The Experts below are selected from a list of 46284 Experts worldwide ranked by ideXlab platform
R. J. Prance - One of the best experts on this subject based on the ideXlab platform.
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Wearable Electric Potential sensing: A new modality sensing hair touch and restless leg movement
UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2016Co-Authors: A. Pouryazdan, R. J. Prance, H. Prance, Daniel RoggenAbstract:© 2016 ACM.Electric Potential sensors (EPS) are classified as capacitive sensors with the ability to measure small variations in Electric Potential or Electric field remotely and accurately. Here we show how a low cost single chip version of EPS can be integrated into a wearable device such as smart watch to provide relevant information about habitual movements specifically, hair touching and scratching as well as leg movement. This new modality could be used in consumer care product research such as studying the quality of shampoos and to study restless leg syndrome remotely without the need of wearing additional sensors. In both scenarios, a single sensor was worn on the wrist, similar to a smart watch, with the sensing electrode pointing away from the body (i.e. no skin contact).
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non invasive electrocardiogram detection of in vivo zebrafish embryos using Electric Potential sensors
Applied Physics Letters, 2015Co-Authors: Elizabeth Rendonmorales, R. J. Prance, H. Prance, Rodrigo AvilesespinosaAbstract:In this letter, we report the continuous detection of the cardiac Electrical activity in embryonic zebrafish using a non-invasive approach. We present a portable and cost-effective platform based on the Electric Potential sensing technology, to monitor in vivo electrocardiogram activity from the zebrafish heart. This proof of principle demonstration shows how electrocardiogram measurements from the embryonic zebrafish may become accessible by using Electric field detection. We present preliminary results using the prototype, which enables the acquisition of electrophysiological signals from in vivo 3 and 5 days-post-fertilization zebrafish embryos. The recorded waveforms show electrocardiogram traces including detailed features such as QRS complex, P and T waves.
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A high sensitivity calibrated Electric field meter based on the Electric Potential sensor
Measurement Science and Technology, 2010Co-Authors: A. Aydin, P. B. Stiffell, R. J. Prance, H. PranceAbstract:An Electric field measurement system with a maximum sensitivity of 2.6 µV m −1 and an associated accuracy of 2% is described. It is based on the ultra-high input impedance Electric Potential sensor and is calibrated using a test structure of well-defined geometry to establish a calculable Electric field. Finite element simulations are used to verify the field geometry and include the effect of finite boundary conditions due to the proximity of grounded structures. These are found to have a considerable effect on the uniformity of the field. The agreement seen between the measurements and simulations is achieved using a single numerical calibration factor and indicates that the presence of the sensor causes no significant perturbation of the Electric field.
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remote detection of human electrophysiological signals using Electric Potential sensors
Applied Physics Letters, 2008Co-Authors: R. J. Prance, C. J. Harland, S T Beardsmorerust, P Watson, H. PranceAbstract:We describe the measurement of human electrophysiological and movement signals remotely from a seated subject. An ultrahigh impedance Electric Potential sensor, designed specifically to reject external noise, is used to measure the Electric field at distances of up to 40cm from the surface of the body. The sensor is able to provide continuous data acquisition, at full sensitivity, without saturation by external noise sources. Respiration and heart signals are seen simultaneously and are separated using digital filtering techniques. All of the results reported were obtained in an open unshielded environment in close proximity to line operated computer equipment.
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Adaptive Electric Potential sensors for smart signal acquisition and processing
Journal of Physics: Conference Series, 2007Co-Authors: R. J. Prance, S. Beardsmore-rust, H. Prance, C. J. Harland, P. B. StiffellAbstract:Current applications of the Electric Potential Sensor operate in a strongly (capacitively) coupled limit, with the sensor physically close to or touching the source. This mode of operation screens the sensor effectively from the majority of external noise. To date however the full capability of these sensors operating in a remote mode has not been realised outside of a screened environment (Faraday cage). This paper describes the results of preliminary work in tailoring the response of the sensors to particular signals and so reject background noise, thereby enhancing both the dynamic range and signal to noise ratio significantly.
Kai J. Miller - One of the best experts on this subject based on the ideXlab platform.
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power law scaling in the brain surface Electric Potential
PLOS Computational Biology, 2009Co-Authors: Kai J. Miller, Larry B. Sorensen, Jeffrey G Ojemann, Marcel Den NijsAbstract:Recent studies have identified broadband phenomena in the Electric Potentials produced by the brain. We report the finding of power-law scaling in these signals using subdural electrocorticographic recordings from the surface of human cortex. The power spectral density (PSD) of the Electric Potential has the power-law form from 80 to 500 Hz. This scaling index, , is conserved across subjects, area in the cortex, and local neural activity levels. The shape of the PSD does not change with increases in local cortical activity, but the amplitude, , increases. We observe a “knee” in the spectra at , implying the existence of a characteristic time scale . Below , we explore two-power-law forms of the PSD, and demonstrate that there are activity-related fluctuations in the amplitude of a power-law process lying beneath the rhythms. Finally, we illustrate through simulation how, small-scale, simplified neuronal models could lead to these power-law observations. This suggests a new paradigm of non-oscillatory “asynchronous,” scale-free, changes in cortical Potentials, corresponding to changes in mean population-averaged firing rate, to complement the prevalent “synchronous” rhythm-based paradigm.
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Power-law scaling in the brain surface Electric Potential
PLoS Computational Biology, 2009Co-Authors: Kai J. Miller, Larry B. Sorensen, Jeffrey G Ojemann, Marcel Den NijsAbstract:Recent studies have identified broadband phenomena in the Electric Potentials produced by the brain. We report the finding of power-law scaling in these signals using subdural electrocorticographic recordings from the surface of human cortex. The power spectral density (PSD) of the Electric Potential has the power-law form P(f ) ∼ Af -χ x from 80 to 500 Hz. This scaling index, χ = 4:0±0:1, is conserved across subjects, area in the cortex, and local neural activity levels. The shape of the PSD does not change with increases in local cortical activity, but the amplitude, A, increases. We observe a "knee" in the spectra at f 0 ≃ 75Hz, implying the existence of a characteristic time scale τ = (2πf 0 ) -1 ≃ 2 - 4ms. Below f 0 , we explore two-power-law forms of the PSD, and demonstrate that there are activity-related fluctuations in the amplitude of a power-law process lying beneath the α/β rhythms. Finally, we illustrate through simulation how, small-scale, simplified neuronal models could lead to these power-law observations. This suggests a new paradigm of non-oscillatory "asynchronous," scalefree, changes in cortical Potentials, corresponding to changes in mean population-averaged firing rate, to complement the prevalent "synchronous" rhythm-based paradigm. © 2009 Miller et al.
H. Prance - One of the best experts on this subject based on the ideXlab platform.
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Wearable Electric Potential sensing: A new modality sensing hair touch and restless leg movement
UbiComp 2016 Adjunct - Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2016Co-Authors: A. Pouryazdan, R. J. Prance, H. Prance, Daniel RoggenAbstract:© 2016 ACM.Electric Potential sensors (EPS) are classified as capacitive sensors with the ability to measure small variations in Electric Potential or Electric field remotely and accurately. Here we show how a low cost single chip version of EPS can be integrated into a wearable device such as smart watch to provide relevant information about habitual movements specifically, hair touching and scratching as well as leg movement. This new modality could be used in consumer care product research such as studying the quality of shampoos and to study restless leg syndrome remotely without the need of wearing additional sensors. In both scenarios, a single sensor was worn on the wrist, similar to a smart watch, with the sensing electrode pointing away from the body (i.e. no skin contact).
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non invasive electrocardiogram detection of in vivo zebrafish embryos using Electric Potential sensors
Applied Physics Letters, 2015Co-Authors: Elizabeth Rendonmorales, R. J. Prance, H. Prance, Rodrigo AvilesespinosaAbstract:In this letter, we report the continuous detection of the cardiac Electrical activity in embryonic zebrafish using a non-invasive approach. We present a portable and cost-effective platform based on the Electric Potential sensing technology, to monitor in vivo electrocardiogram activity from the zebrafish heart. This proof of principle demonstration shows how electrocardiogram measurements from the embryonic zebrafish may become accessible by using Electric field detection. We present preliminary results using the prototype, which enables the acquisition of electrophysiological signals from in vivo 3 and 5 days-post-fertilization zebrafish embryos. The recorded waveforms show electrocardiogram traces including detailed features such as QRS complex, P and T waves.
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A high sensitivity calibrated Electric field meter based on the Electric Potential sensor
Measurement Science and Technology, 2010Co-Authors: A. Aydin, P. B. Stiffell, R. J. Prance, H. PranceAbstract:An Electric field measurement system with a maximum sensitivity of 2.6 µV m −1 and an associated accuracy of 2% is described. It is based on the ultra-high input impedance Electric Potential sensor and is calibrated using a test structure of well-defined geometry to establish a calculable Electric field. Finite element simulations are used to verify the field geometry and include the effect of finite boundary conditions due to the proximity of grounded structures. These are found to have a considerable effect on the uniformity of the field. The agreement seen between the measurements and simulations is achieved using a single numerical calibration factor and indicates that the presence of the sensor causes no significant perturbation of the Electric field.
-
remote detection of human electrophysiological signals using Electric Potential sensors
Applied Physics Letters, 2008Co-Authors: R. J. Prance, C. J. Harland, S T Beardsmorerust, P Watson, H. PranceAbstract:We describe the measurement of human electrophysiological and movement signals remotely from a seated subject. An ultrahigh impedance Electric Potential sensor, designed specifically to reject external noise, is used to measure the Electric field at distances of up to 40cm from the surface of the body. The sensor is able to provide continuous data acquisition, at full sensitivity, without saturation by external noise sources. Respiration and heart signals are seen simultaneously and are separated using digital filtering techniques. All of the results reported were obtained in an open unshielded environment in close proximity to line operated computer equipment.
-
Adaptive Electric Potential sensors for smart signal acquisition and processing
Journal of Physics: Conference Series, 2007Co-Authors: R. J. Prance, S. Beardsmore-rust, H. Prance, C. J. Harland, P. B. StiffellAbstract:Current applications of the Electric Potential Sensor operate in a strongly (capacitively) coupled limit, with the sensor physically close to or touching the source. This mode of operation screens the sensor effectively from the majority of external noise. To date however the full capability of these sensors operating in a remote mode has not been realised outside of a screened environment (Faraday cage). This paper describes the results of preliminary work in tailoring the response of the sensors to particular signals and so reject background noise, thereby enhancing both the dynamic range and signal to noise ratio significantly.
Marcel Den Nijs - One of the best experts on this subject based on the ideXlab platform.
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power law scaling in the brain surface Electric Potential
PLOS Computational Biology, 2009Co-Authors: Kai J. Miller, Larry B. Sorensen, Jeffrey G Ojemann, Marcel Den NijsAbstract:Recent studies have identified broadband phenomena in the Electric Potentials produced by the brain. We report the finding of power-law scaling in these signals using subdural electrocorticographic recordings from the surface of human cortex. The power spectral density (PSD) of the Electric Potential has the power-law form from 80 to 500 Hz. This scaling index, , is conserved across subjects, area in the cortex, and local neural activity levels. The shape of the PSD does not change with increases in local cortical activity, but the amplitude, , increases. We observe a “knee” in the spectra at , implying the existence of a characteristic time scale . Below , we explore two-power-law forms of the PSD, and demonstrate that there are activity-related fluctuations in the amplitude of a power-law process lying beneath the rhythms. Finally, we illustrate through simulation how, small-scale, simplified neuronal models could lead to these power-law observations. This suggests a new paradigm of non-oscillatory “asynchronous,” scale-free, changes in cortical Potentials, corresponding to changes in mean population-averaged firing rate, to complement the prevalent “synchronous” rhythm-based paradigm.
Marcel Den Nijs - One of the best experts on this subject based on the ideXlab platform.
-
Power-law scaling in the brain surface Electric Potential
PLoS Computational Biology, 2009Co-Authors: Kai J. Miller, Larry B. Sorensen, Jeffrey G Ojemann, Marcel Den NijsAbstract:Recent studies have identified broadband phenomena in the Electric Potentials produced by the brain. We report the finding of power-law scaling in these signals using subdural electrocorticographic recordings from the surface of human cortex. The power spectral density (PSD) of the Electric Potential has the power-law form P(f ) ∼ Af -χ x from 80 to 500 Hz. This scaling index, χ = 4:0±0:1, is conserved across subjects, area in the cortex, and local neural activity levels. The shape of the PSD does not change with increases in local cortical activity, but the amplitude, A, increases. We observe a "knee" in the spectra at f 0 ≃ 75Hz, implying the existence of a characteristic time scale τ = (2πf 0 ) -1 ≃ 2 - 4ms. Below f 0 , we explore two-power-law forms of the PSD, and demonstrate that there are activity-related fluctuations in the amplitude of a power-law process lying beneath the α/β rhythms. Finally, we illustrate through simulation how, small-scale, simplified neuronal models could lead to these power-law observations. This suggests a new paradigm of non-oscillatory "asynchronous," scalefree, changes in cortical Potentials, corresponding to changes in mean population-averaged firing rate, to complement the prevalent "synchronous" rhythm-based paradigm. © 2009 Miller et al.