User's Hand Research Articles

GestureLink: Immersive Hand Guided Virtual Interface

This report introduces an innovative Hand Gesture Mouse Controlling system that utilizes hand gestures captured via a webcam through a colour detection technique. This system enables users to navigate the computer cursor and perform clicking and dragging actions using different hand gestures. The proposed system relies solely on a low-resolution webcam functioning as a sensor, effectively tracking the user's hand gestures in multiple dimensions. The implementation will utilize Python and OpenCV for seamless integration. Hand gestures offer a natural and effortless means of communication. The camera's output will be displayed on the monitor, and shape and position information of the gestures will be acquired through colour detection. Additionally, the report outlines the implementation of a file transferring scheme using Python server programming.

ZnO Nanowall Network-Based Tactile/Gesture Sensors and Prediction with Machine Learning.

In low-dimensional material systems, augmented physical and chemical properties may be witnessed through a unique morphological evolution. Here, we report the development of an optimized nanowall network of ZnO for the fabrication of a flexible single-electrode triboelectric nanogenerator (STENG)-based tactile and gesture sensors. The chemically grown nanowall network with an adequate pore area endows superior triboelectric output (current ∼0.6 μA and power ∼20 μW/cm2) by offering an optimum surface area and dielectric constant for pressure sensing applications. The rational comparison of the triboelectric properties of nanowall and nanorod structures of ZnO reveals that the higher surface area offered by the hollow walls leads to superior output characteristics. The demonstration of pressure sensitivity of the STENG ∼1 V/N is promising for self-powered tactile sensing applications. The array of STENG sensors, when attached to a user hand, generates distinguishable signals while holding objects of varying curvature and mass. Again, the observation of sensitivity of ∼0.1 V per degree during finger movement activity indicates the gesture sensing ability of the nanowall-based TENG system, facilitating sign language expression through the movement of fingers. Further, the generated electrical signals during tactile and gesture sensing can be classified and recognized through the deployment of machine learning (ML) techniques. In fact, the implementation of Random Forest and K-Nearest Neighbor models has offered an accuracy of 96% while recognizing the output signals generated by the sensor arrays. The demonstration of superior sensing characteristics with the optimized nanowall network may be advantageous in innovating prototype sensors for the differently abled people to distinguish or classify objects on the basis of material, morphology, and mass during their regular activities.

Rehabilitation process to Control and Predict User Hand gestures through EMG signal based Reinforced Transradial Amputation Model

Rehabilitation process to Control and Predict User Hand gestures through EMG signal based Reinforced Transradial Amputation Model

Design and Implementation of Gesture Music Composition System based on RealSense and Recurrent Neural Network

Aiming at the problems of slow human-computer interaction and low accuracy of hand gesture recognition (HGR) in music composition systems such as human-computer interaction, gesture recognition, and algorithmic composition, this paper designs an HGR music composition system based on real-sense technology and recurrent neural network. The system uses an Intel RealSense 3D camera to shoot the user's hand and extract the information on the hand joint points with Smart Wearable Biosensors (SWBSs). The joint points are used to construct a three-dimensional model of the hand bone, and the joint points' equivalent distance and joint deflection are calculated by the joint point information to match the corresponding Curwen HGR. The matching music data is input into the recurrent neural network. GRU is combined with the Markov chain algorithm to complete the composition and avoid the phenomenon of gradient disappearance or gradient explosion. The HGR recognition function and composition algorithm are simulated and tested to verify the method's feasibility. Cohort verification investigations and efficacy evaluations of wearable biosensors are essential to support their clinical acceptability. The research results show that the HGR music composition system based on real-sense technology and recurrent neural networks can effectively identify the tester's HGRs and assist the tester in completing the composition using intelligent biosensors. The composition mode is close to the professional composition process.

Comparison of AirAngel® vs. Storz® videolaryngoscope and Macintosh® laryngoscope for endotracheal intubation training: prospective randomized crossover study

BackgroundFor both normal and difficult airway management, VL is thought to be more effective. However, VL seems far from being offered as a standard option in both healthcare delivery and educational activities in low-income countries, considering its high costs. Therefore, three-dimensional(3D)printed VLs may be considered an alternative to conventional VLs in low-income countries and other places with limited resources. Our objective was to compare the efficacy of AirAngel 3D-printed VL (3D-PVL) with those of commercially available Storz® VL (SVL) and conventional Macintosh® laryngoscope (MCL) in normal and difficult airway scenarios in the hands of inexperienced users.MethodsThis is a prospective randomized crossover manikin study that included 126 senior medical students with no experience in intubation. The effectiveness of all three laryngoscopy devices in the hands of inexperienced users was evaluated in terms of intubation time, glottic visualization, ease of use, endotracheal tube placement, and intubation success rate. Between 2020 and 2022, 126 last year medical students participated in the study.ResultsMCL resulted in significantly longer intubation times than 3D-PVL and SVL in the difficult airway scenario, with no significant difference between 3DPVL and SVL (Wilcoxon test, p < 0.016; Bonferroni correction MCL: 28.54 s; SVL: 26.68 s; 3DPVL: 26.64 s). Both SVL and 3D-PVL resulted in significantly better Cormack − Lehane grades in both normal and difficult airway scenarios, and thus provided better glottic viewing than MCL, with no significant difference between 3D-PVL and SVL (Wilcoxon test, p < 0.016; Bonferroni correction, MCL: 1.73; SVL: 1.29; 3DPVL: 1.25). The SVL was the easiest device to use for normal airway scenarios (1: very easy, 5: very difficult), while the MCL was the most difficult (MCL: 2.64; 3DPVL: 1.98; SVL: 1.49). Conversely, no significant difference was found between 3DPVL and other devices in terms of ease of use in difficult airway scenarios and in terms of accurate placement of the endotracheal tube and successful intubation attempts.Conclusion3D-PVL is a good educational and possible clinical alternative to conventional VL, particularly in places with limited resources, due to its low cost.

Examining the Flexural Behavior of Thermoformed 3D-Printed Wrist-Hand Orthoses: Role of Material, Infill Density, and Wear Conditions.

This paper examined the mechanical properties of wrist-hand orthoses made from polylactic acid (PLA) and polyethylene terephthalate glycol (PETG), produced through material extrusion with infill densities of 55% and 80%. These orthoses, commonly prescribed for wrist injuries, were 3D-printed flat and subsequently thermoformed to fit the user's hand. Experimental and numerical analyses assessed their mechanical resistance to flexion after typical wear conditions, including moisture and long-term aging, as well as their moldability. Digital Imaging Correlation investigations were performed on PLA and PETG specimens for determining the characteristics required for running numerical analysis of the mechanical behavior of the orthoses. The results indicated that even the orthoses with the lower infill density maintained suitable rigidity for wrist immobilization, despite a decrease in their mechanical properties after over one year of shelf life. PLA orthoses with 55% infill density failed at a mean load of 336 N (before aging) and 215 N (after aging), while PETG orthoses did not break during tests. Interestingly, PLA and PETG orthoses with 55% infill density were less influenced by aging compared to their 80% density counterparts. Additionally, moisture and aging affected the PLA orthoses more, with thermoforming, ongoing curing, and stress relaxation as possible explanations related to PETG behavior. Both materials proved viable for daily use, with PETG offering better flexural resistance but posing greater thermoforming challenges.

To Stick or Not to Stick? Studying the Impact of Offset Recovery Techniques During Mid-Air Interactions.

During mid-air interactions, common approaches (such as the god-object method) typically rely on visually constraining the user's avatar to avoid visual interpenetrations with the virtual environment in the absence of kinesthetic feedback. This paper explores two methods which influence how the position mismatch (positional offset) between users' real and virtual hands is recovered when releasing the contact with virtual objects. The first method (sticky) constrains the user's virtual hand until the mismatch is recovered, while the second method (unsticky) employs an adaptive offset recovery method. In the first study, we explored the effect of positional offset and of motion alteration on users' behavioral adjustments and users' perception. In a second study, we evaluated variations in the sense of embodiment and the preference between the two control laws. Overall, both methods presented similar results in terms of performance and accuracy, yet, positional offsets strongly impacted motion profiles and users' performance. Both methods also resulted in comparable levels of embodiment. Finally, participants usually expressed strong preferences toward one of the two methods, but these choices were individual-specific and did not appear to be correlated solely with characteristics external to the individuals. Taken together, these results highlight the relevance of exploring the customization of motion control algorithms for avatars.

Finger-Individuating Exoskeleton System with Non-Contact Leader-Follower Control Strategy.

This paper proposes a novel finger-individuating exoskeleton system with a non-contact leader-follower control strategy that effectively combines motion functionality and individual adaptability. Our solution comprises the following two interactive components: the leader side and the follower side. The leader side processes joint angle information from the healthy hand during motion via a Leap Motion Controller as the system input, providing more flexible and active operations owing to the non-contact manner. Then, as the follower side, the exoskeleton is driven to assist the user's hand for rehabilitation training according to the input. The exoskeleton mechanism is designed as a universal module that can adapt to various digit sizes and weighs only 40 g. Additionally, the current motion of the exoskeleton is fed back to the system in real time, forming a closed loop to ensure control accuracy. Finally, four experiments validate the design effectiveness and motion performance of the proposed exoskeleton system. The experimental results indicate that our prototype can provide an average force of about 16.5 N for the whole hand during flexing, and the success rate reaches 82.03% in grasping tasks. Importantly, the proposed prototype holds promise for improving rehabilitation outcomes, offering diverse options for different stroke stages or application scenarios.

Shape-position perceptive fusion electronic skin with autonomous learning for gesture interaction

Wearable devices, such as data gloves and electronic skins, can perceive human instructions, behaviors and even emotions by tracking a hand's motion, with the help of knowledge learning. The shape or position single-mode sensor in such devices often lacks comprehensive information to perceive interactive gestures. Meanwhile, the limited computing power of wearable applications restricts the multimode fusion of different sensing data and the deployment of deep learning networks. We propose a perceptive fusion electronic skin (PFES) with a bioinspired hierarchical structure that utilizes the magnetization state of a magnetostrictive alloy film to be sensitive to external strain or magnetic field. Installed at the joints of a hand, the PFES realizes perception of curvature (joint shape) and magnetism (joint position) information by mapping corresponding signals to the two-directional continuous distribution such that the two edges represent the contributions of curvature radius and magnetic field, respectively. By autonomously selecting knowledge closer to the user's hand movement characteristics, the reinforced knowledge distillation method is developed to learn and compress a teacher model for rapid deployment on wearable devices. The PFES integrating the autonomous learning algorithm can fuse curvature-magnetism dual information, ultimately achieving human machine interaction with gesture recognition and haptic feedback for cross-space perception and manipulation.

Kine-Appendage: Enhancing Freehand VR Interaction Through Transformations of Virtual Appendages.

Kinesthetic feedback, the feeling of restriction or resistance when hands contact objects, is essential for natural freehand interaction in VR. However, inducing kinesthetic feedback using mechanical hardware can be cumbersome and hard to control in commodity VR systems. We propose the kine-appendage concept to compensate for the loss of kinesthetic feedback in virtual environments, i.e., a virtual appendage is added to the user's avatar hand; when the appendage contacts a virtual object, it exhibits transformations (rotation and deformation); when it disengages from the contact, it recovers its original appearance. A proof-of-concept kine-appendage technique, BrittleStylus, was designed to enhance isomorphic typing. Our empirical evaluations demonstrated that (i) BrittleStylus significantly reduced the uncorrected error rate of naive isomorphic typing from 6.53% to 1.92% without compromising the typing speed; (ii) BrittleStylus could induce the sense of kinesthetic feedback, the degree of which was parity with that induced by pseudo-haptic (+ visual cue) methods; and (iii) participants preferred BrittleStylus over pseudo-haptic (+ visual cue) methods because of not only good performance but also fluent hand movements.

Development of Flexure‐Based Supernumerary Robotic Finger for Hand Function Augmentation

This study introduces a flexure‐based supernumerary robotic finger (FBSF) inspired by the proportions of the human thumb, aiming to overcome existing limitations in robotic finger design. In pursuit of seamless cooperation with the user's hand, human finger proportions are replicated. Finite element analysis of all five fingers indicates that the thumb‐mimicking configuration offers the largest workspace and bending angle. The FBSF, featuring a polycarbonate paired crossed flexural hinge structure and high impact polystyrene links, closely mirrors the human thumb. Weighing 59 g (main body) and 170 g (control box), the FBSF enables user‐driven control and decoupled actuation based on user intent, utilizing the electromyographic signal of the extensor carpi ulnaris via isometric contractions. An experimental protocol, including task blocks (releasing, clenching), confirms the FBSF's responsiveness to user intentions. When utilizing FBSF, it has been verified using a motion capture camera system that it is possible to extend the existing hand workspace by approximately 29.72%. Performance tests demonstrate the FBSF's capability to grasp various objects and assist in tasks, with a maximum load‐bearing capacity of 2.6 kg experimentally verified. This study demonstrates the potential of the developed FBSF to augment hand functionality in diverse applications.

96‐3: Invited Paper: Next‐Gen Interactions: Creative Sensing Solutions for Automotive Capacitive Knobs on Displays

Automakers are adding back mechanical knobs to modern car cabins to address concerns about the difficulty of adjusting vehicle setting controls through the touchscreen interface. Passive capacitive knobs attached to touchscreens are a great solution as they provide a seamless interface while using the same capacitive sensors that sense finger touches. Existing knobs rely on capacitive coupling to a user's hand, making it difficult to support gloved hands. The proposed knob resolves this by employing a unique sensing architecture while providing additional features such as initial state detection and fall‐off detection.

AI Virtual Mouse System Using Computer Vision to avoid COVID-19 spread

In the contemporary digital landscape, enhancing human-computer interaction efficiency and intuitiveness is essential. Traditional input devices like mice and keyboards are being augmented by innovative approaches such as hand gesture recognition, which provides a more natural method of interaction. This paper aims to generate a virtual mouse controlled by hand gestures using computer vision and deep learning techniques. The system employs a webcam to capture live video of the user's hand movements. These movements are analyzed using convolutional neural networks (CNNs) to identify specific gestures, which are then translated into mouse operations like cursor movement, clicking, and scrolling. This solution is hardware-independent, utilizing only the device's camera, making it accessible and straightforward to use. The goal is to create a seamless and efficient interaction method, allowing users to control their computers with simple hand gestures from a distance. Keywords: Convolutional Neural Network, Deep Learning, Hand Gesture Recognition, Virtual Mouse, Computer Vision, OpenCV

Amateur vs Professional Users of the YO Home Sperm Test: An Assessment of Usability

ObjectivesTo assess the accuracy of home-test use by a real-world / amateur user. MethodsThis multi-site study investigated whether amateur users could use the FDA cleared YO® Home Sperm Test to obtain accurate MSC results when compared to trained laboratory technicians. The qualitative motile sperm concentration (MSC) results of amateur and professional YO users were compared to each other as well as to the results of an established automated sperm quality analyzer (SQA-V above and below a 6m/mL MSC cut-off). ResultsThis was a blinded, prospective study of 316 amateur users and 3 professional laboratory technicians across 3 study sites. Amateur vs. Professional YO users demonstrated accuracy of >97%. Qualitative results of amateurs and professionals vs. SQA-V results showed >95.7% accuracy. ConclusionAmateur users with no prior training were able to follow the YO test directions to receive highly accurate qualitative MSC results. The YO test is user-friendly and can be used as an effective initial home screening tool to gain preliminary insight into the fertility status of the male in a real-world setting. Furthermore, the YO test results correlated with those obtained by the FDA cleared SQA-V laboratory analyzer, confirming that the YO test delivers accurate MSC results in the hands of amateur users.

Work in a Sitting Position at an Ergonomic Workstation to Reduce Complaints and Fatigue to Increase Work Productivity

This article discusses the egonomic position of sitting in a work station chair, because many workers still experience complaints and fatigue when working in a sitting position at a work station. Thus, it is hoped that the sitting position at an ergonomic work station can increase work productivity. This article is written descriptively. Then, all the data that will be processed and discussed is obtained from various opinions or what is called literature study. The analysis used is also descriptive, then concluded. Conclusion: 1) when making chairs and work tables, you must pay attention to the user's anthropometric dimensions. Thus, when working in a sitting position, the legs must be able to lean back (legrests must be provided on chairs and tables), the vertebrae, especially the lumbar spine, must be able to lean against the back of the chair, the angle of the knees can be adjusted at the elbows, a strong chair does not collapse easily for chairs with wheels. chair with five-wheeled legs, when sitting on the knees it must fit under the chair freely, on the work table there must be an area used for work (usual area) and an area sometimes used (occasional area) all of this is made according to the size of the user's hand reach and can also be increased in size table for the outer reach zone area. Then, the work station environment is adjusted to the threshold values, including lighting, climate (temperature, wind speed, humidity), noise, vibration and ultraviolet exposure. 2) that ergonomic work desk chairs and work stations will reduce musculoskeletal complaints and worker fatigue which in the end can increase work productivity

Gesture Controlled Robot for the Disabled using Arduino

Abstract: The gesture-controlled robot project presents a novel approach to human-robot interaction, utilizing hand gestures as an intuitive and natural means of control. This project aims to develop a system where users can seamlessly communicate with a robot using simple hand movements. The project consists of two main components: a handheld device for gesture input and a robot equipped with sensors and actuators for movement. Through wireless communication, the handheld device transmits signals encoding the user's hand gestures to the robot's receiver module, which decodes the signals, processes them, and translates them into commands for controlling the robot's movements. Advantages of this system include intuitive control, wireless operation, real-time interaction, enhanced safety, adaptability, educational value, and versatility. However, challenges such as gesture recognition complexity and limited gesture vocabulary must be addressed to ensure the system's effectiveness. The project has numerous applications, including entertainment, assistive technology, industrial automation, education, home automation, IoT, security, and interactive exhibits. By leveraging gesture-controlled robotics, this project contributes to advancing human-robot interaction technology and fostering innovation in various domains.

Perlindungan Hukum terhadap Anak di Bawah Umur dalam Perkara Tindak Pidana Narkotika

Narcotics crime is an extraordinary crime (extra ordinary crime) modus operandi is quite sophisticated and continues to experience changes to avoid tracking by law enforcement officials. This is the adult mode The latest thing to do is involve minors as couriers or delivery of drugs into the hands of users. The problem is the point attention is that when children are caught by officers they are immediately arrested became a suspect and was taken into custody. Even though children should be placed as a victim of the development of the big bookie mode in distributing drugs. The fact is that children are the perpetrators of the crime Drug criminals have not received maximum rights in the system juvenile criminal justice.

Low-cost GNSS antennas in precise positioning: a focus on multipath and antenna phase center models

The rapid growth of the GNSS equipment market has put affordable receivers and antennas capable of receiving satellite signals into the hands of users. High positioning accuracy, previously achievable only with high-grade devices, is becoming possible with low-cost ones. However, simplifications in the design of these devices, intended to reduce the manufacturing cost, affect their capabilities. This study analyzes the positioning accuracy that may be achieved with recent low-cost antennas. We put particular stress on investigating the susceptibility of such antennas to the multipath effect and implications from the quality of the antenna phase center models. The positioning performance is assessed by employing the Precise Point Positioning method with the integer ambiguity resolution of phase observations. The results obtained with three low-cost antennas are validated against three high-grade antennas. We reveal a two-to threefold decrease in positioning performance with low-cost antennas compared to high-quality equipment. However, positioning accuracy increased when a low-cost antenna with a phase correction model was used, particularly for the eastern component of coordinate bias. In addition, a significant susceptibility of low-cost antennas to the multipath effect was confirmed, especially for GPS L2 and Galileo E5a signals.

Design of Hand Gesture Control Wheel Chair

This study designated a wheelchair which can be meticulous using the user hand gesture. The purpose of this research was to come up with a hand gesture powered wheelchair system intended to provide assistance with the use of hand directions, which would allow users to travel efficiently and with greater ease. The system is made up of various electronics components such as the microcontroller, accelerometer, Bluetooth model, ultrasonic sensor, motor driver, among others. The microcontroller is programmed. The transmitter circuit board is made up of accelerometer sensor like ADSL335 which is able to sense three parameters. The microcontroller forms the main part or the brain of the system, and performs most of the functions. The microcontroller sends the readings sensed by the hand to the Bluetooth transmitter. The ultrasonic sensor detected obstacles, also sent the distance measured to the microcontroller. The microcontroller processed the information to the motor driver. The motor driver then powered the motors to either move forward or backward. It was observed that when the system was activated, the movement of the Wheelchair immediately start to follow the orientation of the user’s hand. The wheelchair was able to be perform five (5) different gestures. The gesture follows the range that had been set. However, this range depends on the position of the accelerometer.

It Sounds Cool: Exploring Sonification of Mid-Air Haptic Textures Exploration on Texture Judgments, Body Perception, and Motor Behaviour.

Ultrasonic mid-air haptic technology allows for the perceptual rendering of textured surfaces onto the user's hand. Unlike real textured surfaces, however, mid-air haptic feedback lacks implicit multisensory cues needed to reliably infer a texture's attributes (e.g., its roughness). In this article, we combined mid-air haptic textures with congruent sound feedback to investigate how sonification could influence people's 1) explicit judgment of the texture attributes, 2) explicit sensations of their own hand, and 3) implicit motor behavior during haptic exploration. Our results showed that audio cues (presented solely or combined with haptics) influenced participants' judgment of the texture attributes (roughness, hardness, moisture and viscosity), produced some hand sensations (the feeling of having a hand smoother, softer, looser, more flexible, colder, wetter and more natural), and changed participants' speed (moving faster or slower) while exploring the texture. We then conducted a principal component analysis to better understand and visualize the found results and conclude with a short discussion on how audio-haptic associations can be used to create embodied experiences in emerging application scenarios in the metaverse.