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Dive into the research topics where Harsimrat Singh is active.

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Featured researches published by Harsimrat Singh.


Artificial Intelligence in Medicine | 2012

Channel selection and classification of electroencephalogram signals

Jianhua Yang; Harsimrat Singh; Evor L. Hines; Friederike Schlaghecken; Daciana Iliescu; Mark S. Leeson; Nigel G. Stocks

OBJECTIVE An electroencephalogram-based (EEG-based) brain-computer-interface (BCI) provides a new communication channel between the human brain and a computer. Amongst the various available techniques, artificial neural networks (ANNs) are well established in BCI research and have numerous successful applications. However, one of the drawbacks of conventional ANNs is the lack of an explicit input optimization mechanism. In addition, results of ANN learning are usually not easily interpretable. In this paper, we have applied an ANN-based method, the genetic neural mathematic method (GNMM), to two EEG channel selection and classification problems, aiming to address the issues above. METHODS AND MATERIALS Pre-processing steps include: least-square (LS) approximation to determine the overall signal increase/decrease rate; locally weighted polynomial regression (Loess) and fast Fourier transform (FFT) to smooth the signals to determine the signal strength and variations. The GNMM method consists of three successive steps: (1) a genetic algorithm-based (GA-based) input selection process; (2) multi-layer perceptron-based (MLP-based) modelling; and (3) rule extraction based upon successful training. The fitness function used in the GA is the training error when an MLP is trained for a limited number of epochs. By averaging the appearance of a particular channel in the winning chromosome over several runs, we were able to minimize the error due to randomness and to obtain an energy distribution around the scalp. In the second step, a threshold was used to select a subset of channels to be fed into an MLP, which performed modelling with a large number of iterations, thus fine-tuning the input/output relationship. Upon successful training, neurons in the input layer are divided into four sub-spaces to produce if-then rules (step 3). Two datasets were used as case studies to perform three classifications. The first data were electrocorticography (ECoG) recordings that have been used in the BCI competition III. The data belonged to two categories, imagined movements of either a finger or the tongue. The data were recorded using an 8 × 8 ECoG platinum electrode grid at a sampling rate of 1000 Hz for a total of 378 trials. The second dataset consisted of a 32-channel, 256 Hz EEG recording of 960 trials where participants had to execute a left- or right-hand button-press in response to left- or right-pointing arrow stimuli. The data were used to classify correct/incorrect responses and left/right hand movements. RESULTS For the first dataset, 100 samples were reserved for testing, and those remaining were for training and validation with a ratio of 90%:10% using K-fold cross-validation. Using the top 10 channels selected by GNMM, we achieved a classification accuracy of 0.80 ± 0.04 for the testing dataset, which compares favourably with results reported in the literature. For the second case, we performed multi-time-windows pre-processing over a single trial. By selecting 6 channels out of 32, we were able to achieve a classification accuracy of about 0.86 for the response correctness classification and 0.82 for the actual responding hand classification, respectively. Furthermore, 139 regression rules were identified after training was completed. CONCLUSIONS We demonstrate that GNMM is able to perform effective channel selections/reductions, which not only reduces the difficulty of data collection, but also greatly improves the generalization of the classifier. An important step that affects the effectiveness of GNMM is the pre-processing method. In this paper, we also highlight the importance of choosing an appropriate time window position.


Frontiers in Human Neuroscience | 2014

The brain's response to pleasant touch: an EEG investigation of tactile caressing.

Harsimrat Singh; Markus Bauer; Wojtek Chowanski; Yi Sui; Douglas Atkinson; Sharon Baurley; Martin E. Fry; Joe Evans; Nadia Bianchi-Berthouze

Somatosensation as a proximal sense can have a strong impact on our attitude toward physical objects and other human beings. However, relatively little is known about how hedonic valence of touch is processed at the cortical level. Here we investigated the electrophysiological correlates of affective tactile sensation during caressing of the right forearm with pleasant and unpleasant textile fabrics. We show dissociation between more physically driven differential brain responses to the different fabrics in early somatosensory cortex – the well-known mu-suppression (10–20 Hz) – and a beta-band response (25–30 Hz) in presumably higher-order somatosensory areas in the right hemisphere that correlated well with the subjective valence of tactile caressing. Importantly, when using single trial classification techniques, beta-power significantly distinguished between pleasant and unpleasant stimulation on a single trial basis with high accuracy. Our results therefore suggest a dissociation of the sensory and affective aspects of touch in the somatosensory system and may provide features that may be used for single trial decoding of affective mental states from simple electroencephalographic measurements.


NeuroImage: Clinical | 2014

Mapping cortical haemodynamics during neonatal seizures using diffuse optical tomography: A case study

Harsimrat Singh; Robert J. Cooper; Chuen Wai Lee; Laura A. Dempsey; Andrea D. Edwards; Sabrina Brigadoi; Dimitrios Airantzis; Nick Everdell; Andrew W. Michell; David S. Holder; Jeremy C. Hebden; Topun Austin

Seizures in the newborn brain represent a major challenge to neonatal medicine. Neonatal seizures are poorly classified, under-diagnosed, difficult to treat and are associated with poor neurodevelopmental outcome. Video-EEG is the current gold-standard approach for seizure detection and monitoring. Interpreting neonatal EEG requires expertise and the impact of seizures on the developing brain remains poorly understood. In this case study we present the first ever images of the haemodynamic impact of seizures on the human infant brain, obtained using simultaneous diffuse optical tomography (DOT) and video-EEG with whole-scalp coverage. Seven discrete periods of ictal electrographic activity were observed during a 60 minute recording of an infant with hypoxic–ischaemic encephalopathy. The resulting DOT images show a remarkably consistent, high-amplitude, biphasic pattern of changes in cortical blood volume and oxygenation in response to each electrographic event. While there is spatial variation across the cortex, the dominant haemodynamic response to seizure activity consists of an initial increase in cortical blood volume prior to a large and extended decrease typically lasting several minutes. This case study demonstrates the wealth of physiologically and clinically relevant information that DOT–EEG techniques can yield. The consistency and scale of the haemodynamic responses observed here also suggest that DOT–EEG has the potential to provide improved detection of neonatal seizures.


affective computing and intelligent interaction | 2011

The affective experience of handling digital fabrics: tactile and visual cross-modal effects

Di Wu; Ting-I Wu; Harsimrat Singh; Stefano Padilla; Douglas Atkinson; Nadia Bianchi-Berthouze; Mike J. Chantler; Sharon Baurley

In the textile sector, emotions are often associated with both physical touch and manipulation of the product. Thus there is the need to recreate the affective experiences of touching and interacting with fabrics using commonly available internet technology. New digital interactive representations of fabrics simulating handling have been proposed with the idea of bringing the digital experience of fabrics closer to the reality. This study evaluates the contribution of handling real fabrics to viewing digital interactive animations of said fabrics and vice versa. A combination of self-report and physiological measures was used. Results showed that having previous physical handling experience of the fabrics significantly increased pleasure and engagement in the visual experience of the digital handling of the same fabrics. Two factors mediated these experiences: gender and interoceptive awareness. Significant results were not found for the opposite condition.


Neurophotonics | 2016

Hemodynamic response to burst-suppressed and discontinuous electroencephalography activity in infants with hypoxic ischemic encephalopathy

Maria Chalia; Chuen Wai Lee; Laura A. Dempsey; Andrea D. Edwards; Harsimrat Singh; Andrew W. Michell; Nick Everdell; Reuben W. Hill; Jeremy C. Hebden; Topun Austin; Robert J. Cooper

Abstract. Burst suppression (BS) is an electroencephalographic state associated with a profound inactivation of the brain. BS and pathological discontinuous electroencephalography (EEG) are often observed in term-age infants with neurological injury and can be indicative of a poor outcome and lifelong disability. Little is known about the neurophysiological mechanisms of BS or how the condition relates to the functional state of the neonatal brain. We used simultaneous EEG and diffuse optical tomography (DOT) to investigate whether bursts of EEG activity in infants with hypoxic ischemic encephalopathy are associated with an observable cerebral hemodynamic response. We were able to identify significant changes in concentration of both oxy and deoxyhemoglobin that are temporally correlated with EEG bursts and present a relatively consistent morphology across six infants. Furthermore, DOT reveals patient-specific spatial distributions of this hemodynamic response that may be indicative of a complex pattern of cortical activation underlying discontinuous EEG activity that is not readily apparent in scalp EEG.


Surgery | 2017

A decade of imaging surgeons' brain function (Part I): terminology, techniques and clinical translation

Hemel N. Modi; Harsimrat Singh; Guang-Zhong Yang; Ara Darzi; Daniel Leff

Background. Functional neuroimaging has the potential to deepen our understanding of technical and nontechnical skill acquisition in surgeons, particularly as established assessment tools leave unanswered questions about inter‐operator differences in ability that seem independent of experience. Methods. In this first of a 2‐part article, we aim to utilize our experience in neuroimaging surgeons to orientate the nonspecialist reader to the principles of brain imaging. Terminology commonly used in brain imaging research is explained, placing emphasis on the “activation response” to an surgical task and its effect on local cortical hemodynamic parameters (neurovascular coupling). Results. Skills learning and subsequent consolidation and refinement through practice lead to reorganization of the functional architecture of the brain (known as “neuroplasticity”), evidenced by changes in the strength of regional activation as well as alterations in connectivity between brain regions, culminating in more efficient use of neural resources during task performance. Conclusion. Currently available neuroimaging techniques that either directly (ie, measure electrical activity) or indirectly (ie, measure tissue hemodynamics) assess brain function are discussed. Finally, we highlight the important practical considerations when conducting brain imaging research in surgeons.


Annals of Surgery | 2017

Temporal Stress in the Operating Room: Brain Engagement Promotes “coping” and Disengagement Prompts “choking”

Hemel N. Modi; Harsimrat Singh; Felipe Orihuela-Espina; Thanos Athanasiou; Francesca Fiorentino; Guang-Zhong Yang; Ara Darzi; Daniel Leff

Objective: To investigate the impact of time pressure (TP) on prefrontal activation and technical performance in surgical residents during a laparoscopic suturing task. Background: Neural mechanisms enabling surgeons to maintain performance and cope with operative stressors are unclear. The prefrontal cortex (PFC) is implicated due to its role in attention, concentration, and performance monitoring. Methods: A total of 33 residents [Postgraduate Year (PGY)1–2 = 15, PGY3–4 = 8, and PGY5 = 10] performed a laparoscopic suturing task under “self-paced” (SP) and “TP” conditions (TP = maximum 2 minutes per knot). Subjective workload was quantified using the Surgical Task Load Index. PFC activation was inferred using optical neuroimaging. Technical skill was assessed using progression scores (au), error scores (mm), leak volumes (mL), and knot tensile strengths (N). Results: TP led to greater perceived workload amongst all residents (mean Surgical Task Load Index score ± SD: PGY1–2: SP = 160.3 ± 24.8 vs TP = 202.1 ± 45.4, P < 0.001; PGY3–4: SP = 123.0 ± 52.0 vs TP = 172.5 ± 43.1, P < 0.01; PGY5: SP = 105.8 ± 55.3 vs TP = 159.1 ± 63.1, P < 0.05). Amongst PGY1–2 and PGY3–4, deterioration in task progression, error scores and knot tensile strength (P < 0.05), and diminished PFC activation was observed under TP. In PGY5, TP resulted in inferior task progression and error scores (P < 0.05), but preservation of knot tensile strength. Furthermore, PGY5 exhibited less attenuation of PFC activation under TP, and greater activation than either PGY1–2 or PGY3–4 under both experimental conditions (P < 0.05). Conclusions: Senior residents cope better with temporal demands and exhibit greater technical performance stability under pressure, possibly due to sustained PFC activation and greater task engagement. Future work should seek to develop training strategies that recruit prefrontal resources, enhance task engagement, and improve performance under pressure.


Medical Teacher | 2017

Eye-tracking technology in medical education: A systematic review

Hajra Ashraf; Mikael H. Sodergren; Nabeel Merali; George P. Mylonas; Harsimrat Singh; Ara Darzi

Abstract Background: Eye-tracking technology is an established research tool within allied industries such as advertising, psychology and aerospace. This review aims to consolidate literature describing the evidence for use of eye-tracking as an adjunct to traditional teaching methods in medical education. Methods: A systematic literature review was conducted in line with STORIES guidelines. A search of EMBASE, OVID MEDLINE, PsycINFO, TRIP database, and Science Direct was conducted until January 2017. Studies describing the use of eye-tracking in the training, assessment, and feedback of clinicians were included in the review. Results: Thirty-three studies were included in the final qualitative synthesis. Three studies were based on the use of gaze training, three studies on the changes in gaze behavior during the learning curve, 17 studies on clinical assessment and six studies focused on the use of eye-tracking methodology as a feedback tool. The studies demonstrated feasibility and validity in the use of eye-tracking as a training and assessment method. Conclusions: Overall, eye-tracking methodology has contributed significantly to the training, assessment, and feedback practices used in the clinical setting. The technology provides reliable quantitative data, which can be interpreted to give an indication of clinical skill, provide training solutions and aid in feedback and reflection. This review provides a detailed summary of evidence relating to eye-tracking methodology and its uses as a training method, changes in visual gaze behavior during the learning curve, eye-tracking methodology for proficiency assessment and its uses as a feedback tool.


Advances in Experimental Medicine and Biology | 2016

Neurovascular Interactions in the Neurologically Compromised Neonatal Brain

Harsimrat Singh; Robert J. Cooper; C. W. Lee; Laura A. Dempsey; Sabrina Brigadoi; A. Edwards; D. Airantzis; Nick Everdell; A. Michell; D. Holder; T. Austin; Jc Hebden

Neurological brain injuries such as hypoxic ischaemic encephalopathy (HIE) and associated conditions such as seizures have been associated with poor developmental outcome in neonates. Our limited knowledge of the neurological and cerebrovascular processes underlying seizures limits their diagnosis and timely treatment. Diffuse optical tomography (DOT) provides haemodynamic information in the form of changes in concentration of de/oxygenated haemoglobin, which can improve our understanding of seizures and the relationship between neural and vascular processes. Using simultaneous EEG-DOT, we observed distinct haemodynamic changes which are temporally correlated with electrographic seizures. Here, we present DOT-EEG data from two neonates clinically diagnosed as HIE. Our results highlight the wealth of mutually-informative data that can be obtained using DOT-EEG techniques to understand neurovascular coupling in HIE neonates.


Brain-Computer Interfaces | 2015

Translational Algorithms: The Heart of a Brain Computer Interface

Harsimrat Singh; Ian Daly

Brain computer Interface (BCI) development encapsulates three basic processes: data acquisition, data processing, and device control. Since the start of the millennium the BCI development cycle has undergone a metamorphosis. This is mainly due to the increased popularity of BCI applications in both commercial and research circles. One of the focuses of BCI research is to bridge the gap between laboratory research and commercial applications using this technology. A vast variety of new approaches are being employed for BCI development ranging from novel paradigms, such as simultaneous acquisitions, through to asynchronous BCI control. The strategic usage of computational techniques, comprising the heart of the BCI system, underwrites this vast range of approaches. This chapter discusses these computational strategies and translational techniques including dimensionality reduction, feature extraction, feature selection, and classification techniques.

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Ara Darzi

Imperial College London

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Daniel Leff

Imperial College London

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Nick Everdell

University College London

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Topun Austin

Cambridge University Hospitals NHS Foundation Trust

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Andrea D. Edwards

Cambridge University Hospitals NHS Foundation Trust

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