The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
Li-chia Tai - One of the best experts on this subject based on the ideXlab platform.
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a multi modal Sweat sensing patch for cross verification of Sweat Rate total ionic charge and na concentration
Lab on a Chip, 2019Co-Authors: Zhen Yuan, Lei Hou, Mallika Bariya, Hnin Yin Yin Nyein, Li-chia TaiAbstract:Sweat sensors introduced in recent years have targeted a variety of Sweat features and biomarkers for non-invasive health monitoring. Amongst these targets, reliable monitoring of Sweat Rate is crucial due to its modulation of Sweat analyte concentrations and its intrinsic significance to numerous medical and physiological health conditions. Here we present a Sweat Rate sensor structure comprising of electrodes with interdigitated fingers in a microfluidic channel. Each time the accumulating Sweat impinges on an electrode finger, the sensor reports a jump in admittance that can be simply and efficiently counted to estimate Sweat Rate, overcoming selectivity limitations of previously reported Sweat Rate sensors. We further integRate an impedimetric sensor for measuring total ionic charge concentration and an electrochemical Na+ sensor, together creating a multi-modal system for analyzing fluid and electrolyte secretion. We demonstRate how low analyte diffusion Rates through this microfluidic device allow for multi-purpose sensor function, including utilizing the Sweat Rate sensor signal to corroboRate total ionic sensor measurements. This cross-verification capability ensures data integrity in real time, satisfying a vital consideration for personalized healthcare technologies. We use the presented patch for continuous analysis of Sweat Rate, total ionic charge concentration, and Na+ concentration during exercise, while demonstrating how multi-modal cross-verification brings new trust to sensor readings.
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A multi-modal Sweat sensing patch for cross-verification of Sweat Rate, total ionic charge, and Na+ concentration.
Lab on a chip, 2019Co-Authors: Zhen Yuan, Lei Hou, Mallika Bariya, Hnin Yin Yin Nyein, Li-chia Tai, Ali JaveyAbstract:Sweat sensors introduced in recent years have targeted a variety of Sweat features and biomarkers for non-invasive health monitoring. Amongst these targets, reliable monitoring of Sweat Rate is crucial due to its modulation of Sweat analyte concentrations and its intrinsic significance to numerous medical and physiological health conditions. Here we present a Sweat Rate sensor structure comprising of electrodes with interdigitated fingers in a microfluidic channel. Each time the accumulating Sweat impinges on an electrode finger, the sensor reports a jump in admittance that can be simply and efficiently counted to estimate Sweat Rate, overcoming selectivity limitations of previously reported Sweat Rate sensors. We further integRate an impedimetric sensor for measuring total ionic charge concentration and an electrochemical Na+ sensor, together creating a multi-modal system for analyzing fluid and electrolyte secretion. We demonstRate how low analyte diffusion Rates through this microfluidic device allow for multi-purpose sensor function, including utilizing the Sweat Rate sensor signal to corroboRate total ionic sensor measurements. This cross-verification capability ensures data integrity in real time, satisfying a vital consideration for personalized healthcare technologies. We use the presented patch for continuous analysis of Sweat Rate, total ionic charge concentration, and Na+ concentration during exercise, while demonstrating how multi-modal cross-verification brings new trust to sensor readings.
Zhen Yuan - One of the best experts on this subject based on the ideXlab platform.
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a multi modal Sweat sensing patch for cross verification of Sweat Rate total ionic charge and na concentration
Lab on a Chip, 2019Co-Authors: Zhen Yuan, Lei Hou, Mallika Bariya, Hnin Yin Yin Nyein, Li-chia TaiAbstract:Sweat sensors introduced in recent years have targeted a variety of Sweat features and biomarkers for non-invasive health monitoring. Amongst these targets, reliable monitoring of Sweat Rate is crucial due to its modulation of Sweat analyte concentrations and its intrinsic significance to numerous medical and physiological health conditions. Here we present a Sweat Rate sensor structure comprising of electrodes with interdigitated fingers in a microfluidic channel. Each time the accumulating Sweat impinges on an electrode finger, the sensor reports a jump in admittance that can be simply and efficiently counted to estimate Sweat Rate, overcoming selectivity limitations of previously reported Sweat Rate sensors. We further integRate an impedimetric sensor for measuring total ionic charge concentration and an electrochemical Na+ sensor, together creating a multi-modal system for analyzing fluid and electrolyte secretion. We demonstRate how low analyte diffusion Rates through this microfluidic device allow for multi-purpose sensor function, including utilizing the Sweat Rate sensor signal to corroboRate total ionic sensor measurements. This cross-verification capability ensures data integrity in real time, satisfying a vital consideration for personalized healthcare technologies. We use the presented patch for continuous analysis of Sweat Rate, total ionic charge concentration, and Na+ concentration during exercise, while demonstrating how multi-modal cross-verification brings new trust to sensor readings.
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A multi-modal Sweat sensing patch for cross-verification of Sweat Rate, total ionic charge, and Na+ concentration.
Lab on a chip, 2019Co-Authors: Zhen Yuan, Lei Hou, Mallika Bariya, Hnin Yin Yin Nyein, Li-chia Tai, Ali JaveyAbstract:Sweat sensors introduced in recent years have targeted a variety of Sweat features and biomarkers for non-invasive health monitoring. Amongst these targets, reliable monitoring of Sweat Rate is crucial due to its modulation of Sweat analyte concentrations and its intrinsic significance to numerous medical and physiological health conditions. Here we present a Sweat Rate sensor structure comprising of electrodes with interdigitated fingers in a microfluidic channel. Each time the accumulating Sweat impinges on an electrode finger, the sensor reports a jump in admittance that can be simply and efficiently counted to estimate Sweat Rate, overcoming selectivity limitations of previously reported Sweat Rate sensors. We further integRate an impedimetric sensor for measuring total ionic charge concentration and an electrochemical Na+ sensor, together creating a multi-modal system for analyzing fluid and electrolyte secretion. We demonstRate how low analyte diffusion Rates through this microfluidic device allow for multi-purpose sensor function, including utilizing the Sweat Rate sensor signal to corroboRate total ionic sensor measurements. This cross-verification capability ensures data integrity in real time, satisfying a vital consideration for personalized healthcare technologies. We use the presented patch for continuous analysis of Sweat Rate, total ionic charge concentration, and Na+ concentration during exercise, while demonstrating how multi-modal cross-verification brings new trust to sensor readings.
Mallika Bariya - One of the best experts on this subject based on the ideXlab platform.
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a multi modal Sweat sensing patch for cross verification of Sweat Rate total ionic charge and na concentration
Lab on a Chip, 2019Co-Authors: Zhen Yuan, Lei Hou, Mallika Bariya, Hnin Yin Yin Nyein, Li-chia TaiAbstract:Sweat sensors introduced in recent years have targeted a variety of Sweat features and biomarkers for non-invasive health monitoring. Amongst these targets, reliable monitoring of Sweat Rate is crucial due to its modulation of Sweat analyte concentrations and its intrinsic significance to numerous medical and physiological health conditions. Here we present a Sweat Rate sensor structure comprising of electrodes with interdigitated fingers in a microfluidic channel. Each time the accumulating Sweat impinges on an electrode finger, the sensor reports a jump in admittance that can be simply and efficiently counted to estimate Sweat Rate, overcoming selectivity limitations of previously reported Sweat Rate sensors. We further integRate an impedimetric sensor for measuring total ionic charge concentration and an electrochemical Na+ sensor, together creating a multi-modal system for analyzing fluid and electrolyte secretion. We demonstRate how low analyte diffusion Rates through this microfluidic device allow for multi-purpose sensor function, including utilizing the Sweat Rate sensor signal to corroboRate total ionic sensor measurements. This cross-verification capability ensures data integrity in real time, satisfying a vital consideration for personalized healthcare technologies. We use the presented patch for continuous analysis of Sweat Rate, total ionic charge concentration, and Na+ concentration during exercise, while demonstrating how multi-modal cross-verification brings new trust to sensor readings.
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A multi-modal Sweat sensing patch for cross-verification of Sweat Rate, total ionic charge, and Na+ concentration.
Lab on a chip, 2019Co-Authors: Zhen Yuan, Lei Hou, Mallika Bariya, Hnin Yin Yin Nyein, Li-chia Tai, Ali JaveyAbstract:Sweat sensors introduced in recent years have targeted a variety of Sweat features and biomarkers for non-invasive health monitoring. Amongst these targets, reliable monitoring of Sweat Rate is crucial due to its modulation of Sweat analyte concentrations and its intrinsic significance to numerous medical and physiological health conditions. Here we present a Sweat Rate sensor structure comprising of electrodes with interdigitated fingers in a microfluidic channel. Each time the accumulating Sweat impinges on an electrode finger, the sensor reports a jump in admittance that can be simply and efficiently counted to estimate Sweat Rate, overcoming selectivity limitations of previously reported Sweat Rate sensors. We further integRate an impedimetric sensor for measuring total ionic charge concentration and an electrochemical Na+ sensor, together creating a multi-modal system for analyzing fluid and electrolyte secretion. We demonstRate how low analyte diffusion Rates through this microfluidic device allow for multi-purpose sensor function, including utilizing the Sweat Rate sensor signal to corroboRate total ionic sensor measurements. This cross-verification capability ensures data integrity in real time, satisfying a vital consideration for personalized healthcare technologies. We use the presented patch for continuous analysis of Sweat Rate, total ionic charge concentration, and Na+ concentration during exercise, while demonstrating how multi-modal cross-verification brings new trust to sensor readings.
Lei Hou - One of the best experts on this subject based on the ideXlab platform.
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a multi modal Sweat sensing patch for cross verification of Sweat Rate total ionic charge and na concentration
Lab on a Chip, 2019Co-Authors: Zhen Yuan, Lei Hou, Mallika Bariya, Hnin Yin Yin Nyein, Li-chia TaiAbstract:Sweat sensors introduced in recent years have targeted a variety of Sweat features and biomarkers for non-invasive health monitoring. Amongst these targets, reliable monitoring of Sweat Rate is crucial due to its modulation of Sweat analyte concentrations and its intrinsic significance to numerous medical and physiological health conditions. Here we present a Sweat Rate sensor structure comprising of electrodes with interdigitated fingers in a microfluidic channel. Each time the accumulating Sweat impinges on an electrode finger, the sensor reports a jump in admittance that can be simply and efficiently counted to estimate Sweat Rate, overcoming selectivity limitations of previously reported Sweat Rate sensors. We further integRate an impedimetric sensor for measuring total ionic charge concentration and an electrochemical Na+ sensor, together creating a multi-modal system for analyzing fluid and electrolyte secretion. We demonstRate how low analyte diffusion Rates through this microfluidic device allow for multi-purpose sensor function, including utilizing the Sweat Rate sensor signal to corroboRate total ionic sensor measurements. This cross-verification capability ensures data integrity in real time, satisfying a vital consideration for personalized healthcare technologies. We use the presented patch for continuous analysis of Sweat Rate, total ionic charge concentration, and Na+ concentration during exercise, while demonstrating how multi-modal cross-verification brings new trust to sensor readings.
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A multi-modal Sweat sensing patch for cross-verification of Sweat Rate, total ionic charge, and Na+ concentration.
Lab on a chip, 2019Co-Authors: Zhen Yuan, Lei Hou, Mallika Bariya, Hnin Yin Yin Nyein, Li-chia Tai, Ali JaveyAbstract:Sweat sensors introduced in recent years have targeted a variety of Sweat features and biomarkers for non-invasive health monitoring. Amongst these targets, reliable monitoring of Sweat Rate is crucial due to its modulation of Sweat analyte concentrations and its intrinsic significance to numerous medical and physiological health conditions. Here we present a Sweat Rate sensor structure comprising of electrodes with interdigitated fingers in a microfluidic channel. Each time the accumulating Sweat impinges on an electrode finger, the sensor reports a jump in admittance that can be simply and efficiently counted to estimate Sweat Rate, overcoming selectivity limitations of previously reported Sweat Rate sensors. We further integRate an impedimetric sensor for measuring total ionic charge concentration and an electrochemical Na+ sensor, together creating a multi-modal system for analyzing fluid and electrolyte secretion. We demonstRate how low analyte diffusion Rates through this microfluidic device allow for multi-purpose sensor function, including utilizing the Sweat Rate sensor signal to corroboRate total ionic sensor measurements. This cross-verification capability ensures data integrity in real time, satisfying a vital consideration for personalized healthcare technologies. We use the presented patch for continuous analysis of Sweat Rate, total ionic charge concentration, and Na+ concentration during exercise, while demonstrating how multi-modal cross-verification brings new trust to sensor readings.
Hnin Yin Yin Nyein - One of the best experts on this subject based on the ideXlab platform.
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a multi modal Sweat sensing patch for cross verification of Sweat Rate total ionic charge and na concentration
Lab on a Chip, 2019Co-Authors: Zhen Yuan, Lei Hou, Mallika Bariya, Hnin Yin Yin Nyein, Li-chia TaiAbstract:Sweat sensors introduced in recent years have targeted a variety of Sweat features and biomarkers for non-invasive health monitoring. Amongst these targets, reliable monitoring of Sweat Rate is crucial due to its modulation of Sweat analyte concentrations and its intrinsic significance to numerous medical and physiological health conditions. Here we present a Sweat Rate sensor structure comprising of electrodes with interdigitated fingers in a microfluidic channel. Each time the accumulating Sweat impinges on an electrode finger, the sensor reports a jump in admittance that can be simply and efficiently counted to estimate Sweat Rate, overcoming selectivity limitations of previously reported Sweat Rate sensors. We further integRate an impedimetric sensor for measuring total ionic charge concentration and an electrochemical Na+ sensor, together creating a multi-modal system for analyzing fluid and electrolyte secretion. We demonstRate how low analyte diffusion Rates through this microfluidic device allow for multi-purpose sensor function, including utilizing the Sweat Rate sensor signal to corroboRate total ionic sensor measurements. This cross-verification capability ensures data integrity in real time, satisfying a vital consideration for personalized healthcare technologies. We use the presented patch for continuous analysis of Sweat Rate, total ionic charge concentration, and Na+ concentration during exercise, while demonstrating how multi-modal cross-verification brings new trust to sensor readings.
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A multi-modal Sweat sensing patch for cross-verification of Sweat Rate, total ionic charge, and Na+ concentration.
Lab on a chip, 2019Co-Authors: Zhen Yuan, Lei Hou, Mallika Bariya, Hnin Yin Yin Nyein, Li-chia Tai, Ali JaveyAbstract:Sweat sensors introduced in recent years have targeted a variety of Sweat features and biomarkers for non-invasive health monitoring. Amongst these targets, reliable monitoring of Sweat Rate is crucial due to its modulation of Sweat analyte concentrations and its intrinsic significance to numerous medical and physiological health conditions. Here we present a Sweat Rate sensor structure comprising of electrodes with interdigitated fingers in a microfluidic channel. Each time the accumulating Sweat impinges on an electrode finger, the sensor reports a jump in admittance that can be simply and efficiently counted to estimate Sweat Rate, overcoming selectivity limitations of previously reported Sweat Rate sensors. We further integRate an impedimetric sensor for measuring total ionic charge concentration and an electrochemical Na+ sensor, together creating a multi-modal system for analyzing fluid and electrolyte secretion. We demonstRate how low analyte diffusion Rates through this microfluidic device allow for multi-purpose sensor function, including utilizing the Sweat Rate sensor signal to corroboRate total ionic sensor measurements. This cross-verification capability ensures data integrity in real time, satisfying a vital consideration for personalized healthcare technologies. We use the presented patch for continuous analysis of Sweat Rate, total ionic charge concentration, and Na+ concentration during exercise, while demonstrating how multi-modal cross-verification brings new trust to sensor readings.
