Underlying Physics of Conductive Polymer Composites and Force Sensing Resistors (FSRs). A Study on Creep Response and Dynamic Loading

Neuromorphic Sensor Based on Force-Sensing Resistors

This work introduces a neuromorphic sensor (NS) based on force-sensing resistors (FSR) and spiking neurons for robotic systems. The proposed sensor integrates the FSR in the schematic of the spiking neuron in order to make the sensor generate spikes with a frequency that depends on the applied force. The performance of the proposed sensor is evaluated in the control of a SMA-actuated robotic finger by monitoring the force during a steady state when the finger pushes on a tweezer. For comparison purposes, we performed a similar evaluation when the SNN received input from a widely used compression load cell (CLC). The results show that the proposed FSR-based neuromorphic sensor has very good sensitivity to low forces and the function between the spiking rate and the applied force is continuous, with good variation range. However, when compared to the CLC, the response of the NS follows a logarithmic-like function with improved sensitivity for small forces. In addition, the power consumption of NS is 128 µW that is 270 times lower than that of the CLC which needs 3.5 mW to operate. These characteristics make the neuromorphic sensor with FSR suitable for bioinspired control of humanoid robotics, representing a low-power and low-cost alternative to the widely used sensors.

Smart Sensing Chairs for Sitting Posture Detection, Classification, and Monitoring: A Comprehensive Review

Incorrect sitting posture, characterized by asymmetrical or uneven positioning of the body, often leads to spinal misalignment and muscle tone imbalance. The prolonged maintenance of such postures can adversely impact well-being and contribute to the development of spinal deformities and musculoskeletal disorders. In response, smart sensing chairs equipped with cutting-edge sensor technologies have been introduced as a viable solution for the real-time detection, classification, and monitoring of sitting postures, aiming to mitigate the risk of musculoskeletal disorders and promote overall health. This comprehensive literature review evaluates the current body of research on smart sensing chairs, with a specific focus on the strategies used for posture detection and classification and the effectiveness of different sensor technologies. A meticulous search across MDPI, IEEE, Google Scholar, Scopus, and PubMed databases yielded 39 pertinent studies that utilized non-invasive methods for posture monitoring. The analysis revealed that Force Sensing Resistors (FSRs) are the predominant sensors utilized for posture detection, whereas Convolutional Neural Networks (CNNs) and Artificial Neural Networks (ANNs) are the leading machine learning models for posture classification. However, it was observed that CNNs and ANNs do not outperform traditional statistical models in terms of classification accuracy due to the constrained size and lack of diversity within training datasets. These datasets often fail to comprehensively represent the array of human body shapes and musculoskeletal configurations. Moreover, this review identifies a significant gap in the evaluation of user feedback mechanisms, essential for alerting users to their sitting posture and facilitating corrective adjustments.

Quantifying muscle contraction with a conductive electroactive polymer sensor: introduction to a novel surface mechanomyography device

Clinicians seek an accurate method to assess muscle contractility during activities to better guide treatment. We investigated application of a conductive electroactive polymer sensor as a novel wearable surface mechanomyography (sMMG) sensor for quantifying muscle contractility. The radial displacement of a muscle during a contraction is detected by the physically stretched dielectric elastomer component of the sMMG sensor which quantifies the changes in capacitance. The duration of muscle activation times for quadriceps, hamstrings, and gastrocnemius muscles demonstrated strong correlation between sMMG and EMG during a parallel squat activity and isometric contractions. A moderate to strong correlation was demonstrated between the sMMG isometric muscle activation times and force output times from a dynamometer. The potential wearable application of an electroactive polymer sensor to measure muscle contraction time is supported.

Piezoresistive Properties of 3D-Printed Polylactic Acid (PLA) Nanocomposites

An increasing interest is focused on the application of 3D printing for sensor manufacturing. Using 3D printing technology offers a new approach to the fabrication of sensors that are both geometrically and functionally complex. This work presents the analysis of the 3D-printed thermoplastic nanocomposites compress under the applied force. The response for the corresponding resistance changes versus applied load is obtained to evaluate the effectiveness of the printed layer as a pressure/force sensor. Multi-walled carbon nanotubes (MWNT) and high-structured carbon black (Ketjenblack) (KB) in the polylactic acid (PLA) matrix were extruded to develop 3D-printable filaments. The electrical and piezoresistive behaviors of the created 3D-printed layers were investigated. The percolation threshold of MWNT and KB 3D-printed layers are 1 wt.% and 4 wt.%, respectively. The PLA/1 wt.% MWNT 3D-printed layers with 1 mm thickness exhibit a negative pressure coefficient (NPC) characterized by a decrease of about one decade in resistance with increasing compressive loadings up to 18 N with a maximum strain up to about 16%. In the cyclic mode with a 1 N/min force rate, the PLA/1 wt.% MWNT 3D-printed layers showed good performance with the piezoresistive coefficient or gauge factor (G) of 7.6 obtained with the amplitude of the piezoresistive response (A_r) of about -0.8. KB composites could not show stable piezoresistive responses in a cyclic mode. However, under high force rate compression, the PLA/4 wt.% KB 3D-printed layers led to responses of large sensitivity (A_r = −0.90) and were exempt from noise with a high value of G = 47.6 in the first cycle, which is a highly efficient piezoresistive behavior.

Enhancing Part-to-Part Repeatability of Force-Sensing Resistors Using a Lean Six Sigma Approach

Polymer nanocomposites have found wide acceptance in research applications as pressure sensors under the designation of force-sensing resistors (FSRs). However, given the random dispersion of conductive nanoparticles in the polymer matrix, the sensitivity of FSRs notably differs from one specimen to another; this condition has precluded the use of FSRs in industrial applications that require large part-to-part repeatability. Six Sigma methodology provides a standard framework to reduce the process variability regarding a critical variable. The Six Sigma core is the DMAIC cycle (Define, Measure, Analyze, Improve, and Control). In this study, we have deployed the DMAIC cycle to reduce the process variability of sensor sensitivity, where sensitivity was defined by the rate of change in the output voltage in response to the applied force. It was found that sensor sensitivity could be trimmed by changing their input (driving) voltage. The whole process comprised: characterization of FSR sensitivity, followed by physical modeling that let us identify the underlying physics of FSR variability, and ultimately, a mechanism to reduce it; this process let us enhance the sensors’ part-to-part repeatability from an industrial standpoint. Two mechanisms were explored to reduce the variability in FSR sensitivity. (i) It was found that the output voltage at null force can be used to discard noncompliant sensors that exhibit either too high or too low sensitivity; this observation is a novel contribution from this research. (ii) An alternative method was also proposed and validated that let us trim the sensitivity of FSRs by means of changing the input voltage. This study was carried out from 64 specimens of Interlink FSR402 sensors.

A Novel Broadband Forcecardiography Sensor for Simultaneous Monitoring of Respiration, Infrasonic Cardiac Vibrations and Heart Sounds

The precordial mechanical vibrations generated by cardiac contractions have a rich frequency spectrum. While the lowest frequencies can be palpated, the higher infrasonic frequencies are usually captured by the seismocardiogram (SCG) signal and the audible ones correspond to heart sounds. Forcecardiography (FCG) is a non-invasive technique that measures these vibrations via force sensing resistors (FSR). This study presents a new piezoelectric sensor able to record all heart vibrations simultaneously, as well as a respiration signal. The new sensor was compared to the FSR-based one to assess its suitability for FCG. An electrocardiogram (ECG) lead and a signal from an electro-resistive respiration band (ERB) were synchronously acquired as references on six healthy volunteers (4 males, 2 females) at rest. The raw signals from the piezoelectric and the FSR-based sensors turned out to be very similar. The raw signals were divided into four components: Forcerespirogram (FRG), Low-Frequency FCG (LF-FCG), High-Frequency FCG (HF-FCG) and heart sounds (HS-FCG). A beat-by-beat comparison of FCG and ECG signals was carried out by means of regression, correlation and Bland–Altman analyses, and similarly for respiration signals (FRG and ERB). The results showed that the infrasonic FCG components are strongly related to the cardiac cycle (R² > 0.999, null bias and Limits of Agreement (LoA) of ± 4.9 ms for HF-FCG; R² > 0.99, null bias and LoA of ± 26.9 ms for LF-FCG) and the FRG inter-breath intervals are consistent with ERB ones (R² > 0.99, non-significant bias and LoA of ± 0.46 s). Furthermore, the piezoelectric sensor was tested against an accelerometer and an electronic stethoscope: synchronous acquisitions were performed to quantify the similarity between the signals. ECG-triggered ensemble averages (synchronized with R-peaks) of HF-FCG and SCG showed a correlation greater than 0.81, while those of HS-FCG and PCG scored a correlation greater than 0.85. The piezoelectric sensor demonstrated superior performances as compared to the FSR, providing more accurate, beat-by-beat measurements. This is the first time that a single piezoelectric sensor demonstrated the ability to simultaneously capture respiration, heart sounds, an SCG-like signal (i.e., HF-FCG) and the LF-FCG signal, which may provide information on ventricular emptying and filling events. According to these preliminary results the novel piezoelectric FCG sensor stands as a promising device for accurate, unobtrusive, long-term monitoring of cardiorespiratory functions and paves the way for a wide range of potential applications, both in the research and clinical fields. However, these results should be confirmed by further analyses on a larger cohort of subjects, possibly including also pathological patients.

Respiration Monitoring via Forcecardiography Sensors

In the last few decades, a number of wearable systems for respiration monitoring that help to significantly reduce patients’ discomfort and improve the reliability of measurements have been presented. A recent research trend in biosignal acquisition is focusing on the development of monolithic sensors for monitoring multiple vital signs, which could improve the simultaneous recording of different physiological data. This study presents a performance analysis of respiration monitoring performed via forcecardiography (FCG) sensors, as compared to ECG-derived respiration (EDR) and electroresistive respiration band (ERB), which was assumed as the reference. FCG is a novel technique that records the cardiac-induced vibrations of the chest wall via specific force sensors, which provide seismocardiogram-like information, along with a novel component that seems to be related to the ventricular volume variations. Simultaneous acquisitions were obtained from seven healthy subjects at rest, during both quiet breathing and forced respiration at higher and lower rates. The raw FCG sensor signals featured a large, low-frequency, respiratory component (R-FCG), in addition to the common FCG signal. Statistical analyses of R-FCG, EDR and ERB signals showed that FCG sensors ensure a more sensitive and precise detection of respiratory acts than EDR (sensitivity: 100% vs. 95.8%, positive predictive value: 98.9% vs. 92.5%), as well as a superior accuracy and precision in interbreath interval measurement (linear regression slopes and intercepts: 0.99, 0.026 s (R² = 0.98) vs. 0.98, 0.11 s (R² = 0.88), Bland–Altman limits of agreement: ±0.61 s vs. ±1.5 s). This study represents a first proof of concept for the simultaneous recording of respiration signals and forcecardiograms with a single, local, small, unobtrusive, cheap sensor. This would extend the scope of FCG to monitoring multiple vital signs, as well as to the analysis of cardiorespiratory interactions, also paving the way for the continuous, long-term monitoring of patients with heart and pulmonary diseases.

Development of Flexible and Conductive Immiscible Thermoplastic/Elastomer Monofilament for Smart Textiles Applications Using 3D Printing

3D printing utilized as a direct deposition of conductive polymeric materials onto textiles reveals to be an attractive technique in the development of functional textiles. However, the conductive fillers—filled thermoplastic polymers commonly used in the development of functional textiles through 3D printing technology and most specifically through Fused Deposition Modeling (FDM) process—are not appropriate for textile applications as they are excessively brittle and fragile at room temperature. Indeed, a large amount of fillers is incorporated into the polymers to attain the percolation threshold increasing their viscosity and stiffness. For this reason, this study focuses on enhancing the flexibility, stress and strain at rupture and electrical conductivity of 3D-printed conductive polymer onto textiles by developing various immiscible polymer blends. A phase is composed of a conductive polymer composite (CPC) made of a carbon nanotubes (CNT) and highly structured carbon black (KB)- filled low-density polyethylene (LDPE) and another one of propylene-based elastomer (PBE) blends. Two requirements are essential to create flexible and highly conductive monofilaments for 3D-printed polymers onto textile materials applications. First, the co-continuity of both the thermoplastic and the elastomer phases and the location of the conductive fillers in the thermoplastic phase or at the interface of the two immiscible polymers are necessary to preserve the flexibility of the elastomer while decreasing the global amount of charges in the blends. In the present work based on theoretical models, when using a two-step melt process, the KB and CNT particles are found to be both preferentially located at the LDPE/PBE interface. Moreover, in the case of the two-step extrusion, SEM characterization showed that the KB particles were located in the LDPE while the CNT were mainly at the LDPE/PBE interface and TEM analysis demonstrated that KB and CNT nanoparticles were in LDPE and at the interface. For one-step extrusion, it was found that both KB and CNT are in the PBE and LDPE phases. These selective locations play a key role in extending the co-continuity of the LDPE and PBE phases over a much larger composition range. Therefore, the melt flow index and the electrical conductivity of monofilament, the deformation under compression, the strain and stress and the electrical conductivity of the 3D-printed conducting polymer composite onto textiles were significantly improved with KB and CNT-filled LDPE/PBE blends compared to KB and CNT-filled LDPE separately. The two-step extrusion processed 60%(LDPE16.7% KB + 4.2% CNT)/40 PBE blends presented the best properties and almost similar to the ones of the textile materials and henceforth, could be a better material for functional textile development through 3D printing onto textiles.

An Ultra-Sensitive Modular Hybrid EMG-FMG Sensor with Floating Electrodes

To improve the reliability and safety of myoelectric prosthetic control, many researchers tend to use multi-modal signals. The combination of electromyography (EMG) and forcemyography (FMG) has been proved to be a practical choice. However, an integrative and compact design of this hybrid sensor is lacking. This paper presents a novel modular EMG–FMG sensor; the sensing module has a novel design that consists of floating electrodes, which act as the sensing probe of both the EMG and FMG. This design improves the integration of the sensor. The whole system contains one data acquisition unit and eight identical sensor modules. Experiments were conducted to evaluate the performance of the sensor system. The results show that the EMG and FMG signals have good consistency under standard conditions; the FMG signal shows a better and more robust performance than the EMG. The average accuracy is 99.07% while using both the EMG and FMG signals for recognition of six hand gestures under standard conditions. Even with two layers of gauze isolated between the sensor and the skin, the average accuracy reaches 90.9% while using only the EMG signal; if we use both the EMG and FMG signals for classification, the average accuracy is 99.42%.

Design of Pressure Sensor Arrays to Assess Electrode Contact Pressure During In Vivo Recordings in the Gut. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020;2020:4204-4207. [PMID: 33018924 DOI: 10.1109/embc44109.2020.9175843]

The gastrointestinal (GI) tract is in part controlled by slow wave electrical activity. Recordings of slow waves with high-resolution (HR) electrode arrays are used to characterize normal and abnormal conduction pathways. Improving the quality of these electrical recordings is important for developing a better understanding of abnormal activity. Contact pressure is one factor that can affect the quality of electrical recordings. We compared the performance of two pressure sensing devices for measuring HR electrode array contact pressure. A Velostat-based sensor array was custom designed and built in a 4 × 2 conguration (area: 30 mm² per sensor) to be integrated into electrical recordings. Commercially available FlexiForce A201 sensors were used to compare to the Velostat-based sensors. Benchtop testing of these sensors was performed; the error of the Velostat-based sensors (14-31%) was better than that of the FlexiForce sensors (20-49%) within a range of 2666-6666 Pa. The Velostat-based sensors were also more repeatable than the FlexiForce sensors over the same pressure range. Simultaneous pressure and slow wave recordings were performed in vivo on a rabbit small intestine. The Velostat-based sensors were able to resolve spatiotemporal changes in contact pressure in the range of 0-10 000 Pa.

Assessing the Influence of the Sourcing Voltage on Polyaniline Composites for Stress Sensing Applications

Polyaniline (PANI) has recently gained great attention due to its outstanding electrical properties and ease of processability; these characteristics make it ideal for the manufacturing of polymer blends. In this study, the processing and piezoresistive characterization of polymer composites resulting from the blend of PANI with ultra-high molecular weight polyethylene (UHMWPE) in different weight percentages (wt %) is reported. The PANI/UHMWPE composites were uniformly homogenized by mechanical mixing and the pellets were manufactured by compression molding. A total of four pellets were manufactured, with PANI percentages of 20, 25, 30 and 35 wt %. Fourier-transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), differential thermal analysis (DTA), scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS) were used to confirm the effective distribution of PANI and UHMWPE particles in the pellets. A piezoresistive characterization was performed on the basis of compressive forces at different voltages; it was found that the error metrics of hysteresis and drift were influenced by the operating voltage. In general, larger voltages lowered the error metrics, but a reduction in sensor sensitivity came along with voltage increments. In an attempt to explain such a phenomenon, the authors developed a microscopic model for the piezoresistive response of PANI composites, aiming towards a broader usage of PANI composites in strain/stress sensing applications as an alternative to carbonaceous materials.

Fabrication and Evaluation of a Novel Non-Invasive Stretchable and Wearable Respiratory Rate Sensor Based on Silver Nanoparticles Using Inkjet Printing Technology

The respiration rate (RR) is a key vital sign that links to adverse clinical outcomes and has various important uses. However, RR signals have been neglected in many clinical practices for several reasons and it is still difficult to develop low-cost RR sensors for accurate, automated, and continuous measurement. This study aims to fabricate, develop and evaluate a novel stretchable and wearable RR sensor that is low-cost and easy to use. The sensor is fabricated using the soft lithography technique of polydimethylsiloxane substrates (PDMS) for the stretchable sensor body and inkjet printing technology for creating the conductive circuit by depositing the silver nanoparticles on top of the PDMS substrates. The inkjet-printed (IJP) PDMS-based sensor was developed to detect the inductance fluctuations caused by respiratory volumetric changes. The output signal was processed in a Wheatstone bridge circuit to derive the RR. Six different patterns for a IJP PDMS-based sensor were carefully designed and tested. Their sustainability (maximum strain during measurement) and durability (the ability to go bear axial cyclic strains) were investigated and compared on an automated mechanical stretcher. Their repeatability (output of the sensor in repeated tests under identical condition) and reproducibility (output of different sensors with the same design under identical condition) were investigated using a respiratory simulator. The selected optimal design pattern from the simulator evaluation was used in the fabrication of the IJP PDMS-based sensor where the accuracy was inspected by attaching it to 37 healthy human subjects (aged between 19 and 34 years, seven females) and compared with the reference values from e-Health nasal sensor. Only one design survived the inspection procedures where design #6 (array consists of two horseshoe lines) indicated the best sustainability and durability, and went through the repeatability and reproducibility tests. Based on the best pattern, the developed sensor accurately measured the simulated RR with an error rate of 0.46 ± 0.66 beats per minute (BPM, mean ± SD). On human subjects, the IJP PDMS-based sensor and the reference e-Health sensor showed the same RR value, without any observable differences. The performance of the sensor was accurate with no apparent error compared with the reference sensor. Considering its low cost, good mechanical property, simplicity, and accuracy, the IJP PDMS-based sensor is a promising technique for continuous and wearable RR monitoring, especially under low-resource conditions.

Ultrasoft, Adhesive and Millimeter Scale Epidermis Electronic Sensor for Real-Time Enduringly Monitoring Skin Strain

Epidermal electronic sensors (EESs) possess great advantages in the real-time and enduring monitoring of human vital information compared to the traditional medical device for intimately making contact with human skin. Skin strain is a significant and effective routine to monitor motion, heart rate, wrist pulse, and skin growth in wound healing. In this paper, a novel skin sensor combined with a ternary conductive nanocomposite (Carbon black (CB)/Decamethylcyclopentasiloxane (D5)/Silbione) and a two-stage serpentine connector is designed and fabricated to monitor skin strain. The ultrasoft (~2 kPa) and adhesive properties of the ternary conductive nanocomposite ensure the capacity of the EES to intimately couple with human skin in order to improve accuracy with a relative error of 3.39% at strain 50% as well as a large strain range (0~50%) and gauge factor (GF ~2.5). The millimeter scale EES (~5 mm × 1 mm × 100 μm), based on the micro-nano fabrication technique, consisted of a two-stage serpentine connector and screen print of the ternary conductive nanocomposite. EESs with high comprehensive performance (electrical and mechanical properties) are fabricated to confirm the analytical results and monitor the motion of a human hand. The good agreement between experimental and analytical results paves the way for bettering monitoring of skin growth during wound healing in order to avoid necrosis and scarring. This EES in monitoring the motion of a human exhibit presents a promising application for assisting prosthetic movement.

A Flexible and Highly Sensitive Inductive Pressure Sensor Array Based on Ferrite Films

There is a rapid growing demand for highly sensitive, easy adaptive and low-cost pressure sensing solutions in the fields of health monitoring, wearable electronics and home care. Here, we report a novel flexible inductive pressure sensor array with ultrahigh sensitivity and a simple construction, for large-area contact pressure measurements. In general, the device consists of three layers: a planar spiral inductor layer and ferrite film units attached on a polyethylene terephthalate (PET) membrane, which are separated by an array of elastic pillars. Importantly, by introducing the ferrite film with an excellent magnetic permeability, the effective permeability around the inductor is greatly influenced by the separation distance between the inductor and the ferrite film. As a result, the value of the inductance changes largely as the separation distance varies as an external load applies. Our device has achieved an ultrahigh sensitivity of 1.60 kPa^-1 with a resolution of 13.61 Pa in the pressure range of 0-0.18 kPa, which is comparable to the current state-of-the-art flexible pressure sensors. More remarkably, our device shows an outstanding stability when exposed to environmental interferences, e.g., electrical noises from skin surfaces (within 0.08% variations) and a constant pressure load for more than 32 h (within 0.3% variations). In addition, the device exhibits a fast response time of 111 ms and a good repeatability under cyclic pressures varying from 38.45 to 177.82 Pa. To demonstrate its practical usage, we have successfully developed a 4 × 4 inductive pressure sensor array into a wearable keyboard for a smart electronic calendar application.

Evaluation of Force Sensing Resistors for the Measurement of Interface Pressures in Lower Limb Prosthetics

Understanding pressure distributions at the limb-socket interface is essential to the design and evaluation of prosthetic components for lower limb prosthesis users. Force sensing resistors (FSRs) are employed in prosthetics research to measure pressure at this interface due to their low cost, thin profile, and ease of use. While FSRs are known to be sensitive to many sources of error, few studies have systematically quantified these errors using test conditions relevant to lower limb prosthetics. The purpose of this study was to evaluate FSR accuracy for the measurement of lower limb prosthetics interface pressures. Two FSR models (Flexiforce A201 and Interlink 402) were subjected to a series of prosthetic-relevant tests. These tests included: (1) static compression, (2) cyclic compression, and (3) a combined static and cyclic compression protocol mimicking a variable activity (Walk-Sit-Stand) procedure. Flexiforce sensors outperformed Interlink sensors and were then subjected to two additional tests: (4) static curvature and (5) static shear stress. Results demonstrated that FSRs experienced significant errors all five tests. We concluded that: (1) if used carefully, FSRs can provide an estimate of prosthetic interface pressure, but these measurements should be interpreted within the expected range of possible measurement error given the setup; (2) FSRs should be calibrated in a setup that closely matches how they will be used for taking measurements; and (3) both Flexiforce and Interlink sensors can be used to estimate interface pressures, however in most cases Flexiforce sensors are likely to provide more accurate measurements.

Modelling and Design of MEMS Piezoresistive Out-of-Plane Shear and Normal Stress Sensors

In this paper, the design of MEMS piezoresistive out-of-plane shear and normal stress sensor is described. To improve the sensor sensitivity, a methodology by the incorporation of stress concentration regions, namely surface trenches in the proximity of sensing elements was explored in detail. The finite element (FE) model, verified by a five-layer analytical model was developed as a tool to model the performance of the sensor and guide the geometric optimization of the surface trenches. Optimum location and dimensions of the surface trenches have been obtained through a comprehensive FE analysis. The microfabrication and packing scheme was introduced to prototype the sensor with optimum geometric characteristics of surface trenches. Signal output from the prototyped sensor was tested and compared with those from FE simulation. Good agreement has been achieved between the simulation and experimental results. Moreover, the results suggest the incorporation of surface trenches can help improve the sensor sensitivity. More specifically, the sum of signal output from the sensor chip with surface trenches are 4.52, 5.06 and 5.72 times higher compared to flat sensor chip for center sensing area, edge sensing areas 1 and 2, respectively.

Self-Compensated Driving Circuit for Reducing Drift and Hysteresis in Force Sensing Resistors

Force Sensing Resistors (FSRs) are manufactured from a blend of conductive nanoparticles dispersed in an insulating polymer matrix. FSRs exhibit large amounts of hysteresis and drift error, but currently, a great effort is placed on improving their performance through different techniques applied during sensor manufacturing. In this article, a novel technique for improving the performance of FSRs is presented; the method can be applied to already-manufactured sensors, which is a clear benefit of the proposed procedure. The method is based on driving the sensors with a modified-astable 555 oscillator, in which the oscillation frequency is set from the sensor’s capacitance and resistance. Considering that the sensor’s capacitance and resistance have opposite signs in the drift characteristic, the driving circuit provides self-compensated force measurements over extended periods of time. The feasibility of the driving circuit to reduce hysteresis and to avoid sensitivity degradation is also tested. In order to obtain representative results, the experimental measurements from this study were performed over eight FlexiForce A201-25 sensors.

A Piezoresistive Sensor to Measure Muscle Contraction and Mechanomyography

Measurement of muscle contraction is mainly achieved through electromyography (EMG) and is an area of interest for many biomedical applications, including prosthesis control and human machine interface. However, EMG has some drawbacks, and there are also alternative methods for measuring muscle activity, such as by monitoring the mechanical variations that occur during contraction. In this study, a new, simple, non-invasive sensor based on a force-sensitive resistor (FSR) which is able to measure muscle contraction is presented. The sensor, applied on the skin through a rigid dome, senses the mechanical force exerted by the underlying contracting muscles. Although FSR creep causes output drift, it was found that appropriate FSR conditioning reduces the drift by fixing the voltage across the FSR and provides voltage output proportional to force. In addition to the larger contraction signal, the sensor was able to detect the mechanomyogram (MMG), i.e., the little vibrations which occur during muscle contraction. The frequency response of the FSR sensor was found to be large enough to correctly measure the MMG. Simultaneous recordings from flexor carpi ulnaris showed a high correlation (Pearson's r > 0.9) between the FSR output and the EMG linear envelope. Preliminary validation tests on healthy subjects showed the ability of the FSR sensor, used instead of the EMG, to proportionally control a hand prosthesis, achieving comparable performances.