Low-power direct resistive sensor-to-microcontroller interfaces

“© © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”This paper analyzes the energy consumption of direct interface circuits where the data conversion of a resistive sensor is performed by a direct connection to a set of digital ports of a microcontroller (µC). The causes of energy consumption as well as their relation to the measurement specifications in terms of uncertainty are analyzed. This analysis yields a tradeoff between energy consumption and measurement uncertainty, which sets a design procedure focused on achieving the lowest energy consumption for a given uncertainty and a measuring range. Together with this analysis, a novel experimental setup is proposed that allows one to measure the µC’s timer quantization uncertainty. An application example is shown where the design procedure is applied. The experimental results fairly fit the theoretical analysis, yielding only 5 µJ to achieve nine effective number of bits (ENOB) in a measuring range from 1 to 1.38 k. With the same ENOB, the energy is reduced to 1.9 µJ when the measurement limits are changed to 100 and 138 k.Peer ReviewedPostprint (published version

Two proposals to simplify resistive sensor readout based on Resistance-to-Time-to-Digital conversion

Direct Interface Circuits (DICs) are simple circuits used in readouts for all types of sensors. For resistive sensors, all DICs perform a resistance-to-time-to-digital conversion using just the sensor, some calibration resistors, one or two capacitors, and a Digital Processor. These circuits require a variable number of charging and discharging cycles of a capacitor to estimate the sensor resistance, Rx, increasing both acquisition time and power consumption. This paper presents two resistive DICs capable of estimating Rx by means of a single charging-discharging process, simplifying the readout process. Furthermore, this is achieved without increasing hardware requirements. Only two time measurements are used to obtain Rx. Despite the simplicity of the new circuits, the experimental results show that relative errors of estimating Rx can be below 0.8 %, and this in a wide range of resistances of over 40 dB. Moreover, acquisition time and energy consumption can be reduced by up to 75 %.Funding for open access charge: Universidad de Málaga / CBUA. This work was supported by the Spanish Government under contract PID2021-125091OB-I0

Smart Brace for Static and Dynamic Knee Laxity Measurement

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

Low-power direct resistive sensor-to-microcontroller interfaces

“© © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”This paper analyzes the energy consumption of direct interface circuits where the data conversion of a resistive sensor is performed by a direct connection to a set of digital ports of a microcontroller (µC). The causes of energy consumption as well as their relation to the measurement specifications in terms of uncertainty are analyzed. This analysis yields a tradeoff between energy consumption and measurement uncertainty, which sets a design procedure focused on achieving the lowest energy consumption for a given uncertainty and a measuring range. Together with this analysis, a novel experimental setup is proposed that allows one to measure the µC’s timer quantization uncertainty. An application example is shown where the design procedure is applied. The experimental results fairly fit the theoretical analysis, yielding only 5 µJ to achieve nine effective number of bits (ENOB) in a measuring range from 1 to 1.38 k. With the same ENOB, the energy is reduced to 1.9 µJ when the measurement limits are changed to 100 and 138 k.Peer Reviewe