Multi-Domain Simulation of Human Mechanics for Dynamic Analysis

Digital human models (DHM) offer a great possibility of design evaluation for products humans interact with. One field to apply DMHs is the dynamic analysis of human-machine interaction. Thereby, the dynamics of the human body can significantly influence the entire system behavior and thus it is important to consider during the design process. For the modeling language Modelica no simulation library for this application is available, so far. The language is especially suitable for the simulation across different domains which makes a DHM in Modelica useful. In this paper a DHM predicting the dynamic behavior of the human body during human-machine interaction is implemented in Modelica. It consists of a multi-body skeleton model, an inverse kinematics algorithm for the limbs and a controller for the skeleton joints inspired by human motor control. The capability of the proposed simulation approach to take the relevant dynamical properties of the human body and motor control into account is demonstrated in a use-case simulation. As use-case the aircraft-pilot coupling during a strong gust acting on a sports aircraft is investigated

Performing Economics: A Critique of 'Teaching and Learning'

Economics students find difficulty in developing effective learning strategies; they would also welcome and benefit from a more pluralistic teaching of economics. Nevertheless, economics teaching has become less pluralistic over the recent past. Recent benchmark statements seem content to underwrite an essentially monist approach to the discipline in the hope that a deepening crisis in economics teaching can be averted by expanding teaching and learning programmes taking the content of teaching as given and instead concentrating on presentational reform. The paper argues that such teaching and learning strategies are part of the problem rather than its solution.

Perancangan Mekanik Pulmonary Rehabilitation Robot sebagai Pendukung Mekanisme Rehabilitasi Asma Breathing Retraining

Penyakit asma merupakan proses inflamasi pada saluran pernapasan yang menyebabkan saluran pernapasan menjadi hyperresponsive sehingga mudah terjadi pembatasan aliran udara. Penanganan penyakit asma membutuhkan fokus jangka panjang sehingga membutuhkan rehabilitasi. Rehabilitasi asma pada umumnya melibatkan beban anggota tubuh pada saat pelatihan. Breathing retraining merupakan mekanisme rehabilitasi yang tepat. Untuk membantu pendertita asma bertahan dengan mekanisme tersebut sesuai dengan waktu pelatihan rehabilitasi yang distandarkan, maka dirancanglah mekanik platform pulmonary rehabilitation robot. Platform ini terdiri dari tiga mekanisme yakni armpit support, thoracic push dan belt. Mekanisme armpit support dan belt menggunakan one pulley intraction, sedangkan thoracic push menggunakan sistem scissor jack lift. Dibandingkan platform yang sudah ada untuk penderita COPD, platform ini memiliki keunggulan yakni penambahan mekanisme belt sebagai pendukung untuk ekspansi rongga dada saat inhalasi. Selain itu, penambahan audio melalui headphone untuk meredam suara platform yang bising menjadikan pengguna asma tidak mudah otot pernapasannya menjadi hyperresponsive

Ergonomic modelling parameters and the influence of ergonomics on planning workplaces

ArticleModern economic research divides all economics into structural levels: mega - economics, macroeconomics, meso - economics, micro - economics, and nano - economics. From the point of such traditional divisions, the research is topical in the primary economic struct ure of society – nano - economics – and thanks to this work operations can be subdivided into workplaces in the form of transformation processes. The aim of the research is to develop ergonomic modelling parameters and to discover the influence of ergonomics on the planning of workplaces ba sed on a case study. The research involved a study of workplace ergonomic planning methods and principles. Solutions for a series of problems which are related to the improvement of workplace ergonomics may be discovered in the following ways: improving wo rk organisation in every workplace by using work process - related micro - elemental methods and a determination of work expenditure, the levels of physical strenuousness involved in the work, the complexity of the work, and the social importance of the workpl ace. These parameters will allow the workplace quantity characteristics to be discovered, such as in terms of a generalised parameter which conforms to the requirements which describe a workplace, and in terms of operational management via the condition of workplaces and the salary systems being utilised. The research provides a case study in which ergonomic modelling parameters are developed and concrete workplace interventions are introduced

Gaze Estimation Technique for Directing Assistive Robotics

AbstractAssistive robotics may extend capabilities for individuals with reduced mobility or dexterity. However, effective use of robotic agents typically requires the user to issue control commands in the form of speech, gesture, or text. Thus, for unskilled or impaired users, the need for a paradigm of intuitive Human-Robot Interaction (HRI) is prevalent. It can be inferred that the most productive interactions are those in which the assistive agent is able to ascertain the intention of the user. Also, to perform a task, the agent must know the user's area of attention in three-dimensional space. Eye gaze tracking can be used as a method to determine a specific Volume of Interest (VOI). However, gaze tracking has heretofore been under-utilized as a means of interaction and control in 3D space. This research aims to determine a practical volume of interest in which an individual's eyes are focused by combining past methods in order to achieve greater effectiveness. The proposed method makes use of eye vergence as a useful depth discriminant to generate a tool for improved robot path planning. This research investigates the accuracy of the Vector Intersection (VI) model when applied to a usably large workspace volume. A neural network is also used in tandem with the VI model to create a combined model. The output of the combined model is a VOI that can be used as an aid in a number of applications including robot path planning, entertainment, ubiquitous computing, and others

A trap motion in validating muscle activity prediction from musculoskeletal model using EMG

Musculoskeletal modeling nowadays is becoming the most common tool for studying and analyzing human motion. Besides its potential in predicting muscle activity and muscle force during active motion, musculoskeletal modeling can also calculate many important kinetic data that are difficult to measure in vivo, such as joint force or ligament force. This paper will validate muscle activity predicted by the model during a static motion like knee flexion motion (squat motion). In this experiment, knee flexion motion was performed by 5 healthy subjects and modeled by using Gait Lower Extremity model from AnyBody Modeling System (AMS). Eight lower limb muscle activity prediction from the model will be validated by 8 EMG electrodes that measured the same muscles during squat motion. Muscle activity pattern and the position of onset would be used as a key factor in this validation study. Pearson correlation coefficient will be used to compare the pattern of both graphs. Knee joint force prediction from the model will also be compared with the literature studies. The result showed that 3 muscles showed high correlation coefficient, while the other 4 muscles showed slightly medium and one showed low correlation. Time delay of muscle activation between the model and EMG was recorded from Vastus Medialis muscle (18.38 ms) and Vastus Lateralis (22.8 ms), with muscle activation from the model was late compared to EMG. In conclusion, this statistical study has shown some detail differences between EMG and muscle activity prediction from the model. Knee flexion motion can be used as a trap motion when validating muscle activity of a musculoskeletal model, because the model will activate muscle activity based on motion data of markers, while in knee-flexed position, there was no marker’s movement, but the EMG was highly active due to the posture of the subjects in maintaining the knee-flexed position. However, the knee compressive force prediction from the model has showed positive confirmation from the literatures