Improving the SNR of EEG generated by deep sources with weighted multielectrode leads

Väisänen, Outi; Malmivuo, Jaakko

doi:10.1016/j.jphysparis.2009.07.003

Cited by 16 publications

(11 citation statements)

References 19 publications

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“…As already noted, contemporary EEG systems typically acquire a single signal stream per site and are configured in a manner that virtually precludes the simultaneous acquisition of multiple signal streams per site. Furthermore, since the tangential separation of the electrodes in the configurations presented in this paper is much smaller than 10.0 mm, tangential contributions should be substantially identical [36][37][38][39][40][41] with a correlation coefficient of 1.0. However, as illustrated by the results presented, distinct signal streams can indeed be obtained from sensors placed at the same site on the surface representing the source of the bio-signals.…”

Section: Discussionmentioning

confidence: 97%

“…Frank Edughom Ekpar on the movement of the subject (allowing longer duration recordings) and has good temporal resolution -in the order of 1 millisecond -but is hampered by low spatial resolution. The optimum electrode distance for the EEG seems to be between 10.0 mm and 50.0 mm on the basis of estimated variable brain-skull-scalp resistivity ratios and the use of the reciprocity theorem, superposition principle, lead field theorem and theoretical spatial frequency (spatial Nyquist) considerations [36][37][38][39][40][41]. Attempts to localize the sources of the EEG signals (or to solve the forward and inverse problems) typically employ large numbers of electrodes (in the order of 100 electrodes) and provide only crude estimates [42][43][44].…”

Section: Introductionmentioning

confidence: 99%

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System for Nature-inspired Signal Processing: Principles and Practice

Ekpar

2019

EJECE

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This paper establishes the foundational principles and practice for a unified theory of arbitrary information management by disclosing systems, devices and methods for the management of substrates or biological substrates. In this context, a substrate is any aspect of any entity that is capable of responding to or emitting stimuli irrespective of whether the stimuli actually emanate from any aspect of the entity or not. Management of substrates could be achieved through the management of stimuli that modulate or moderate or influence any aspect of the substrate as well as through the management of any stimuli emanating from the substrate. The results enable a wide range of novel applications in a variety of fields with far-reaching implications. For example, the functional organization of many regions of the brain including the superior temporal cortex which is believed to play a critical role in the hierarchical processing of human visual and auditory stimuli is poorly understood. It is not known precisely which layer within which region of the brain is responsible for which aspect of visual or auditory processing. Simultaneous non-invasive acquisition of bio-signals representing contributions from multiple layers of neuronal populations within the brain could provide new insights leading to the resolution of many of these outstanding issues and provide a deeper understanding of the underlying physiological processes.

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Section: Discussionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

System for Nature-inspired Signal Processing: Principles and Practice

Ekpar

2019

EJECE

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“…One of the concerns in the EEG measurements is the high signal to noise ratio (SNR) to ensure the signal quality, and it could be achieved by ensemble mean via repetitions ( Väisänen and Malmivuo, 2009 ). In this study, we preferred EEG power spectra to investigate the cortical responses to NPCS, since it requires less repetition or signal length than the measurement of intact waveform of SSEP in the time domain.…”

Section: Discussionmentioning

confidence: 99%

Electroencephalographic Measurement on Post-stroke Sensory Deficiency in Response to Non-painful Cold Stimulation

Huang

Jiao

et al. 2022

Front. Aging Neurosci.

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BackgroundReduced elementary somatosensation is common after stroke. However, the measurement of elementary sensation is frequently overlooked in traditional clinical assessments, and has not been evaluated objectively at the cortical level. This study designed a new configuration for the measurement of post-stroke elementary thermal sensation by non-painful cold stimulation (NPCS). The post-stroke cortical responses were then investigated during elementary NPCS on sensory deficiency via electroencephalography (EEG) when compared with unimpaired persons.MethodTwelve individuals with chronic stroke and fifteen unimpaired controls were recruited. A 64-channel EEG system was used to investigate the post-stroke cortical responses objectively during the NPCS. A subjective questionnaire of cold sensory intensity was also administered via a numeric visual analog scale (VAS). Three water samples with different temperatures (i.e., 25, 10, and 0°C) were applied to the skin surface of the ventral forearm for 3 s via glass beaker, with a randomized sequence on either the left or right forearm of a participant. EEG relative spectral power (RSP) and topography were used to evaluate the neural responses toward NPCS with respect to the independent factors of stimulation side and temperature.ResultsFor unimpaired controls, NPCS initiated significant RSP variations, mainly located in the theta band with the highest discriminative resolution on the different temperatures (P < 0.001). For stroke participants, the distribution of significant RSP spread across all EEG frequency bands and the temperature discrimination was lower than that observed in unimpaired participants (P < 0.05). EEG topography showed that the NPCS could activate extensive and bilateral sensory cortical areas after stroke. Significant group differences on RSP intensities were obtained in each EEG band (P < 0.05). Meanwhile, significant asymmetry cortical responses in RSP toward different upper limbs were observed during the NPCS in both unimpaired controls and participants with stroke (P < 0.05). No difference was found between the groups in the VAS ratings of the different temperatures (P > 0.05).ConclusionThe post-stroke cortical responses during NPCS on sensory deficiency were characterized by the wide distribution of representative RSP bands, lowered resolution toward different temperatures, and extensive activated sensory cortical areas.

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“…In particular, the possibility of detecting the neural drive from brainstem generated signals is one of the scientific challenges that might be addressed by a convenient arrangement of the EEG sensors [51] and the exploitation of the spectral selectivity attributed to these signals in the high/very high frequency range. Identifying the existence and electrophysiological characteristics of feedback related potentials to be used for the on-line monitoring of the patient ventilator synchrony is a second scientific aspect to be solved in the near future.…”

Section: Discussionmentioning

confidence: 99%

Patient Machine Interface for the Control of Mechanical Ventilation Devices

2013

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The potential of Brain Computer Interfaces (BCIs) to translate brain activity into commands to control external devices during mechanical ventilation (MV) remains largely unexplored. This is surprising since the amount of patients that might benefit from such assistance is considerably larger than the number of patients requiring BCI for motor control. Given the transient nature of MV (i.e., used mainly over night or during acute clinical conditions), precluding the use of invasive methods, and inspired by current research on BCIs, we argue that scalp recorded EEG (electroencephalography) signals can provide a non-invasive direct communication pathway between the brain and the ventilator. In this paper we propose a Patient Ventilator Interface (PVI) to control a ventilator during variable conscious states (i.e., wake, sleep, etc.). After a brief introduction on the neural control of breathing and the clinical conditions requiring the use of MV we discuss the conventional techniques used during MV. The schema of the PVI is presented followed by a description of the neural signals that can be used for the on-line control. To illustrate the full approach, we present data from a healthy subject, where the inspiration and expiration periods during voluntary breathing were discriminated with a 92% accuracy (10-fold cross-validation) from the scalp EEG data. The paper ends with a discussion on the advantages and obstacles that can be forecasted in this novel application of the concept of BCI.

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Improving the SNR of EEG generated by deep sources with weighted multielectrode leads

Cited by 16 publications

References 19 publications

System for Nature-inspired Signal Processing: Principles and Practice

System for Nature-inspired Signal Processing: Principles and Practice

Electroencephalographic Measurement on Post-stroke Sensory Deficiency in Response to Non-painful Cold Stimulation

Patient Machine Interface for the Control of Mechanical Ventilation Devices

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