Finger Sensor Research Articles

Photocuring 3D printable flexible strain sensor enhanced by in situ grown silk fibroin nanoparticles

The growing demand for flexible strain sensors across diverse applications necessitates elevated standards regarding the outstanding mechanical performance and customizability of their polymer-based substrates. In this study, the ionically conductive gels with in situ generation of silk fibroin nanoparticles (SFN) for photocuring 3D printing were successfully designed. The silk fibroin underwent chain folding as a result of phase separation with the photocurable resins (PCR), leading to the direct in situ generation of nanoparticles within the PCR. The results demonstrated a significant improvement in the stability of liquid PCR/SFN and the mechanical performance of ionogels prepared via the in situ SFN growth method, manifesting a notable enhancement in tensile strength and elongation at break by 340% and 62.8%, respectively. Moreover, reliable loading behavior was maintained under large strain conditions of 600% tensile strain and 50% compressive strain throughout long-term cycles, accompanied by stable signals. The customization, stability, and sensitivity of sensing behavior were achieved through the fabrication of customized porous-structured flexible sensor components from the PCR/SFN system, including a series of finger, wrist, and throat sensors, as well as an insole gait sensor. The facile strategy of in situ SFN growth could be an effective approach for manufacturing nanocomposite conductive ionogels, offering new avenues for modulating the mechanical performance of 3D-printed flexible strain sensors.

Evaluating the Accuracy of Off-Label Placement of Pulse Oximetry Sensors in Comparison to On-Label Placement in the Adult Cardiac Intensive Care Unit Patient Population.

Continuous pulse oximetry (Spo2) is a commonly utilized tool to obtain an indirect, noninvasive measurement of hemoglobin oxygen saturation. Difficulty obtaining measurement with Spo2 sensors can lead nurses to try off-label sites until they find placement that provides a signal. Currently, there is limited evidence to support this application. The purpose of this study was to evaluate the accuracy of off-label placement of pulse oximetry sensors in comparison to on-label placement in adult cardiac intensive care patients. Data were collected on 24 participants. At the time of a medically necessary arterial blood gas laboratory draws, 4 Spo2 measurements were gathered from an on-label finger sensor, an off-label finger sensor, an on-label ear sensor, and an off-label ear sensor. Results were analyzed using 4 Pearson correlation coefficients, Bland-Altman plots, and 2 linear mixed-effect models. Our study found that while both our on-label finger and off-label finger pulse oximetry sensor overestimated when compared to the arterial hemoglobin saturation (gold standard), there was greater overestimation found with the off-label placement. Though there was not a significant difference observed between the ear probe on the nose and the gold standard, figures examining off-label ear probe and gold standard measures show that, in lower ranges of oxygen saturation, the off-site probe substantially overestimates true oxygen saturation, while in higher ranges of oxygen saturation, the off-site ear probe underestimates true oxygen saturation. No changes should be made to the current practice of using pulse oximetry sensor placement.

Validity and reliability of measurement of peripheral oxygen saturation during the 6-Minute Walk Test in patients with systemic sclerosis

Peripheral oxygen saturation (SpO2) using the fingers may have important limitations due to Raynaud’s phenomenon and sclerodactyly in patients with systemic sclerosis (SSc). Sensors located at more central body positions may be more accurate as these as less prone to Raynaud attacks. To determine the validity and reliability of the SpO2 measured at the finger, forehead, and earlobe during the 6-Minute Walk Test (6MWT). Eighty two patients with SSc had an arterial line placed while performing the 6MWT. Peripheral oxygen saturation was simultaneously measured by finger, forehead, and earlobe sensors and compared to the arterial oxygen saturation (SaO2) measured before and after the 6MWT. 40 patients repeated the 6MWT one week later to determine re-test reliability. We used Bland–Altman plots to display the agreement between SpO2 and SaO2. The intraclass correlation coefficient for repeated measurement of minimum SpO2 was calculated. The mean difference between SpO2 and SaO2 after the 6MWT was − 3% (SD: ± 5), 0% (SD: ± 2), and 1% (SD: ± 2) for the finger, forehead, and earlobe, respectively. The minimum SpO2 measured at the finger demonstrated the poorest re-test reliability: The ICC (95% CI) showed good agreement using the ear and forehead probe (ICCear = 0.89 [95% CI 0.80; 0.94]; ICCforehead = 0.77 [95% CI 0.60; 0.87]), while a modest reliability was found using the finger probe (ICCfinger = 0.65 95% CI [0.43; 0.80]). SpO2 should be measured using either the earlobe or forehead during the 6MWT in patients with SSc. Clinical Trials.Gov (NCT04650659).

Engineered IPMC sensors: modeling, characterization, and application towards wearable postural-tactile measurement

This paper focuses on the modeling and development of engineered ionic polymer-metal composite (eIPMC) sensors for applications such as postural and tactile measurement in mechatronics/robotics-assisted finger rehabilitation therapy. Specifically, to tailor the sensitivity of the device, eIPMCs, fabricated using a polymer-surface abrading technique, are utilized as the sensing element. An enhanced chemoelectromechanical model is developed that captures the effect of the abrading process on the multiphysics sensing behavior under different loading conditions. The fabricated sensors are characterized using scanning electron microscopy imaging and cyclic voltammetry and chronoamperometry. Results show significant improvement in the electrochemical properties, including charge storage, double layer capacitance, and surface conductance, compared to the control samples. Finally, prototype postural-tactile finger sensors composed of different eIPMC variants are created and their performance validated under postural and tactile experiments. The tailored eIPMC sensors show increased open-circuit voltage response compared to control IPMCs, with 7.7- and 4.7-times larger peak-to-peak bending response under postural changes, as well as a 3.2-times more sensitive response under compression during tactile loading, demonstrating the feasibility of eIPMC sensors.

Implementation of a novel thoracostomy tube trainer with real-time feedback

ObjectivesSimulation-based training leads to improved clinical performance but may be influenced by quality and frequency of training. Within simulation training, chest tube insertion remains a challenge as one of the...

A data-driven robotic tactile material recognition system based on electrode array bionic finger sensors

A data-driven robotic tactile material recognition system based on electrode array bionic finger sensors

Estimating the cardiac signals of chimpanzees using a digital camera: validation and application of a novel non-invasive method for primate research

Cardiac measures such as heart rate measurements are important indicators of both physiological and psychological states. However, despite their extraordinary potential, their use is restricted in comparative psychology because traditionally cardiac measures involved the attachment of sensors to the participant’s body, which, in the case of undomesticated animals such as nonhuman primates, is usually only possible during anesthesia or after extensive training. Here, we validate and apply a camera-based system that enables contact-free detection of animals’ heart rates. The system automatically detects and estimates the cardiac signals from cyclic change in the hue of the facial area of a chimpanzee. In Study 1, we recorded the heart rate of chimpanzees using the new technology, while simultaneously measuring heart rate using classic PPG (photoplethysmography) finger sensors. We found that both methods were in good agreement. In Study 2, we applied our new method to measure chimpanzees’ heart rate in response to seeing different types of video scenes (groupmates in an agonistic interaction, conspecific strangers feeding, nature videos, etc.). Heart rates changed during video presentation, depending on the video content: Agonistic interactions and conspecific strangers feeding lead to accelerated heart rate relative to baseline, indicating increased emotional arousal. Nature videos lead to decelerated heart rate relative to baseline, indicating a relaxing effect or heightened attention caused by these stimuli. Our results show that the new contact-free technology can reliably assess the heart rate of unrestrained chimpanzees, and most likely other primates. Furthermore, our technique opens up new avenues of research within comparative psychology and facilitates the health management of captive individuals.

Design of Wearable Finger Sensors for Rehabilitation Applications

As an emerging technology, smart textiles have attracted attention for rehabilitation purposes or to monitor heart rate, blood pressure, breathing rate, body posture, as well as limb movements. Traditional rigid sensors do not always provide the desired level of comfort, flexibility, and adaptability. To improve this, recent research focuses on the development of textile-based sensors. In this study, knitted strain sensors that are linear up to 40% strain with a sensitivity of 1.19 and a low hysteresis characteristic were integrated into different versions of wearable finger sensors for rehabilitation purposes. The results showed that the different finger sensor versions have accurate responses to different angles of the index finger at relaxation, 45° and 90°. Additionally, the effect of spacer layer thickness between the finger and sensor was investigated.

An ultra-sensitive humidity sensor based on lead-free halide perovskite Cs2TeI6 for real-time human breath and finger monitoring

Lead halide perovskites have been investigated for humidity sensors as they have shown outstanding success in optoelectronic applications but still suffer from some inherent instability and toxicity issues. In this work, we synthesized the all-inorganic, lead-free halide perovskite Cs2TeI6 by a hydrothermal method and demonstrated its impedimetric humidity-sensitive performance for the first time. The Cs2TeI6 sensor exhibits an ultra-high impedance variation of 4.25 × 103 with a response time of 3 s at a relative humidity (RH) of 11–97% and offers good reversibility and impressive stability. On this basis, a human respiration monitoring sensor and a relative humidity non-contact finger sensor were simulated to perform real-time humidity detection in relation to the human body. Our results provide a favorable candidate for humidity detection and further provide new insights into high-performance sensory devices using lead-free halide perovskites for real-time touchless physiological monitoring.

Anthropomorphic Grasping of Complex-Shaped Objects Using Imitation Learning

This paper presents an autonomous grasping approach for complex-shaped objects using an anthropomorphic robotic hand. Although human-like robotic hands have a number of distinctive advantages, most of the current autonomous robotic pickup systems still use relatively simple gripper setups such as a two-finger gripper or even a suction gripper. The main difficulty of utilizing human-like robotic hands lies in the sheer complexity of the system; it is inherently tough to plan and control the motions of the high degree of freedom (DOF) system. Although data-driven approaches have been successfully used for motion planning of various robotic systems recently, it is hard to directly apply them to high-DOF systems due to the difficulty of acquiring training data. In this paper, we propose a novel approach for grasping complex-shaped objects using a high-DOF robotic manipulation system consisting of a seven-DOF manipulator and a four-fingered robotic hand with 16 DOFs. Human demonstration data are first acquired using a virtual reality controller with 6D pose tracking and individual capacitive finger sensors. Then, the 3D shape of the manipulation target object is reconstructed from multiple depth images recorded using the wrist-mounted RGBD camera. The grasping pose for the object is estimated using a residual neural network (ResNet), K-means clustering (KNN), and a point-set registration algorithm. Then, the manipulator moves to the grasping pose following the trajectory created by dynamic movement primitives (DMPs). Finally, the robot performs one of the object-specific grasping motions learned from human demonstration. The suggested system is evaluated by an official tester using five objects with promising results.

Acute Effects of a Single-Session of Full-Body Foam Rolling on Heart Rate Variability.

Self-myofascial release has been demonstrated to increase relaxation and improve blood flow, yet it is unknown if it can elicit an acute effect on heart rate variability (HRV). This study aimed to determine if a single-bout of foam rolling could increase parasympathetic activity as measured by HRV. Twenty (20) participants volunteered and their baseline HRV was assessed using a finger sensor while lying supine, and then a second measure was recorded with them sitting upright with feet on the ground. This study utilized a practical HRV collection method designed for use in the field settings, and the data is recorded in arbitrary units (A.U.). Participants then oscillated on a closed-cell cylindrical foam roller using their body weight on the triceps surae, hamstrings, quadriceps, lumbar spine, and pectoral muscles each for 60 sec. Participants first massaged the right limb and then repeated on the matching muscle group on the left before continuing to the next region. Follow-up HRV measurements were recorded using the same procedures. Paired samples t tests assessing pre- and post-foam-rolling HRV measures in supine and seated positions revealed no difference between supine measures (p = .05, d = 0.21), nor the seated measures (p = .27, d = 0.17) among all participants. When sexes were analyzed separately, males showed a significant decrease in HRV in supine positions (p = .03, d = 0.33), but females did not (p = .55, d = 0.09). The single bout of foam rolling on large muscle groups did not increase parasympathetic activity as hypothesized. Males and females responded differently in supine positions, but no difference was present in seated positions across sexes. The task of self-massage may have prevented the anticipated response from the massage. Further research should investigate if passive massage is more effective on HRV response.

A new noninvasive finger sensor (NICCI system) for continuous blood pressure and pulse pressure variation monitoring: A method comparison study in patients having neurosurgery.

The NICCI system (Getinge, Gothenburg, Sweden) is a new noninvasive haemodynamic monitoring system using a finger sensor. We aimed to investigate the performance of the NICCI system to measure blood pressure and pulse pressure variation compared with intra-arterial measurements. A prospective method comparison study. University Medical Center Hamburg-Eppendorf, Hamburg, Germany. Forty-seven neurosurgery patients. We performed a method comparison study in 47 neurosurgery patients to compare NICCI blood pressure measurements (BP NICCI ) with intra-arterial blood pressure measurements (BP ART ) (Bland-Altman analysis, four-quadrant plot, error grid analysis) and NICCI pulse pressure variation measurements (PPV NICCI ) with pulse pressure variation calculated manually from the intra-arterial blood pressure waveform (PPV ART ) (Bland-Altman analysis, predictive agreement, Cohen's kappa). The mean of the differences ± standard deviation (95% limits of agreement) between BP NICCI and BP ART was 11 ± 10 mmHg (-8 to 30 mmHg) for mean blood pressure (MBP), 3 ± 12 mmHg (-21 to 26 mmHg) for systolic blood pressure (SBP) and 12 ± 10 mmHg (-8 to 31 mmHg) for diastolic blood pressure (DBP). In error grid analysis, 54% of BP NICCI and BP ART MBP measurement pairs were classified as 'no risk', 43% as 'low risk', 3% as 'moderate risk' and 0% as 'significant risk' or 'dangerous risk'. The mean of the differences between PPV NICCI and PPV ART was 1 ± 3% (-4 to 6%). The predictive agreement between PPV NICCI and PPV ART was 80% and Cohen's kappa was 0.55. The absolute agreement between BP NICCI and BP ART was not clinically acceptable. We recommend not using the current version of the NICCI system for blood pressure monitoring during surgery. The absolute agreement between PPV NICCI and PPV ART was clinically acceptable with moderate predictive agreement regarding pulse pressure variation categories. The NICCI system needs to be further developed and re-evaluated when an improved version is available. The study was registered in the German Clinical Trials Register (DRKS00023188) on 2 October 2020.

Biomarkers based on continuous non-invasive blood pressure - review and outlook

Abstract Stationary devices for continuous blood pressure (BP) with user-friendly finger sensors are getting common in various clinical fields and new wearable BP-monitors are about to enter the medical world. Apart from the commonly used parameters systolic and diastolic BP, beat-to-beat as well as pulse shape information of these devices is not easily accessible. This article is a review of existing pattern recognition analysis and an outlook to new biomarkers giving a deep insight into the cardiovascular system and its control.

Geometric design optimization of polyaniline/graphite nanocomposite based flexible humidity sensor for contactless sensing and breath monitoring

• Polyaniline-graphite nanocomposite based 2D humidity sensor was screen-printed. • Adding graphite leads to faster response, improved thermal stability and hysteresis. • Improved long term stability with high performance was demonstrated over 180 days. • Sensor geometry (inter-electrode distance and number of electrodes) was optimized. • Contactless sensing and respiration monitoring applications were demonstrated. We report a low cost flexible polyaniline-graphite nanocomposite based resistive type humidity sensor, screen printed on a PET substrate with interdigitated silver electrodes. The composite with a 3:1 ratio of polyaniline and graphite was found to be ideal with a sensing response of 93.4%, took 24 s to reach 54% RH, a maximum response/recovery time of 35/39 s and low hysteresis (1.12%). Graphite acting as the support material increased the sensor's thermal stability, allowing it to be operated at temperatures as high as 55 ⁰C. To further improve sensor performance and find an optimum device architecture, geometric parameters such as inter-electrode distance and number of electrodes were studied and optimised. Based on this, a relative humidity contactless finger sensor (1.5 cm range) and a human breath monitoring sensor to map different breathing rates were demonstrated.

A new noninvasive finger sensor (NICCI system) for cardiac output monitoring: A method comparison study in patients after cardiac surgery.

The new noninvasive finger sensor system NICCI (Getinge; Gothenburg, Sweden) allows continuous cardiac output monitoring. We aimed to investigate its cardiac output measurement performance. To investigate the NICCI system's cardiac output measurement performance. Prospective method comparison study. University Medical Center Hamburg-Eppendorf, Hamburg, Germany. Fifty-one patients after cardiac surgery. We performed a method comparison study in 51 patients after cardiac surgery to compare NICCI cardiac output (CO NICCI ) and NICCI cardiac output calibrated to pulmonary artery thermodilution cardiac output measurement (CO NICCI-CAL ) with pulmonary artery thermodilution cardiac output (CO PAT ). As a secondary analysis we also compared CNAP cardiac output (CO CNAP ) and externally calibrated CNAP cardiac output (CO CNAP-CAL ) with CO PAT . We analysed 299 cardiac output measurement pairs. The mean of the differences (95% limits of agreement) between CO NICCI and CO PAT was 0.6 (-1.8 to 3.1) l min -1 with a percentage error of 48%. The mean of the differences between CO NICCI-CAL and CO PAT was -0.4 (-1.9 to 1.1) l min -1 with a percentage error of 29%. The mean of the differences between CO CNAP and CO PAT was 1.0 (-1.8 to 3.8) l min -1 with a percentage error of 53%. The mean of the differences between CO CNAP-CAL and CO PAT was -0.2 (-2.0 to 1.6) l min -1 with a percentage error of 35%. The agreement between CO NICCI and CO PAT is not clinically acceptable. The study was registered in the German Clinical Trial Register (DRKS00023189) after inclusion of the first patient on October 2, 2020.

Improved Heart Rate Measurement Accuracy by Reducing Artifact Noise from Finger Sensors Using Digital Filters

Heart rate is an important indicator in the health sector that can be used as an effective and rapid evaluation to determine the health status of the body. Motion or noise artifacts, power line interference, low amplitude PPG, and signal noise are all issues that might arise when measuring heart rate. This study aims to develop a digital filter that reduces noise artifacts on the finger sensor to improve heart rate measurement accuracy. Adaptive LMS and Butterworth are the two types of digital filters used in this research. In this study, data were collected from the patient while he or she was calm and moving around. In this research, the Nellcor finger sensor was employed to assess the blood flow in the fingers. The heart rate sensor will detect any changes in heart rate, and the measurement results will be presented on a personal computer (PC) as signals and heart rate values. The results of this investigation showed that utilizing an adaptive LMS filter and a Butterworth low pass filter with a cut-off frequency of 6Hz, order 4, and a sampling frequency of 1000Hz, with the Butterworth filter producing the least error value of 7.57 and adaptive LMS maximum error value of 27.65 as predicted by the researcher to eliminate noise artifacts. This research could be applied to other healthcare equipment systems that are being monitored to increase patient measurement accuracy.

Heart rate variability as a predictor of disease exacerbation in pediatric inflammatory bowel disease

ObjectivesHeart rate variability (HRV), a marker of the parasympathetic vagal activity, was reportedly significantly lower in patients with inflammatory bowel disease (IBD) compared to healthy controls. The aim of this study was to evaluate HRV as a predictor of clinical outcomes in pediatric IBD. MethodsThis was a prospective study. Children (12–18 years of age) with IBD were prospectively recruited. Each patient underwent two 10-min HRV measurements by means of a photoplethysmograph finger sensor. The square root of the mean squared differences of successive R-R pulse intervals (RMSSD), an indirect index of vagal activity, was calculated. Clinical data, including demographic variables, disease activity and course, medications, and laboratory results were collected during a follow-up of 12 months. The relation between RMSSD and clinical outcomes was examined, adjusting for confounders. ResultsA total of 34 children with IBD were included. Patients in clinical remission had a significantly higher RMSSD compared to patients with active disease (67.72 ± 27.81 versus 45.76 ± 22.04, respectively, P = 0.022). A multivariate analysis revealed that a higher RMSSD was a significant and independent predictor of lower risk of IBD exacerbation (odds ratio = 0.941, 95% confidence interval 0.887–0.998, p = 0.044). ConclusionHRV correlates with IBD activity and may also serve as an independent predictor of disease exacerbation in pediatric IBD.

Smoking Cessation System for Preemptive Smoking Detection.

Smoking cessation is a significant challenge for many people addicted to cigarettes and tobacco. Mobile health-related research into smoking cessation is primarily focused on mobile phone data collection either using self-reporting or sensor monitoring techniques. In the past 5 years with the increased popularity of smartwatch devices, research has been conducted to predict smoking movements associated with smoking behaviors based on accelerometer data analyzed from the internal sensors in a user's smartwatch. Previous smoking detection methods focused on classifying current user smoking behavior. For many users who are trying to quit smoking, this form of detection may be insufficient as the user has already relapsed. In this paper, we present a smoking cessation system utilizing a smartwatch and finger sensor that is capable of detecting pre-smoking activities to discourage users from future smoking behavior. Pre-smoking activities include grabbing a pack of cigarettes or lighting a cigarette and these activities are often immediately succeeded by smoking. Therefore, through accurate detection of pre-smoking activities, we can alert the user before they have relapsed. Our smoking cessation system combines data from a smartwatch for gross accelerometer and gyroscope information and a wearable finger sensor for detailed finger bend-angle information. We compare the results of a smartwatch-only system with a combined smartwatch and finger sensor system to illustrate the accuracy of each system. The combined smartwatch and finger sensor system performed at an 80.6% accuracy for the classification of pre-smoking activities compared to 47.0% accuracy of the smartwatch-only system.

Non-Invasive Classification of Blood Glucose Level for Early Detection Diabetes Based on Photoplethysmography Signal

Monitoring systems for the early detection of diabetes are essential to avoid potential expensive medical costs. Currently, only invasive monitoring methods are commercially available. These methods have significant disadvantages as patients experience discomfort while obtaining blood samples. A non-invasive method of blood glucose level (BGL) monitoring that is painless and low-cost would address the limitations of invasive techniques. Photoplethysmography (PPG) collects a signal from a finger sensor using a photodiode, and a nearby infrared LED light. The combination of the PPG electronic circuit with artificial intelligence makes it possible to implement the classification of BGL. However, one major constraint of deep learning is the long training phase. We try to overcome this limitation and offer a concept for classifying type 2 diabetes (T2D) using a machine learning algorithm based on PPG. We gathered 400 raw datasets of BGL measured with PPG and divided these points into two classification levels, according to the National Institute for Clinical Excellence, namely, “normal” and “diabetes”. Based on the results for testing between the models, the ensemble bagged trees algorithm achieved the best results with an accuracy of 98%.

Comparison of forehead and finger oximetry sensors during the six minute walk test.

BackgroundMeasurement of oxygen saturation (SpO2) during the 6 minute walk test (6MWT) could be impacted by the measurement site.AimsTo compare SpO2 and heart rate (HR) between forehead and finger sensors during the 6MWT. Sensor readings were also to be compared for signal quality and with capillary blood gas (CBG) pre and post 6MWT.Method80 subjects with pulmonary vascular disease (PVD) and/or interstitial lung disease (ILD) performed the 6MWT. Pulse oximetry was recorded at 30 s intervals. CBG was taken pre and post 6MWT to determine capillary oxygen saturation (SCO2).ResultsThe forehead sensor recorded higher values for SpO2 (p < 0.001) and HR (p < 0.01) compared with the finger sensor during the 6MWT. For both sensors, the demonstrated bias compared to CBG post 6MWT was higher and more variable in subjects who desaturated. During the 6MWT there was a higher occurrence (p < 0.001) of poor signal quality in the finger sensor compared with the forehead sensor.ConclusionThis study suggests that the sensor site can impact pulse oximetry readings. The variance in bias suggests pulse oximetry may not accurately reflect SCO2 measurements particularly in subjects who desaturate during 6MWT.