1989
DOI: 10.1109/16.30936
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Integrated multi-biosensors based on an ion-sensitive field-effect transistor using photolithographic techniques

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Cited by 44 publications
(16 citation statements)
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“…A linear relationship was observed between the potential and the logarithm of urea concentration between 0.1 mM and 10 mM. The linear range was wider than ISFET-based sensors [8,10]. The sensitivity in this range of concentration (regression coef®-cient) was 28.3 mV per decade of urea concentration with a correlation coef®cient of 0.968.…”
Section: Calibration Plotmentioning
confidence: 87%
“…A linear relationship was observed between the potential and the logarithm of urea concentration between 0.1 mM and 10 mM. The linear range was wider than ISFET-based sensors [8,10]. The sensitivity in this range of concentration (regression coef®-cient) was 28.3 mV per decade of urea concentration with a correlation coef®cient of 0.968.…”
Section: Calibration Plotmentioning
confidence: 87%
“…A couple of examples of the combination of target analytes include glucose and triolein [106], glucose and urea [63,64,106]. Examples of integration are also found with the ion-selective electrodes.…”
Section: Integration Of Sensors and Electrochemical Microsystemsmentioning
confidence: 99%
“…Since the pH in a solution is almost constant in case of no chemical disturbance, the modulator will output bitstream data, whose average value in a given period of time is a scaled version of the FM's carrier frequency, as described by (2). Recall that the carrier frequency of the FM signal is dependent on pH, so the easy way to examine the relationship between pH and the output of the sigma-delta modulator is to evaluate the DC content of the bitstream output.…”
Section: Total Systemmentioning
confidence: 99%
“…Nevertheless, when the sampling frequency is over twice that of the maximum FM frequency, a D-flip-flop can do the counting, whereas the subtraction can be done using an XOR gate. Hovin [11] has shown that the linear relationship between discrete and continuous is (2) assuming that , and is the sampling time, is the quantization noise at time , while is the previous quantization noise at time . Equation (2) reveals that the digital output contains the analog input with a gain factor of , whereas the quantization noise is first-order differentiated.…”
Section: Chip Organizationmentioning
confidence: 99%
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