER ELECTRONICS, Vol: 28, Pages: 2437-2447, ISSN: 0885-8993
  • CONFERENCE PAPER
    Saraswat R, Rodriguez-Villegas E, 2013,

    A Low Emission, Low Power Non-Linear Frequency Modulation Based Transmitter For Implanted Devices

    , 35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Publisher: IEEE, Pages: 826-829, ISSN: 1557-170X
  • JOURNAL ARTICLE
    Kafali O, Bromuri S, Sindlar M, van der Weide T, Pelaez EA, Schaechtle U, Alves B, Zufferey D, Rodriguez-Villegas E, Schumacher MI, Stathis Ket al., 2013,

    COMMODITY12: A smart e-health environment for diabetes management

    , JOURNAL OF AMBIENT INTELLIGENCE AND SMART ENVIRONMENTS, Vol: 5, Pages: 479-502, ISSN: 1876-1364
  • CONFERENCE PAPER
    Rajagopal MK, Rodriguez-Villegas E, 2013,

    Towards Wearable Sleep Diagnostic Systems for Point-of-Care Applications

    , 1st IEEE-EMBS Special Topic Conference on Point-of-Care (POCT) Healthcare Technologies (PHT), Publisher: IEEE, Pages: 26-29
  • JOURNAL ARTICLE
    Abdulghani AM, Casson AJ, Rodriguez-Villegas E, 2012,

    Compressive sensing scalp EEG signals: implementations and practical performance

    , MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, Vol: 50, Pages: 1137-1145, ISSN: 0140-0118
  • JOURNAL ARTICLE
    Aguilar-Pelaez E, Chen G, Rodriguez-Villegas E, 2012,

    Technique for Interference Reduction in Battery Powered Physiological Monitoring Devices

    , IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 59, Pages: 3197-3203, ISSN: 0018-9294
  • JOURNAL ARTICLE
    Logesparan L, Casson AJ, Rodriguez-Villegas E, 2012,

    Optimal features for online seizure detection

    , MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, Vol: 50, Pages: 659-669, ISSN: 0140-0118
  • PATENT
    Rodriguez-Villegas E, 2012,

    Feature characterization for breathing monitor
  • CONFERENCE PAPER
    Mardell J, Witkowski M, Spence R, 2012,

    An Interface for Visual Inspection based on Image Segmentation

    , International Working Conference on Advanced Visual Interfaces (AVI), Publisher: ASSOC COMPUTING MACHINERY, Pages: 697-700
  • CONFERENCE PAPER
    Hizon JRE, Rodriguez-Villegas E, 2012,

    A High Transconductance Efficiency FGMOS OTA for g(m)-C Ladder Filters

    , 55th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), Publisher: IEEE, Pages: 105-108, ISSN: 1548-3746
  • CONFERENCE PAPER
    Casson AJ, Rodriguez-Villegas E, 2012,

    Signal agnostic compressive sensing for Body Area Networks: Comparison of signal reconstructions

    , 34th Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBS), Publisher: IEEE, Pages: 4497-4500, ISSN: 1557-170X
  • CONFERENCE PAPER
    Hizon JRE, Rodriguez-Villegas E, 2012,

    A Compact Linearly Tunable Low Voltage Triode OTA Using Self-Cascodes

    , IEEE International Symposium on Circuits and Systems, Publisher: IEEE, Pages: 440-443, ISSN: 0271-4302
  • CONFERENCE PAPER
    Logesparan L, Casson AJ, Rodriguez-Villegas E, 2012,

    Improving seizure detection performance reporting: analysing the duration needed for a detection

    , 34th Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBS), Publisher: IEEE, Pages: 1069-1072, ISSN: 1557-170X
  • JOURNAL ARTICLE
    Shad A, Rodriguez-Villegas E, 2012,

    Proof of concept of a shoe based human activity monitor.

    , Conf Proc IEEE Eng Med Biol Soc, Vol: 2012, Pages: 6398-6401, ISSN: 1557-170X

    This paper presents the proof of concept of a low power, low cost, wearable activity monitor. The functionality of the system is based on accurate stride detection from signals generated by two force sensing resistors integrated within a normal shoe. A novel algorithm is proposed that is able to differentiate between walking and non-walking activities with high accuracy. The performance of the proof of concept system was validated in five subjects who underwent five repetitions of three different speed walking tests, and five repetitions of five non-walking artefact generating tests. The system achieved a total sensitivity of 96% with 98% specificity and an overall accuracy of 94%.
  • JOURNAL ARTICLE
    He C, Kiziroglou ME, Yates DC, Yeatman EMet al., 2011,

    A MEMS Self-Powered Sensor and RF Transmission Platform for WSN Nodes

    , IEEE SENSORS JOURNAL, Vol: 11, Pages: 3437-3445, ISSN: 1530-437X
  • JOURNAL ARTICLE
    He C, Kiziroglou ME, Yates DC, 2011,

    A MEMS Self-Powered Sensor and RF Transmission Platform for WSN Nodes

    , IEEE Sensors Journal, Vol: 11, Pages: 3437-3445
  • JOURNAL ARTICLE
    Logesparan L, Rodriguez-Villegas E, 2011,

    A Novel Phase Congruency Based Algorithm for Online Data Reduction in Ambulatory EEG Systems

    , IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 58, Pages: 2825-2834, ISSN: 0018-9294
  • JOURNAL ARTICLE
    Casson AJ, Rodriguez-Villegas E, 2011,

    Utilising noise to improve an interictal spike detector

    , JOURNAL OF NEUROSCIENCE METHODS, Vol: 201, Pages: 262-268, ISSN: 0165-0270
  • CONFERENCE PAPER
    Logesparan L, Casson AJ, Rodriguez-Villegas E, 2011,

    Performance metrics for characterization of a seizure detection algorithm for offline and online use

    , 5th International Workshop on Seizure Prediction

    Purpose: To select appropriate previously reported performance metrics to evaluate a new seizure detection algorithm for offline and online analysis, and thus quantify any performance variation between these metrics.Methods: Traditional offline algorithms mark out any EEG section (epoch) of a seizure (event), so that neurologists only analyze the detected and adjacent sections. Thus, offline algorithms could be evaluated using number of correctly detected events, or event-based sensitivity (SEVENT), and epoch-based specificity (percentage of incorrectly detected background epochs). In contrast, online seizure detection (especially, data selection) algorithms select for transmission only the detected EEG sections and hence need to detect the entire duration of a seizure. Thus, online algorithms could be evaluated using percentage of correctly detected seizure duration, or epoch-based sensitivity (SEPOCH), and epoch-based specificity. Here, a new seizure detection algorithm is evaluated using the selected performance metrics for epoch duration ranging from 1s to 60s.Results: For 1s epochs, the area under the event-based sensitivity-specificity curve was 0.95 whilst SEPOCH achieves 0.81. This difference is not surprising, as intuitively, detecting any epoch within a seizure is easier than detecting every epoch - especially as seizures evolve over time. For longer epochs of 30s or 60s, SEVENT falls to 0.84 and 0.82 respectively and SEPOCH reduces to 0.76. Here, decreased SEVENT shows that fewer seizures are detected, possibly due to easy-to-detect short seizure sections being masked by surrounding EEG. However, detecting one long epoch constitutes a larger percentage of a seizure than a shorter one and thus SEPOCH does not decrease proportionately.Conclusions: Traditional offline and online seizure detection algorithms require different metrics to effectively evaluate their performance for their respective applications. Using such metrics, it has been shown that a decre
  • JOURNAL ARTICLE
    Rodriguez-Villegas E, Casson AJ, Corbishley P, 2011,

    A Subhertz Nanopower Low-Pass Filter

    , IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, Vol: 58, Pages: 351-355, ISSN: 1549-7747
  • JOURNAL ARTICLE
    Casson AJ, Rodriguez-Villegas E, 2011,

    A 60 pW g(m)C Continuous Wavelet Transform Circuit for Portable EEG Systems

    , IEEE JOURNAL OF SOLID-STATE CIRCUITS, Vol: 46, Pages: 1406-1415, ISSN: 0018-9200
  • CONFERENCE PAPER
    Saremi-Yarahmadi S, Fobelets K, Toumazou C, 2011,

    Coupled RF inductive sensors for monitoring the conductivity of electrolyte solutions

    , Pages: 20-23

    The use of closely coupled inductors, operating in the region of 10 MHz to 1 GHz, for detection of change in the concentration of ionic species present in a liquid sample, is reported here. The S-parameters were measured for the coupled inductors with liquid samples under varying pH conditions on one inductor only. S12 parameters were used as an indicator for the coupling between the two inductors. The results from this study show that coupled coil systems can be employed in simple sensing systems to monitor electrolyte solutions without the need for direct physical contact to the sensor itself. This design has the potential of being used for applications such as monitoring DNA hybridization or monitoring the conductance of electrolyte solutions with high conductivity while simplifying packaging steps required. © 2011 IEEE.
  • BOOK CHAPTER
    Casson AJ, Rodriguez-Villegas E, 2011,

    Interfacing Biology and Circuits: Quantification and Performance Metrics

    , CMOS Biomicrosystems: Where Electronics Meet Biology, Pages: 1-32, ISBN: 9780470641903
  • CONFERENCE PAPER
    Logesparan L, Casson AJ, Rodriguez-Villegas E, 2011,

    Assessing the impact of signal normalization: preliminary results on epileptic seizure detection

    , 33rd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBS), Publisher: IEEE, Pages: 1439-1442, ISSN: 1557-170X
  • CONFERENCE PAPER
    Saremi-Yarahmadi S, Fobelets K, Toumazou C, 2011,

    Coupled Inductive Sensors for Monitoring the pH of Electrolyte Solutions

    , IEEE International Conference on Dielectric Liquids (ICDL), Publisher: IEEE
  • CONFERENCE PAPER
    Brinded T, Mardell J, Witkowski M, Spence Ret al., 2011,

    The Effects of Image Speed and Overlap on Image Recognition

    , 15th International Conference on Information Visualisation (IV), Publisher: IEEE COMPUTER SOC, Pages: 3-11, ISSN: 1550-6037
  • CONFERENCE PAPER
    Casson AJ, Rodriguez-Villegas E, 2011,

    Algorithms and circuits for truly wearable physiological monitoring

    , 33rd international conference of the IEEE Engineering in Medicine and Biology Society
  • JOURNAL ARTICLE
    Casson AJ, Rodriguez-Villegas E, 2011,

    "A review and modern approach to LC ladder synthesis,"

    , Journal of Low Power Electronics and Applications, Vol: 1, Pages: 20-44
  • CONFERENCE PAPER
    Mardell J, Witkowski M, Spence R, 2011,

    Gaze-contingent enhancements for a visual search and rescue task.

    , Publisher: ACM, Pages: 109-109
  • CONFERENCE PAPER
    Abdulghani AM, Casson AJ, Rodriguez-Villegas E, 2010,

    Quantifying the performance of compressive sensing on scalp EEG signals

    Compressive sensing is a new data compression paradigm that has shown significant promise in fields such as MRI. However, the practical performance of the theory very much depends on the characteristics of the signal being sensed. As such the utility of the technique cannot be extrapolated from one application to another. Electroencephalography (EEG) is a fundamental tool for the investigation of many neurological disorders and is increasingly also used in many non-medical applications, such as Brain-Computer Interfaces. This paper characterises in detail the practical performance of different implementations of the compressive sensing theory when applied to scalp EEG signals for the first time. The results are of particular interest for wearable EEG communication systems requiring low power, real-time compression of the EEG data. ©2010 IEEE.
  • CONFERENCE PAPER
    Holmes AS, Howey DA, Bansal A, Yates DCet al., 2010,

    Self-powered wireless sensor for duct monitoring

    , PowerMEMS 2010, the 10th International Workshop on Micro and Nanotechnology for Power Generation and Energy Conversion Applications, Pages: 115-118

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