bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial Intelligence Algorithms in Precision Medicine: a New Approach in Clinical Decision-Making
Authors: Damato Valeria , Campiglia Pietro , Bassano Clara
Published: June 2022

US National Institutes of Health described the precision medicine as ‘an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment and lifestyle for each person.’ In other words, on the basis of the definition, the precision medicine allows to treat patients based on their genetic, lifestyle, and environmental data. Nevertheless, the complexity and rise of data in healthcare arising from cheap genome sequencing, advanced biotechnology, health sensors patients use at home, and the collection of information about patients’journey in healthcare with hand-held devices unquestionably require a suitable toolkit and advanced analytics for processing the huge information. The artificial intelligence algorithms (AI) can remarkably improve the ability to use big data to make predictions by reducing the cost of making predictions. The advantages of artificial intelligence algorithms have been extensively discussed in the medical literature. In this paper based on the collection of the data relevant for the health of a given individual and the inference obtained by AI, we provide a simulation environment for understanding and suggesting the best actions that need to be performed to improve the individual’s health. Such simulation modelling can help improve clinical decision-making and the fundamental understanding of the healthcare system and clinical process.
Roles and Competences of Data Science Projects
Authors: Dukino Claudia , Kutzias Damian , Link Maike
Published: June 2022

In recent years, it has become increasingly apparent that data is playing an ever more important role in companies and the need for IT (Information Technology) applications to support people in their activities is growing. The requirements for data-driven projects for the automation and augmentation of processes and tasks are significantly higher than for standard IT projects. An essential requirement is to learn from company data and to use it for new applications. The composition of the project team plays an essential role. It is necessary to recognize which roles and competences are required for the implementation of the project and to recognize how these may change during the project. In the following, due to the interdisciplinary nature of data science projects, new competences and roles for project execution will be identified and discussed. Possible risks that can arise from unstructured project planning and from role and competence planning will be identified. The differences compared to standard projects are highlighted and the challenges compared to them are examined. To support project planning, the use of tools can be helpful. The requirements a tool or method should fulfil in order to add value for a broad spectrum of enterprises are addressed. Exemplary criteria in this context are neutrality, branch independence and free availability of the method. In addition, the usability and areas of application of such tools are discussed.
Implementation of AI Technologies in manufacturing - success factors and challenges
Authors: Kutz Janika , Neuhüttler Jens , Spilski Jan , Lachmann Thomas
Published: June 2022

There is a broad consensus on the potential of smart services for production and the added value their use offers. Industrial artificial intelligence (AI) has several advantages. AI technologies, for example, can strengthen resilience, support work processes, increase product quality and thus improve competitiveness. Many companies have recognised these potentials and are developing AI solutions. There are many successful proof-of-concepts (PoC) and pilot projects, but AI technologies successfully implemented in the real environment are scarce. Successful implementation of smart services based on industrial AI in production operations can be understood as its repetitive use and integration into operational business, which is a prerequisite for exploiting the potentials. Currently, little is known about how to achieve successful implementation. In contrast, there is much evidence that the implementation and operation of AI in manufacturing is associated with extensive challenges and barriers. The factors that positively influence the roll-out of AI technologies in manufacturing, however, are little explored. Therefore, this paper focuses on the identification of success factors and barriers for the implementation and operation of AI solutions in manufacturing. Furthermore, it is analysed whether and how the identified success factors and barriers differ from each other in order to subsequently derive initial recommendations for action. The methodology is based on explorative qualitative research. First, 10 semi-structured interviews were conducted with AI experts from a German Original Equipment Manufacturer (OEM). In an expert workshop, the main findings were validated, and possible solution and support options were discussed. Our findings confirm the results found in the literature and complement them with new insights. Success factors and challenges can be found on the technical, organisational, and human side and relate most often to "data", "development and operational processes" and "stakeholder engagement".
Towards the role of smart services as well as AI in building and enhancing entrepreneurial resilience in small and medium-sized service companies
Authors: Gorovoj Alexander , Schiller Christian , Friedrich Michaela , Rahman Abdel Razek Abdul
Published: June 2022

The aim of this paper is to provide practitioners and consultants with guidelines for enhancing organizational resilience in small and medium-sized businesses. It describes the actions an organization could perform and what goals should be pursued in order to successfully respond to potential threats. Design/methodology/approach – The paper builds on existing research on organizational resilience as well as the resilience of complex systems and the theories established there. By linking these research areas, it describes an adapted framework that considers the use of artificial intelligence and the provision of smart services in service companies. In addition, the paper illustrates the practicality of the framework by applying it to a small brick-and-mortar retail business.Findings – This paper proposes the use of a structured approach and methods such as stress testing and simulations to increase organizational resilience. It suggests that using artificial intelligence as well as offering smart services can have a positive impact on the resilience of a small and medium sized business.Originality/value – The paper contributes to the better applicability of measures aimed at increasing organizational resilience by suggesting a structured approach as well as appropriate avenues for action.Keywords: Organizational Resilience, Complex Systems, Smart Services, Artificial Intelligence
Essential Areas of Action for the Smartification of Traditional Products and Services Considering the Capabilities of SMEs
Authors: Frings Sandra , Kett Holger , Falkner Jürgen
Published: June 2022

One way for small and medium sized (SMEs) enterprises developing traditional physical products to follow the digital transformation is to smartify their products and develop smart services according to business or customer needs. The process to set up a smartification strategy for the first time covers many different organizational, human, technical and business process related aspects. With our research we provide a decision framework to support CEOs in identifying, which areas of action should be focused upon and enterprise-specifically further developed for the smartification of selected products. This paper derives the areas of action, which build the base for the decision framework’s underlying capability and maturity model.
An approach for developing and assessing sustainable business models
Authors: Ahner Lena , Neuhüttler Jens , Gladilov Nicole
Published: June 2022

With sustainability becoming an increasingly important factor in a globalized world, there is an increasing demand for ways to systematically incorporate sustainable activities into companies. Representing the value creation logic of a company, business models play an important role in this development. In this paper we suggest an approach to support organizations in developing and evaluating sustainability aspects in their business model by helping select appropriate measures as well as considering assessment indicators that help evaluate their successful implementation.
The Soul of a New Machine: Promises and Pitfalls of Artificial Intelligence in Finance
Authors: Stiefmueller Christian
Published: June 2022

After decades of development and many false dawns Artificial Intelligence (AI), in its various guises, finally appears poised for mainstream commercial adoption. The financial sector, in particular, is looking with great interest at a broad range of applications. In April 2021, the European Commission published draft legislation that endeavours to create a comprehensive regulatory framework for the civilian use of AI. With its proposal for an "Artificial Intelligence Act" (AI Act) the Commission aims at striking a balance between the twin objectives of promoting the uptake of AI in the European Union and the need to address the risks associated with some of its uses. To this end the AI Act identifies a number of applications that are either deemed "high risk", and therefore subject to specific requirements and enhanced supervision, or prohibited outright. Only one of the “high risk” applications listed in the initial proposal relates to the financial services sector. This contribution examines other potential intersections between the proposed AI Act and the extensive body of existing financial-sector legislation and seeks to provide an initial assessment of the proposed regulatory framework.
Sustainability-related gamified design science approaches for successful value creation
Authors: Poecze Flora , Min Tjoa A
Published: June 2022

The use of gamified designs has been gaining exponential research interest during the last decade, centered around user-centric designs aiming to persuade individuals to a successful individual behavioral change. In the focus of scientific interest are those, which lead to a maintained behavioral change led by intrinsic motivation. Such designs are at the center of attention in diverse sustainability-related topics as well (e.g., education, crowdsourcing, healthcare, individual wellbeing, eco-friendly behaviors, etc.). A focal point of such approaches lies in their rigorous conceptualization, for which design science offers detailed guidelines, resulting in successful artifacts, generated to deliver tailored solutions for users, providing value creation. The present paper aims to investigate, in what types of sustainability-related contexts are gamified approaches proposed as design science artifacts for successful value reaction. The goal of the paper is to identify and explore these research areas and hand a holistic overview about promising and innovative, applied approaches, conducted as design science artifacts. This goal is reached through a narrative synthesis method, searching and selecting papers at Scopus, Web of Science, and ACM Digital Library as databases, following the PRISMA 2020 Guidelines, interpreting N = 14 records. The results of this study deliver a structured summary about successfully gamified design science artifacts centered around value creation in pro-sustainability areas, offering a snapshot of the present standing of research in this applied domain of interest
From Alibaba to Youtube: User Search for Digital Democracy Topics in Switzerland
Authors: Glauser Christoph , Serdült Uwe
Published: June 2022

Digital Democracy tools such as e-consultation, e-petitions or internet voting play an increasing role and are part of the digitalisation process in politics and government. Digital life styles in general and during the pandemic in particular might have pushed for an increasing demand for so called civic tech tools. Digital democracy search terms were monitored across multiple digital channels for several months in the year 2021 and contrasted to the offer for such tools in the German, French and Italian speaking part of the country. To measure the offer for digital participation tools an index per canton established in 2021 is being used.
Interaction as a concept for Social Service Engineering
Authors: Zinke-Wehlmann Christian , Friedrich Julia , Römer Vanita , Gilbert Kristin , Pietrzyk Ulrike , Steputat Rätze Anne
Published: June 2022

Purpose: Human factors play a central part in the design and management of services and service systems. This paper asks the conceptual question of the role of human factors in service science, speaking about the dimensions of human interactions in service design. Design/methodology/approach: Our research is deeply embedded in the approach of design science research (DSR). In contrast to the DSR which focuses primarily on designing and evaluating practical solutions, this work concentrates on theory building during DSR cycles. Hence, it systematically develops practical solution experiences and theoretical conceptualizations accordingly. Findings: While current research in service science focuses on service systems with service as the central element, the present paper evaluates the importance of interaction as the basis for the co-creation of value and, thus, linking service system and work system. It introduces the concept of interaction as a phenomenon that describes the in-actu situation in which actors co-create value by exchanging service – especially in human-human interaction. Work and service design as well as service engineering means to design all conditions for a successful interaction – avoiding value destruction (e.g., stress and unhealthy work conditions) as well as promoting co-creation of value (e.g., wellbeing, satisfaction as well as monetary value).
Combining digital and physical user interfaces – concept of a self-service system for exhibitions
Authors: Zagel Christian , Leyendecker Matthia
Published: June 2022

Digitization is finding its way into many different areas and applications, including exhibitions and museums. While until a few decades ago the information presented was purely restricted to physical elements, self-service systems are now increasingly applied in exhibitions. They allow the visitors to enhance their experience by obtaining additional digital information. Usually, these self-service systems are implemented using standard computers, equipped either with a keyboard or a touchscreen. Nevertheless, the added value of interacting with physical elements in our environment is undeniable. This article presents work in progress and describes the concept and prototype of a novel system that cleverly combines digital information with the interaction through physical elements using innovative technology. The aim is to design an interactive exhibition for museums that combines the traditional, physical user interface with the digital version and thus creates a mixture of both worlds. Using the example of a physical city map, the system offers visitors the opportunity to interact by touch and wooden cubes equipped with NFC tags. The article concludes with an outlook for an evaluation of the prototype and recommendations for further research.
Effect of the backpack load on students’ discomfort
Authors: Ashok Chougule Nutan , Ahmed Aliuddin , Li Yueqing
Published: June 2022

Backpacks are very useful in our day-to-day life, work, offices, and school. Especially students carry backpack to school every day with heavy loads of textbooks, notebooks, and laptop. This is an increasing concern of students carrying heavy backpacks in most countries. From the article of Huntsville Hospital, in the United States around 79 million students carry backpack to school. In 2007, more than 23,000 backpack-related injuries were treated at hospital rooms, physician offices and clinics. The load exerted from the backpack is one of the reasons of variations in the cervical and shoulder posture and it is suggested that carrying a backpack weighing 15% of body weight will be heavy for adults. This study evaluates the effect of backpack loads on the user discomfort in neck, shoulder, upper back, lower back, and knee during a walking activity. For this experiment, 12 participants were selected in the age group of between 18 to 21 years old from Lamar University. The backpack load which is exerted by the backpack was independent variable. As per the research, 15% of total weight of the body is the standard weight to carry the backpack during walking activity. Since, we have considered 10%, 15% and 20% weights of the backpack to the total body weight of participants. The user discomfort is considered as dependent variable. The walkway was embedded with three force plates with various backpack loads (10%, 15%, and 20%). Participants were told to walk on defined route for 10 minutes. After each task, participants had 5-minutes break and were asked to rate their discomfort level. The same procedure was carried out for all participants and measurement data were collected.The result showed a significant main effect of backpack load on the user discomfort of neck, shoulder, upper back, lower back and knee. The user discomfort with 20% load was significantly higher than that with 10% load for all 5 body parts. During the experiment, it was observed that female participant who weighs in range of 100-120 lbs. were experienced most discomfort and not able continue experiment when the weight of the backpack was more than 15% of the total body weight. Whereas the participants with the range of body weight around 160-180 lbs. experienced less discomfort in their neck and shoulder throughout the experiment. In conclusion, the research found that the backpack load significantly affects the user discomfort when student walk carrying the backpack. The research should have practical meaning to decide the appropriate weight of the students’ backpack and develop a more user-friendly design.
Effect of the shoe heel height on lower-limb muscle activity
Authors: Mitsuno Tamaki , Sugawara Ami
Published: June 2022

Women often wear high-heeled shoes to make their feet look slender and tall. We focused on the muscle activity of the lower limbs and investigated how the presence or absence of shoes and the change in heel height affect the lower-limb muscles. The participants were eight women in their twenties, and the lower-limb muscle activity was measured while the participants wore running/low-heeled/high-heeled shoes. The surface myoelectric potential was measured for eight muscles around the knee/waist using a multi-channel telemeter as the participants walked on a treadmill. The root-mean-square myoelectric potential and thus muscle activity were significantly higher for bare feet than for wearing shoes. Additionally, there was no significant difference in muscle activity between low-heeled and high-heeled shoes, but the activity was less for these shoes than for running shoes. Thus, as the heel height in-creased, the muscle activity around the knee decreased whereas that around the lumbar spine increased.
Effects of carbon fiber insole on lower-extremity muscle activation and wearing comfort during treadmill running
Authors: Ko Myeonghoon , Ma Tiejun , Xiong Shuping
Published: June 2022

Background and Objective: Although the role of shoes on sports performance and injury has been extensively examined, only a few studies investigated the effects from insoles. Recent studies on carbon fiber insoles (CFI) on athletic performance reported that CFI could improve sports performance by reducing energy loss and increasing energy return. However, there are scarce reports on the effects of CFI on muscle fatigue and wearing comfort. While stiffer CFI insoles are superior in energy loss reduction and energy return, they could increase more muscle activation to absorb the shock or provide more propulsive force to push CFI, leading to increased muscle fatigue and discomfort. Therefore, this study aims to evaluate the effect of CFI on lower-extremity muscle activation and wearing comfort during treadmill running. Methods: Three types of insoles were compared, namely CFI, CFI with cushioning (CFIC), and a benchmark commercial insole (COM). Fifteen healthy young men participated in the experiment. Each participant wore the same sports shoe, three different insoles in a random order, and ran on a treadmill at a speed of 10 km/h for 5 minutes. Surface electromyography signals of four lower-extremity muscles (Rectus femoris, Tibialis anterior, Biceps femoris, and Gastrocnemius medialis) were recorded in real-time for measuring muscle activation. After completing a trial run with each experimental insole, the participants provided their subjective ratings on perceived insole stiffness, energy support, overall comfort, and fatigue. Analysis of variance (ANOVA) and post-hoc grouping analysis were conducted to statistically evaluate the effects from three different insoles. Paired t-test was performed to compare CFI and CFIC and explore any cushioning effect. Results: In terms of lower-extremity muscle activation, even though CFIC and COM showed no significant difference for all four lower-extremity muscles, CFI induced a marginally significant increase of 1.5% on Gastrocnemius medialis (p = 0.063) and a significant reduction of 0.7% on rectus femoris (p=0.011) than COM. For the subjective ratings, both CFI and CFIC were significantly stiffer than COM (p < 0.001), but there were no significant differences in overall comfort, energy support, and fatigue. Compared with CFI, CFIC significantly reduced Gastrocnemius medialis muscle usage by 2.1% (p = 0.012) and was marginally less stiff (p = 0.102).Conclusions: This preliminary study showed that the carbon fiber insole CFI induced higher calf muscle usage and was perceived to be stiffer during treadmill running, which could contribute to provide the propulsive force for better sports performance. Carbon fiber insole with cushioning (CFIC) can help to relieve muscular fatigue. Further research should be conducted to examine the carbon insole effects on sports performance and long-term muscle activation and perceived feelings.
Cycling Stability and Symmetry using a Corrective Bib Short
Authors: Henderieckx Senne , Van Gastel Alexander , Vleugels Jochen , Smets Sam , Verwulgen Stijn
Published: June 2022

In cycling, biomechanical posture optimization strives to improve core stability and symmetry in the lower and upper extremities to raise power output. In addition, the shape and pose of the cyclists determine the projected frontal area, which is the major factor influencing drag during cycling. In this study, a high-fidelity prototype garment was developed that includes kinetic bands and proprioceptive devices to adjust biomechanical posture during cycling. The aim is to measure improved projected frontal area, stability, and symmetry as a result of wearing a corrective cycling garment. Thirty participants were gathered under strict exclusion criteria to ensure a representative sample of the population. Two exploratory studies were conducted: experimental and reference measurements of 1) 11 cyclists’ pedal balance and projected frontal area, and 2) 5 cyclists’ biomechanical movements through an optical motion tracking system. The results indicate an improved pedal balance and deteriorated stability and symmetry for the corrective bib short.
Prediction of Muscle Fatigue During Dynamic Exercises based on Surface Electromyography Signals Using Gaussian Classifier
Authors: Tatt Cheah Yeok , Wing Frances Wan Ka , Yip Joanne
Published: June 2022

Muscle fatigue is shown to be associated with incidence of musculoskeletal injuries found with sports training and competition. The real-time detection of fatigue onset allows preventative measures to be taken in time to minimize injuries. In this paper, we aim to provide a framework that classifies muscle fatigue based on surface electromyography (sEMG) features extracted during dynamic exercises. This includes the use of data segmentation, real-time-compatible data normalization, a principal component analysis (PCA) based feature reduction and Gaussian classifier methods.An experiment has been carried out to acquire the sEMG signals of the upper two pairs of rectus abdominis muscles of four healthy adult volunteers during weighted decline and bench-assisted sit-ups. The collected sEMG signals are then segmented into concentric and eccentric segments by using the inertial measurement unit (IMU) data. Eight commonly used sEMG features are extracted from each segment. We fit two Gaussian models (GMs) on the distribution of fatigued and non-fatigued data samples and show that the GM can utilize this information to predict the number of repetitions possible before task failure. We fit another set of GM on a reduced feature space by projecting the data onto principal component axes obtained through singular value decomposition (SVD). By projecting the features onto the first two principal axes, we achieve similar accuracy and f1-scores compared to the GM by using 6 handpicked features. This reduction in the feature space greatly reduces the training samples necessary for such class-imbalanced datasets. This classifier can also be directly used in the real-time detection of muscle fatigue during dynamic movements, which can be adopted in applications in sports, workplaces, and rehabilitation sciences. These frequency-time characteristics also provide insight into the function of low-level feature extractors when developing deep learning models to identify muscle fatigue.
Integrating sEMG into NIOSH protocol: a manual material handling risk assessment in the fruit and vegetable department of a supermarket
Authors: Silvetti Alessio , Ranavolo Alberto , Chini Giorgia , Varrecchia Tiwana , Tatarelli Antonella , Fiori Lorenzo , Papale Adriano , Fiorelli Ari , Draicchio Francesco
Published: June 2022

The biomechanical risk of cashiers in the retail sector has been extensively studied in literature. Despite high back pain prevalence in this sector manual material handling (MMH), instead, seems almost ignored. The aim of our study is MMH risk assessment in a fruit and vegetable department of a supermarket. This task wasn't still investigated, to date, together with standardized protocols and instru-mental-based tools. The sizes of the shelf allowed the use of the NIOSH protocol for the low level, whereas middle and high did not allow its use due to horizontal distance that exceeded the 63 cm set by the protocol. To integrate the NIOSH pro-tocol was used surface electromyography (sEMG). The recommended weight limit (RWL) in our case, according through NIOSH liftinq equation, was 17 Kg. The maximum handled weight from the workers was 14 Kg. The maximum mean peak value while lifting 14 Kg at a low level was 40.1% of Maximum Voluntary Contraction (MVC) in the left Erector Spinae. We assumed this sEMG value to be a safety value and used as a limit for lifts at the middle and high shelf levels because the maximum handled weight of 14 Kg was lower than the 17 Kg limit calculated through the NIOSH equation for the low level. This sEMG limit was exceeded, in the middle, while lifting 14 Kg (47.8% MVC), and in the high level lifting 10 Kg (44.7% MVC), 12 Kg (50.3% MVC), and 14 Kg (57.7% MVC). Our findings show that, for the analyzed shelf and for the male working popula-tion of that supermarket, we could accept as reasonably safe handling boxes up to 14 Kg for the low level, up to 12 Kg in the middle, and up to 8 Kg in high. This study shows that the integration of different assessment tools, such sEMG and NIOSH protocol, could help to a better estimation of biomechanical risk assess-ment. The study, moreover, provided practical guidelines for the health and safety service concerning the recommended load handled on each shelf level to minimize the risk of MMH in the fruit and vegetable department.
Anxiety level among industrial engineering students in virtual learning
Authors: Corrales Cesar , Rojas Jonatan , Atoche Wilmer
Published: June 2022

Stress is one of the most important psychosocial risks and it can produce, among other things, different degrees of anxiety, in work life, in studies or in any field of activities carried out by human beings. Anxiety is a state of mind and a physiological response of the person when facing a situation that causes anguish, fear and mental and emotional blockage. Among young university students, this occurs to a greater or lesser degree and is often not diagnosed or evaluated in its true magnitude. The Covid 19 pandemic has generated a radical change in the teaching modality that has gone to a virtual learning, which has aggravated the usual anxiety levels in students. The aim of this study was to examine the anxiety level of industrial engineering students of different academic levels, in this pandemic environment, to help them cope with this problem. To do this, a study sample was taken and an evaluation instrument was applied that allowed these levels to be established. Relationships were established with the number of credits taken on average and the study cycle of the students in the sample. The results show significant information that can help academic leaders and students themselves to take measures that help improve their anxiety levels.
Assessment of risk factors of upper-limb musculoskeletal disorders in a fish processing industry
Authors: Cunha Dos Reis Diogo , Renato Pereira Moro Antônio
Published: June 2022

A large number of studies show that awkward postures and repetitive hand and wrist movements contribute to the development of work-related musculoskeletal disorders (WMSDs). To effectively prevent these problems, there is a need for precise and quantitative knowledge about the relation between exposure and effect. In most epidemiological studies of disorders of the upper limbs, information about exposure is too limited or imprecise. Moreover, the exposure often involves several dimensions, and therefore it is necessary to use reliable methods to obtain trustworthy risk estimates. Therefore, the aim of this study was to evaluate the risks in relation to repetitive movements of the upper limbs of workers, as well as analyze the effects of a reduced work pace on the risk levels in a fish processing industry. The study was conducted in a Brazilian fish processing industry with 1,900 workers, who were divided into two work shifts. The OCRA checklist was used to assess 10% of the total workforce during work tasks. The 13 main work tasks (homogeneous groups) of the productive sector were analyzed. The occupational repetitive actions performed by workers were 81.5 ± 19.2 per minute, representing 10 points on the OCRA scale (0 to 10 point scale). The average score of the OCRA checklist was 18.4 ± 2.9 (moderate risk). Considering the five risk categories proposed by the OCRA method, 12 tasks were deemed moderate risk (92%) and 1 low risk level (8%). Due to the predominance of the highly repetitive movements of the upper limbs in fish processing work, and previous studies suggesting a reduced work pace to prevent UL-WMSDs, simulations of a pace with very low risk levels were carried out utilizing the OCRA checklist. By conducting these simulated interventions, it was possible to reduce the risk of UL-WMSDs to very low levels in all tasks by only decreasing the work pace (-42.8 ± 17.7%). These results suggest that most of the tasks carried out by workers were classified as moderate risk, predisposing workers to a greater probability of developing UL-WMSDs (10.8 to 21.5%) than the population that was not exposed. Simulations of a reduced work pace showed the effectiveness of this organizational measure in lowering the risk of UL-WMSDs.
Physical, Psychophysical and Demographic Changes Require Automated & Autonomous Machines & Equipment (AAM&E) in Construction
Authors: Choi Sang , G Borchardt James
Published: June 2022

Construction is one of the most dangerous with high prevalence of work-related fatalities and injuries among the high-risk industrial sectors. Concurrently, the construction industry is experiencing workforce demographic changes and shortages of skilled trade/construction workers. This paper provides an overview of the shifting construction workforce and the benefits & exposures from the evolving automated and autonomous machines & equipment (AAM&E) under development for the construction industry. Specifically, this paper describes a synopsis of design methodology and principles of AAM&E associated with human-related factors (e.g., self-efficacy, mental/cognitive workload, situation awareness). Also, this paper discusses potential practical applications and insights on the human-machine interaction/collaboration and key factors for building trust in human-robot teamwork (e.g., rule-based framework, transparency/feedback, observation, predictability). This paper can assist human factors & ergonomics (HFE) and safety professionals who may not be current with this evolving AAM&E technology to pre-plan and design control methods into industrial and construction projects.
The effects of flash frequency and amount of information in mitigating the effects of fatigue
Authors: Zhang Xiaoyan , Xue Hongjun
Published: June 2022

Fatigue is a crucial factor related to aviation safety and is likely to result in negative impacts in cockpit operation tasks, especially for warning information recognition in emergency situations. The aim of this study was to examine the effects of sleep deprivation induced fatigue on task performance of warning recognition tasks, and how the above effects were moderated by two presentation characteristics of warning information (i.e., flash frequency and amount of information). Nine participants participated in an experiment in which they performed warning recognition tasks under both normal and fatigue conditions. Fatigue condition was induced by one night of sleep deprivation. Flash frequency ranged from 1 to 5 HZ in increments of 1 HZ, while amount of information was indicated by the number of information elements and ranged from 3 to 5. The results indicated that sleep deprivation induced fatigue and overload information amount impaired performance significantly, while flash frequency yielded no significant effect on human performance in fatigue condition. Besides, fatigue interacted with amount of information. Interestingly, in fatigue condition when the information amount raised up to 5, the response time significantly decreased by 100ms compared with 4, while in normal condition the response time increased with the information amount increasing. The findings suggested that fatigue and overload information amount are risk factors of aviation safety, and flash frequency has no mitigating effect under fatigue condition.
Introduction of Distractions in Immersive Virtual Reality Laparoscopic Surgery Training – a Pilot Study
Authors: Wu Xintong , Luo Tianren , Xiong Shuping , Liu Yuanyuan , Li Meng
Published: June 2022

Reducing human errors by surgeons is of great importance to patient safety. The main drawback of current VR laparoscopic surgery training is that it only focuses on improving the proficiency of basic surgical skills while lacking the true representation of the busy and chaotic OR surroundings. Multiple distractions were introduced into this study to explore the influence on the laparoscopic surgery training process. A VR headset displayed a video of a laparoscopy procedure recorded by a 360° camera in a real OR, which contains various distractions occurring during the surgery. Ten surgical trainees performed a standardized training task in the virtual OR under both non-distractive and distractive conditions. Questionnaires, videos and semi-structured interviews were used to collect data. The results showed that the introduction of distractions significantly reduced participants' task performance (p<0.001) and increased their mental workload (p=0.001). Participants also showed different degrees of sensitivity to various distractions. In addition, most participants raised the need for system personalization. This VR-based immersive virtual OR demonstrated its potential to enhance surgeons' ability to deal with distractions in laparoscopic training. Future work will focus on improving the personalization and interactivity of the system, thereby increasing the training efficiency.Keywords: Immersive virtual reality; Surgical training; Distractions; Human error; Cognitive Workload
Plantar Soft Tissue Stiffness Automatic Estimation in Ultrasound Imaging using Deep learning
Authors: Pusparani Yori , Liau Ben-Yi , Jan Yih-Kuen , Cheng Hsu-Tang , Ardhianto Peter , Akhyar Fityanul , Lung Chi-Wen , Lin Chih-Yang
Published: June 2022

Preventing diabetic foot ulcers (DFU) is critical for diabetes mellitus (DM) patients. Increased stiffness of plantar foot may cause higher plantar pressure leading to a higher risk of DFU. Soft tissue stiffness can be determined by measuring the soft tissue thickness with indentation depth and stress. Therefore, we hypothesized that the deep learning model could detect the ultrasound image pixel change under soft tissue compression. This study aimed to apply the deep learning model to analyze the ultrasound image pixel thickness of plantar foot, then predict the soft tissue indentation depth and loading force for estimating the stiffness. This study has developed a motor-driven ultrasound indentation system to apply programmable compression and simultaneously assess soft tissue mechanical properties and responses in indentation depth and loading force. In addition, the effective Young's modulus was calculated to characterize mechanical properties of soft tissues in the first metatarsal head. The deep learning method employed the YOLOv5x model to train and detect the small object in the indentation depth, such as ultrasound image pixel changes. Finally, the dataset images were processed with labeling annotation from the soft tissue indentation depth and loading force. The deep learning results showed 0.995 in mean Average Precision (mAP), 0.999 in precision, 1.000 in Recall, and 0.013 in Loss. A significant correlation was found between the ultrasound image pixel changes and soft tissue indentation depth (r = 0.98, p < 0.05). Furthermore, a significant correlation was observed between the ultrasound image pixel changes and the loading force in the first metatarsal head (r = 0.85, p < 0.05). The validation and prediction models were lower than the training models in the effective Young's modulus results. However, the results of the initial modulus were similar between the three models. Our findings recommend that applying deep learning in the ultrasound image can predict soft tissue indentation depth and loading force to calculate the stiffness of the plantar foot.
The physical load of the Human body during Motion with BP Neural Network
Authors: Zhou Biyun , Lihao Xue , Liu Xiaopeng , Yang Qing , Ma Liangsheng , Ding Li
Published: June 2022

Background: Unreasonable tasks will increase the person’s physical load, leading to safety accidents and occupational diseases. To ensure a reasonable physical load and improve the operational efficiency of the person as far as possible, it is necessary to predict and evaluate the physical load of workers in real-time.Objective: A prediction model of the physical load intensity of the human body based on a neural network was established, and its effectiveness was verified.Methods: Twelve volunteers completed four movements walking, jogging, climbing, and jumping. The surface electromyography (sEMG) on the left and right sides of the rectus femoris and biceps femoris was measured, and the motor posture of volunteers was obtained by Vicon, the joint torque, maximum muscle activity, and muscular force parameters were calculated based on the reverse dynamic model of human motion. The sEMG eigenvalue and mechanical load parameters in different postures were considered input and output, respectively, and 80% of all data were used as the training set and the rest as the validation set.Results: In this study, we found that the hip joint, knee joint, and ankle joint have a sizeable joint torque during movement, in which the joint torque of the ankle joint is the largest and twice human body weight at its peak. Besides, a larger muscle load occurs at the beginning and end of contact between the human foot and the ground, and the muscle strength of the rectus femoris was significantly higher than that of the biceps femoris (p<0.05). The number of neurons in the input layer, an output layer, and a hidden layer of the model is 32, 13, and 12, respectively. This study found that the prediction error of maximum muscle activity was 6.4%. The average prediction error of joint torque was 8.7%, and the prediction error of the muscular force of the rectus femoris muscle was no more than 9.5%. This model can reasonably predict the physical load of the human body.Conclusions: A workload evaluation model based on the BP neural network was established in this research, which can analyze the biomechanics of the human body in motion and judge the human body’s physical load effectively according to the EMG signal.Application: This model can measure the body load of soldiers and firefighters in real-time during task training and provide a reference for task design.
Modeling of changes in lumbar joint stiffness by pelvic tightening based on physique and pelvic alignment
Authors: Yoshida Michihiro , Takayuki Tanaka , Tsuchiya Yoshio
Published: June 2022

We have been elucidated the mechanism by which pelvic belt reduces lumbar burden. Pelvic tightening increases the lumbar joint stiffness and inhibits the flexion of the lumbar spine in the forward bending. Flexion of the lumbar joint is substituted by the hip joint, which corrects the posture during forward bending and reduces the lumbar burden (lumbar joint torque). The level of the assisting effect of the tightening force has the individual difference, but at present, it is not clear what factors cause it. In this study, we develop a model that represents the assistance effect based on the physique such as height and weight, and the posture and shape of the pelvis and lumbar spine (pelvic alignment).This study developed a regression model that expresses the amount of change in joint stiffness due to tightening force, using the individual physique and pelvic alignment characteristics as input. The joint stiffness was estimated from motion measurement using optical motion capture and obtained from the equation of motion of the link model representing the human body. Pelvic alignment was measured by X-ray images, and five features were obtained: sacral inclination angle (SS angle), pelvic inclination angle (PT angle), inclination angle of the sacrum relative to the pelvis (PI angle), curvature of the lumbar lordosis, and pelvic aperture angle. Among these, the SS angle, PT angle, and PI angle were measured under two conditions: standing and 45 degrees forward bending and obtained a total of eight pelvic alignment features. In addition, height, weight, BMI, and back muscle strength were added as physique characteristics expressing body size and muscle strength, for a total of 12 variable measured. These features were measured on 15 subjects. Among the 12 features, three to four variables were input to the model by excluding those that were strongly correlated with each other and less capable of explaining changes in the target value, joint stiffness.From the proposed model, changes in joint stiffness could be estimated from pelvic alignment and physique characteristics. At large forward bending angles, we found that to obtain a high assistance effect, tilting of the sacrum anteriorly relative to the pelvis and forward tilting of pelvis is necessary. On the other hand, in the mild forward bending, the person who is higher body weight in addition to the forward tilt of the PT and PI angles tend to obtain higher assistive effect.
Developing a computer-vision model to estimate anatomical joint coordinates during manual lifting tasks
Authors: Hsiao Chih-Yu , Chang Chien-Chi , Chen Ting-Yu , Lin Yi-Ting
Published: June 2022

This study developed a Computer-Vision based anatomical joint coordinates estimation model to predict the 3D joint coordinates with the help of Artificial Intelligence image recognition technology during manual lifting tasks based on single camera video inputs. The workflow of the proposed Computer-Vision model includes 2D joint detection and 3D joint reconstruction. The 3D joint error is calculated based on the Euclidean distance between the predicted 3D joint coordinates from the CV-based method and the corresponding joint coordinates of the ground truth from the Visual 3D TM skeletal model. The results indicated that the floor to shoulder lifting height path induced a greater 3D joint error than the floor to knuckle and knuckle to shoulder lifting height paths (p-value = 0.01). The 3D joint error of the hand was the largest than the other estimated joints. This study verified that the proposed Computer-Vision model could predict 3D joint points. Therefore, while the marker-based motion tracking system is inapplicable, the model can be used as an alternative solution for predicting lifting motion.
Posture Analysis of Mass Rapid Transit (MRT) Passengers Using the REBA Method in Jakarta, Indonesia
Authors: Laksyana Utami Dessy , Luthfianisa Putri Aisy
Published: June 2022

Transit-oriented development (TOD) is one of the sustainable urban development concepts in tackling congestion, environmental degradation, and energy efficiency. To realise transit-oriented development, the government issued a transit-oriented development policy at every rapid mass transit (MRT) station in DKI Jakarta. The Mass Rapid Transit train (MRT) Jakarta has dimensions of 20 meters long, 2.9 meters wide and 3.9 meters high. Dominated by metallic blue and grey, the train body is made of stainless steel with an empty weight per train reaching 31 to 35 tons. PT MRT Jakarta provides 16 train series (one series consists of six trains) so that the carrying capacity of one series reaches 1,950 people per series. The train’s interior is equipped with air conditioning, two CCTVs, hand straps, priority seats and a particular wheelchair area. Seats are made of fibre reinforced plastic (FRP) which is fire resistant with a width of 43 cm x 42 cm. This study aims to analyse the passenger posture by the Reba method with the results of measurements obtained in section, namely 6, section b is 5, and the meeting point between parts a and b is 8. That is, the results of the Reba score have a high level of risk with immediate action needed. From the results of calculations, it is found that the sitting position of the MRT passenger is not ergonomic. Therefore, the authors analysed the posture of the passengers of the Jakarta MRT passenger with the Reba method to provide suggestions for improving posture and seats.