Skin-mounted Sensors Research Articles

Flexible Sensor-based Whole-body Biomechanics of Exoskeleton-assisted Patient Handling

The issue of work-related musculoskeletal disorders (WMSDs) stemming from manual handling tasks remains a significant economic and societal burden, with healthcare workers being one of the most persistently affected groups. Exoskeletons have seen growing implementation for aiding manual handling tasks in industrial sectors. Traditional measurements and analyses of joint kinematics and dynamics commonly utilize optical motion capture systems and force plates. Nevertheless, the limitations of optical motion capture systems include their dependence on marker visibility and the necessity for a controlled lab environment. An innovative wireless technology featuring miniaturized, skin-mounted sensors, BioStamp nPoint (MC10, Inc., MA, USA) exhibits significant potential in addressing the challenges mentioned above. Therefore, the objective of this study was to explore a flexible sensor-based approach to assessing the effects of a back exoskeleton on joint kinematics during patient handling.

Iontronic Dynamic Sensor with Broad Bandwidth and Flat Frequency Response Using Controlled Preloading Strategy.

Rapid advancements in human-machine interaction and voice biometrics impose desirability on soft mechanical sensors for sensing complex dynamic signals. However, existing soft mechanical sensors mainly concern quasi-static signals such as pressure and pulsation for health monitoring, limiting their applications in emerging wearable electronics. Here, we propose a hydrogel-based soft mechanical sensor that enables recording a wide range of dynamic signals relevant to humans by combining a preloading design strategy and iontronic sensing mechanism. The proposed sensor offers a two-orders-of-magnitude larger working bandwidth (up to 1000 Hz) than most of the reported soft mechanical sensors and meanwhile provides a high sensitivity (-23 dB) that surpasses the common commercial microphone. The amplitude-frequency characteristic of the proposed sensor can be precisely tuned to meet the desired requirement by adjusting the preloads and the parameters of the microstructured hydrogel. The sensor is capable of recording instrumental sounds with high fidelity from simple pure tones to melodic songs. Demonstration of a skin-mountable sensor used for human-voice-based remote control of a toy car shows great potential for applications in the voice user interface of human-machine interactions.

Wearable fabric-based ZnO nanogenerator for biomechanical and biothermal monitoring

Wearable devices that can mechanically conform to human skin are a necessity for reliable monitoring and decoding of biomechanical activities through skin. Most inorganic piezoelectrics, however, lack deformability and damage tolerance, impeding stable motion monitoring. Here, we present an air-permeable fabric-based ZnO nanogenerator with mechanical adaptivity to diverse deformations for wearable piezoelectric sensors, collecting biomechanical health data. We fabricate ZnO nanorods incorporated throughout the entire nylon fabric, with a strategically positioned neutral mechanical plane, for bending-sensitive electronics (2.59 μA mm). Its hierarchically interlocked geometry also permits sensitive tactile sensing (0.15 nA kPa-1). Various physiological information about activities, including pulse beating, breathing, saliva swallowing, and coughing, is attained using skin-mounted sensors. Further, the pyroelectric sensing capability of a mask-attached device is demonstrated by identifying specific respiratory patterns. Our wearable healthcare sensors hold great promise for real-time monitoring of health-related vital signs, informing individuals’ health status without disrupting their daily lives.

Continuous Glucose Monitoring in Endurance Athletes: Interpretation and Relevance of Measurements for Improving Performance and Health

Blood glucose regulation has been studied for well over a century as it is intimately related to metabolic health. Research in glucose transport and uptake has also been substantial within the field of exercise physiology as glucose delivery to the working muscles affects exercise capacity and athletic achievements. However, although exceptions exist, less focus has been on blood glucose as a parameter to optimize training and competition outcomes in athletes with normal glucose control. During the last years, measuring glucose has gained popularity within the sports community and successful endurance athletes have been seen with skin-mounted sensors for continuous glucose monitoring (CGM). The technique offers real-time recording of glucose concentrations in the interstitium, which is assumed to be equivalent to concentrations in the blood. Although continuous measurements of a parameter that is intimately connected to metabolism and health can seem appealing, there is no current consensus on how to interpret measurements within this context. Well-defined approaches to use glucose monitoring to improve endurance athletes’ performance and health are lacking. In several studies, blood glucose regulation in endurance athletes has been shown to differ from that in healthy controls. Furthermore, endurance athletes regularly perform demanding training sessions and can be exposed to high or low energy and/or carbohydrate availability, which can affect blood glucose levels and regulation. In this current opinion, we aim to discuss blood glucose regulation in endurance athletes and highlight the existing research on glucose monitoring for performance and health in this population.

Flexible biosensor based on signal amplification of gold nanoparticles-composite flower clusters for glucose detection in sweat

Flexible non-invasive glucose monitoring sensor addresses the limitations of intermittent detection and provides the opportunity for optimal therapeutic interventions. However, the low sensitivity of non-invasive sensors restricted their wide applications. In this study, a facile and versatile three-dimensional flexible glucose sensor based on nano-material signal amplification through the structural design and surface modification of sensing electrodes was constructed. Tannic acid-3-aminopropyltriethoxysilane (TA-APTES) coatings were prepared on the activated carbon cloth (aCC) via Michael addition and Schiff base reactions, followed by in situ reductions of gold nanoparticles (AuNPs) to yield AuNPs/TA-APTES/aCC electrodes. Subsequently, glucose oxidases (GOx) were immobilized at the surface of AuNPs to form the sensor. The GOx AuNPs/TA-APTES/aCC sensors exhibit high sensitivity, low detection limit, and fast response rate. The advantage of the GOx AuNPs/TA-APTES/aCC sensors is further illustrated by the excellent stability and the performance in sweat samples with complex components. The design concept of the GOx AuNPs/TA-APTES/aCC for flexible biosensors could potentially drive the development of flexible skin-mountable sensors for monitoring glucose in biofluids.

Atypical triceps surae force and work patterns underlying gait in children with cerebral palsy.

The purpose of this study was to quantitatively assess Achilles tendon mechanical behavior during gait in children with cerebral palsy (CP). We used a newly designed noninvasive sensor to measure Achilles tendon force in 11 children with CP (4F, 8-16 years old) and 15 typically developing children (controls) (9F, 8-17 years old) during overground walking. Mechanical work loop plots (force-displacement plots) were generated by combining muscle-tendon kinetics, kinematics, and EMG activity to evaluate the Achilles tendon work generated about the ankle. Work loop patterns in children with CP were substantially different than those seen in controls. Notably, children with CP showed significantly diminished work production at their preferred speed compared to controls at their preferred speed and slower speeds. Despite testing a heterogeneous population of children with CP, we observed a homogenous spring-like muscle-tendon behavior in these participants. This is in contrast with control participants who used their plantar flexors like a motor during gait. Statement of Clinical Significance: These data demonstrate the potential for using skin-mounted sensors to objectively evaluate muscle contributions to work production in pathological gait.

Science, Medicine, and the Anesthesiologist

Science, Medicine, and the Anesthesiologist

Validation method for body-mounted sensor attachments

Abstract Small sensor devices like inertial measurement units enable mobile movement and gait analysis, whereby existing systems differ in data acquisition, data processing, and gait parameter calculation. Concerning the validation, recent studies focus on the captured motion and the influence of sensor positioning with respect to the accuracy of the computed biomechanical parameters in comparison to a reference system. Although soft tissue artifact is a major source of error for skin-mounted sensors, there are no investigations regarding the relative movement between the body segment and sensor attachment itself. The aim of this study is to find an evaluation method and to determine parameters that allow the validation of various sensor attachment types and different sensor positionings. The analysis includes the comparison between an adhesive and strap attachment variant as well as the frontal and lateral sensor placement. To validate different attachments, an optical marker-based tracking system was used to measure the body segment and sensor position during movement. The distance between these two positions was calculated and analyzed to determine suitable validation parameters. Despite the exploratory research, the results suggest a feasible validation method to detect differences between the attachments, independent of the sensor type. To have representative and statistically validated results, further studies that involve more participants are necessary.

Role of data measurement characteristics in the accurate detection of Parkinson\u2019s disease symptoms using wearable sensors

BackgroundParkinson’s disease (PD) is a progressive neurological disease, with characteristic motor symptoms such as tremor and bradykinesia. There is a growing interest to continuously monitor these and other symptoms through body-worn sensor technology. However, limited battery life and memory capacity hinder the potential for continuous, long-term monitoring with these devices. There is little information available on the relative value of adding sensors, increasing sampling rate, or computing complex signal features, all of which may improve accuracy of symptom detection at the expense of computational resources. Here we build on a previous study to investigate the relationship between data measurement characteristics and accuracy when using wearable sensor data to classify tremor and bradykinesia in patients with PD.MethodsThirteen individuals with PD wore a flexible, skin-mounted sensor (collecting tri-axial accelerometer and gyroscope data) and a commercial smart watch (collecting tri-axial accelerometer data) on their predominantly affected hand. The participants performed a series of standardized motor tasks, during which a clinician scored the severity of tremor and bradykinesia in that limb. Machine learning models were trained on scored data to classify tremor and bradykinesia. Model performance was compared when using different types of sensors (accelerometer and/or gyroscope), different data sampling rates (up to 62.5 Hz), and different categories of pre-engineered features (up to 148 features). Performance was also compared between the flexible sensor and smart watch for each analysis.ResultsFirst, there was no effect of device type for classifying tremor symptoms (p > 0.34), but bradykinesia models incorporating gyroscope data performed slightly better (up to 0.05 AUROC) than other models (p = 0.01). Second, model performance decreased with sampling frequency (p < 0.001) for tremor, but not bradykinesia (p > 0.47). Finally, model performance for both symptoms was maintained after substantially reducing the feature set.ConclusionsOur findings demonstrate the ability to simplify measurement characteristics from body-worn sensors while maintaining performance in PD symptom detection. Understanding the trade-off between model performance and data resolution is crucial to design efficient, accurate wearable sensing systems. This approach may improve the feasibility of long-term, continuous, and real-time monitoring of PD symptoms by reducing computational burden on wearable devices.

(Invited) Wearable and Flexible Bio-Electronics Enabled By 'crack'-Driven Transfer Printing Methods

Emerging transfer printing methods provide means to build a range of mechanically flexible and wearable bioelectronics, opening up a new prospect in the field of biomedical technologies. The mechanical flexibility allow the devices to intimately integrate with biological systems such as biological cells, tissues, and/or the skin at their length scale. The embedded semiconducting nanomaterials provide the electronic functionalities that can monitor and/or stimulate them with spatial and temporal controls. This presentation will talk about a novel class of transfer printing method by exploiting controlled “crack” that is capable of liberating various nanoelectronics from their native wafer over large scale. The liberated nanoelectronics can be then thinly placed onto an arbitrary surface of biological systems of interest including cells and tissues, and therefore can provide the desired electronic functionalities at the intimate interface. A multiscale computational model that incorporates atomistic debonding mechanisms into macroscale interface delamination reveals the underlying working mechanisms and provide a quantitative guidance for controllable cracking process. The knowledge obtained from these studies provides important insights to improve the manufacturability in terms of scalability, controllability, and reproducibility. System-level demonstrations include skin-mountable sensors and cell-injectable silicon nano-needles, which can validate their utility in wearable healthcare systems and intracellular drug delivery platform. Discussions about the results of detailed experimental and theoretical studies will follow to reveal the essential attributes of the materials, devices, and fabrication process.

Quantification of Equine Sacral and Iliac Motion During Application of Manual Forces and Comparison Between Motion Capture With Skin-Mounted and Bone-Fixated Sensors

Diagnosis of sacroiliac dysfunction in horses includes manual motion palpation of the equine ilium and sacrum. Motion of the ilium and sacrum during manual force application to the equine pelvis has been measured previously in vitro. The aim of this study was to measure the amount and direction of motion in vivo, including comparison of bone-fixated and skin-mounted inertial sensors. Sensors were skin-mounted over tuber sacrale (TS) and third sacral spinous process of six Thoroughbred horses and later attached via Steinmann pins inserted into the same bony landmarks. Orientations of each TS and sacrum were recorded by one investigator during six trials of manual force applied to the pelvis, inducing cranial, caudal, and oblique rotations. Mean values were reported in Euler angles for the three orthogonal planes lateral bending, flexion–extension (FE), and axial rotation (AR). Differences between skin- and bone-fixated markers were determined with significance set at P < .05. The largest mean values recorded during rotations applied to the pelvises were for FE, (2.08° ± 0.35°) with bone-fixated sensors. AR gave the largest values recorded with skin mountings (1.70° ± 0.48°). There was a poor correlation between skin-mounted and bone-fixated markers with AR being the orthogonal plane in which results from skin mounting were closest to results from bone-fixated sensors Bony kinematics during external movement applied to the pelvis cannot be predicted from skin-mounted sensors, due to differences between skin- and bone-mounted sensors.

Dispenser printing of piezo-resistive nanocomposite on woven elastic fabric and hysteresis compensation for skin-mountable stretch sensing

Recently, piezo-resistive nanocomposites have emerged as an important smart material for realizing less obtrusive and more comfortable stretch sensing applications. To manufacture cost-effective and skin-mountable stretch sensor, dispenser printing is advantageous method because piezo-resistive nanocomposites can be directly printed on a woven elastic fabric in various patterns. However, both electrical and mechanical properties of the nanocomposites need to be modulated to achieve favorable sensing performance as well as strong adhesion between the nanocomposite and the fabric to sustain large strains. Moreover, inherent hysteretic behavior of the soft nanocomposite should be compensated to obtain consistent stretch sensing. This paper presents silicone rubber mixed with long multi-walled carbon nanotubes (Long-MWCNTs) composites as a piezo-resistive transducing material for dispenser printing. High aspect ratio of the Long-MWCNTs resulted in low viscosity of a liquid state nanocomposite and high electrical conductivity. Due to the low viscosity, the liquid state nanocomposite could permeate into gaps of the woven elastic fabrics and ensured strong bonding force in large strains up to 35%. In addition, a modified Prandtl-Ishilinskii (MPI) model was adopted to compensate for piezo-resistive hysteresis of the nanocomposite. For validation, the skin-mountable sensor was applied to estimate rotation angle of a wrist. The sensor system estimated the rotation angle of the wrist with an estimation error of 1.93 degrees within 65 degrees range (2.9%) for the step increment and decrement test, and 7.15 degrees within 75 degrees range (9.5%) for the arbitrary movement test. Thus, the experimental results show that the dispenser printing method incorporated with hysteresis compensation can provide a guideline to implement skin-mountable smart fabrics for stretch sensing using various nanocomposites

Head Impact Exposure in Junior and Adult Australian Football Players.

This study measured and compared the frequency, magnitude, and distribution of head impacts sustained by junior and adult Australian football players, respectively, and between player positions over a season of games. Twelve junior and twelve adult players were tracked using a skin-mounted impact sensor. Head impact exposure, including frequency, magnitude, and location of impacts, was quantified using previously established methods. Over the collection period, there were no significant differences in the impact frequency between junior and adult players. However, there was a significant increase in the frequency of head impacts for midfielders in both grades once we accounted for player position. A comparable amount of head impacts in both junior and adult players has implications for Australian football regarding player safety and medical coverage as younger players sustained similar impact levels as adult players. The other implication of a higher impact profile within midfielders is that, by targeting education and prevention strategies, a decrease in the incidence of sports-related concussion may result.

Numerical Modeling of the Transient Chilldown of a Cryogenic Propellant Transfer Line

Before cryogenic fuel depots can be fully realized, efficient methods with which to chill down the spacecraft transfer line and receiver tank are required. This paper presents numerical modeling of the chilldown of a liquid hydrogen tank-to-tank propellant transfer line using the Generalized Fluid System Simulation Program. To compare with data from recently concluded turbulent liquid hydrogen chilldown experiments, seven different cases were run across a range of inlet liquid temperatures and mass flow rates. Both trickle and pulse chilldown methods were simulated. The Generalized Fluid System Simulation Program model qualitatively matches external skin-mounted temperature readings, but large differences are shown between measured and predicted internal stream temperatures. Discrepancies are attributed to the simplified model correlation used to compute two-phase flow, boiling heat transfer. Flow visualization from testing shows that the initial bottoming out of skin-mounted sensors corresponds to annular flow but that considerable time is required for the stream sensor to achieve steady state as the system moves through annular, churn, and bubbly flows. The Generalized Fluid System Simulation Program model does adequately well in tracking trends in the data, but further work is needed to refine the two-phase flow modeling to better match observed test data.

Broadband measurement of translational and angular vibrations using a single continuously scanning laser Doppler vibrometer

A continuous scanning laser Doppler velocimetry (CSLDV) technique is used to measure the low frequency broadband vibrations associated with human skeletal muscle vibrations (typically f < 100 Hz) by continuously varying the orientation of laser beam over distances that are short compared to the characteristic wavelengths of the vibrations. The high frequency scan (compared to the vibration frequency) enables the detection of broadband translational and angular velocities at a single point using amplitude demodulation of the CSDLV signal. For instance, linear scans allow measurement of the normal surface velocity and one component of angular velocity vector, while circular scans allow measurement of an additional angular velocity component. This CSLDV technique is first validated here using gel samples mimicking soft tissues and then applied to measure multiple degrees of freedom (DOF) of a subject's hand exhibiting fatigue-induced tremor. Hence this CSLDV technique potentially provides a means for measuring multiple DOF of small human body parts (e.g., fingers, tendons, small muscles) for various applications (e.g., haptic technology, remote surgery) when the use of skin-mounted sensors (e.g. accelerometers) can be problematic due to mass-loading artifacts or tethering issues.

Synchronized vibrations measurements at multiple locations using a single continuously scanning laser doppler vibrometer. Applications to non-contact sensing of human body vibrations

Laser Doppler vibrometry (LDV) is a non-contact method to measure surface velocity. Typical LDV configurations uses one fixed laser (He-Ne) beam at a specific point and orientation on a surface under test. A continuously scanning laser Doppler vibrometry (CSLDV) technique using a single laser beam performing quickly a long scan was developed to measure surface velocity at each laser position during its scan. This fast CSLDV can then replace several fixed LDVs. This technique is especially advantageous for sensing human body natural vibrations (typically below 100 Hz) at multiple locations (e.g., along small muscles) as it does not require traditional skin-mounted sensors (e.g., accelerometers array), which eliminates mass artifacts and the set-up time to attach those sensors. Experimental measurements were conducted using a CSLDV with a 200 Hz linear scan rate, over scan lengths up to 5 cm, to measure low-frequency vibrations (f&amp;lt;100 Hz) on gel samples which mimic human soft tissues. Validations of the CSLDV measurements were done using an array of several fixed LDVs distributed along the same scan line. The effects of speckle noise on CSLDV measurements will be quantified. Applications of this CSLDV technique for active and passive elastography measurements will be presented.

Measurement of Knee Laxity and Pivot-Shift Kinematics With Magnetic Sensors

This article describes work to develop a system to measure translational and rotational knee laxity and complex “dynamic” tests, such as the pivot-shift test, by the use of electromagnetic sensors mounted onto the limb segments with specially developed splints and clamps. We have measured in vitro and in vivo the motion of bone-mounted sensors versus skin-mounted sensors, and thus shown that there was an overall accuracy of approximately ±1 mm in translation and ±1° in rotation when the movements were relatively slow. It was found that, for clinical pivot-shift testing, the dynamic motion led to inaccuracy because of the inertia of the sensor mounting system, which led to the peaks of the sudden reduction motions not being measured; this system requires further development. We show that it also is possible to use this system in the clinic to record both rotational and translational knee laxity motions, both of which are integral to the pivot-shift instability. The force and torque were applied to the limb with sets of constant-force springs, which allowed the knee to be flexed while maintaining a constant load across the knee. This maneuver led to graphs showing the limits of translation and rotation laxity, across the range of knee flexion, for a series of 60 patients. It was then shown that the pivot-shift motion occurred within these laxity limits. The level of measurement accuracy means that the system described should be clinically useful.

Study of the motion artefacts of skin-mounted inertial sensors under different attachment conditions

A common problem shared by accelerometers, inertial sensors and any motion measurement method based on skin-mounted sensors is the movement of the soft tissues covering the bones. The aim of this work is to propose a method for the validation of the attachment of skin-mounted sensors. A second-order (mass–spring–damper) model was proposed to characterize the behaviour of the soft tissue between the bone and the sensor. Three sets of experiments were performed. In the first one, different procedures to excite the system were evaluated to select an adequate excitation stimulus. In the second one, the selected stimulus was applied under varying attachment conditions while the third experiment was used to test the model. The heel drop was chosen as the excitation method because it showed lower variability and could discriminate between different attachment conditions. There was, in agreement with the model, a trend to increase the natural frequency of the system with decreasing accelerometer mass. An important result is the development of a standard procedure to test the bandwidth of skin-mounted inertial sensors, such as accelerometers mounted on the skin or markers heavier than a few grams.

Passive in vivo elastography from skeletal muscle noise

Measuring the in vivo elastic properties of muscles (e.g., stiffness) provides a means for diagnosing and monitoring muscular activity. The authors demonstrated a passive in vivo elastography technique without an active external radiation source. This technique instead uses cross correlations of contracting skeletal muscle noise recorded with skin-mounted sensors. Each passive sensor becomes a virtual in vivo shear wave source. The results point to a low-cost, noninvasive technique for monitoring biomechanical in vivo muscle properties. The efficacy of the passive elastography technique originates from the high density of cross paths between all sensor pairs, potentially achieving the same sensitivity obtained from active elastography methods.

MODELLING OF LUMBAR SIPNE MOTION USING BA YESIAN BELIEF NETWORK

Seventeen healthy volunteers (4 male and 17 female, age 71.8±3.3 years old, mean body height = 156.1±8.9cm, mean body weight = 59.0±11.3kg, body mass index (BMI) = 24.1±3.6) were recruited. An electromagnetic motion tracking system (Fastrak®, Polhemus, 40 Hercules Dr, Colchester, Vermont, USA) was used to obtain skin displacement information related to the movements of the lumbar spine. Four sensors, which were fitted with radio-opaque markers, were attached to the skin overlying spinous processes from the first lumbar (L1) to first sacral (S1) vertebrae. Lateral radiographs (Philips M50 CP-H X-ray machine) were obtained for each subject with the sensors attached to the back for three postures: neutral upright, full flexion, and full extension. Bayesian network was employed to describe the associations among element nodes, which represented the variables of interest and the observations. In this study, the variables of interest were the coordinates of the four corners of the quadrangles which represented the vertebrae, and the observations were the coordinates of the radio-opaque markers of the skin-mounted sensors. Belief propagation algorithms were used to predict the variables of interest based on the framework of the network. The flexion and extension images were used as input data for modeling, together with movement information derived from skin surface using an electromagnetic motion tracking system. The validity of the model was established by comparing the predicted positions of the vertebrae in the neutral position with those obtained from the x-ray image in the neutral posture.