Tuning of frictional properties in torsional contact by means of disk grading

The contact of two surfaces in relative rotating motion occurs in many practical applications, from mechanical devices to human joints, displaying an intriguing interplay of effects at the onset of sliding due to the axisymmetric stress distribution. Theoretical and numerical models have been developed for some typical configurations, but work remains to be done to understand how to modify the emergent friction properties in this configuration. In this paper, we extend the two-dimensional (2D) spring-block model to investigate friction between surfaces in torsional contact. We investigate how the model describes the behavior of an elastic surface slowly rotating over a rigid substrate, comparing results with analytical calculations based on energy conservation. We show that an appropriate grading of the tribological properties of the surface can be used to avoid a non-uniform transition to sliding due to the axisymmetric configuration.

Preparation and tensile conductivity of carbon nanotube/polyurethane nanofiber conductive films based on the centrifugal spinning method

Flexible conductive thin films have recently become a research area of focus in both academia and industry. In this study, a method of preparing nanofiber conductive films by centrifugal spinning is proposed. Polyurethane (PU) nanofiber films were prepared by centrifugal spinning as the flexible substrate film, and carbon nanotubes (CNTs) were used as the conducting medium, to obtain CNTs/PU nanofiber conductive films with good conductivity and elasticity. The effects of different CNT concentrations on the properties of the nanofiber films were investigated. It was found that the conductivity of the nanofiber conductive films was optimal when an impregnation concentration of 9% CNTs was used in the stretching process. Cyclic tensile resistance tests showed that the nanofiber conductive films have good durability and repeatability. Physical and structural property analysis of the CNT/PU conductive films indicate that the adsorption of the CNTs on the PU surface was successful and the CNTs were evenly dispersed on the surface of the matrix. Moreover, the CNTs improved the thermal stability of the PU membrane. The CNT/PU conductive films were pasted onto a human finger joint, wrist joint, and Adam's apple to test the detection of movement. The results showed that finger bending, wrist bending, and laryngeal prominence movement all caused a change in resistance of the conductive film, with an approximately linear curve. The results indicate that the CNT/PU nanofiber conductive film developed in this study can be used to test the motion of human joints.

Molecular Responses to High Hydrostatic Pressure in Eukaryotes: Genetic Insights from Studies on Saccharomyces cerevisiae

High hydrostatic pressure is common mechanical stress in nature and is also experienced by the human body. Organisms in the Challenger Deep of the Mariana Trench are habitually exposed to pressures up to 110 MPa. Human joints are intermittently exposed to hydrostatic pressures of 3–10 MPa. Pressures less than 50 MPa do not deform or kill the cells. However, high pressure can have various effects on the cell’s biological processes. Although Saccharomyces cerevisiae is not a deep-sea piezophile, it can be used to elucidate the molecular mechanism underlying the cell’s responses to high pressures by applying basic knowledge of the effects of pressure on industrial processes involving microorganisms. We have explored the genes associated with the growth of S. cerevisiae under high pressure by employing functional genomic strategies and transcriptomics analysis and indicated a strong association between high-pressure signaling and the cell’s response to nutrient availability. This review summarizes the occurrence and significance of high-pressure effects on complex metabolic and genetic networks in eukaryotic cells and how the cell responds to increasing pressure by particularly focusing on the physiology of S. cerevisiae at the molecular level. Mechanosensation in humans has also been discussed.

Towards a Diagnostic Tool for Diagnosing Joint Pathologies: Supervised Learning of Acoustic Emission Signals

Acoustic emission (AE) testing detects the onset and progression of mechanical flaws. AE as a diagnostic tool is gaining traction for providing a tribological assessment of human joints and orthopaedic implants. There is potential for using AE as a tool for diagnosing joint pathologies such as osteoarthritis and implant failure, but the signal analysis must differentiate between wear mechanisms—a challenging problem! In this study, we use supervised learning to classify AE signals from adhesive and abrasive wear under controlled joint conditions. Uncorrelated AE features were derived using principal component analysis and classified using three methods, logistic regression, k-nearest neighbours (KNN), and back propagation (BP) neural network. The BP network performed best, with a classification accuracy of 98%, representing an exciting development for the clustering and supervised classification of AE signals as a bio-tribological diagnostic tool.

Development of multi-angle fiber array for accurate measurement of flexion and rotation in human joints

Herein, we have proposed a method that uses a highly stretchable and conductive fiber-based multi-angle fiber array, which precisely measures human joint motion in various degrees of freedom (flexion and rotation) at the shoulders, knees, and wrists in real time. By embedding conductive carbon nanotubes (CNTs) within spandex fibers of high elasticity and shape recovery ratio, we monitored joint motion stably without degrading the fiber’s conductivity even during repeated stretching and contraction of different lengths. The strain occurring in a specific direction was monitored using mapping images generated due to the change in resistance that occurred when 12 CNT-embedded spandex fibers arranged in radial lines at intervals of 15° were stretched or contracted by an external force. The proposed high-precision joint-monitoring technology measures human motion accurately and is applicable for use in wearable healthcare devices that require precise measurements.

Artificial Intelligence Assistive Technology in Hospital Professional Nursing Technology

Global aging is becoming more and more serious, and the nursing problems of the elderly will become very serious in the future. The article designs a control system with ATmega128 as the main controller based on the function of the multifunctional nursing robot. The article uses a convolutional neural network structure to estimate the position of 3D human joints. The article maps the joint coordinates of the colour map to the depth map based on the two camera parameters. At the same time, 15 joint heat maps are constructed with the joint depth map coordinates as the centre, and the joint heat map and the depth map are bound to the second-level neural network. The prediction of the position of the user’s armpit is further completed by image processing technology. We compare this method with other attitude prediction methods to verify the advantages of this research method. The research background of this article is carried out in the context of global aging in the 21st century.

GERAK SENDI PEMBELAJARAN PAKEM UNTUK MENINGKATKAN DAYA INGAT SISWA PADA PEMBELAJARAN SENDI MANUSIA

The purpose of this best practice is to find out how the implementation of the PAKEM approach to joint motion in improving the learning memory of class VIII A students of SMP Negeri 1 Anggaberi, Konawe Regency in the discussion of the types of human joints in the subject of Natural Sciences. The results of the learning activities indicate that the application of the Pakem learning approach with joint motion can improve the ability to remember the subject matter of the types of human joints in class VIII A students of SMP Negeri 1 Anggaberi. The results of the quiz on identifying the types of joints in humans before the application of the joint movement grip learning in previous learning activities showed the average percentage of ability to remember materials to identify materials only reached a value of 50%, still below the KKM value set for the types of joints in humans, and increased after learning activities that apply the gripping joint motion approach to the quiz results considering the material on identifying joints in humans, the percentage of analysis of quiz results reaches a value of 85%, above the KKM that has been set on the material for joint types in humans. ABSTRAKTujuan best practice ini adalah untuk mengetahui bagaimana implementasi pendekatan PAKEM gerak sendi dalam meningkatkan daya ingat belajar siswa kelas VIII A SMP Negeri 1 Anggaberi Kabupaten Konawe pada pembahasan materi jenis-jenis sendi manusia, mata pelajaran Ilmu Pengetahuan Alam. Hasil kegiatan pembelajaran menunjukkan bahwa penerapan pendekatan belajar Pakem dengan gerak sendi dapat meningkatkan kemampuan mengingat materi pelajaran jenis-jenis sendi manusia pada siswa kelas VIII A SMP Negeri 1 Anggaberi. Hasil kuis mengidentifikasi jenis sendi pada manusia sebelum penerapan pembelajaran Pakem gerak sendi pada kegiatan pembelajaran sebelumnya menunjukkan rata-rata persantase kemampuan mengingat materi mengidentifikasi materi hanya mencapai nilai 50%, masih di bawah nilai KKM yang ditetapakan pada jenis sendi pada manusia, dan mengalami peningkatan setelah kegiatan pembelajaran yang menerapkan pendekatan Pakem gerak sendi hasil kuis mengingat materi mengidentifikasi sendi pada manusia persentase analisis hasil kuis mencapai nilai 85%, di atas KKM yang telah ditetapkan pada materi jenis sendi pada manusia.

MARS: mmWave-based Assistive Rehabilitation System for Smart Healthcare

Rehabilitation is a crucial process for patients suffering from motor disorders. The current practice is performing rehabilitation exercises under clinical expert supervision. New approaches are needed to allow patients to perform prescribed exercises at their homes and alleviate commuting requirements, expert shortages, and healthcare costs. Human joint estimation is a substantial component of these programs since it offers valuable visualization and feedback based on body movements. Camera-based systems have been popular for capturing joint motion. However, they have high-cost, raise serious privacy concerns, and require strict lighting and placement settings. We propose a millimeter-wave (mmWave)-based assistive rehabilitation system (MARS) for motor disorders to address these challenges. MARS provides a low-cost solution with a competitive object localization and detection accuracy. It first maps the 5D time-series point cloud from mmWave to a lower dimension. Then, it uses a convolution neural network (CNN) to estimate the accurate location of human joints. MARS can reconstruct 19 human joints and their skeleton from the point cloud generated by mmWave radar. We evaluate MARS using ten specific rehabilitation movements performed by four human subjects involving all body parts and obtain an average mean absolute error of 5.87 cm for all joint positions. To the best of our knowledge, this is the first rehabilitation movements dataset using mmWave point cloud. MARS is evaluated on the Nvidia Jetson Xavier-NX board. Model inference takes only 64 s and consumes 442 J energy. These results demonstrate the practicality of MARS on low-power edge devices.

Design, Construction and Validation of a Proof of Concept Flexible–Rigid Mechanism Emulating Human Leg Behavior

In most robotics simulations, human joints (e.g., hips and knees) are assumed to be revolute joints with limited range rotations. However, this approach neglects the internal flexibility of the joint, which could present a significant drawback in some applications. We propose a tensegrity-inspired robotic manipulator that can replicate the kinematic behavior of the human leg. The design of the hip and knee resembles the musculoskeletal connections within the human body. Our implementation represents muscles, tendons and ligament connections as cables, and bones as rods. This particular design manipulates muscles to replicate a human-like gait, which demonstrates its potential for use as an anatomically correct assistive device (prosthetic, exoskeleton, etc.). Using the [EJ]OpenSim 3.0 simulation environment, we estimated the kinematics and structural integrity of the proposed flexural joint design and determined the actuation strategies for our prototype. Kinematics for the prototype include the mechanical limitations and constraints derived from the simulations. We compared the simulation, physical prototype, and human leg behaviors for various ranges of motion and demonstrated the potential for using [EJ]OpenSim 3.0 as a flexible–rigid modeling and simulation environment.

Body-powered variable impedance: An approach to augmenting humans with a passive device by reshaping lifting posture

The movement patterns appropriate for exercise and manual labor do not always correspond to what people instinctively choose for better comfort. Without expert guidance, people can even increase the risk of injury by choosing a comfortable posture rather than the appropriate one, notably when lifting objects. Even in situations where squatting is accepted as a desirable lifting strategy, people tend to choose the more comfortable strategy of stooping or semisquatting. The common approach to correcting lifting posture, immobilizing vulnerable joints via fixation, is insufficient for preventing back injuries sustained from repetitive lifting. Instead, when lifting small but heavy objects, the entire kinetic chain should cooperate to achieve a series of squat-lifting patterns. Inspired by the observation that force fields affect the coordination of voluntary human motion, we devised a passive exosuit embedded with a body-powered variable-impedance mechanism. The exosuit adds impedance to the human joints according to how far the wearer’s movement is from the squat-lifting trajectories so that it hinders stooping but facilitates squatting. In an experiment that entailed lifting a small 10-kg box, 10 first-time users changed their voluntary lifting motion closer to squatting on average. Simulation results based on recorded kinematic and kinetic data showed that this postural change reduced the compression force, shear force, and moment on the lumbosacral joint. Our work demonstrates the potential of using an exosuit to help people move in a desirable manner without requiring a complicated, bulky mechanical system.