Non-contact Sensor Research Articles

3D Vibration Analysis using Phase-Based Displacement Estimation and Stereo Cameras

Non-contact sensors are increasingly integral to the field of Structural Health Monitoring (SHM), with camera being widely utilized due to their high spatial resolution and cost-effectiveness in measuring structural displacements. Phase-based optical flow (POF) techniques have proven valuable for accurate and computationally efficient 2D vibration measurements. However, these techniques are typically confined to single-camera systems and encounter challenges in measuring vibrations in out-of-plane directions. Previous research on 3D vibration measurement has predominantly centered on pixel intensity-based techniques using stereo camera systems. Although these methods demonstrate high performance in calculating global strains and stresses, they are less suitable for accurate vibration measurement. To address these limitations, this study proposes a novel 3D vibration measurement approach that integrates POF within the context of stereo camera systems. 2D vibrations are extracted by applying Complex Gabor filters to stereo images, and subsequently, 3D vibration measurements are estimated through camera calibration and triangulation, using computed camera internal and external parameters. To validate the method, modal analysis experiments are conducted on an aluminum plate. The 3D vibration measurement results are compared with those obtained through 3D Digital Image Correlation (DIC) and contact sensors and the accuracy is demonstrated.

Phase-based Full-field Displacement Measurement with Phase Nonlinearity Weighting Process

The camera, as a non-contact sensor, has evolved into a robust tool for measuring the full-field vibration of complex structures. It offers distinct advantages over traditional contact sensors, including flexible positioning, simultaneous multi-point tracking, and high spatial resolution. Vibration imaging techniques have been developed to identify structural operational conditions through feature extraction methods. Phase-based vibration imaging techniques can visualize full-field operational shapes or vibrational features in a less-supervised manner. While phase-based optical flow with Gabor filters provides accurate displacement estimation, managing a large amount of image data can pose challenges in extracting full-field displacement efficiently. In this paper, we propose a compressive sensing approach for full-field phase-based optical flow and vibration imaging. Compressive sensing serves as an efficient sampling method that requires significantly fewer frames than traditional approaches, selecting frames at less than one third of the original video. Features are extracted from the displacement of the compressed video frames. Subsequently, the vibration features are transformed into images. The proposed methodology is validated through experiments conducted on an air compressor. Comparative results between vibration imaging from video with compressive sensing and that from the original video demonstrate that vibrational features can be extracted using only a few frames of the original video. Consequently, this approach can reduce processing time and data volume while preserving the performance of vibration feature extraction.

Application of regression and remote sensing technology for determining sufficiency of contact-based sensors in long-term SHM of civil structures

Long-span bridges are huge, complex, and vital civil engineering structures for every society. Due to the critical importance of such structures, structural health monitoring (SHM) systems utilizing both contact and non-contact sensor platforms are often considered to measure influential parameters, such as environmental/operational factors and various structural responses. In some circumstances, such as bridge locations, services, weather conditions, harsh environments, and budget constraints, it may not be practical or necessary to utilize all possible sensor systems and measure all parameters, especially environmental/operational (E/O) factors. To devise and implement an affordable SHM program for large-scale civil structures, it is necessary to develop more efficient sensing systems compared to state-of-the-art ones. Against this backdrop, this paper proposes a new methodology for verifying the sufficiency of contact-based E/O sensors installed in long-span bridges using spaceborne remote sensing and regression modeling. The main premise of the proposed methodology is that structural responses obtained from certain remote sensing products enable us to assess the sufficiency of contact sensors and the impacts of both measured and unmeasured E/O conditions. Utilizing structural displacement responses from remote sensing and measured E/O data from contact-based sensors, a supervised regression model using a feedforward artificial neural network is developed to reconstruct or predict displacement responses and to determine the regression accuracy using the R-squared measure. When the accuracy rate is high, one can infer that the contact-based E/O sensors are sufficient; otherwise, it may be essential to install additional E/O sensors and apply the proposed methodology with new information. Real-world long-span bridges are examined to validate the proposed methodology, using displacement responses and recorded temperature data from contact-based thermocouples. The results demonstrate that the methodology offers an effective but affordable system for long-term SHM programs.

Enhancing Predictive Maintenance in Contour Cutting Machines: A Similarity-Based Approach for Band Blade Remaining Useful Life Estimation and Early Fault Detection

Anticipating the Remaining Useful Life (RUL) of cutting tools is crucial for optimising operational efficiency, ensuring safety, and minimising maintenance costs. This paper addresses the unresolved challenge of unexpected band blade failures in contour cutting machines within the foam and plastic industry, where such failures disrupt production, lead to material wastage, and pose operational hazards. Band blades circulate continuously at very high speeds during operation, and no classic sensor technology can be applied to them. Any information required to estimate the condition of the band blades must be acquired externally. Using similarity-based prediction models, a strategy for estimating band blades' effective RUL is proposed. Historical failure data is systematically collected from a contour-cutting machine operating under various load conditions using multiple contact and non-contact sensors mounted on the machine. Features are extracted and processed from the mounted sensors in both time and frequency domains using classical condition monitoring techniques. The classification of damaged and undamaged states of the blade is performed using bagged decision trees, which consider predefined health levels of the band blade during test runs. Degradation trends are generated for a test set of blade failures, and a similarity model is trained on this data to determine the remaining life. Different features are selected based on their prognostic capabilities to optimise the proposed algorithm's performance. The developed model is tested on new data, demonstrating efficacy in predicting band blades' health status and RUL with good accuracy. This research contributes to cutting tool condition monitoring and predictive maintenance by offering a novel and reliable approach for early fault detection and estimation of the RUL of band blades in contour cutting machines, mitigating disruptions, reducing material wastage, and enhancing overall operational efficiency. The procedures are validated in situ with a latest generation's real contour-cutting machine.

화물차의 제동장치에서 발생하는 과열 예측방안 연구

Recently, due to the increase in domestic and international online e-commerce platforms and the increase in container traffic at domestic ports, the operating ratio of large trucks has increased, and the number of truck fires is continuously increasing. In particular, spontaneous combustion is the most common cause of truck fires. Various academic approaches have been attempted to prevent truck fires, but due to the lack of research on the spontaneous tire ignition phenomenon that occurs during braking, this research directly designed and manufactured an experimental device to establish an environment similar to the braking system of a truck. A non-contact temperature sensor was installed on the brake device of the experimental device to collect temperature data generated from the brake device. Based on the data collected from the temperature sensor of the brake device and the temperature sensor on the tire surface, the ARIMA model among the time series prediction models was used to Appropriate parameters were selected to suit the temperature change trend, and as a result of comparing and analyzing the measured and predicted data, an accuracy of over 90% was obtained. Based on this, a plan was proposed to reduce the rate of fires in trucks by providing real-time warnings and support for truck drivers to respond to overheating phenomena occurring in the braking system.

Synthesis, luminescent and thermometric properties of the Tb3+ doped Gd2TeO6 phosphor

Gadolinium tellurate phosphor Gd2TeO6 pure and Tb3+ doped were successfully synthesised by solid-state reaction. The crystal structure and photoluminescence properties were characterised by X-ray powder diffraction (XRD) and fluorescence spectroscopy. The influence of Tb3+ concentration on the behaviour of the relative emission intensity and chromaticity coordinates were systematically investigated as a function of energy excitation and temperature. From the Tb3+ emission spectra the CIE (x,y) values and G/B = I(5D4 → 7F5)/I(5D4 → 7F6) ratio were calculated. While the G/B ratio is found temperature independent for all samples, the CIE runs from reddish to greenish region. The thermometric properties are also determined and a good relative thermal sensitivity Sr value 0.98 %K−1 was obtained. The investigation results show that these phosphors could be potentially interesting for use in white light-emitting devices as well as noncontact temperature sensors.

Validation Scores to Evaluate the Detection Capability of Sensor Systems Used for Autonomous Machines in Outdoor Environments

The characterization of the detection capability assumes significance when the reliable monitoring of the region of interest by a non-contact sensor is a safety-relevant function. This paper introduces new validation scores that evaluate the detection capability of non-contact sensors intended to be applied to outdoor machines. The scores quantify, in terms of safety, the suitability of the sensor for the intended implementation in an environmental perception system of (highly) automated machines. This was achieved by developing an extension to the new Real Environment Detection Area (REDA) method and linking the methodology with the sensor standard IEC/TS 62998-1. The extension includes point-by-point and statistic-based error evaluation which leads to the Usability-Score, Availability-Score, and Reliability-Score. By applying the principle in the agricultural sector using ISO 18497 and linking this with data from a real outdoor test stand, it was possible to show that the validation scores offer a generic approach to quantify the detection capability and express this in a machine manufacturer-oriented manner. The findings of this study have significant implications for the advancement of safety-related sensor systems integrated into machines operating in complex environments. In order to achieve full implementation, it is necessary to define in the standards which score is required for each Performance Level (PL).

Na5Y9F32:Yb3+/Ho3+/Tm3+ up-conversion luminescent single crystals for highly sensitive optical temperature sensor

A novel non-contact optical temperature sensor with excellent performance of its adequate temperature resolution (δ(T) = 0.017 K) and exceptional relative thermal sensitivity (Sr = 1.97% K−1) was developed based on the up-conversion fluorescence intensity ratio (FIR) of Ho3+/Tm3+/Yb3+ triply incorporated Na5Y9F32 single crystal grown by Bridgman method. The up-conversion (UC) emission bands at 482 nm/669 nm/700 nm of Tm3+ and 522 nm/542 nm/653 nm of Ho3+ ions were observed upon excitation of 980 nm. The effects of Yb3+ concentration from 0.5 to 4 mol% on the UC emission of the Ho3+/ Tm3+ fixed doped Na5Y9F32 single crystal were also carried out. It has been demonstrated through the calculation of the steady-state rate equation that the intensity of UC emission is linearly heightened with the pump power, confirming the conversion mechanism. The temperature sensing performance of the Ho3+/Tm3+/Yb3+ incorporated Na5Y9F32 single crystals was explored by analyzing the FIR employing thermally coupled energy levels (TCLs) and non-thermally coupled energy levels (NTCLs). The maximum values of absolute sensitivity (Sa) and relative sensitivity (Sr) of the material are estimated to be 19.1% K−1 (323 K) and 1.97% K−1 (398 K), separately, which are far higher than those of previously reported RE3+-doped UC optical temperature sensor materials. This study shows that the transparent single crystal has the great potential as a non-contact optical thermometer, and provides a new idea for studying other highly optical sensing materials.

Phase-Directed Assembly of Triboelectric Nanopaper for Self-Powered Noncontact Sensing.

Noncontact sensing technology serves as a pivotal medium for seamless data acquisition and intelligent perception in the era of the Internet of Things (IoT), bringing innovative interactive experiences to wearable human-machine interaction perception networks. However, the pervasive limitations of current noncontact sensing devices posed by harsh environmental conditions hinder the precision and stability of signals. In this study, the triboelectric nanopaper prepared by a phase-directed assembly strategy is presented, which possesses low charge transfer mobility (1618 cm2 V-1 s-1) and exceptional high-temperature stability. Wearable self-powered noncontact sensors constructed from triboelectric nanopaper operate stably under high temperatures (200 °C). Furthermore, a temperature warning system for workers in hazardous environments is demonstrated, capable of nonintrusively identifying harmful thermal stimuli and detecting motion status. This research not only establishes a technological foundation for accurate and stable noncontact sensing under high temperatures but also promotes the sustainable intelligent development of wearable IoT devices under extreme environments.

Agreement between Vital Signs Measured Using Mat-Type Noncontact Sensors and Those from Conventional Clinical Assessment.

Vital signs are crucial for assessing the condition of a patient and detecting early symptom deterioration. Noncontact sensor technology has been developed to take vital measurements with minimal burden. This study evaluated the accuracy of a mat-type noncontact sensor in measuring respiratory and pulse rates in patients with cardiovascular diseases compared to conventional methods. Forty-eight hospitalized patients were included; a mat-type sensor was used to measure their respiratory and pulse rates during bed rest. Differences between mat-type sensors and conventional methods were assessed using the Bland-Altman analysis. The mean difference in respiratory rate was 1.9 breaths/min (limits of agreement (LOA): -4.5 to 8.3 breaths/min), and proportional bias existed with significance (r = 0.63, p < 0.05). For pulse rate, the mean difference was -2.0 beats/min (LOA: -23.0 to 19.0 beats/min) when compared to blood pressure devices and 0.01 beats/min (LOA: -11.4 to 11.4 beats/min) when compared to 24-h Holter electrocardiography. The proportional bias was significant for both comparisons (r = 0.49, p < 0.05; r = 0.52, p < 0.05). These were considered clinically acceptable because there was no tendency to misjudge abnormal values as normal. The mat-type noncontact sensor demonstrated sufficient accuracy to serve as an alternative to conventional assessments, providing long-term monitoring of vital signs in clinical settings.

Self-powered noncontact triboelectric nanogenerators with microstructured square-loop surface and dielectric electron-blocking layer for far-distance motion perception and trajectory tracking

Continuous monitoring of indoor human activities is crucial for the healthcare of elder people or patients. The self-powered noncontact triboelectric nanogenerator (TENG) sensor has been recently developed as a promising noncontact sensing tool with many advantages, but its capability of detecting object motion in a far distance still remains inferior. Herein, by implementing multiple strategies of micro-structuring triboelectric surface, introducing dielectric layer, and using functional nano fillers, we develop a single-electrode-mode noncontact TENG sensor by constructing a triboelectric cobalt nanoporous carbon/Ecoflex nanocomposite layer with microstructured square-loop surface on top of a dielectric copper calcium titanate/Ecoflex nanocomposite layer with colossal permittivity. After in-depth optimization of the material selection, component composition and structure design, the developed sensor with effective electrode area of 6.25 cm2 can deliver a high output voltage of 29 V at 1 cm, and is capable of detecting motions at an extremely far distance of 6 m. Towards practical applications, the TENG unit for single-motion detection of mouth breathing, human walking, and basketball bouncing are demonstrated. Furthermore, multiple TENG units can be assembled into array to realize the complex trajectory tracking for the use of proximity touch pad, indoor human activity monitoring, and garage car parking. This work for the first time extends the TENG noncontact sensing capability to several meters, which is potential in the proximity motion detection and indoor activity monitoring.

Noncontact Sensors for Vital Signs Measurement: A Narrative Review.

Vital signs are crucial for monitoring changes in patient health status. This review compared the performance of noncontact sensors with traditional methods for measuring vital signs and investigated the clinical feasibility of noncontact sensors for medical use. We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE) database for articles published through September 30, 2023, and used the key search terms "vital sign," "monitoring," and "sensor" to identify relevant articles. We included studies that measured vital signs using traditional methods and noncontact sensors and excluded articles not written in English, case reports, reviews, and conference presentations. In total, 129 studies were identified, and eligible articles were selected based on their titles, abstracts, and full texts. Three articles were finally included in the review, and the types of noncontact sensors used in each selected study were an impulse radio ultrawideband radar, a microbend fiber-optic sensor, and a mat-type air pressure sensor. Participants included neonates in the neonatal intensive care unit, patients with sleep apnea, and patients with coronavirus disease. Their heart rate, respiratory rate, blood pressure, body temperature, and arterial oxygen saturation were measured. Studies have demonstrated that the performance of noncontact sensors is comparable to that of traditional methods of vital signs measurement. Noncontact sensors have the potential to alleviate concerns related to skin disorders associated with traditional skin-contact vital signs measurement methods, reduce the workload for healthcare providers, and enhance patient comfort. This article reviews the medical use of noncontact sensors for measuring vital signs and aimed to determine their potential clinical applicability.

Non-contact microwave sensor for FDM 3D printing quality control

ABSTRACT In recent years, 3D printing has undergone a transformational journey – from prototyping technology, limited to laboratories, to a production method used in industry – becoming a powerful tool for creating functional objects. Despite this progress, 3D printing faces ongoing challenges related to defect detection and print quality control. We present an innovative, non-contact, fast and cheap microwave sensor for detecting defects in printed components, related to both mechanical errors and conductivity inhomogeneities. We discuss in detail the methodology of the microwave surface mapping technique and the results obtained for several samples printed with popular filaments. Tests show the ability to detect faults with millimetre precision. The simple design of the entire quality control module allows for easy integration with various types of 3D printers, from popular ones used by hobbyists to professional, highly specialised ones.

Experimental and numerical investigations to the aeroelastic response of flexible thin airfoil

The paper investigates the phenomenon of the aeroelastic response of flexible thin airfoils under various angles of attack (AOAs) and flow velocities through wind tunnel experiments and numerical simulations. The vibration modal characteristics are explored, including vibration frequencies, amplitudes, modal transition, and instantaneous characteristics. Vibration is directly measured using non-contact laser sensors, and the numerical model is appropriately configured to simulate the fluid–structure interaction (FSI) problem under large deformation. Experiments cover a range of AOAs (1°–20°) and incoming velocities (from 10 to 73 m/s), with dynamic responses measured using four laser sensors. Both average and instantaneous modal response features are analyzed, revealing multi-modal characteristics as velocity and AOA increase. The vibration mode transitions from pure bending to higher-order modes as incoming velocity increases. Specifically, at higher velocities and increased AOA, the high-order vibration component shifts from bending-torsional coupled mode to pure-torsional mode. Comparison of vibration frequencies between experimental measurements and finite element method simulations highlights significant shifts, particularly in the pure-torsional mode. Furthermore, employing commercial software ANSYS CFX and ANSYS Mechanical, a two-way three-dimensional FSI model successfully replicates flutter boundaries observed experimentally at 1° AOA and approximately incoming velocity 73 m/s. This FSI model is extended to simulate the multi-modal vibrations at 15° AOA, yielding insights into flow phenomena contributing to multi-modal vibration at this AOA. An explanation is provided for the multi-modal vibration phenomenon observed in the experiments based on the above insight. Finally, the differences between the experimental and numerical simulations are speculated upon.

Facile Electret-Based Self-Powered Soft Sensor for Noncontact Positioning and Information Translation.

Noncontact sensors have demonstrated significant potential in human-machine interactions (HMIs) in terms of hygiene and less wear and tear. The development of soft, stable, and simply structured noncontact sensors is highly desired for their practical applications in HMIs. This work reports on electret-based self-powered noncontact sensors that are soft, transparent, stable, and easy to manufacture. The sensors contain a three-layer structure with a thickness of 0.34 mm that is fabricated by simply stacking a polymeric electret layer, an electrode layer, and a substrate layer together. The fabricated sensors show high charge-retention capability, keeping over 98% of the initial surface potential even after 90 h, and can accurately and repeatedly sense external approaching objects with impressive durability. The intensity of the detected signal shows a strong dependence on the distance between the object and the sensor, capable of sensing a distance as small as 2 mm. Furthermore, the sensors can report stable signals in response to external objects over 3000 cycles. By virtue of the signal dependence on distance, an intelligent noncontact positioning system is developed that can precisely detect the location of an approaching object. Finally, by integrating with eyeglasses, the transparent sensor successfully captures the movements of blinks for information translation. This work may contribute to the development of stable and easily manufactured noncontact soft sensors for HMI applications, for instance, assisting with communication for locked-in syndrome patients.

A Novel Non-Contact Method for Monitoring the Acoustic Emission From Mixed Elastohydrodynamic Lubrication Contacts

Abstract Lubricated non-conformal contacts, such as between gear teeth, operate with high levels of mixed lubrication, where the amount of direct asperity contact depends on operating parameters that influence the film thickness. Understanding of the levels of surface interaction is key to optimizing component life, and there is considerable interest in sensitive monitoring methods such as Acoustic Emission (AE). Researchers have shown that AE can detect subtle changes in lubrication conditions, using sensors mounted directly on the rotating gears. However, the use of such sensors is complex and unsuitable for implementation in real gearboxes. The alternative, of using sensors placed on housings, is hampered by signal attenuation and noise. This paper presents a novel, non-contact stationary sensor, coupled by an oil film to the rotating gear, which is shown to be capable of detecting important changes in lubrication conditions with significantly higher consistency and precision than housing-mounted sensors, whilst avoiding the complexities of gear-mounted sensors.

Development of a Six-Degree-of-Freedom Analog 3D Tactile Probe Based on Non-Contact 2D Sensors.

In this paper, a six-degree-of-freedom analog tactile probe with a new, simple, and robust mechanical design is presented. Its design is based on the use of one elastomeric ring that supports the stylus carrier and allows its movement inside a cubic measuring range of ±3 mm. The position of the probe tip is determined by three low-cost, noncontact, 2D PSD (position-sensitive detector) sensors, facilitating a wider application of this probe to different measuring systems compared to commercial ones. However, several software corrections, regarding the size and orientation of the three LED light beams, must be carried out when using these 2D sensors for this application due to the lack of additional focusing or collimating lenses and the very wide measuring range. The development process, simulation results, correction models, experimental tests, and calibration of this probe are presented. The results demonstrate high repeatability along the X-, Y-, and Z-axes (2.0 µm, 2.0 µm, and 2.1 µm, respectively) and overall accuracies of 6.7 µm, 7.0 µm, and 8.0 µm, respectively, which could be minimized by more complex correction models.

Cross-modal zero-sample diagnosis framework utilizing non-contact sensing data fusion

Gearboxes, fundamental components in the domains of manufacturing, transportation, and aerospace apparatus, are highly susceptible to impairments. The emerging technique of non-contact sensing measurement holds promise as a valuable tool for real-time monitoring and diagnosis of gearboxes, especially in challenging, dynamic environments. However, historical non-contact diagnostic techniques often face difficulties due to load-variation-induced interference, which leads to inconsistent diagnostic results. Moreover, acquiring sufficient non-contact sensing data for specific rare or severe gearbox faults can be exceedingly challenging and, at times, unattainable. This data scarcity limits the application of existing supervised and semi-supervised non-contact diagnostic methods. To address these limitations, this paper develops a novel diagnostic model, called Non-Contact Sensing Data Fusion Driven Cross-Modal Zero-sample Diagnostic Network. Specifically, we first develop a novel central fusion module to facilitate feature-level fusion at both global and local scales utilizing infrared thermal and acoustic data, thereby establishing a rich and comprehensive fault representation. Following that, we construct an end-to-end cross-modal zero-sample diagnostic architecture to mine and fuse complementary fault information. This approach enhances zero-sample diagnostic performance through efficient information utilization and cross-modal feature fusion. Afterward, we adopt a cross-modal self-enhancing fusion strategy during the training phase, which improves the information fusion performance of intra-class features from various modalities. This strategy effectively reduces misclassification risks and augments the robustness of the proposed zero-sample diagnostic network against interference from load variations. Comprehensive experimental results confirm that our proposed NCFZD sets the new state-of-the-art in multiple non-contact, zero-sample diagnostic scenarios, reaching HM scores of 86.06 %, 81.53 %, and 62.56 % respectively. By incorporating the information fusion theory, this model advances gearbox diagnostics in non-contact sensing and contributes to the broader field of information fusion theory by demonstrating its practical application in real-world problem-solving scenarios.

Enhancing force plate design through optimization of spring constant distribution

Force plates have been widely used in various scientific fields to measure ground reaction forces experienced by animals and humans. A force plate that incorporates mechanical springs and non-contact displacement sensors offers the advantages of facilely modifying its shape and performance. However, the design protocol was limited to adjusting the plate size and spring constants of the springs supporting the plate at the four corners. Herein, we propose an optimization method for determining the spring constant distribution of a force plate. The proposed design enables the use of simulations to optimize the mechanical properties of the force plate, such as resonant frequency and error due to position. The experimental results demonstrated that the resonant frequency of the fabricated force plate was 133 Hz and the error due to position was within ±5 %. These results confirm that the proposed force plate can be effectively adjusted through optimization.

Intrinsically stretchable jellyfish-like gold nanowires film as multifunctional wearable chemical and physical sensors

We report on an intrinsically stretchable jellyfish-like gold nanowires film as a multifunctional wearable platform that can detect both chemical and physical biometrics. The film inherently exhibits multifunctionality, serving directly as an electrochemical electrode, strain sensor, temperature sensor, pressure sensor, and noncontact humidity sensor without the need of any additional materials. Our results highlight the excellent electrochemical properties, evidenced by a large electrochemical active surface area (EASA) of approximately 22.39 cm2 and the ability to withstand significant strain values up to 70 %. Leveraging these attributes, a stretchable electrochemical glucose biosensor was further designed with high sensitivity (45.40μA·mM−1·cm−2) and low limit of detection (10 μM). In addition, its sensing applications in strain, temperature, pressure and noncontact humidity were systematically explored. Impressively, the gold film is capable of monitoring multiple human motions and physiological signals, including joints bending, pulse motions, throat motions (e.g., drinking, speaking, swallowing and pronunciation recognition) and breathing. Furthermore, the film exhibited great versatility by integrating with 3D printing hydrogels, enabling customized patterning. The results demonstrate that our gold nanowires coating approach represent a new route to design multimodal soft wearable platforms for applications in personalized medicine and next-generation healthcare systems.