Analysis of a Direct Microcontroller Interface for Capacitively Coupled Resistive Sensors

Direct interface circuits (DICs) avoid the need for signal conditioning circuits and analog-to-digital converters (ADCs) to obtain digital measurements of resistive sensors using only a few passive elements. However, such simple hardware can lead to quantization errors when measuring small resistance values as well as high measurement times and uncertainties for high resistances. Different solutions to some of these problems have been presented in the literature over recent years, although the increased uncertainty in measurements at higher resistance values is a problem that has remained unaddressed. This article presents an economical hardware solution that only requires an extra capacitor to reduce this problem. The circuit is implemented with a field-programmable gate array (FPGA) as a programmable digital device. The new proposal significantly reduces the uncertainty in the time measurements. As a result, the high resistance errors decreased by up to 90%. The circuit requires three capacitor discharge cycles, as is needed in a classic DIC. Therefore, the time to estimate resistance increases slightly, between 2.7% and 4.6%.

Section: Introductionmentioning

confidence: 99%

Two-Capacitor Direct Interface Circuit for Resistive Sensor Measurements

Hidalgo-López

Oballe-Peinado

Castellanos-Ramos

et al. 2021

“…As mentioned before, the measurement of each stretch is obtained by conditioning the sensor output with a front-end (labeled as “Passive Network” in Figure 2 ). In order to simplify the analog-to-digital conversion of the sensor output in terms of size and power consumption [ 26 , 27 ], a direct microcontroller interface (DIC) was selected. The microcontroller excites with a voltage V 0 the sensor in series with a fixed capacitor of capacitance C and then measures the discharge time T m from the maximum value and a predefined threshold V th when the excitation signal is set at 0 V. With this method, the resistance R of the sensor can be calculated with Equation (1):

…”

Section: Smart Brace Designmentioning

confidence: 99%

Smart Brace for Static and Dynamic Knee Laxity Measurement

Bellitti

Borghetti

Lopomo

et al. 2022

Every year in Europe more than 500 thousand injuries that involve the anterior cruciate ligament (ACL) are diagnosed. The ACL is one of the main restraints within the human knee, focused on stabilizing the joint and controlling the relative movement between the tibia and femur under mechanical stress (i.e., laxity). Ligament laxity measurement is clinically valuable for diagnosing ACL injury and comparing possible outcomes of surgical procedures. In general, knee laxity assessment is manually performed and provides information to clinicians which is mainly subjective. Only recently quantitative assessment of knee laxity through instrumental approaches has been introduced and become a fundamental asset in clinical practice. However, the current solutions provide only partial information about either static or dynamic laxity. To support a multiparametric approach using a single device, an innovative smart knee brace for knee laxity evaluation was developed. Equipped with stretchable strain sensors and inertial measurement units (IMUs), the wearable system was designed to provide quantitative information concerning the drawer, Lachman, and pivot shift tests. We specifically characterized IMUs by using a reference sensor. Applying the Bland–Altman method, the limit of agreement was found to be less than 0.06 m/s2 for the accelerometer, 0.06 rad/s for the gyroscope and 0.08 μT for the magnetometer. By using an appropriate characterizing setup, the average gauge factor of the three strain sensors was 2.169. Finally, we realized a pilot study to compare the outcomes with a marker-based optoelectronic stereophotogrammetric system to verify the validity of the designed system. The preliminary findings for the capability of the system to discriminate possible ACL lesions are encouraging; in fact, the smart brace could be an effective support for an objective and quantitative diagnosis of ACL tear by supporting the simultaneous assessment of both rotational and translational laxity. To obtain reliable information about the real effectiveness of the system, further clinical validation is necessary.

“…The same author, in 2022, proposed a direct approach to connect three-wire [28] and four-wire [29] resistive sensors to the digital port of a microcontroller. A technique to directly connect a capacitively coupled resistive sensor with a microcontroller was presented by Areekath et al in 2020 [30]. Measurement methods for capacitive sensors [31] and lossy capacitive relative humidity sensors [32] based on a direct sensor-to-microcontroller interface circuit were proposed by Czaja in 2020 and 2021.…”

Section: Introductionmentioning

confidence: 99%

Efficient and Accurate Analog Voltage Measurement Using a Direct Sensor-to-Digital Port Interface for Microcontrollers and Field-Programmable Gate Arrays

Grossi

2024

Portable sensor systems are usually based on microcontrollers and/or Field-Programmable Gate Arrays (FPGAs) that are interfaced with sensors by means of an Analog-to-Digital converter (ADC), either integrated in the computing device or external. An alternative solution is based on the direct connection of the sensors to the digital input port of the microcontroller or FPGA. This solution is particularly interesting in the case of devices not integrating an internal ADC or featuring a small number of ADC channels. In this paper, a technique is presented to directly interface sensors with analog voltage output to the digital input port of a microcontroller or FPGA. The proposed method requires only a few passive components and is based on the measurements of the duty cycle of a digital square-wave signal. This technique was investigated by means of circuit simulations using LTSpice and was implemented in a commercial low-cost FPGA device (Gowin GW1NR-9). The duty cycle of the square-wave signal features a good linear correlation with the analog voltage to be measured. Thus, a look-up table to map the analog voltage values to the measured duty cycle is not required with benefits in terms of memory occupation. The experimental results on the FPGA device have shown that the analog voltage can be measured with a maximum accuracy of 1.09 mV and a sampling rate of 9.75 Hz. The sampling rate can be increased to 31.35 Hz and 128.31 Hz with an accuracy of 1.61 mV and 2.68 mV, respectively.