Mastication plays a critical role in the food digestive process. A chewing robot was developed to simulate the food masticatory process to evaluate food properties. The artificial oral cavity of the robot failed to simulate the compliant contact between food and soft oral tissue and deserved redesign. The flourishing of soft robotics recently makes it possible to build a soft oral cavity. The design of an oral cavity made of silicone rubber is illustrated in this paper. The cavity is actuated by the inflation and deflation of an air chamber embedded on the inside of the cavity wall. The deformation of the chamber is studied through FEA simulation and experiments to validate its effectiveness. Moreover, the actuating frequencies of the chambers are tested to validate that they can perform food repositioning at the same pace as human chewing.
With the birth of the concept of a smart cockpit and the rapid development of a variety of central control screens, many smart phone applications have been integrated into the on-board infotainment system. However, the addition of these new functions will affect drivers' safe driving and move their eyes away from roads in order to interact with the on-board information system, causing potential safety hazards and even traffic accidents. More and more researchers have begun to pay attention to and optimise the automobile human-machine interface (HMI). In a laboratory environment, this paper studies when the on-board information system faces drivers 20°, 30° and 40°, which angle has the least impact on drivers' psychological load. NASA-TLX standard scale is used to record and calculate their psychological load. Finally, it is found that psychological load of drivers becomes the minimum at 40°, which can be used as a reference for future design of central control screen in new smart cockpit.
The introduction of augmented reality (AR) technology is an innovative development in nursing education. The Manukau Institute of Technology (MIT) of Te Pūkenga Institute of Skills and Technology in New Zealand has recently implemented HoloLens, an AR technology, in their Bachelor of Nursing Program to improve the overall learning experience. In an experimental project, HoloLens was utilised for revision classes to compare to traditional classroom-based teaching. Pre-registration nursing students participated in either in-person revision sessions or through a HoloLens headset or with a HoloPatient mobile phone application. The results indicate that using HoloLens substantially improves the student learning experience; however, face-to-face interactions still yield better outcomes. The HoloPatient's 3D holographic health scenarios were highly valued by users and had great potential to improve nursing pedagogy. However, there were several challenges during the experiment, such as time constraints, the experiment being too close to the exam, problems with headset adjustment, and insufficient user training. Blending traditional face-to-face teaching with AR technology integration can significantly enhance the nursing education experience.
Fabric-based sensorised gloves are a low-cost alternative that can drive the feedback loop for neuroprosthetic systems or evaluate functional outcomes. However, their applicability to complex hand manipulation tasks is limited as the fabric imparts constraints on the hand and affects the sensors' measurement performance. This work presents the design for a rapid prototypeable low-profile glove. The primary design consideration was to house sensors to measure force at the fingertips and their joint motion. Secondly, to minimise resistance to finger movements often seen with a fabric-based glove. The proposed glove design offers 19 degree-of-freedom allowing coordinated motion of the digits and thumb. In addition, the rapid prototypability allows modifications for resizeability and integration of other sensors. The design files from this work are also made available open for researchers.
Robotic arm application is gaining more importance in the present era. The accuracy and precision of a robotic arm is important in various applications. The available robotic arms have lesser accuracy. This paper presents an artificial arm which is capable of performing the task like a human arm like picking up, moving an object and gripping a substance. In the human arm, the bending or movement depends on sensor data and muscular movements, which are replicated using flex sensors, motor and string arrangement. Servo motors were used to actuate the movements of the robotic arm. The designed system can be developed with comparatively much lesser cost involvement and thus is more acceptable to the common mass. The low power requirement is also one of the novel attributes of the proposed system. The accuracy of this system is more than satisfactory and can be a potential tool for human assistive applications.
This paper aims to explore the change of brightness on the driver's cognition when the driver's attention shifts from the driving perspective to the HMI in a car to improve the driving safety. The Likert IO-point subjective scale is used to evaluate the driving difficulty. The software Scanner is used to simulate the road environment with different levels of brightness. The analytic hierarchy process (AHP) is used to analyse the questionnaire index and the opinion weight of the subjects. The particle swarm optimisation algorithm (PSO) is used to optimise the evaluation of the non-consensus rating items. The three combination modes of visual light adaptation, dark adaptation and no brightness difference are prioritised. PSO is introduced in this paper into the driving safety evaluation, which improves the reliability of subjective evaluation and provides a reference for human machine interface (HMI) brightness design.
In this paper, the efficiency of a non-model-based robust-adaptive controller for the trajectory tracking of a cable-driven manipulator with elastic cables is studied. Therefore, the manipulator’s dynamics, considering the effect of fluid forces, are presented at first. Using a linear spring model for the cables, the effect of elasticity on system dynamics is then defined. Later, two controllers consisting of inverse dynamics and robust-adaptive are implemented into the system. The robust-adaptive controller’s performance is compared to the ID controller, which shows its effectiveness in dealing with the effect of cable elasticity on the trajectory tracking of the robot. Moreover, this controller compensates for the effect of robot and fluid uncertainties.
Soft robots are becoming increasingly popular because of their high flexibility, lightweight, and safe interaction with the surrounding environment. Based on the physical adaptations, agility, reconfigurability, and multi-functionality seen in living creatures, an actuator made from soft materials have the potential to serve a variety of purposes, including rehabilitation, physiotherapy, and prosthesis. Further, each actuator's performance and compatibility play a critical role in determining its suitability for a particular application. Here the materials, design, and actuation strategies of soft actuators used in manufacturing wearable devices and body-powered prostheses are discussed. The majority of these actuators are not only force-compliant and flexible but also possess features like adaptability, multiple degrees of freedom, and easy integration with existing mechanical systems. Our final discussion focuses on improving their performance when deployed in real-world applications to overcome challenges associated with installation, portability, and added physical intelligence.
In order to ensure the stable operation of the wall-climbing robot on the ship's complex curved wall surface, analysis and optimisation method of non-contact permanent magnet adsorption unit is discussed in this paper. The influence of magnet arrangement, coupling, air gap distance and other factors on the adsorption force is analysed by finite element simulation software, and the parameter magnet-to-mass ratio is introduced to quantitatively compare these schemes. In the two scenarios of planar wall and curvature-varying wall, the structural parameters of the Halbach array are optimised with the maximum magnetic-to-mass ratio as the optimisation objective, and the ratio of adsorption force variation is proposed as the reference of design to ensure the performance of the adsorption unit on the variable-curvature wall. The running stability of the wall-climbing robot with designed magnetic adsorption unit is verified by experiments on the wall with varying curvature.
The ability to mimic the tactile feedback of the human hand to improve its dexterity, grasp/gripping and manipulation has been widely considered in robotic development. During robotic grasping, three forces are produced: grasp force (pressure), friction force, and tangential force (shear). Most of the tactile sensors are focused on pressure and normal force. However, shear stress is of great importance in manipulation for the prediction of gripping slippage and the implementation of force control. Improved measurement of shear stress can facilitate robots that mimic human-like robot gripping techniques and achieve advanced manipulation tasks. This paper reviews the state-of-the-art of shear/slip sensors for improving robotic and human dexterity. Tactile shear sensors for robotics and biomedical are reviewed, with an analytical comparison of the advantages and disadvantages of different sensing technologies.
This brief report investigates a mechanically simple pavement energy harvester using a linear electromagnetic solenoid. This energy harvester will harvest energy from human foot traffic and the design is unique in the sense that it has a very limited vertical displacement of only 1.5 mm and hence minimal effect on the walking gait. This prototype can generate output energy of 164 mW and 833 mW for a single step across a 27 Ω load when a person makes a single step and jump on the pavement respectively. Using a rectifier, the charging of a capacitor with each foot step has been demonstrated. The energy can be increased by having more electromagnetic solenoids.
Soft robotics has become an active research area due to its compliance with the natural anatomy, volume to weight ratio, and overall compatibility. However, the difficulties in controlling soft robots have remained a challenge for employing soft wearable robots for clinical applications. In this paper, a fuzzy-based nonlinear PID controller and higher-order sliding mode controllers which can maintain robustness in the presence of a disturbance signal have been designed and analysed. A simple innovative way to include pain signals in control design has been developed; the patient is actively involved by feeding the pain signal to the controller. The pain signal will be characterised into predefined categories from the physiotherapist's knowledge; a fuzzy controller is developed to generate reference force output for the controller from pain feedback and rate of change of muscle elongation. The developed models were analysed and simulated in MATLAB Simulink and Simscape's physical modelling environment.
Wearable exoskeleton is an assistive device for humans to carry heavy loads over long distance. The main aim of the study is to analyse the effect of an exoskeleton on human body during stand to sit motion, the study is accomplished by the use of a biomechanical analysis software called LifeMOD®. In this work, the activations of biceps femoris, rectus femorus and tensor fasclae latae (TLF) have been studied. The muscle activations during stand to sit with exoskeleton is found to be lesser than normal human movement, resulting in reduced expenditure of human energy. The results are helpful in training the control algorithms that are dependent on muscle activations measured by surface electromyography and to establish a framework for the study of behaviour of muscle activation while performing various activities driven by wearable exoskeleton.
Growing need for variety of micro-electro-mechanical systems necessitates advances in manufacturing technologies for high volume production at low cost. In the bio-medical field, drug delivery is one of the areas that attract the most attention for MEMS because of its potential to make drug delivery less invasive, more precise and less painful. A typical micro pump is a MEMS device, which provides the actuation source to transfer the fluid, in this case, the drug from the drug reservoir to the body (tissue or blood vessel) with precision, accuracy and reliability. Micro pumps are therefore an essential component in the drug delivery systems. In this study, a mechanical micro pump (with moving mechanical parts) will be modelled using MEMS module of COMSOL simulation tool. The micro pump will be based on electrostatic actuation which in-turn is based on the Coulomb attraction force between oppositely charged plates. The objective of this study is to determine the performance characteristics of electrostatic diaphragm driver for a range of applied voltages.
Surface electromyographic (sEMG) signal is commonly used as main input information to control robotic prosthetic systems. sEMG signals vary from person to person; gender is a factor influencing this variation. Thus, the aim of the study is to detect gender-related differences in sEMG activity of two main ankle-flexor muscles [tibialis anterior (TA) and gastrocnemius lateralis (GL)] during walking at comfortable speed and cadence. Statistical analysis of sEMG signals, performed in seven male (M-group) and seven female (F-group) adults, showed clear gender-related differences in muscle behaviour. The assessment of the different activation modalities, indeed, allowed to detect that F-group adopts a walking modality with a higher number of activations during gait cycle, compared to M-group. This suggests a female propensity for a more complex muscle recruitment, during walking. This novel information suggests considering a separate approach for males and females, in providing electromyographic signals as input information to control robotic systems.
In response to a thermal stimulation, skin tumours produce different temperature variations in comparison with healthy tissues. In this paper, we exploit this fact to design an intelligent melanoma detection system that estimates the development stage of a skin tumour. This system is based on a feed-forward artificial neural network, which receives a signal of the thermal response measured from the skin surface, and predicts the growth stage of the tumour. The measurement should be performed during the heat recovery after removing a cold stimulus. In order to train and test the neural network, here, these signals are provided by FEM-based simulations that solve the Pennes' bioheat transfer equation. Also, the signals are processed quantitatively and their convenient features are extracted. The achieved accuracy of 96% shows that the thermal response as the distinguishing criterion is an appropriate choice for the early diagnosis of the melanoma type of skin cancer.
