Kenneth Camilleri
University of Malta, Systems and Control Engineering, Faculty Member
Non-contact vital sign monitoring is an area of increasing interest in the clinical scenario since it offers advantages over traditional monitoring using leads and wires. These advantages include reduction in transmission of infection and... more
Non-contact vital sign monitoring is an area of increasing interest in the clinical scenario since it offers advantages over traditional monitoring using leads and wires. These advantages include reduction in transmission of infection and more freedom of movement. Yet there is a paucity of studies available in the clinical setting particularly in paediatric anaesthesia. This scoping review aims to investigate why contactless monitoring, specifically with red-green-blue cameras, is not implemented in mainstream practise. The challenges, drawbacks and limitations of non-contact vital sign monitoring, will be outlined, together with future direction on how it can potentially be implemented in the setting of paediatric anaesthesia, and in the critical care scenario.
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Recent trends in the field of eye-gaze tracking have been shifting towards the estimation of gaze direction in everyday life settings, hence calling for methods that alleviate the constraints typically associated with existing methods,... more
Recent trends in the field of eye-gaze tracking have been shifting towards the estimation of gaze direction in everyday life settings, hence calling for methods that alleviate the constraints typically associated with existing methods, which limit their applicability in less controlled conditions. In this paper, we propose a method for eye-gaze estimation as a function of both eye and head pose components, without requiring prolonged user-cooperation prior to gaze estimation. Our method exploits the trajectories of salient feature trackers spread randomly over the face region for the estimation of the head rotation angles, which are subsequently used to drive a spherical eye-in-head rotation model that compensates for the changes in eye region appearance under head rotation. We investigate the validity of the proposed method on a publicly available data set.
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Besides the traditional regression model-based techniques to estimate the gaze angles (GAs) from electrooculography (EOG) signals, more recent works have investigated the use of a battery model for GA estimation. This is a white-box,... more
Besides the traditional regression model-based techniques to estimate the gaze angles (GAs) from electrooculography (EOG) signals, more recent works have investigated the use of a battery model for GA estimation. This is a white-box, explicit and physically-driven model which relates the monopolar EOG potential to the electrode-cornea and electrode-retina distances. In this work, this model is augmented to cater for the blink-induced EOG signal characteristics, by modelling the eyelid-induced shunting effect during blinks. Specifically, a channel-dependent parameter representing the extent to which the amount of eyelid opening affects the particular EOG channel is introduced. A method to estimate these parameters is also proposed and the proposed model is validated by incorporating it in a Kalman filter to estimate the eyelid opening during blinks. The results obtained have demonstrated that the proposed model can accurately represent the blink-related eyelid-induced shunting.
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In this paper we propose a biometric recognition system based on steady-state visual evoked potentials (SSVEPs), exploiting brain signals elicited by repetitive stimuli having a constant frequency as identifiers. EEG responses to SSVEP... more
In this paper we propose a biometric recognition system based on steady-state visual evoked potentials (SSVEPs), exploiting brain signals elicited by repetitive stimuli having a constant frequency as identifiers. EEG responses to SSVEP stimuli flickering at different frequencies are recorded, and both mel-frequency cepstral coefficients (MFCCs) and autoregressive (AR) reflection coefficients are used as discriminative features of the enrolled users. An analysis of the permanence across time of the brain response to SSVEP stimuli is also performed, by exploiting EEG data acquired in sessions disjoint in time. The employed database is composed by EEG recordings taken from 25 healthy subjects during two different sessions with 15 day average distance between them. The results show that good recognition performance and a high level of permanence can be reached exploiting the proposed method.
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The heart rate is a fundamental measure which can be used to monitor an individual’s level of health or fitness, as well as a range of medical conditions.Conventional heart rate devices used in hospitals require continuous contact with... more
The heart rate is a fundamental measure which can be used to monitor an individual’s level of health or fitness, as well as a range of medical conditions.Conventional heart rate devices used in hospitals require continuous contact with specific points on the patient’s body, depending on the device being used. Such continuous contact could prove to be a risk for skin irritation or infections and may also be of inconvenience to the patients, potentially restricting movement. A contactless approach for measuring heart rate could thus prove significant benefits over conventional, contact-based devices.This paper presents a method for the contactless extraction of heart rate measurements from a video footage using principal component analysis, with no pre-defined region of interest being required. Three different ways of presenting the outcome from principal component analysis are presented and the results obtained are discussed.
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Digital copies of musical scores may be saved on tablet devices, compressing volumes of scores into a single portable device. Tablet screens are however typically smaller than printed sheet music such that the score needs to be resized... more
Digital copies of musical scores may be saved on tablet devices, compressing volumes of scores into a single portable device. Tablet screens are however typically smaller than printed sheet music such that the score needs to be resized for readability. This necessitates additional page turning which is made more complex when repeat instructions are used since these give rise to forward and backward page turns of the music. In this paper, we tackle this problem by first performing image analysis of the score in order to identify repeat instructions and hence flatten the score. Thus, the music player is presented the score as it should be played. We then propose the use of eye-gaze tracking to provide a hands-free page turning mechanism. Thus, the player remains in full control of when the page turn occurs. Through a preliminary study, we found that our proposed score flattening and eye-gaze page turning reduced the time spent navigating the page turns by 47% in comparison to available music score reading tools.
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Research Interests: Thermography and Medicine
The reference signal in EEG recordings can affect features such as signal energy, phase synchrony and coherence, acquired from the EEG data [1–3]. In this study we investigate the influence of referencing methods on the performance of... more
The reference signal in EEG recordings can affect features such as signal energy, phase synchrony and coherence, acquired from the EEG data [1–3]. In this study we investigate the influence of referencing methods on the performance of task discrimination techniques used in BCIs. Together with more commonly used referencing methods we also consider the reference electrode standardization technique developed by Yao [4]. We perform tests on simulated as well as real EEG data. In particular, we use band power estimates, the method of common spatial patterns, and the phase-locking value, to determine the influence of the various referencing possibilities on classification rates for the discrimination of motor imagery tasks. The results obtained suggest that the phase synchronization measure is more sensitive to the choice of reference when compared to the band power estimates and the method of CSP. For the phase synchronization measure, references that attempt to reproduce a zero reference scalp voltage give the best performance.
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Abstract Objective Electrooculography (EOG) is an eye movement recording technique based on the electrical activity due to the eyes, which may be used to develop human computer interfaces. The EOG signal baseline is subject to drifting... more
Abstract Objective Electrooculography (EOG) is an eye movement recording technique based on the electrical activity due to the eyes, which may be used to develop human computer interfaces. The EOG signal baseline is subject to drifting and, although several baseline drift mitigation techniques have been proposed in the literature, the specific technique and the corresponding parameters are generally arbitrarily chosen. Furthermore, the literature does not establish which is the most suitable technique. Hence, this work aims to review these different techniques, and qualitatively and quantitatively compare their performance in mitigating the baseline drift using the same EOG data. This dataset is also being made publicly available to serve as a benchmark for future work. Methods The state-of-the-art baseline drift mitigation techniques, namely, frequent DC reference resetting, signal differencing, high-pass filtering, wavelet decomposition and polynomial fitting, were implemented and statistically compared. Results Generally, frequent resetting and signal differencing were statistically significantly better than the other techniques. Furthermore, high-pass filtering and wavelet decomposition had statistically similar performance, while the polynomial fitting technique was never superior to the other techniques. Conclusions While frequent resetting and signal differencing gave the best performance, the former disrupts the user's interaction with the system whereas the latter undesirably changes the EOG signal morphology. From the remaining techniques, high-pass filtering and wavelet decomposition would be the most suitable, but only the former would be applicable to real-time applications. Significance This work compares five state-of-the-art EOG baseline drift mitigation techniques and provides a guideline for future work.
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Research Interests: Computer Science, Human Computer Interaction, CAD, Ambiguity, Qa, and 3 moreTS, Sketch, and Sketch Recognition
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... AND BRIAN J. REARDON PART THREE: PROTOTYPE KIC SYSTEMS 113 Knowledge Intensive'Paper-based'Form Sketching 115 PHILIP J. FARRUGIA, JONATHAN C. BORG, KENNETH P. CAMILLERI, DAWN SCICLUNA, Xiu T. YAN, AND JOSEPH MUSCAT... more
... AND BRIAN J. REARDON PART THREE: PROTOTYPE KIC SYSTEMS 113 Knowledge Intensive'Paper-based'Form Sketching 115 PHILIP J. FARRUGIA, JONATHAN C. BORG, KENNETH P. CAMILLERI, DAWN SCICLUNA, Xiu T. YAN, AND JOSEPH MUSCAT Design ...
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Summarization: EEG analysis is widely used for clinical investigations of several neurological disorders. As EEG signal is normally a low amplitude (microvolts) signal and recording is multichannel, with epochs lasting from several... more
Summarization: EEG analysis is widely used for clinical investigations of several neurological disorders. As EEG signal is normally a low amplitude (microvolts) signal and recording is multichannel, with epochs lasting from several minutes to hours depending on the test focus, difficulties can arise due to artefacts contaminating the data and also due to the presence of various events in the signal that could occur frequently. This is why, in order to improve the accuracy of clinical conclusions based on EEG analysis, it is important to provide the scientific research and then the clinical routine with EEG prepocessing methods aiming to remove major artefacts, perform suitable segmentation of EEG for further analysis and for accurate characterisation of events detected in segmented epochs such as the epileptic seizure event reducing the uncertainty in clinical analysis. Here we describe several methods for that goal.Presented on
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The electrooculography (EOG) signal baseline is subject to drifting, and several different techniques to mitigate this drift have been proposed in the literature. Some of these techniques, however, disrupt the overall ocular pose-induced... more
The electrooculography (EOG) signal baseline is subject to drifting, and several different techniques to mitigate this drift have been proposed in the literature. Some of these techniques, however, disrupt the overall ocular pose-induced DC characteristics of the EOG signal and may also require the data to be zero-centred, which means that the average point of gaze (POG) has to lie at the primary gaze position. In this work, we propose an alternative baseline drift mitigation technique which may be used to de-drift EOG data collected through protocols where the subject gazes at known targets. Specifically, it uses the target gaze angles (GAs) in a battery model of the eye to estimate the ocular pose-induced component, which is then used for baseline drift estimation. This method retains the overall signal morphology and may be applied to non-zero-centred data. The performance of the proposed baseline drift mitigation technique is compared to that of five other techniques which are commonly used in the literature, with results showing the general superior performance of the proposed technique.
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To date the use of thermography in the context of obstetrics has been primarily limited to the acquisition and analysis of static thermal images. In contrast, dynamic thermography involves the acquisition of a sequence of thermal images,... more
To date the use of thermography in the context of obstetrics has been primarily limited to the acquisition and analysis of static thermal images. In contrast, dynamic thermography involves the acquisition of a sequence of thermal images, taking into account temporal variations that would otherise be overlooked. However, dynamic recordings of regions of interest in human participants are likely to be affected by unavoidable participant movement due to breathing and other involuntary movements. In this work, a triangulation-based video registration technique using local affine transformations is proposed to register the abdominal region in dynamic thermal sequences. The proposed method is tested on one hour recordings of thermal data obtained from 10 pregnant and 10 non-pregnant female participants. The results obtained show that the proposed approach can compensate for movements and significantly improve region alignment throughout the thermal image sequence, thereby facilitating subsequent analysis of spatiotemporal temperature data in the considered image sequence.
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The development of electrooculography (EOG)-based human-computer interface systems is generally based on the processing of the commonly referred to horizontal and vertical bipolar EOG channels, which are computed from a... more
The development of electrooculography (EOG)-based human-computer interface systems is generally based on the processing of the commonly referred to horizontal and vertical bipolar EOG channels, which are computed from a horizontally-aligned and another vertically-aligned pair of electrodes, respectively. Horizontal (vertical) target displacements are assumed to result in changes in the horizontal (vertical) EOG channel only, and any cross-talk between the bipolar channels is often neglected or incorrectly attributed solely to electrode misalignment with respect to the ocular rotation axes. Objective. The aim of this work is to demonstrate that such cross-talk is intrinsic to the geometric relationship between the orientation of the verging ocular globes and the planar displacement of the gaze target with respect to the primary gaze position. Approach. Since it is difficult to record actual EOG data with electrodes which are perfectly-aligned with the ocular rotation axes, this is st...
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In this work, a novel method to estimate the ocular pose from electrooculography (EOG) signals is proposed. This method is based on an electrical battery model of the eye which relates the EOG potential to the distances between an... more
In this work, a novel method to estimate the ocular pose from electrooculography (EOG) signals is proposed. This method is based on an electrical battery model of the eye which relates the EOG potential to the distances between an electrode and the left/right cornea and retina centre points. In this work, this model is used to estimate the ocular angles (OAs), that is the orientation of the two ocular globes separately. Using this approach, an average cross-validated horizontal and vertical OA estimation error of 2.91 ± 0.86° and 2.42 ± 0.58° respectively was obtained. Furthermore, we show how these OA estimates may be used to estimate the gaze angles (GAs) without requiring the distance between the subject’s face-plane and the target-plane, as in previous work. Using the proposed method, a cross-validated horizontal and vertical GA estimation error of 2.13 ± 0.73° and 2.42 ± 0.58° respectively was obtained, which compares well with the previous distance-based GA estimation technique.
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The segmentation of media-adventitia and lumen-intima boundaries of the Carotid Artery forms an essential part in assessing plaque morphology in Ultrasound Imaging. Manual methods are tedious and prone to variability and thus, developing... more
The segmentation of media-adventitia and lumen-intima boundaries of the Carotid Artery forms an essential part in assessing plaque morphology in Ultrasound Imaging. Manual methods are tedious and prone to variability and thus, developing automated segmentation algorithms is preferable. In this paper, we propose to use deep convolutional networks for automated segmentation of the media-adventitia boundary in transverse and longitudinal sections of carotid ultrasound images. Deep networks have recently been employed with good success on image segmentation tasks, and we thus propose their application on ultrasound data, using an encoder-decoder convolutional structure which allows the network to be trained end-to-end for pixel-wise classification. Concurrently, we evaluate the performance for various configurations, depths and filter sizes within the network. In addition, we further propose a novel fusion of envelope and phase congruency data as an input to the network, as the latter provides an intensity-invariant data source to the network. We show that this data fusion and the proposed network structure yields higher segmentation performance than the state-of-the-art techniques.
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In this work, a novel method to estimate the gaze angles using electrooculographic (EOG) signals is presented. Specifically, this work investigates the use of a battery model of the eye, which relates the recorded EOG potential with the... more
In this work, a novel method to estimate the gaze angles using electrooculographic (EOG) signals is presented. Specifically, this work investigates the use of a battery model of the eye, which relates the recorded EOG potential with the distances between the corresponding electrode and the centre points of the cornea and retina, for gaze angle estimation. Using this method a cross-validated horizontal and vertical gaze angle error of 2.42±0.91° and 2.30±0.50° respectively was obtained across six subjects, demonstrating that the proposed methods and the battery model may be used to estimate the user’s ocular pose reliably.
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The use of foot mounted inertial and other auxiliary sensors for kinematic gait analysis has been extensively investigated during the last years. Although, these sensors still yield less accurate results than those obtained employing... more
The use of foot mounted inertial and other auxiliary sensors for kinematic gait analysis has been extensively investigated during the last years. Although, these sensors still yield less accurate results than those obtained employing optical motion capture systems, the miniaturization and their low cost have allowed the estimation of kinematic spatiotemporal parameters in laboratory conditions and real life scenarios. The aim of this work was to present a comprehensive approach of this scientific area through a systematic literature research, breaking down the state-of-the-art methods into three main parts: (1) zero velocity interval detection techniques; (2) assumptions and sensors’ utilization; (3) foot pose and trajectory estimation methods. Published articles from 1995 until December of 2018 were searched in the PubMed, IEEE Xplore and Google Scholar databases. The research was focused on two categories: (a) zero velocity interval detection methods; and (b) foot pose and traject...
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Sketching is a natural and intuitive communication tool used for expressing concepts or ideas which are difficult to communicate through text or speech alone. Sketching is therefore used for a variety of purposes, from the expression of... more
Sketching is a natural and intuitive communication tool used for expressing concepts or ideas which are difficult to communicate through text or speech alone. Sketching is therefore used for a variety of purposes, from the expression of ideas on two-dimensional (2D) physical media, to object creation, manipulation, or deformation in three-dimensional (3D) immersive environments. This variety in sketching activities brings about a range of technologies which, while having similar scope, namely that of recording and interpreting the sketch gesture to effect some interaction, adopt different interpretation approaches according to the environment in which the sketch is drawn. In fields such as product design, sketches are drawn at various stages of the design process, and therefore, designers would benefit from sketch interpretation technologies which support these differing interactions. However, research typically focuses on one aspect of sketch interpretation and modeling such that l...
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This work develops a method for automatically extracting temperature data from prespecified anatomical regions of interest from thermal images of human hands, feet, and shins for the monitoring of peripheral arterial disease in diabetic... more
This work develops a method for automatically extracting temperature data from prespecified anatomical regions of interest from thermal images of human hands, feet, and shins for the monitoring of peripheral arterial disease in diabetic patients. Binarisation, morphological operations, and geometric transformations are applied in cascade to automatically extract the required data from 44 predefined regions of interest. The implemented algorithms for region extraction were tested on data from 395 participants. A correct extraction in around 90% of the images was achieved. The process of automatically extracting 44 regions of interest was performed in a total computation time of approximately 1 minute, a substantial improvement over 10 minutes it took for a corresponding manual extraction of the regions by a trained individual. Interrater reliability tests showed that the automatically extracted ROIs are similar to those extracted by humans with minimal temperature difference. This se...
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To evaluate the potential of thermography as an assessment tool for the detection of foot complications by understanding the variations in temperature that occur in type 2 diabetes mellitus (DM). Participants were categorized according to... more
To evaluate the potential of thermography as an assessment tool for the detection of foot complications by understanding the variations in temperature that occur in type 2 diabetes mellitus (DM). Participants were categorized according to a medical examination, ankle brachial index, doppler waveform analysis, and 10-gram monofilament testing into five groups: healthy adult, DM with no complications, DM with peripheral neuropathy, DM with neuroischaemia, and DM with peripheral arterial disease (PAD) groups. Thermographic imaging of the toes and forefeet was performed. 43 neuroischaemic feet, 41 neuropathic feet, 58 PAD feet, 21 DM feet without complications, and 126 healthy feet were analyzed. The temperatures of the feet and toes were significantly higher in the complications group when compared to the healthy adult and DM healthy groups. The higher the temperatures of the foot in DM, the higher the probability that it is affected by neuropathy, neuroischaemia, or PAD. Significant d...
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Brain-computer interface (BCI) systems have emerged as an augmentative technology that can provide a promising solution for individuals with motor dysfunctions and for the elderly who are experiencing muscle weakness. Steady-state... more
Brain-computer interface (BCI) systems have emerged as an augmentative technology that can provide a promising solution for individuals with motor dysfunctions and for the elderly who are experiencing muscle weakness. Steady-state visually evoked potentials (SSVEPs) are widely adopted in BCI systems due to their high speed and accuracy when compared to other BCI paradigms. In this paper, we apply combined magnitude and phase features for class discrimination in a real-time SSVEP-based BCI platform. In the proposed real-time system users gain control of a motorised bed system with seven motion commands and an idle state. Experimental results amongst eight participants demonstrate that the proposed real-time BCI system can successfully discriminate between different SSVEP signals achieving high information transfer rates (ITR) of 82.73 bits/min. The attractive features of the proposed system include noninvasive recording, simple electrode configuration, excellent BCI response and mini...
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The use of brain signals for person recognition has in recent years attracted considerable interest because of the increased security and privacy these can offer when compared to conventional biometric measures. The main challenge lies in... more
The use of brain signals for person recognition has in recent years attracted considerable interest because of the increased security and privacy these can offer when compared to conventional biometric measures. The main challenge lies in extracting features from the EEG signals that are sufficiently distinct across individuals while also being sufficiently consistent across multiple recording sessions. A range of EEG phenomena including eyes open and eyes closed activity, visual evoked potentials (VEPs) through image presentation, and other mental tasks have been studied for their use in biometry.
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This work focusses on reducing the training time required for a brain–computer interface (BCI) music player based on steady-state visually evoked potentials (SSVEPs). The music player is menu driven, featuring three different interfaces... more
This work focusses on reducing the training time required for a brain–computer interface (BCI) music player based on steady-state visually evoked potentials (SSVEPs). The music player is menu driven, featuring three different interfaces with up to six continuously flickering stimuli, similar to typical smart phone applications. This work investigates whether it is possible to go from a menu driven training approach to one which uses a single stimuli session only for training, or one which uses solely the data collected from the menu with the largest number of stimuli. Results show that the latter reduces the training time by 38.90%, specifically from 21 to 12.83 min without significant degradation in classification performance. Furthermore, promising results were also revealed when using a subject independent classifier which avoids individual training for new subjects by using training data from a database of other subjects. Although this work was targeted towards the brain controlled music player, the results are applicable to any SSVEP based BCI system having multiple interfaces with different number of flickering stimuli.