Finger Research Articles

ZFP36 Facilitates Senecavirus A (SVA) Replication by Inhibiting the Production of Type I Interferon.

Zinc finger proteins (ZFPs) play an important role in the host-virus interplay. Zinc finger protein 36 is a member of the zinc finger protein 36 family, which includes two other paralogs, namely ZFP36L1 and ZFP36L2. Studies have demonstrated that ZFP36L1 acts as a host defender against influenza A virus and flaviviruses. However, the role of ZFP36 in host-virus interactions has not been thoroughly investigated. Here, we demonstrated that human zinc finger protein 36 (hZFP36) exhibited potent pro-viral activity during Senecavirus A infection. Overexpression of ZFP36 facilitated Senecavirus A infection, while hZFP36 knockdown inhibited viral replication. The ZF motifs of hZFP36 are key for promoting viral proliferation. hZFP36 stabilized Senecavirus A VP1 by binding to it. Furthermore, hZFP36 inhibited SeV-mediated IFN-β production through inducing caspase-dependent cleavage for MAVS. These findings provide insights into the mechanism of action of ZFP36 in host-virus interactions.

Bio-inspired carbon-based artificial muscle with precise and continuous morphing capabilities

Abstract In the face of advancements in micro-robotics, intelligent control, and precision medicine, artificial muscle actuation systems must meet demands for precise control, high stability, environmental adaptability, and high integration miniaturization. Carbon materials, with their lightweight, high strength, conductivity, and flexibility, show great potential for artificial muscles. Inspired by the butterfly's proboscis, we have developed a carbon-based artificial muscle, HsGDY-M, fabricated efficiently using an emerging hydrogen-substituted graphdiyne (HsGDY) film with an asymmetrical surface structure. This muscle features reversible, rapid, and continuously adjustable deformation capabilities similar to the butterfly's proboscis, triggered by the conversion of carbon bonds. The size of the HsGDY-M can be tuned by tailoring the HsGDY film width from ∼1 cm to 100 µm. Our research demonstrates HsGDY-M's stability and adaptability, maintaining performance at temperatures as low as -25°C. This artificial muscle was successfully integrated into a robotic mechanical arm, allowing it to swiftly adjust its posture and lift objects up to 11 times its own weight. Its beneficial responsiveness is transferable, enabling the transformation of “inert” objects like copper foil into actuators via surface bonding. Since its super sensitive and rapid deformation, HsGDY-M was applied to create a real-time tracking system for human finger bending movements, achieving real-time simulation and large-hand-to-small-hand control. Our study indicates that HsGDY-M holds significant promise for advancing smart robotics and precision medicine.

Bending and sensing performances of electro-ionic soft actuators based on carboxylated cellulose nanofibers reinforced with graphene nanoplatelets

Abstract Soft robots not only possess greater degrees of freedom and the capability for continuous transformation, but they also offer exceptionally high safety in human-robot interactions, avoiding harm to the human body. Soft actuators are essential for developing high-performance soft robots, offering significant bending deformation, rapid response times, and prolonged operational capabilities. Herein, we present an ionic electroactive soft actuator based on functional cellulose nanofibers, graphene nanoplatelets, and ionic liquid. The proposed actuator achieved a large displacement about ±8 mm under 2.0 V at 0.1 Hz, with long working stability (98% of initial peak displacement maintained after 1260 cycles of cycling). The human-robot interaction applications of this actuator were explored by simulating human fingers. More importantly, the static and dynamic sensing performances of the actuator were investigated, finding that it generated a sensing voltage of 0.37 V at a vibration displacement of only 1.75 mm. The designed actuator provides a promising approach for developing high-performance soft robots, soft actuators, flexible sensors, and flexible active devices.

A Method to Improve the Accuracy for the Comparison of Consecutively Determined Upper Limb Cross-Sectional Area Profiles of Test Subjects: Impact on (Segmental) Limb Volume and Local Limb Circumference.

Background: Chronic edema management depends on measuring small volume changes over time. Therefore, a highly sensitive, accurate, and reliable technique is needed to objectively judge sequential measurements. Methods and Results: The prototype of the Peracutus Aqua Meth (PAM), a new volumetric measuring device, was used in an experimental study. Thirty-nine healthy test subjects were measured three times. The measuring principle of the PAM is based on obtaining a profile of cross-sectional areas along the length of an object or limb. Besides total arm volumes, the volume of any chosen segment can be determined. The utmost tip of the middle finger appeared to be an unreliable reference point. Instead, the concept of "hand median" was introduced to align and compare profiles of cross-sectional areas of sequential measurements. Using the hand median strongly improved the measuring accuracy, rendering standard deviation values of 0.4%-1.3% for (segmental) volume determination. Conclusions: Measurements with the PAM show that accurate local/segmental volume determination of a limb is possible. Standard deviations of less than 1.3% are easily obtained for cross-sectional area and volume determination.

Artificial Tactile Sensory Finger for Contact Pattern Identification Based on High Spatiotemporal Piezoresistive Sensor Array.

Human fingertip tactile perception relies on the activation of densely distributed tactile receptors to identify contact patterns in the brain. Despite significant efforts to integrate tactile sensors with machine learning algorithms for recognizing physical patterns on object surfaces, developing a tactile sensing system that emulates human fingertip capabilities for identifying contact patterns with a high spatiotemporal resolution remains a formidable challenge. In this study, we present the development of an artificial tactile finger for accurate contact pattern identification, achieved through the integration of a high spatiotemporal piezoresistive sensor array (PRSA) and a convolutional neural network (CNN) model. Spatiotemporal characterization tests reveal that the artificial finger exhibits a fast temporal resolution of approximately 7 ms and achieves a two-point threshold of 1.5 mm, surpassing that of the human fingertip. To compare the performance of the artificial finger with the human finger in recognizing different patterns, we acquired pressure images by pressing the artificial finger, coated with a flexible PRSA film, onto both simple embossed and complex curved patterns while also recording human recognition results of perceiving these patterns. Experimental findings demonstrate that the artificial finger achieves higher classification accuracy in recognizing both simple and complex patterns (99.0 and 96.1%, respectively) compared to the human fingertip (69.1 and 22.7%). This artificial finger serves as a promising platform with great potential for various robotic tactile sensing applications including prosthetics, skin electronics, and robotic surgery.

Alternatives to Friction Coefficient: Fine Touch Perception Relies on Frictional Instabilities.

Fine touch perception is often correlated to material properties and friction coefficients, but the inherent variability of human motion has led to low correlations and contradictory findings. Instead, we hypothesized that humans use frictional instabilities to discriminate between objects. We constructed a set of coated surfaces with physical differences which were imperceptible by touch but created different types of instabilities based on how quickly a finger is slid and how hard a human finger is pressed during sliding. We found that participant accuracy in tactile discrimination most strongly correlated with formations of steady sliding, and response times negatively correlated with stiction spikes. Conversely, traditional metrics like surface roughness or average friction coefficient did not predict tactile discriminability. Identifying the central role of frictional instabilities as an alternative to using friction coefficients should accelerate the design of tactile interfaces for psychophysics and haptics.

A Pneumatic Soft Exoskeleton System Based on Segmented Composite Proprioceptive Bending Actuators for Hand Rehabilitation.

Soft pneumatic actuators/robotics have received significant interest in the medical and health fields, due to their intrinsic elasticity and simple control strategies for enabling desired interactions. However, current soft hand pneumatic exoskeletons often exhibit uniform deformation, mismatch the profile of the interacting objects, and seldom quantify the assistive effects during activities of daily life (ADL), such as extension angle and predicted joint stiffness. The lack of quantification poses challenges to the effective and sustainable advancement of rehabilitation technology. This paper introduces the design, modeling, and testing of pneumatic bioinspired segmented composite proprioceptive bending actuators (SCPBAs) for hand rehabilitation in ADL tasks. Inspired by human finger anatomy, the actuator's soft-joint-rigid-bone segmented structure provides a superior fit compared to continuous structures in traditional fiber-reinforced actuators (FRAs). A quasi-static model is established to predict the bending angles based on geometric parameters. Quantitative evaluations of predicted joint stiffness and extension angle utilizing proprioceptive bending are performed. Additionally, a soft under-actuated hand exoskeleton equipped with SCPBAs demonstrates their potential in ADL rehabilitation scenarios.

Modular soft pneumatic actuator mimics elephant trunk locomotion

Robots support and facilitate tasks in all life fields. Soft robots specifically have the advantages of inherent compliance, safe interaction and flexible deformability. Soft pneumatic network (Pneu-Net) is a soft pneumatic actuator (SPA) composed of network of chambers that is actuated by pneumatic power. Soft Pneu-Net fits the human interface applications perfectly. In this paper, a bio-inspired modular based design for Pneu-Net actuator is developed. The actuator mimics the elephant trunk curling to be employed for rehabilitation of human hand fingers. The actuator is an integrated four Pneu-Net modules actuator which is attached to hand’s finger. The main introduced advantages in the new developed actuator are: providing four degrees of freedom (DoF) essential for finger’s motion by single compound actuator and developing a methodology for a modular soft Pneu-Net actuator that is efficiently reproducible. The actuator’s design is developed using computer aided design (CAD) software SOLIDWORKS. The design is simulated using finite element modeling (FEM) software ABAQUS. Fabrication process uses 3D printed molds. Soft material is molded in the 3D printed molds, forming actuator’s modules. Actuator’s modules are integrated by adhesion using the soft material. A proposed non-standard hyper-elastic material biaxial tension test is introduced as a quick material properties identification method that can produce a test table used for material identification in the FEM. Enhanced version for the actuator uses reinforcement fibers. Results show advances for the reinforced actuator, as it limits the unwanted actuator’s strain and deformation. The reinforced actuator shows improved energy efficiency reaches to 46%.

Multimodal, Ultrasensitive, and Biomimetic Electronic Skin Based on Gradient Micro‐Frustum Ionogel for Imaginary Keyboard and Haptic Cognition

AbstractElectronic skins (E‐skins) are poised to revolutionize human interaction not only with one another but also with machines, electronics, and surrounding environment. However, the wearable E‐skin that simultaneously offers multiple sensing capabilities, high sensitivity, and broad sensing ranges remains a great challenge. Here, drawing inspiration from human haptic perception, a multimodal, ultrasensitive, and biomimetic E‐skin (MES) founded on micro‐frustum ionogel is developed based on iontronic capacitive and triboelectric effects for imaginary keyboard and multifunctional haptic cognition. Leveraging simultaneously the ionogel as capacitive layer and triboelectric layer, the MES enables human‐dermis perception performances of high sensitivity (357.56 kPa−1), low limit of detection (0.47 Pa), and broad linear detection range (0–500 kPa). Moreover, human finger joint movements can be precisely monitored by the attached MES and be transferred into accurate typed letter information on an imaginary keyboard. More importantly, by harnessing signal acquisition/processing circuits and machine learning, the real‐time haptic cognition of different materials, surface roughness, and contact pressure can be achieved by the MES, which endows the advancement of interaction between next‐generation intelligent robot and physical environment. Consequently, the proposed MES demonstrates impressive potentials in the fields of wearable electronics, human–machine interaction (HMI), and Artificial Intelligence (AI).

Numerical and Experimental Study of a Wearable Exo-Glove for Telerehabilitation Application Using Shape Memory Alloy Actuators

Hand paralysis, caused by conditions such as spinal cord injuries, strokes, and arthritis, significantly hinders daily activities. Wearable exo-gloves and telerehabilitation offer effective hand training solutions to aid the recovery process. This study presents the development of lightweight wearable exo-gloves designed for finger telerehabilitation. The prototype uses NiTi shape memory alloy (SMA) actuators to control five fingers. Specialized end effectors target the metacarpophalangeal (MCP), proximal interphalangeal (PIP), and distal interphalangeal (DIP) joints, mimicking human finger tendon actions. A variable structure controller, managed through a web-based Human–Machine Interface (HMI), allows remote adjustments. Thermal behavior, dynamics, and overall performance were modeled in MATLAB Simulink, with experimental validation confirming the model’s efficacy. The phase transformation characteristics of NiTi shape memory wire were studied using the Souza–Auricchio model within COMSOL Multiphysics 6.2 software. Comparing the simulation to trial data showed an average error of 2.76°. The range of motion for the MCP, PIP, and DIP joints was 21°, 65°, and 60.3°, respectively. Additionally, a minimum torque of 0.2 Nm at each finger joint was observed, which is sufficient to overcome resistance and meet the torque requirements. Results demonstrate that integrating SMA actuators with telerehabilitation addresses the need for compact and efficient wearable devices, potentially improving patient outcomes through remote therapy.

Design of novel test rig for prosthetic finger distal interphalangeal and phalanx strengths.

Testing is one of the most significant phases of any engineering process, the last process followed by conceptualization, designing, and fabricating. If the testing outcomes are not genealogy sensible measurables, then eventually it calls for a redesign overhaul. Existing testing equipment to analyze the load and failures are conventional digital universal testing machines with minimum jigs and fixtures. In addition, the existing fixtures cannot be adapted to the anatomy of a human finger. Consequently, the present work explores the best possible design of a jig for testing the naturally articulated movement of a human finger (prosthetic wear-on). Furthermore, the present jig design checks a wide range of parameters such as freedom of motion, a path along with curvature, load, failures, and intermittent positions of applied load, which is adaptable to existing universal testing machines available for broader applications.

A novel trident shaped microstrip antenna sensor for glucose detection in human blood

A novel trident-shaped microstrip patch antenna sensor with great sensitivity is developed to estimate the amounts of glucose in blood samples of human. The suggested sensor is built on a 30 × 24 × 1.6 mm3 FR-4 substrate layer with a quality factor of 64 and a dielectric constant value of 4.3 resonating at 4.5 GHz. A finger phantom is the replica of the human finger and it is originated in the electromagnetic simulator in order to forecast the glucose content. By positioning the phantom replica at various localities on the constructed antenna sensor, the frequency shifts are observed for various levels of glucose concentration in different degrees, ranging from 0 to 1000 mg/dL are detected. The proposed sensor can identify diabetic conditions in patients as it has a finger phantom positioned parallel to the feed at the top of the antenna giving a 156 MHz paramount shift in frequency, sensitivity of 156 kHz/(mg/dL), and a minimum frequency shift of 24 MHz and sensitivity of 24 kHz/(mg/dL). To confirm the suggested sensor's functionality in a real-time environment, its performance is examined for various actual human finger postures, and the resulting resonance frequencies are observed. In order to detect the levels of glucose concentration, the suggested sensor's error performance is calculated and are found to be near to 1%.

Quantitative analysis of human blood glucose by dynamic optical rotation angle of multiple wavelengths based on the polarization camera

Measurement of blood glucose concentration is important in the prevention and treatment of diabetes. To improve the measurement signal-to-noise ratio and accuracy, using a polarization camera as the sensor, this paper proposes a multi-wavelength dynamic optical rotation angle method to quantitatively analyze human blood glucose. First, this paper utilizes a split-time approach to drive nine different wavelengths of light sources to work separately to achieve the collection of multiple different wavelengths of data and increase the amount of information. Second, to capture images with an array sensor such as a camera, using space-for-accuracy, this paper uses the cumulative value of the gray values of all pixel points in the image at each angle as the light intensity value to improve the amplitude (light intensity) resolution. Third, the extraction method of the dynamic optical rotation angle in this paper is to extract the difference between the maximum and minimum values of the optical rotation angle from each cycle of the signal of the continuous cyclic change of the length of the optical path, and the accumulated value of the difference of multiple cycles is recorded as the dynamic optical rotation angle, which not only reduces the errors caused by the individual differences, the external environment and the measuring instrument, but also has the effect of averaging and improves the signal-to-noise ratio of the optical rotation angle. To prove the effectiveness of the proposed methods, human finger real and simulation experiments are carried out, respectively. Firstly, the polarization camera is used to collect the image data of elliptically polarized light of nine different wavelengths of linearly polarized light after passing through the human body’s finger, and obtains the optical rotation angle under each wavelength that changes with the photoplethysmography (PPG) through data processing, and extracts the dynamic optical rotation angles of the nine wavelengths by the extraction method, and the human body’s blood glucose can be quantitatively analyzed. Secondly, this paper builds a simulation model to simulate the blood volume conversion of the human finger, and uses the simulation experimental system to collect the dynamic optical rotation angles of nine wavelengths of a total of 137 human serum samples, and uses partial least squares regression to establish a model between the dynamic optical rotation angles and blood glucose concentration. In the results of predicting all samples using the model, the correlation coefficient and root mean square error were 0.7960 and 2.16 mmol/L, respectively, both of which improved by 137.26 % and decreased by 35.33 %, respectively, compared to the existing method. The experimental results show that the method in this paper has high accuracy in detecting the blood glucose concentration in human beings, which is of great significance in realizing the noninvasive quantitative analysis of human blood glucose components by the polarized light method.

Optimal Design of a Bilateral Stand-Alone Robotic Motion-Assisted Finger Exoskeleton for Home Rehabilitation

This paper presents a novel exoskeleton robot that can be used at home to rehabilitate the index fingers of stroke-affected patients. This exoskeleton is designed as a one-degree-of-freedom four-bar mechanism able to guide the human index finger to perform a finger curl exercise motion. The proposed device is the only lateral, stand-alone mechanism built to date that can carry the weight of the human hand, thus making the user free from wearing it. The design starts by tracing the trajectory of the index finger using ‘Angulus’ software. ‘SALAR Mechanism Synthesizer’ software is used for dimensional synthesis of the four-bar mechanism. Using additive manufacturing technology, a prototype of the proposed device is developed. Static force analysis is performed to select the most appropriate actuator for producing the required torque to manipulate the fingers effectively. The kinematics of the index finger while performing a finger curl exercise is obtained. The proposed linkage mechanism can drive the index fingers of both hands. Simulation and experimental results proved the feasibility and effectiveness of the proposed design to be used for index finger rehabilitation for a wide range of users and applications by making simple minor alterations in the design. Also, a scheme for when the device can be used for rehabilitating the middle finger together with the index finger when performing flexion and extension motions is discussed.

Analysis of the Structural Organization of the Human Finger Phalanges Using Anatomical Network Models

Despite the fact that the morphogenetic mechanisms of human finger transformation during ontogenesis are currently known, the issues of how they are organized into a complex integrated structure of the distal hand remains open. This question remains unanswered for several reasons, including the lack of consensus on conceptual definitions and approaches, as well as tools for assessing and comparing variations in several anatomical parts of the hand. The aim of the study was to investigate the structural organization of the human finger phalanges using anatomical network analysis (AnNA). Material and methods. In this study, the authors applied the IGRAPH package functions in the R data analysis programming environment for AnNA. Network modeling and layout were performed using the Fruchterman-Reingold algorithm. Analysis of the structure, as well as modularity and integration in the networks, was performed using the spin-glass algorithm. X-ray osteometric indices of the I–V fingers phalanx length were used to assess AnNA in 100 men and 100 women of the middle age without traumatic changes, deformations, and developmental deviations. Results. AnNA demonstrates a two-level organization of the distal hand in the form of a proximal module including the proximal phalanges and a distal module combining the middle and distal phalanges. When comparing the features of the network models of the distal hand, it was found that in women, the organization of the finger phalanges is characterised by higher morphological integration and modularity (modularity 0.43) than in men (modularity 0.38). orphological modularity and integration are organizing factors in the structure of the finger phalanges of the human distal hand. Conclusion. The study results demonstrate that the structural organization of the finger phalanges of the human hand is a system of individual anatomical modules of the phalanges.

DIFFERENCES IN FINGER LENGTH RATIO BETWEEN STUDENTS OF PSYCHOLOGY AND SPECIAL EDUCATION AND REHABILITATION

Background: The disproportionate length of human fingers has generated much interest among researchers. Attention has been drawn to the relationship between the palmar digit (2D:4D) ratio and personality, but the obtained results have been inconsistent. This pilot research project was a qualitative study that aimed to investigate the similarity or differences in the length of fingers 2 and 4 in two groups of students aged 20-21 years from different study programs (psychology and special education and rehabilitation) from Tetova University in Tetova to see if the selection of study program is influenced by the length of certain fingers. Materials and procedure: Single measures of the lengths of the 2nd and 4th digits from the fingertip to the ventral proximal crease of the left and right hand were collected using a ruler calibrated to 0.05 cm. The measurements were anonymous and performed in October of 2023 by the lecturer of teaching subjects in 30 consenting students who participated voluntarily and without any compensation in the participation. At the same time, the data analysis was done statistically using the paired samples test. Results: Means and standard deviations of the parameters with respect to group differences were calculated. We found a nonsignificant group difference in the 2D:4D ratio for the right hand (p=0.402) and for the left hand (p=0.775). Conclusion: Detailed information of finger length parameters and D2:D4 index in a sample study with more participants in the future period will be used from the perspective of neuropsychology.

Photoacoustic thermal-strain measurement towards noninvasive and accurate temperature mapping in photothermal therapy

Photothermal therapy is a promising tumor treatment approach that selectively eliminates cancer cells while assuring the survival of normal cells. It transforms light energy into thermal energy, making it gentle, targeted, and devoid of radiation. However, the efficacy of treatment is hampered by the absence of accurate and noninvasive temperature measurement method in the therapy. Therefore, there is a pressing demand for a noninvasive temperature measurement method that is real-time and accurate. This article presents one such attempt based on thermal strain photoacoustic (PA) temperature measurement. The method was first modelled, and a circular array-based photoacoustic photothermal system was developed. Experiments with Indian ink as tumor simulants suggest that the temperature monitoring in this work achieves a precision of down to 0.3 °C. Furthermore, it is possible to accomplish real-time temperature imaging, providing accurate two-dimensional temperature mapping for photothermal therapy. Experiments were also conducted on human fingers and nude mice, validating promising potentials of the proposed method for practical implementations.

Microwave Radiation Assisted Construction of Fused Deposition Modeling 3D Printing Flexible Sensors

AbstractWith the rapid development of the internet of things, the simple preparation of sensors has become a challenge. The present work presents the simple preparation of flexible sensors by using the fused deposition modeling (FDM) 3D printing combined with the microwave radiation‐assisted treatment of the thermoplastic polyurethane (TPU) with carbon nanotubes (CNTs) as conductive fillers to create the flexible sensors. The as‐prepared TPU/CNT composites exhibit the 7.27 MPa tensile strength and 401% elongation at break, similar to those of the pure TPU. After 200 tensile cycles, the TPU/CNT composites can still stably convert pressure into electrical signals, which can be used as flexible sensors with high sensitivity (0.879 kPa−1). In addition, shoe insoles and finger cover with sensing performance are fabricated through the FDM 3D printing technology, demonstrating the potential of the sensors to monitor human gait, finger straightening, and bending movements. The as‐proposed method involves the embedding CNTs as conductive fillers on the surface of TPU to form the TPU/CNT composite conductive layers on the surface of TPU, which is beneficial for maintaining the elasticity of the polymer matrix. The challenges in preparing stable, low‐cost, and scalable flexible sensors and highlights of the advantages of 3D printing technology in manufacturing flexible piezoresistive sensors are also deeply discussed.

Piezoelectricity in NbOI2 for piezotronics and nanogenerators

2-dimensional (2D) piezoelectric materials have gained significant attention due to their potential applications in flexible energy harvesting and storage devices. Recently, niobium oxide dihalides NbOI2 stands out as a multifunctional anisotropic semiconductor family with an exceptionally high lateral piezoelectric constant (~21.8 pm/V), making it a promising candidate for energy conversion applications. Here we report the experimental observation of anisotropic in-plane piezoelectricity in multilayer NbOI2. Current-voltage relationships reveal a significant piezotronic effect in two typical crystalline orientations. Additionally, cyclic tensile and release experiments demonstrate an intrinsic current output of up to 140 pA when subjected to a tensile strain of 0.51%. A flexible piezoelectric nanogenerator prototype is demonstrated on the human finger and wrist, which opens up new avenues for the development of wearable electronic devices and provides valuable insights for further exploration in this field.

Development of a finger dummy for contact safety assessment by investigating the dimensions and mechanical characteristics of human fingers

Development of a finger dummy for contact safety assessment by investigating the dimensions and mechanical characteristics of human fingers