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This technical note presents a discussion on the dynamic modeling and analysis of the adaptive controller of a Mechanical Prosthetic finger with constraints mass (m) of the mechanical finger and constant friction (K1) with variation in spring constraint (K2) parameter during grasping action. For the design of the adaptive controller and assessment of adaptation gain, an underdamped second-order control system has been considered and variation of adaptation gain (γ) within certain pre-defined limits of system parameters, variation in the adaptation mechanism has been analyzed using Gradient method MIT rule. To ensure global stability along with the convergence on nonconformity of plant parameters Lyapunov Rule has been utilized towards closed-loop asymptotic tracking.

In this paper, Diagnostic Electromyography (D-EMG) signal interpretation of human arm towards characterization of arm-muscle interaction during various arm movements has been discussed. EMG signals from four important arm muscle (i.e., Bicepsbracci, Tricepsbracci, brachioradialis, and lateral deltoids) are recorded clinically during five different arm movements (i.e., Extension of the forearm, flexion of elbow joint, pronation of forearm, shoulder abduction, and Wrist flexor stretch) under load condition (a load of 2 Kg & 4 Kg maintained during experimental arm movement), the recorded D-EMG signals are properly enveloped within a range of 5-100 Hz and quantized within a proper sampling frequency range to produce a knowledge-based database of muscle activity. In addition, correlation of muscle activity and Power spectral density (PSD) analysis has been carried out towards muscle process discriminating during various arm actions.

The article analyses the possibility of conducting research on the competitive environment and assessing the potential effect of introducing promising technological solutions based on the use of patent landscapes even before the construction of new mining machines begins. The authors suggest that the oriented adaptation of patent analytics tools will allow solving a large-scale scientific problem. That is identifying patterns and dependences of changes in the main parameters of mining machines over time and developing a methodology for predicting and substantiating the promising parameters of various mining machines, both of one functional purpose and multifunctional ones, ensuring their efficient operation for a given period of time.

This study describes a new method for gripping and sensing a physical object (or material) with a prosthetic arm that uses haptic technologies, kinaesthetic communication, and machine learning. Haptic technology is a method of determining if an object is firm or soft as if it were gripped by a human and determining how much gripping force the object can withstand without crushing it. The bending moment and gripping force are measured using a flex sensor in human fingers and a pressure sensor applied by the tip of the human fingers. Three different types of objects (soft sponge, hard sponge, and plastic) are studied and tested in this work by pressing them with varying gripping pressures (soft, firm, and firmer). In addition, a model (Haptic Intelligence Recorder arm) is proposed that can anticipate the object type and gripping force based on the recorded intelligence data. The major goal is to educate our prosthetic hand to be able to grip various items with varying finger pressures, much like we can do naturally. Finally, a glove is created that is tailored to the intelligence arm’s ability to anticipate grabbing items.

This research has the objective to design an electrical circuit model which can compute the respiratory process. This analysis of the proposed electrical circuit model has been done in linear, non-linear, and hardware experimental processes. This work presents the electrical model realization of the respiratory system along with the introduction of a state space model under the nonlinear control domain to realize the same. Through dead and saturation zone nonlinearity, the output response of this model has been restored and its polar plot has been reexamined to determine the intersection of this characterizing function. The simulation's outcome suggests that the system is stable, based on the idea of a limit cycle in a nonlinear domain. The ExpEYES-17 development kit was used to implement the suggested circuit as proposed hardware implantable model and justified it as a reliable system. Various achieved output shows that within the lung frequency range 0.25 Hz–5 Hz, the generated output pressure is within the range of 25 to 33 Pa which resembles pressure of human lung.

People with lower limb amputations struggle through difficulties during locomotion in their daily activities. People with transtibial amputations take support from prosthetic legs for systematic movement. During motion, they experience some mobility issues while using general prosthetic limbs regarding gait pattern. The design of a prosthetic-controlled lower limb with gait synchronization for physically disabled persons is the main goal of the present research work, which can provide an improved walking experience. The design and performance analysis of prosthetic lower limbs for people with transtibial amputations is performed in the present paper. The designed rehabilitation system shows synchronization between the normal and the prosthetic limbs achieved with gait coordination. The dynamics of the lower extremities in different postural activities are used for design purpose utilizing Euler–Lagrange motion theory. The artificial motion of the knee and the ankle joints function through the angular movement of the servo motors according to the movements of the rotary encoders placed on the sound limb joints. The range of motion of both the sound and prosthetic limbs are compared for different steps during a gait cycle. The prosthetic electronic system design of the artificial lower limb is able to show the gait style of human being with body kinesics. The nonlinear domain stability analysis of the designed prosthetic limb is presented through the Lyapunov method. A PIDF2 controller tuning process is implemented for the designed limb’s performance improvement. The designed prosthetic system is beneficial for people with unilateral transtibial amputations with a great societal impact.

Students are the future of a nation. Personalizing student interests in higher education courses is one of the biggest challenges in higher education. Various AI and ML approaches have been used to study student behaviour. Existing AI and ML algorithms are used to identify features for various fields, such as behavioural analysis, economic analysis, image processing, and personalized medicine. However, there are major concerns about the interpretability and understandability of the decision made by a model. This is because most AI algorithms are black-box models. In this study, explain- able AI (XAI) aims to break the black box nature of an algorithm. In this study, XAI is used to identify engineering students’ interests, and BRB and SP-LIME are used to explain which attributes are critical to their studies. We also used (PCA) for feature selection to identify the student cohort. Clustering the cohort helps to analyse the between influential features in terms of engineering discipline selection. The results show that there are some valuable factors that influence their study and, ultimately, the future of a nation.

In this paper A mobile application has been developed that can fetch various information about a car through various sensors interfaced with a microcontroller NodeMCU and the collected data uploaded to the cloud through raspberry pi server. NodeMCU sends signals to Raspberry pi to store the data in the cloud so that the mobile application developed may receive all these sensory signals and alert the passengers and driver. The proposed model also includes a feature to detect an accident and send the location of the accident to the user assigned person and local police station as a mobile message. In addition, the mobile application shall alert the driver to keep away from high speed vehicles coming from the rear side, present location of the car through google API, identify the road condition through pi camera interfacing and advise the upper speed limit, spray liquid nitrogen to reduce the temperature of tyres in the safe range of temperature, detect the driver status of drowsiness or alcoholic, detect the air quality about the harmful gas levels inside the car.

System performance and efficiency depends on the stability criteria. The lower limb prosthetic model design requires some prerequisites such as hardware design functionality and compatibility of the building block materials. Effective implementation of mathematical model simulation symmetry towards the achievement of hardware design is the focus of the present work. Different postures of lower limb have been considered in this paper to be analyzed for artificial system design of lower limb movement. The generated polynomial equations of the sitting and standing positions of the normal limb are represented with overall system transfer function. The behavioral analysis of the lower limb model shows the nonlinear nature. The Euler-Lagrange method is utilized to describe the nonlinearity in the field of forward dynamics of the artificial system. The stability factor through phase portrait analysis is checked with respect to nonlinear system characteristics of the lower limb. The asymptotic stability has been achieved utilizing the most applicable Lyapunov method for nonlinear systems. The stability checking of the proposed artificial lower extremity is the newer approach needed to take decisions on output implementation in the system design.

Self-inoculation takes major part for the transmission of infections. Basically self-inoculation is nothing but a type of contact transmission. A person’s contaminated hands make contact with other parts of the body by Self-inoculation. Many infections mainly respiratory infections (e.g., influenza, coronavirus) can transmit via self-inoculation. In this pandemic situation it is very necessary to resist the transmission of infection (corona virus) via self-inoculation. In this paper a module of personal protective intelligent hat has been proposed for the protection of human being. The protective intelligent hat fabricates with two ends (i) Face Side End System (FSES) and (ii) Hand Side End System (HSES). FSES is made up with hall sensor whereas HSES is set up with magnet set ring or band. The novel corona virus enters the human body by eyes, nose and mouth when all are touched by infected hand. Avoid touching of contaminated hand is one of the key to survive from the attack of corona virus as well as other bacteria. The smart hat not only applicable to protect COVID-19, it is also applicable to protect various diseases which caused by contaminated hand like Influenza, Common cold, Chicken Pox etc.