Redmond, Stephen - University of New South Wales - Graduate School of Biomedical Engineering

个人简介

A/Prof Stephen Redmond is an Australian Research Council (ARC) Future Fellow at the Graduate School of Biomedical Engineering at The University of New South Wales (UNSW), where he has worked since 2008. He completed his Bachelor of (Electronic) Engineering at University College Dublin (UCD), Ireland, in 2002. He also completed his PhD in biosignal processing at the same institute, in 2006.

研究领域

His primary research interests revolve around the application of signal processing and pattern recognition techniques to solve or understand biomedical engineering problems. The principal application areas for these signal processing and pattern recognition techniques can be arranged in three broad themes, listed below. 1) Telehealth: Telehealth involves the monitoring and management of health and wellbeing remotely, bringing fundamental biomonitoring into the home to assist sufferers of chronic disease, or even a general population who wish to better manage their health. A/Prof Redmond's group have been pioneers in the development of telehealth technologies and associated software algorithms to interpret the acquired telehealth physiological data. Telehealth technologies promise to change the concept, quality and cost of healthcare forever. 2) Fall detection and prediction: Along similar lines, his group is developing wearable ambulatory and environmental monitoring technologies to reduce the burden of falls among older individuals. The group's inertial sensors and signal processing algorithms are developed in-house. They have developed algorithms to detect falls when they occur, or to predict future falls by identifying instability during normal movement, triggering the administration of a preventative rehabilitation program. They are also attempting to detect falls which occur at night time in the homes of older people living alone, using unobtrusive motion sensors and furniture load sensors; they have also investigated the use of 3D cameras systems, such as the Microsoft Kinect, for the same purpose. 3) Tactile physiology and sensing: A/Prof Redmond is also involved in a number of other research areas, including the application of pattern recognition and signal processing methods to decode the neural responses of populations of afferent mechanoreceptors in the fingertip, which will improve our understanding of why the human sense of touch is so sophisticated. His group, which is a collaborative network of researchers from UNSW, Neuroscience Research Australia, and The University of Western Sydney, is also using these discoveries to design tactile sensors, which might provide upper limb prosthetics of the future, or autonomous robotic manipulators, with a sense of touch.

近期论文

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Wang J; Redmond SJ; Bertoux M; Hodges JR; Hornberger M, 2016, 'A comparison of magnetic resonance imaging and neuropsychological examination in the diagnostic distinction of Alzheimer's disease and behavioral variant frontotemporal dementia', Frontiers in Aging Neuroscience, vol. 8, no. JUN, http://dx.doi.org/10.3389/fnagi.2016.00119 Del Rosario MB; Lovell NH; Redmond SJ, 2016, 'Quaternion-Based Complementary Filter for Attitude Determination of a Smartphone', IEEE Sensors Journal, vol. 16, no. 15, pp. 6008 - 6017, http://dx.doi.org/10.1109/JSEN.2016.2574124 Khamis H; Weiss R; Xie Y; Chang CW; Lovell NH; Redmond SJ, 2016, 'QRS Detection Algorithm for Telehealth Electrocardiogram Recordings', IEEE Transactions on Biomedical Engineering, vol. 63, no. 7, pp. 1377 - 1388, http://dx.doi.org/10.1109/TBME.2016.2549060 Ooi HL; Seera M; Ng SC; Lim CP; Loo CK; Lovell NH; Redmond SJ; Lim E, 2016, 'Classification of Implantable Rotary Blood Pump States with Class Noise', IEEE Journal of Biomedical and Health Informatics, vol. 20, no. 3, pp. 829 - 837, http://dx.doi.org/10.1109/JBHI.2015.2412375 Xie Y; Schreier G; Hoy M; Liu Y; Neubauer S; Chang DCW; Redmond SJ; Lovell NH, 2016, 'Analyzing health insurance claims on different timescales to predict days in hospital', Journal of Biomedical Informatics, vol. 60, pp. 187 - 196, http://dx.doi.org/10.1016/j.jbi.2016.01.002 Brodie MAD; Coppens MJM; Lord SR; Lovell NH; Gschwind YJ; Redmond SJ; Del Rosario MB; Wang K; Sturnieks DL; Persiani M; Delbaere K, 2016, 'Wearable pendant device monitoring using new wavelet-based methods shows daily life and laboratory gaits are different', Medical and Biological Engineering and Computing, vol. 54, no. 4, pp. 663 - 674, http://dx.doi.org/10.1007/s11517-015-1357-9 Santoso F; Redmond SJ, 2015, 'Indoor location-aware medical systems for smart homecare and telehealth monitoring: State-of-the-art', Physiological Measurement, vol. 36, no. 10, pp. R53 - R87, http://dx.doi.org/10.1088/0967-3334/36/10/R53 Brodie MA; Wang K; Delbaere K; Persiani M; Lovell NH; Redmond SJ; Del Rosario MB; Lord SR, 2015, 'New methods to monitor stair ascents using a wearable pendant device reveal how behavior, fear, and frailty influence falls in octogenarians', IEEE Transactions on Biomedical Engineering, vol. 62, no. 11, pp. 2595 - 2601, http://dx.doi.org/10.1109/TBME.2015.2464689 del Rosario MB; Redmond SJ; Lovell NH, 2015, 'Tracking the evolution of smartphone sensing for monitoring human movement', Sensors, vol. 15, no. 8, pp. 18901 - 18933, http://dx.doi.org/10.3390/s150818901 Xie Y; Schreier G; Chang DCW; Neubauer S; Liu Y; Redmond SJ; Lovell NH, 2015, 'Predicting Days in Hospital Using Health Insurance Claims', IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 4, pp. 1224 - 1233, http://dx.doi.org/10.1109/JBHI.2015.2402692 Khamis H; Birznieks I; Redmond SJ, 2015, 'Decoding tactile afferent activity to obtain an estimate of instantaneous force and torque applied to the fingerpad', Journal of Neurophysiology, vol. 114, no. 1, pp. 474 - 484, http://dx.doi.org/10.1152/jn.00040.2015 Lim PK; Ng SC; Jassim WA; Redmond SJ; Zilany M; Avolio A; Lim E; Tan MP; Lovell NH, 2015, 'Improved measurement of blood pressure by extraction of characteristic features from the cuff oscillometric waveform', Sensors, vol. 15, no. 6, pp. 14142 - 14161, http://dx.doi.org/10.3390/s150614142 Wang C; Lu W; Narayanan MR; Redmond SJ; Lovell NH, 2015, 'Low-power technologies for wearable telecare and telehealth systems: A review', Biomedical Engineering Letters, vol. 5, no. 1, http://dx.doi.org/10.1007/s13534-015-0174-2 Mohktar MS; Redmond SJ; Antoniades NC; Rochford PD; Pretto JJ; Basilakis J; Lovell NH; McDonald CF, 2015, 'Predicting the risk of exacerbation in patients with chronic obstructive pulmonary disease using home telehealth measurement data', Artificial Intelligence in Medicine, vol. 63, no. 1, pp. 51 - 59, http://dx.doi.org/10.1016/j.artmed.2014.12.003 Brodie MA; Lovell NH; Redmond SJ; Lord SR, 2015, 'Bottom-up subspace clustering suggests a paradigm shift to prevent fall injuries', Medical Hypotheses, vol. 84, no. 4, pp. 356 - 362, http://dx.doi.org/10.1016/j.mehy.2015.01.017 Abd Sukor J; Mohktar MS; Redmond SJ; Lovell NH, 2015, 'Signal quality measures on pulse oximetry and blood pressure signals acquired from self-measurement in a home environment', IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 1, pp. 102 - 108, http://dx.doi.org/10.1109/JBHI.2014.2361654 Del Rosario MB; Wang K; Wang J; Liu Y; Brodie M; Delbaere K; Lovell NH; Lord SR; Redmond SJ, 2014, 'A comparison of activity classification in younger and older cohorts using a smartphone', Physiological Measurement, vol. 35, no. 11, pp. 2269 - 2286, http://dx.doi.org/10.1088/0967-3334/35/11/2269 Weatherall A; Garner A; Lovell N; Redmond S; Lee A; Skowno J; Egan J, 2014, 'Study protocol for the PHANTOM study: Prehospital assessment of noninvasive tissue oximetry monitoring', Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, vol. 22, no. 1, http://dx.doi.org/10.1186/s13049-014-0057-z Klenk J; Chiari L; Helbostad JL; Zijlstra W; Aminian K; Todd C; Bandinelli S; Kerse N; Schwickert L; Mellone S; Bagalá F; Delbaere K; Hauer K; Redmond SJ; Robinovitch S; Aziz O; Schwenk M; Zecevic A; Zieschang T; Becker C; FARSEEING Consortium and the FARSEEING Meta-Database Consensus Group, 2013, 'Development of a standard fall data format for signals from body-worn sensors : the FARSEEING consensus.', Zeitschrift fuer Gerontologie und Geriatrie: Organ der Deutschen Gesellschaft fuer Gerontologie und Geriatrie, vol. 46, no. 8, pp. 720 - 726, http://dx.doi.org/10.1007/s00391-013-0554-0 Marschollek M; Schulze M; Gietzelt M; Lovell NH; Redmond SJ, 2013, 'Sensor-based fall risk assessment-dagger of the mind?', Studies in Health Technology and Informatics, vol. 192, no. 1-2, pp. 1048, http://dx.doi.org/10.3233/978-1-61499-289-9-1048