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Papers by CHRISTOPHER JAMES
IFMBE Proceedings, 2009
ABSTRACT Bipolar disorder (BD) is a mental disorder characterized by recurrent episodes of mania ... more ABSTRACT Bipolar disorder (BD) is a mental disorder characterized by recurrent episodes of mania and depression. The disorder can be very disruptive and relapses often result in hospitalization. With adequate training, sufferers are able to control their symptoms and reduce the disruption to their daily lives. As an aid to this self-control process the Personalized Ambient Monitoring (PAM) project is being developed. The PAM project aims to allow patients with BD to monitor their condition and obtain indications of their mental state. This will be achieved through the use of multiple discreet sensors, personalized for each patient’s needs. The sensors will detect the correlates of mania and depression, which will be used to derive trends in the mental health state of the patient. The major symptoms of BD center on the patient’s activity level and circadian rhythm. Manic episodes are typified by increased energy and activity, often with a decreased need for sleep. Depressive episodes however often present with diminished activity. It is our aim that by measuring the patient’s activity levels and circadian rhythm we can provide information that the patient can use to help control their symptoms. Here we present some preliminary work aimed at distinguishing different activities and activity levels in normal controls, based on a small, body-mounted triaxial accelerometer. A number of participants were asked to complete some basic activities whilst wearing the accelerometer. The data was preprocessed to extract a number of salient features, which were used to train a Neuroscale algorithm. Neuroscale produces a generative mapping that visualizes high-dimensional data in a lower-dimensional space, which, with the addition of a clustering algorithm, can be used to classify unknown data points. It is expected that this approach, combined with data from other sensor types will form the backbone of the PAM approach applied to BD.
Yeast, 1995
... stability, recombi-nation (Leem and Ogawa, 1992), centromere func-tion, meiotic gene expressi... more ... stability, recombi-nation (Leem and Ogawa, 1992), centromere func-tion, meiotic gene expression (Neigeborn and Mitchell, 1991; Shero and Hieter ... ORF G1880 shares with all of these proteins, sequences similar to the seven conserved motifs found in two super-families of ...
Lecture Notes in Computer Science, 2004
Page 1. CG Puntonet and A. Prieto (Eds.): ICA 2004, LNCS 3195, pp. 10251032, 2004. © Springer-Ve... more Page 1. CG Puntonet and A. Prieto (Eds.): ICA 2004, LNCS 3195, pp. 10251032, 2004. © Springer-Verlag Berlin Heidelberg 2004 A Comparison of Time Structure and Statistically Based BSS Methods in the Context of Long-Term Epileptiform EEG Recordings ...
Journal of Psychophysiology, Mar 2, 2015
Background: The default mode interference hypothesis (Sonuga-Barke &a... more Background: The default mode interference hypothesis (Sonuga-Barke & Castellanos, 2007) predicts (1) the attenuation of very low frequency oscillations (VLFO; e.g., .05 Hz) in brain activity within the default mode network during the transition from rest to task, and (2) that failures to attenuate in this way will lead to an increased likelihood of periodic attention lapses that are synchronized
Conference Proceedings Annual International Conference of the Ieee Engineering in Medicine and Biology Society Ieee Engineering in Medicine and Biology Society Conference, Feb 1, 2007
The goal of this work is to discover and extract critical features from pressure signals in the a... more The goal of this work is to discover and extract critical features from pressure signals in the aural canal resulting from actions (tongue movements) within the oral cavity. Its scope encompasses the identification of critical features of pressure signals sensed in the ear resulting from tongue motion and the development of algorithms and methodologies to extract features from sets of these signals. We report successfully isolating 15 components associated with four different tongue motions and clustering them into 3 groups based on similarity in characteristics. The components are consistently extracted with every repetition, irrespective of the start of the tongue movement, thus providing a venue of correlating the signal to the action without dependency on complicated algorithms identifying the start and endpoints of the signal. To our knowledge, this work is the first ever analysis of components of pressure signals in the ear canal associated with tongue movement. In future work, these findings are expected to lead to an entirely new generation of unobtrusive human-machine interface mechanisms.
Conference Proceedings Annual International Conference of the Ieee Engineering in Medicine and Biology Society Ieee Engineering in Medicine and Biology Society Conference, 2009
Detecting artifacts produced in electroencephalographic (EEG) data by muscle activity, eye blinks... more Detecting artifacts produced in electroencephalographic (EEG) data by muscle activity, eye blinks and electrical noise, etc., is an important problem in EEG signal processing research. These artifacts must be corrected before further analysis because it renders subsequent analysis very error-prone. One solution is to reject the data segment if artifact is present during the observation interval, however, the rejected data
Abstract To make commercially acceptable condensed phase hydrogen storage systems, it is importan... more Abstract To make commercially acceptable condensed phase hydrogen storage systems, it is important to understand quantitatively the risks involved in using these materials. A rigorous set of environmental reactivity tests have been developed based on modified ...
2008 Computers in Cardiology, Sep 1, 2008
Aspects of Educational and Training Technology Series, 1992
Audiology and Neurotology, 2009
To compare performance on a song recognition task of bilaterally combined electric and acoustic h... more To compare performance on a song recognition task of bilaterally combined electric and acoustic hearing (bimodal stimulation) with electric or acoustic hearing alone. Subjects were 14 adults with cochlear implants (CI) who continued to use a hearing aid (HA) in one/both ears. Subjects were asked to identify excerpts from 15 popular songs, which were familiar to them, presented in a random order via a single loudspeaker. Presentation conditions were fixed in order: bimodal, CI alone and then HA alone. Musical excerpts were presented in each condition with and then without lyrics. In a subgroup of subjects (n = 8) with better low-frequency residual hearing (thresholds <85 dB hearing level (HL)), mean scores for bimodal stimulation were significantly greater than for CI alone. In addition, mean 'no lyrics' scores for HA alone (59.7%) were significantly greater than for CI alone (38.8%). All of these subjects considered bimodal stimulation to be the most enjoyable way to listen to music. For the remaining subjects (n = 6) there was no benefit from using bimodal stimulation over CI alone, and the majority of these preferred to listen to music using CI alone. Bimodal stimulation provides better perception of popular music, particularly melody recognition, compared to CI alone when low-frequency residual hearing is better than 85 dB HL.
ABSTRACT ICA is a technique for the extraction of statistically independent components from a set... more ABSTRACT ICA is a technique for the extraction of statistically independent components from a set of measured signals. This technique enjoys numerous applications in biomedical signal analysis in the literature, especially in the analysis of electromagnetic (EM) brain signals (measured via the EEG and MEG). Standard implementations of ICA are limiting mainly due to the assumptions of equal numbers of sources and measured signals inherent with methods that assume square mixing. For EM brain signal recordings which have large numbers of channels (e.g. MEG), the large number of resulting extracted sources makes the subsequent analysis laborious and highly subjective. However, there are many instances in neurophysiological analysis where there is strong a priori information about the signals being sought, such signals generally include artifacts, as well as specific rhythms or even seizure or spike waveforms in the ictal and interictal EEG. Constrained ICA, as introduced by Lu and Rajapakse (1), consists of a variation of standard ICA that can extract signals that are statistically independent, yet which are constrained to be similar to some reference signal – the measure of similarity could be, for example, mean-squared error, correlation, or any other suitable a priori information that can be included. The algorithm is fast and suitable for online analysis and here we demonstrate this method on a number of artifactual and clinically significant waveforms identified in recordings of EEG and MEG, where constrained ICA was applied to each in turn using a crude reference waveform derived from the raw recordings in each case. The algorithm repeatedly converged to the desired component within a few iterations and subjective analysis indicated waveforms of the expected morphologies and with realistic spatial distributions. Here we show that constrained ICA can be applied with great success to EM brain signal analysis, automating artifact extraction in MEG and EEG, as well as on seizure extraction in the EEG.
Ieee Transactions on Bio Medical Engineering, Jul 2, 2010
IFMBE Proceedings, 2009
ABSTRACT Bipolar disorder (BD) is a mental disorder characterized by recurrent episodes of mania ... more ABSTRACT Bipolar disorder (BD) is a mental disorder characterized by recurrent episodes of mania and depression. The disorder can be very disruptive and relapses often result in hospitalization. With adequate training, sufferers are able to control their symptoms and reduce the disruption to their daily lives. As an aid to this self-control process the Personalized Ambient Monitoring (PAM) project is being developed. The PAM project aims to allow patients with BD to monitor their condition and obtain indications of their mental state. This will be achieved through the use of multiple discreet sensors, personalized for each patient’s needs. The sensors will detect the correlates of mania and depression, which will be used to derive trends in the mental health state of the patient. The major symptoms of BD center on the patient’s activity level and circadian rhythm. Manic episodes are typified by increased energy and activity, often with a decreased need for sleep. Depressive episodes however often present with diminished activity. It is our aim that by measuring the patient’s activity levels and circadian rhythm we can provide information that the patient can use to help control their symptoms. Here we present some preliminary work aimed at distinguishing different activities and activity levels in normal controls, based on a small, body-mounted triaxial accelerometer. A number of participants were asked to complete some basic activities whilst wearing the accelerometer. The data was preprocessed to extract a number of salient features, which were used to train a Neuroscale algorithm. Neuroscale produces a generative mapping that visualizes high-dimensional data in a lower-dimensional space, which, with the addition of a clustering algorithm, can be used to classify unknown data points. It is expected that this approach, combined with data from other sensor types will form the backbone of the PAM approach applied to BD.
Yeast, 1995
... stability, recombi-nation (Leem and Ogawa, 1992), centromere func-tion, meiotic gene expressi... more ... stability, recombi-nation (Leem and Ogawa, 1992), centromere func-tion, meiotic gene expression (Neigeborn and Mitchell, 1991; Shero and Hieter ... ORF G1880 shares with all of these proteins, sequences similar to the seven conserved motifs found in two super-families of ...
Lecture Notes in Computer Science, 2004
Page 1. CG Puntonet and A. Prieto (Eds.): ICA 2004, LNCS 3195, pp. 10251032, 2004. © Springer-Ve... more Page 1. CG Puntonet and A. Prieto (Eds.): ICA 2004, LNCS 3195, pp. 10251032, 2004. © Springer-Verlag Berlin Heidelberg 2004 A Comparison of Time Structure and Statistically Based BSS Methods in the Context of Long-Term Epileptiform EEG Recordings ...
Journal of Psychophysiology, Mar 2, 2015
Background: The default mode interference hypothesis (Sonuga-Barke &a... more Background: The default mode interference hypothesis (Sonuga-Barke & Castellanos, 2007) predicts (1) the attenuation of very low frequency oscillations (VLFO; e.g., .05 Hz) in brain activity within the default mode network during the transition from rest to task, and (2) that failures to attenuate in this way will lead to an increased likelihood of periodic attention lapses that are synchronized
Conference Proceedings Annual International Conference of the Ieee Engineering in Medicine and Biology Society Ieee Engineering in Medicine and Biology Society Conference, Feb 1, 2007
The goal of this work is to discover and extract critical features from pressure signals in the a... more The goal of this work is to discover and extract critical features from pressure signals in the aural canal resulting from actions (tongue movements) within the oral cavity. Its scope encompasses the identification of critical features of pressure signals sensed in the ear resulting from tongue motion and the development of algorithms and methodologies to extract features from sets of these signals. We report successfully isolating 15 components associated with four different tongue motions and clustering them into 3 groups based on similarity in characteristics. The components are consistently extracted with every repetition, irrespective of the start of the tongue movement, thus providing a venue of correlating the signal to the action without dependency on complicated algorithms identifying the start and endpoints of the signal. To our knowledge, this work is the first ever analysis of components of pressure signals in the ear canal associated with tongue movement. In future work, these findings are expected to lead to an entirely new generation of unobtrusive human-machine interface mechanisms.
Conference Proceedings Annual International Conference of the Ieee Engineering in Medicine and Biology Society Ieee Engineering in Medicine and Biology Society Conference, 2009
Detecting artifacts produced in electroencephalographic (EEG) data by muscle activity, eye blinks... more Detecting artifacts produced in electroencephalographic (EEG) data by muscle activity, eye blinks and electrical noise, etc., is an important problem in EEG signal processing research. These artifacts must be corrected before further analysis because it renders subsequent analysis very error-prone. One solution is to reject the data segment if artifact is present during the observation interval, however, the rejected data
Abstract To make commercially acceptable condensed phase hydrogen storage systems, it is importan... more Abstract To make commercially acceptable condensed phase hydrogen storage systems, it is important to understand quantitatively the risks involved in using these materials. A rigorous set of environmental reactivity tests have been developed based on modified ...
2008 Computers in Cardiology, Sep 1, 2008
Aspects of Educational and Training Technology Series, 1992
Audiology and Neurotology, 2009
To compare performance on a song recognition task of bilaterally combined electric and acoustic h... more To compare performance on a song recognition task of bilaterally combined electric and acoustic hearing (bimodal stimulation) with electric or acoustic hearing alone. Subjects were 14 adults with cochlear implants (CI) who continued to use a hearing aid (HA) in one/both ears. Subjects were asked to identify excerpts from 15 popular songs, which were familiar to them, presented in a random order via a single loudspeaker. Presentation conditions were fixed in order: bimodal, CI alone and then HA alone. Musical excerpts were presented in each condition with and then without lyrics. In a subgroup of subjects (n = 8) with better low-frequency residual hearing (thresholds <85 dB hearing level (HL)), mean scores for bimodal stimulation were significantly greater than for CI alone. In addition, mean 'no lyrics' scores for HA alone (59.7%) were significantly greater than for CI alone (38.8%). All of these subjects considered bimodal stimulation to be the most enjoyable way to listen to music. For the remaining subjects (n = 6) there was no benefit from using bimodal stimulation over CI alone, and the majority of these preferred to listen to music using CI alone. Bimodal stimulation provides better perception of popular music, particularly melody recognition, compared to CI alone when low-frequency residual hearing is better than 85 dB HL.
ABSTRACT ICA is a technique for the extraction of statistically independent components from a set... more ABSTRACT ICA is a technique for the extraction of statistically independent components from a set of measured signals. This technique enjoys numerous applications in biomedical signal analysis in the literature, especially in the analysis of electromagnetic (EM) brain signals (measured via the EEG and MEG). Standard implementations of ICA are limiting mainly due to the assumptions of equal numbers of sources and measured signals inherent with methods that assume square mixing. For EM brain signal recordings which have large numbers of channels (e.g. MEG), the large number of resulting extracted sources makes the subsequent analysis laborious and highly subjective. However, there are many instances in neurophysiological analysis where there is strong a priori information about the signals being sought, such signals generally include artifacts, as well as specific rhythms or even seizure or spike waveforms in the ictal and interictal EEG. Constrained ICA, as introduced by Lu and Rajapakse (1), consists of a variation of standard ICA that can extract signals that are statistically independent, yet which are constrained to be similar to some reference signal – the measure of similarity could be, for example, mean-squared error, correlation, or any other suitable a priori information that can be included. The algorithm is fast and suitable for online analysis and here we demonstrate this method on a number of artifactual and clinically significant waveforms identified in recordings of EEG and MEG, where constrained ICA was applied to each in turn using a crude reference waveform derived from the raw recordings in each case. The algorithm repeatedly converged to the desired component within a few iterations and subjective analysis indicated waveforms of the expected morphologies and with realistic spatial distributions. Here we show that constrained ICA can be applied with great success to EM brain signal analysis, automating artifact extraction in MEG and EEG, as well as on seizure extraction in the EEG.
Ieee Transactions on Bio Medical Engineering, Jul 2, 2010