Purpose - The purpose of this paper is to investigate the effects of rational green packaging claims vs emotional green packaging claims on consumers' purchase propensity for organic coffee.

Design/methodology/approach - Three within-subjects experiment were carried out (N=87, N=245, N=60). The experimental design encompasses packaging with rational green claims, emotional green claims, as well as a neutral (control) claim. Measured variables are introduced to assess participants' environmental commitment and information processing ability. A manipulated between-subjects variable is introduced to test how distraction interacts with preference for the claims.

Findings - Overall, consumers prefer products with green claims over those with neutral (control) claims, and products with emotional green claims to those with rational green claims. The studies also reveal that this effect is moderated by participants' environmental commitment, information processing ability and by distraction. The findings were statistically significant (p<0.05).

Research limitations/implications - As a lab experiment, the study provides limited generalizability and external validity. Practical implications - For most organic FMCG products, it is advisable to employ emotional packaging claims.

Social implications - The presented findings provide marketers with tools to influence consumer behavior toward sustainable choices.

Originality/value - The paper validates previous contributions on the effects of product claim types, and extends them by introducing comprehensive empirical data on all the Elaboration Likelihood Model's criteria for rational decision-making; motivation, opportunity and ability.

A novel 2D particle tracking method, that uses 1) iteration, 2) fast quadratic sub-pixel estimation (with only 28 multiplications per movement), and 3) a previous kernel, has been evaluated and compared with a full-search block-matching method. The comparison with high-frequency ultrasound data (40 MHz) was conducted in silico and on phantoms, which comprised lateral, diagonal, and ellipsoidal movement patterns with speeds of 0–15 mm/s. The mean tracking error was reduced by 68% in silico and 71% for the phantom measurements. When only sub-pixel estimation was used, the decrease in the tracking error was 61% in silico and 57% for the phantom measurements. As well as decreasing the tracking error, the new method only used 70% of the computational time needed by the full-search block-matching method. With a fast method having good tracking ability for high-frequency ultrasound data, we now have a tool to better investigate tissue movements and its dynamic functionality.

The aim of this study was to evaluate tracking performance when an extra reference block is added to a basic block-matching method, where the two reference blocks originate from two consecutive ultrasound frames. The use of an extra reference block was evaluated for two putative benefits: (i) an increase in tracking performance while maintaining the size of the reference blocks, evaluated using in silico and phantom cine loops; (ii) a reduction in the size of the reference blocks while maintaining the tracking performance, evaluated using in vivo cine loops of the common carotid artery where the longitudinal movement of the wall was estimated. The results indicated that tracking accuracy improved (mean - 48%, p<0.005 [in silico]; mean - 43%, p<0.01 [phantom]), and there was a reduction in size of the reference blocks while maintaining tracking performance (mean - 19%, p<0.01 [in vivo]). This novel method will facilitate further exploration of the longitudinal movement of the arterial wall. (C) 2014 World Federation for Ultrasound in Medicine & Biology.

This paper investigates the feasibility of using the periocular region for expression recognition. Most works have tried to solve this by analyzing the whole face. Periocular is the facial region in the immediate vicinity of the eye. It has the advantage of being available over a wide range of distances and under partial face occlusion, thus making it suitable for unconstrained or uncooperative scenarios. We evaluate five different image descriptors on a dataset of 1,574 images from 118 subjects. The experimental results show an average/overall accuracy of 67.0%/78.0% by fusion of several descriptors. While this accuracy is still behind that attained with full-face methods, it is noteworthy to mention that our initial approach employs only one frame to predict the expression, in contraposition to state of the art, exploiting several order more data comprising spatial-temporal data which is often not available.

Current research in iris recognition is moving towards enabling more relaxed acquisition conditions. This has effects on the quality of acquired images, with low resolution being a predominant issue. Here, we evaluate a super-resolution algorithm used to reconstruct iris images based on Eigen-transformation of local image patches. Each patch is reconstructed separately, allowing better quality of enhanced images by preserving local information. Contrast enhancement is used to improve the reconstruction quality, while matcher fusion has been adopted to improve iris recognition performance. We validate the system using a database of 1,872 near-infrared iris images. The presented approach is superior to bilinear or bicubic interpolation, especially at lower resolutions, and the fusion of the two systems pushes the EER to below 5% for down-sampling factors up to a image size of only 13×13.

Injuries in the female gymnast are common and it is important to understand the biomechanical factors responsible for injury. The Back Walkover maneuver requires one of the greatest amounts of lumbar hyperextension compared to other common gymnastic maneuvers. During the Back Walkover large lateral and vertical impact forces follows on the spine. The spine and muscles around the spine have to absorb generally large forces; therefore the loads on the back and certainly on the lower back are of significant interest. Additionally, it takes a lot of strength and a vast range of motion to perform gymnastic maneuvers such as The Back Walkover. It is of interest to study mechanical loads on a female gymnast since they show higher occurrences of stress-related pathologies of the lumbar spine.

Therefore the purpose of this project was to examine the loads on the spine during the gymnastic maneuver Back Walkover. Tests on a single female gymnast were made at the sports engineering lab at the University of Adelaide in Australia. Using the 3D-camera system; Optitrack Motion Capture System and Kistler Force Plate, positional data for two dimensions, X-direction (anterior-posterior) and Z-direction (vertical), and ground force were received. Data received were progressed into a graph, diagrams and biomechanical calculations where forces for the vertebrae L1 were calculated in vertical and horizontal direction. The received forces were compared to vertical and horizontal forces in L1 during standing position. Together with developed videos this assisted to model the loads of the spine (L1) during the gymnastic maneuver the “Back Walkover”. The study has led to a deeper knowledge for the community about the risks for female gymnasts and has widened the experience of the project participant, as the project aimed. 

Background: Lately, barefoot running has become popular and there is a debate on the pros and cons of barefoot running with regards to running injuries. Many factors are causing injuries and one of the factors discussed is the fact that we run in shoes. When we run in shoes the biomechanics of the running technique may and therefore be a possible cause to injury. Aim: The aim of the study was to assess how the foot strike pattern, angle of the knee and ankle joint at time of initial contact, as well as the step length changes between a shod and barefoot running condition in habitually shod runners when running in a pace equivalent to their running pace over ten kilometers. Method: Twenty-seven healthy runners (18 male, 9 female) were included in the study. The study took place at the fitness center of Halmstad University. Subjects ran on a treadmill, in an individual pace equivalent to their running pace over ten km, both in a shod and barefoot running condition. Two-dimensional analysis of the sagittal plane kinematics of the knee joint, ankle joint and foot position to horizontal, foot strike pattern and step length was done. Participants ran for ten minutes with shoes and for five minutes barefoot. Running technique was videotaped using an Iphone 6 camera and landmarks were marked with white tape to ease the analysis. Results: Changes in foot strike pattern was observed. When running barefoot 63% of the subjects adopted a non-heel strike pattern compared to 18.5% when shod (p=0.001). Knee flexion was increased at IC for the barefoot condition, with 164°±6 relative knee angle compared to 167°±6 when shod (p=0.001). Ankle angle at IC did not show a statistical significant difference between conditions (p=0.657). When barefoot the angle was 117°±8 compared to 115°±8 when shod. Foot angle to horizontal showed a flatter foot placement at IC with a less dorsiflexed foot for the barefoot condition (-4°±8) compared to shod (-12°±8), (p=0.001). Step length was decreased for the barefoot condition (0.82m ±0.15)   compared to shod (0.85m ±0.13), (p=0.008). Conclusion: Results are consistent with previous findings that barefoot running in some cases change the running technique with a flatter foot placement, an increased knee flexion at IC and a decreased step length. However, caution must be taken when habitually shod runners transition to barefoot running in regards to the biomechanical changes that may occur. To benefit from barefoot running a non-heel strike pattern is required. Further, the running technique may be the more important factor, regardless of wearing shoes or not.

CBCT images suffer from acute shading artifacts primarily due to scatter. Numerous image-domain correction algorithms have been proposed in the literature that use patient-specific planning CT images to estimate shading contributions in CBCT images. However, in the context of radiosurgery applications such as gamma knife, planning images are often acquired through MRI which impedes the use of polynomial fitting approaches for shading correction. We present a new shading correction approach that is independent of planning CT images. Our algorithm is based on the assumption that true CBCT images follow a uniform volumetric intensity distribution per material, and scatter perturbs this uniform texture by contributing cupping and shading artifacts in the image domain. The framework is a combination of fuzzy C-means coupled with a neighborhood regularization term and Otsu’s method. Experimental results on artificially simulated craniofacial CBCT images are provided to demonstrate the effectiveness of our algorithm. Spatial non-uniformity is reduced from 16% to 7% in soft tissue and from 44% to 8% in bone regions. With shading-correction, thresholding based segmentation accuracy for bone pixels is improved from 85% to 91% when compared to thresholding without shading-correction. The proposed algorithm is thus practical and qualifies as a plug and play extension into any CBCT reconstruction software for shading correction. © Springer Nature Singapore Pte Ltd. 2017.

A consequence of the fragmented and siloed healthcare landscape is that patient care (and data) is split along multitude of different facilities and computer systems and enabling interoperability between these systems is hard. The lack interoperability not only hinders continuity of care and burdens providers, but also hinders effective application of Machine Learning (ML) algorithms. Thus, most current ML algorithms, designed to understand patient care and facilitate clinical decision-support, are trained on limited datasets. This approach is analogous to the Newtonian paradigm of Reductionism in which a system is broken down into elementary components and a description of the whole is formed by understanding those components individually. A key limitation of the reductionist approach is that it ignores the component-component interactions and dynamics within the system which are often of prime significance in understanding the overall behaviour of complex adaptive systems (CAS). Healthcare is a CAS.

Though the application of ML on health data have shown incremental improvements for clinical decision support, ML has a much a broader potential to restructure care delivery as a whole and maximize care value. However, this ML potential remains largely untapped: primarily due to functional limitations of Electronic Health Records (EHR) and the inability to see the healthcare system as a whole. This viewpoint (i) articulates the healthcare as a complex system which has a biological and an organizational perspective, (ii) motivates with examples, the need of a system's approach when addressing healthcare challenges via ML and, (iii) emphasizes to unleash EHR functionality - while duly respecting all ethical and legal concerns - to reap full benefits of ML.

Objective

To develop and evaluate a standardised method for unbiased measurements of epithelial thickness taking the variability of the dermal papillae in consideration.

Methods

A computer-assisted measurement program suitable for haematoxylin and eosin routine stained specimens has been developed.

Results

The developed program was designed to measure four different distance parameters, taking the number, height and width of dermal papillae into account. The measurement program gave very accurate results compared with manual measurements. The measurement results can be presented as tables or star graphs, and the results can be further processed by multivariate analysis.

Conclusion

The computer-assisted measurement program is considered to be a valuable and reliable tool for measurements of epithelial thickness, irrespectively of the variability of the epithelial morphology. Since length, size and number of the papillae may change with certain pathological conditions, age and also under hormonal influence, this method can be a helpful diagnostic tool.

We consider the vacuum energy for the configuration of two cylinders and obtain its asymptotic expansion if the radius of one of these cylinders becomes large while the radius of the other one and their separation are kept fixed. We calculate explicitly the next-to-leading order correction to the vacuum energy for the radius of the other cylinder becoming large or small.

Although rheumatoid arthritis (RA) patients frequently experience muscle weakness, limited information exists on disease specific muscle changes. The common hand deformity in RA includes disturbed finger extension with subsequent flexion deformities. The aims of this study were to measure finger extension force and finger flexion force in patients with rheumatoid arthritis and compare them with healthy subjects.  We also wanted to explore the possible causes of impaired finger extension force with the help of ultrasound muscle analyses.

The study group comprised of 40 women: 20 patients with RA (median disease duration 20 years) and 20 healthy age-matched controls. The finger extension force measurements were performed with a newly developed device (EX-it), finger flexion force was measured with the Grippit. The extensor digitorum communis muscle was examined with ultrasound.

Significant differences were found between the two groups, concerning extension and flexion force (p<0.001). Ultrasound measurements indicated significant differences in structural parameters (Cross Section Area (p< 0.05), muscle thickness (p < 0.05) and fascicle length (p < 0.05)). Overall changes in muscle architecture during contraction were more pronounced in the control group than in the RA group (p < 0.01).

The results indicate differences in structural parameters as well as functional tests, i.e. contraction time and extension muscle force capacity, between normal and RA muscles. Whether these differences depend on a disease-specific effect on the muscles in RA, or are secondary to inactivity or hand deformities, remains to be elucidated.

According to statistics, in 2010 there were 26 individuals seen by a group of 100,000 who were depending in home oxygen therapy (HOT). Oxygen treatment adds a certain amount of Oxygen to the patient because the ability to breathe correctly and sufficiently is negatively affected.

The dominant disease that leads to HOT is COPD, chronic obstructive pulmonary disease. As the name suggests, it is a chronic disease which gives inflammatory changes to the lung bronchioles. These changes affect the breathing surface which results in that the individuals’ respiratory capacity becomes reduced.

The project used methods from dynamic product development with the user in focus. This to obtain a functional prototype that could be used by the target group and to fulfill the purpose, goals and requirements set for the project's results. An important component of the project therefore was to work with the collection of data. For this, various methods were used to obtain information from users as well as prescribers of HOT. All of the methods used have been tested earlier and proven reliable. This project collected information from interviews, observations, matrix arrays, risk analysis and usability testing in patients with HOT.

The prototype developed in the project resulted in that the target group could perform live test without any risks during testing. The results showed that the aim and objective for the project were fulfilled, expressed in that patients would be able to move the oxygen tube used in HOT.

It was further concluded that the results fulfilled the patients' desire and opportunity to move the Oxygen tube in their home and at the same time answered the questions that the project was to answer. There were no existing solutions to the problem which is included in the project, but it was possible to develop a first prototype that met the purpose and object of the project.

This paper discusses imaging with complex data from micro-wave, mm-wave, and optical interferometers. An overview of methods to extract physical parameters as images from interferometer data is made and two- and three-dimensional images of gas flows, quasi-stellar objects, steel melts, and fiber material such as wood are presented.

The purpose of this study was to investigate the effect of ball temperature on impact ball speed and carry distance during golf drives in a blind randomized test design. The balls were exposed to a temperature-controlled environment (4 °C, 18 °C, 32 °C, and 46 °C) for 24 h prior to the test and each temperature group consisted of 30 balls. The 120 drives were performed by an elite male golfer (handicap: 0.0) in an indoor driving range. All drives were measured by a Doppler-radar system to determine the club-head speed, launch angle, spin rate, ball speed, and carry distance. Differences between the groups were investigated using a one-way analysis of variance. The results indicated that ball-speed and carry-distance differences occurred within the four groups (p < 0.001 and p < 0.01, respectively). The post hoc analyses showed that the ball temperatures of 18 °C and 32 °C had greater ball speeds and carry distances than balls at 4 °C and 46 °C (all p < 0.05). The intervals for the between-group differences were 0.6–0.7 m s ^–1 and 2.9–3.9 m for ball speed and carry distance, respectively. Hence, the results showed that ball temperature influences both the ball speed and the carry distance. Based on the findings in this study, standardization of ball temperature should be factored into governing body regulation tests for golf equipment. © IMechE 2018.

This paper has evaluated a new type of prosthetic foot, X-Balance, which aim was to facilitate the performance on uneven ground for the user. This study have performed gait analyzes with three prosthetic feet, the X-Balance, Flex-Foot and assure Ottobock9192 on flat and uneven surfaces using 3D analysis system QTM (Qualisys Track Manager) and associated force plates. During the project a prototype of a design that can perform a mechanical gait were manufactured. The prototype has then been used to fulfill the purpose and objective of this study which is to make different final sets that demonstrate differences between prosthetic feet. Gait analyses of individuals have also been performed to get an idea of what normal gait is. The reliability of the prototype was measured and compared to the study with individuals. By comparison, it could be established that the structure had a higher reliability than the individuals, thus making it easier to compare prosthetic feet against each other. There are no measurements to show that proves that the mechanical gait with the prototype has a high validity. The evaluation findings shows that Ottobock9192 reduce the forces in the Z- and Y-direction most and thus contributes to a gentler heel strike than the other two prosthetics. The results also shows that X-Balance allows greater flexibility in sideway direction (supination) and contributing to a more gentle and easier gait for the user once operate the prosthetic foot over an object with the medial part of the forefoot.

Lindhe Xtend is a prosthetics company in Halmstad with the ambition of providing the amputee with functional mobility and a high quality of life. Their main product, the Xtend Foot is a patented prosthetic foot developed to imitate the natural features of the human foot.

Dissatisfaction with prostheses often stems from poor fitting of the part that connects to the body. This often leads to chafing, pistoning and strain. Amongst users of leg prostheses, the strain often results in a reduction of limb volume, further augmenting the bad fit. The development of suspension systems has excelled through the recent years as many prosthetics companies has developed products with integrated vacuum assisted suspension systems, a mounting method where vacuum is used to hold the prosthesis against the body. This mounting mechanism of the limb onto the prosthesis has been proven to prevent fluctuations of limb volume as well as reducing chafing and pistoning.

A vacuum assisted suspension system integrated with the Xtend Foot has been invented using the product development process. The project group has used motion analysis, calculations and concept generation to reach a final concept to be prototyped, called Unify Xtend. Unify Xtend is made to demonstrate the function of the final concept, to actively produce a vacuum during ambulation using a pneumatic actuator.

This project has addressed prosthetics and pneumatics. The project group has, using their knowledge of mechanical engineering and physiology, combined and applied them in this thesis.

Further user testing is needed to evaluate the usability of the prototype, due to reaching target pressure considerably faster than the products of main market competitors.

The skeleton has several fundamental functions in the body, providing protection and structure and safeguarding organs, enabling movement and bearing of weight. The significance of having a complete and strong skeleton is essential for individuals, but it is far from certain for those with a skeletal disorder. Skeletal disorders can manifest in various ways, with the common condition of a more fragile skeleton that is prone to fractures under low force and load. Currently, there are over 450,000 individuals estimated to have the most common skeletal disorder, Osteoporosis, in Sweden alone. In 2019, it was estimated that a total of 124,000 fractures related solely to skeletal disorders occurred in Sweden, equivalent to 338 fractures per day. A registry extract from the Swedish Cause of Death Register in 2019 revealed that deaths related to osteoporotic fractures were the third leading cause of death in Sweden, following dementia and cardiovascular disease. Skeletal disorders not only result in a reduced quality of life for individuals but also impose a state cost of nearly 18 billion SEK per year. This cost exceeds the combined expenses of diabetes care and care for patients with multiple sclerosis today. Despite this, skeletal disorders, according to the Swedish Agency for Health Technology Assessment and Assessment of Social Services, remain an undertreated segment, with the majority of cases neither diagnosed, treated, nor provided with other preventive measures for fractures.

For Sofie Hellström and her son Gabriel, their perspective on life changed in the summer of 2020 with a diagnosis of Osteogenesis Imperfecta, a skeletal disorder. At Karolinska Institutet, they were offered a piece of mattress as hip protection. Sofie then discovered a global lack of functional clothing for individuals in need of extra protection in their daily lives. This became the starting point for the company OICAN and the vision of providing all children with the best conditions to explore the world.

The aim of the project has been to create integrated knee protectors that can prevent injuries and fractures to the knee and femur. The goal has been to develop a pair of pants with integrated protection that does not compromise on protective capability, freedom of movement, or aesthetic design. The project has resulted in prototypes of integrated knee protectors for both adults and children, along with corresponding injection molding tools. In the final stages of the project, the prototypes have been integrated into pants and tested with excellent results.

Reverse Total Shoulder Arthroplasty (rTSA) is an increasingly common approach to treating different shoulder injuries. The rTSA results in increased force from m. deltoideus which originates from acromion. However, postoperative fractures on the scapula have occurred in some cases. These fractures are divided into 3 different types depending on where the fracture occurs. There is no recommended treatment for type 3 fractures. This project is a product development project with the purpose to find a solution to the fixation problem of type 3 fractures.To reach the project goal, the group has used well-known and proven product development methods, calculations, FEM analyzes and a model assembly analysis. The concept development was performed by interviewing orthopedics who have a lot of experience with rTSA and osteosynthesis related to these fractures. A prototype, which shows the features of the fixation plate, was made using 3D printers.The result of this project has provided a fixation plate that meets the groups requirements and has features that a modern fixation plate has today. In addition, two types of extra plates mounted on the fixation plate to the thin structure of spina scapula, was developed to counteract the axial force. The fixation plate shows excellent results on the FEM analyzes and assembly analysis performed on a scapula model. The prototype has also been given good testimonials from the orthopedics who participated in the project.

Massage guns operate by delivering high-frequency percussions to muscles to alleviate tension, amethod proven to increase the range of motion and reduce delayed onset muscle soreness. Thesedevices are widely used by athletes, fitness enthusiasts, manual laborers, and healthcareprofessionals such as chiropractors, who rely on them for warming up, relaxation, and pain reliefduring treatments. However, current massage gun attachments lack integrated heating andcooling functions, which are essential for enhancing the effectiveness of treatments.This project aimed to develop innovative massage gun attachments (fork-, flat-, and round-head)with integrated heating and cooling capabilities, applicable to multiple massage gun models. Thegoal was to improve the efficiency of muscle recovery, reduce fatigue, enhance blood circulation,and decrease swelling. A market survey revealed a significant demand for these features amongusers who expressed the need for enhanced treatment effects.Our prototypes demonstrated the intended thermal effects but highlighted the need forimprovements in maintaining consistent cooling. Future iterations will incorporate additionalcooling mechanisms and refined materials to enhance ergonomic and functional performance.By integrating heating and cooling functions, these new attachments promise to elevate treatmentoutcomes for athletes, fitness enthusiasts, and healthcare professionals, offering a sustainable andcost-effective solution that extends the lifecycle of massage guns. The growing wellness market,projected to reach USD 33.71 billion by 2031, underscores the potential impact and demand forour innovative product

Health care has taken interest in the use of AI (Artificial Intelligence) and mental health services are in need of support. Intelligent decision support systems can contribute to reduced workload for health care professionals and better treatment for patients, but the sensitive nature of health care and the possible consequences in the event of neglect or malpractice pose ethical challenges. Treatment of mental illness is complex and needs to be explored in order to identify the potential ethical challenges that can arise. Through an interview study consisting of eight participants, the problem area has been explored amongst both AI researchers and health care professionals, where insights from both contexts have been analysed in order to identify and explore recurring ethical challenges. Through empirical data and a literature study, five ethical challenges have been identified and explored: handle incorrect recommendations, handle moral dilemmas, achieve patient autonomy, the liability dilemma, and generate trust. 

Introduction

In sports, force production and movement are predominantly generated in a unilateral weight-bearing stance. Therefore, unilateral resistance training may possibly elicit more sport-specific strength gains compared to traditional bilateral strength training. Hip- and trunk- muscles stabilize the pelvis and trunk to maintain proper technique and posture in resistance training and are thought to play a central role in sports performance as well as injury prevention. Hip- and trunk- muscle activity increases as the body weight balance change from a bilateral to a unilateral stance. Little research has examined the magnitude of change in muscle activation differences between bilateral and unilateral stance in lower body exercises.

Aim

The aim of this study was to examine the electromyographic (EMG) activity in hip and trunk muscles in three bodyweight exercises performed in a bilateral and a unilateral stance.

Methods

14 healthy, young adults participated in a single session, single-group, observational study. Manual muscle testing was used to attain a maximal voluntary isometric contraction (MVC) value for gluteus medius, gluteus maximus, rectus abdominis, and erector spinae. EMG measurements (4 channel ME6000, MegaWin Software, Kuopio, Finland) were taken during performance of squat, bridge, and plank exercises in both a bilateral and a unilateral stance.

Results

In all three exercises, EMG activity (presented as magnitude of change) was greater in the unilateral stance compared to the bilateral stance (p< 0.05), for the muscles gluteus medius (squat 478%, bridge 204%, plank 285%) and gluteus maximus (squat 371%, bridge 172%, plank 233%). In addition, in plank, EMG activity was greater in unilateral stance compared to the bilateral stance (p< 0.05) in rectus abdominis (120%) and erector spinae (127%). In the squat and bridge, no differences were identified in EMG activity for rectus abdominis and erector spinae between the bilateral and the unilateral stance.

Discussion

Nearly all unilateral exercises activated the hip muscles (gluteus medius, gluteus maximus) more than double compared to the same exercises performed bilaterally. In particular, gluteal muscle activity during the unilateral squat was more than 3.5 fold greater as compared to the bilateral stance. This greater magnitude of change in the unilateral squat might be explained by the single contact point with the ground in the squat, whereas the bridge and plank exercises include more ground contact points even in their unilateral stance. A unilateral training program including squat exercises might be beneficial for developing hip strength which is of great importance in sports performance.

The D4Active concept, a complete diabetes care system, was founded by two former innovation engineering students. Autumn 2019 Andrea Stare and Anna Fransson took over the D4Active development and during the last year of development, the system has gone from a concept to a functioning wireless prototype system that can demonstrate the most important functions of diabetes care. D4Active provides a package solution consisting of only three essential units for diabetes care; a central communication device in the form of an interactive application, a divisible insulin pump and a sensor that can measure current insulin levels in the body. D4Actives application follows the strict medical regulations for health care products. The target group consist of people diagnosed with type 1 diabetes. Living with diabetes means that the body cannot naturally produce insulin that keeps the body's glucose levels stable. Through market research and interviews with focus groups, consisting of diabetics, relatives of diabetics who are not often indispensable to the affected and diabetic nurses, the system is developed with the user in focus. We aim to promote good health by enabling a more active lifestyle for diabetics; with our application they can gather the necessary care units and data in one system. In short, the system reduces the number of care units for diabetics to carry with them, which increases mobility and the possibility of a more active everyday life. In addition, we have focused on developing and strengthening the units' lifecycle and durability by retaining the components that are unnecessarily discarded, when in fact they could be used more.

This thesis aims to implement a system called SafeWalk to help visually impaired people to sense obstacles in their path and provide them with more independence and more effortless life routines without any external help. SafeWalk is a low power consuming system designed to replace the daily used white cane. It consists of sensors, a buzzer, a vibrating motor, and a software application. The system will be installed on the user's shoe. It detects the objects in front of the user using an Ultrasonic sensor that measures the distance to the targeted object by transmitting sound waves. This will produce vibration in the shoe and causes the buzzer to start playing when the object gets closer. Similarly, using the provided application, signals will be received in the user's smartphone, which will begin to vibrate when the object is detected. The system works just as planned. The final prototype senses objects in the walking path very well. The connection to the app was strong and never disconnected while in use. The phone vibrates stronger if an object on the ground gets closer; if there is an object in the air, the buzzer and vibrator signal the user. 

Background and purpose: Patients’ adherence to medication is a complex, multidimensional phenomenon. Dispensation data and electronic health records are used to approximate medication-taking through refill adherence. In-depth discussions on the adverse effects of data quality and computational differences are rare. The purpose of this article is to evaluate the impact of common pitfalls when computing medication adherence using electronic health records.

Procedures: We point out common pitfalls associated with the data and operationalization of adherence measures. We provide operational definitions of refill adherence and conduct experiments to determine the effect of the pitfalls on adherence estimations. We performed statistical significance testing on the impact of common pitfalls using a baseline scenario as reference.

Findings: Slight changes in definition can significantly skew refill adherence estimates. Pickup patterns cause significant disagreement between measures and the commonly used proportion of days covered. Common data related issues had a small but statistically significant (p < 0.05) impact on population-level and significant effect on individual cases.

Conclusion: Data-related issues encountered in real-world administrative databases, which affect various operational definitions of refill adherence differently, can significantly skew refill adherence values, leading to false conclusions about adherence, particularly when estimating adherence for individuals. © 2020 The Authors. Published by Elsevier B.V. 

Innovations that employ novel technologies can be problematic, particularly when sources of uncertainty can lead to severe financial, social, and reputational losses. Nowhere is this more evident than in innovations across Medical Device (MD) developments. In healthcare, described by stricter safety requirements, adapting the MD process to ongoing regulatory principles intended to balance benefits and risks is often elusive. We investigate a single case study comprising four medical device technology developments implemented in products and services. Does this study explore how a healthcare firm changes its medical device development process to adaptive regulations? Our study offers three contributions. First, we contribute to the innovation literature by proposing a flexible MD process in which safety standards are continuously revised, and development stages are regulated differently. For example, when the legal and regulatory aspects of emerging technologies are unpredictable, unknown firms are encouraged to de-risk the early-stage potential problem in adopting the emerging technology. Second, we contribute to the literature on Technology Development by showing how introducing digital technologies innovation requires a significant change in the culture and mindset of the organization. In the healthcare industry, where rules and procedures are hindering risky and uncertain investment, nurturing the culture of people towards risk-taking and learning from failure is a crucial dimension of digital transformation. Third, we propose a combined process that leverages traditional MD phases. The change management theory suggests a way to enact a digital transformation in a hyper-regulated environment.

This paper is concerned with kernel-based techniques for automatedcategorization of laryngeal colour image sequences obtained by videolaryngostroboscopy. Features used to characterize a laryngeal imageare given by the kernel principal components computed using the$N$-vector of the 3-D colour histogram. The least squares supportvector machine (LS-SVM) is designed for categorizing an imagesequence (video) into the healthy, cancerous and noncancerous classes. The kernel function employed by theLS-SVM is defined over a pair of matrices, rather than over a pairof vectors. The classification accuracy of over 85% was obtainedwhen testing the developed tools on data recorded during routinelaryngeal videostroboscopy.

This paper presents the results of a study performed on Parallel Convolutional Neural Network (PCNN) toward detecting heart abnormalities from the heart sound signals. The PCNN preserves dynamic contents of the signal in a parallel combination of the recurrent neural network and a Convolutional Neural Network (CNN). The performance of the PCNN is evaluated and compared to the one obtained from a Serial form of the Convolutional Neural Network (SCNN) as well as two other baseline studies: a Long- and Short-Term Memory (LSTM) neural network and a Conventional CNN (CCNN). We employed a well-known public dataset of heart sound signals: the Physionet heart sound. The accuracy of the PCNN, was estimated to be 87.2% which outperforms the rest of the three methods: the SCNN, the LSTM, and the CCNN by 12%, 7%, and 0.5%, respectively. The resulting method can be easily implemented in an Internet of Things platform to be employed as a decision support system for the screening heart abnormalities.

Av de tusentals olyckor som sker varje vinter kan kylan bidra till förödande komplikationer. Vär- meförlust från kroppen kan leda till att personer drabbas av hypotermi. Hypotermi inträffar när en persons kroppstemperatur understiger 35 °C och kroppens värmeproduktion slås ut. De låga kropps- temperaturerna gör det svårare att klara av överlevande aktiviteter så som att andas och att stoppa blödningar. För att förhindra fortsatt nedkylning krävs det att personen skyddas mot värmeförlusten och att extern värme tillförs.

För några år sedan ändrades riktlinjerna för hur extern värme får tillföras i fält och det blev då tillåtet för räddningspersonal att tillföra värme redan vid olycksplatsen. Dock reagerade inte marknaden på detta direktiv och räddningstjänsten är idag tvungna att använda bristfälliga produkter. Svenska Sjöräddningssällskapet, SSRS, har uttryckt ett stort behov av nya, kompletta lösningar som ger rätt vård till patienten.

Resterande innehåll i sammanfattningen är sekretesskyddad enligt kapitel 2 då det röjer nyheter som förhindrar patentsökande.

Background: Machine learning (ML) is an emerging tool for predicting need of end-of-life discussion and palliative care, by using mortality as a proxy. But deaths, unforeseen by emergency physicians at time of the emergency department (ED) visit, might have a weaker association with the ED visit.

Objectives: To develop an ML algorithm that predicts unsurprising deaths within 30 days after ED discharge.

Methods: In this retrospective registry study, we included all ED attendances within the Swedish region of Halland in 2015 and 2016. All registered deaths within 30 days after ED discharge were classified as either “surprising” or “unsurprising” by an adjudicating committee with three senior specialists in emergency medicine. ML algorithms were developed for the death subclasses by using Logistic Regression(LR), Random Forest (RF), and Support Vector Machine (SVM).

Results: Of all 30-day deaths (n = 148), 76% (n = 113) were not surprising to the adjudicating committee. The most common diseases were advanced stage cancer, multidisease/frailty, and dementia. By using LR, RF, and SVM, mean area under the receiver operating characteristic curve (ROC-AUC) of unsurprising deaths in the test set were 0.950 (SD 0.008), 0.944 (SD 0.007), and 0.949 (SD 0.007), respectively. For all mortality, the ROC-AUCs for LR, RF, and SVM were 0.924 (SD 0.012), 0.922 (SD 0.009), and 0.931 (SD 0.008). The difference in prediction performance between all and unsurprising death was statistically significant (P < .001) for all three models.

Conclusion: In patients discharged to home from the ED, three-quarters of all 30-day deaths did not surprise an adjudicating committee with emergency medicine specialists. When only unsurprising deaths were included, ML mortality prediction improved significantly. © 2021 The Author(s). Published by Elsevier Inc.

When blood sampling is performed, problems and complications occasionally occur. Sometimes the blood sampling fails. Statistically, blood sampling fails at the first attempt in 28 percent of all cases for adults. For children, the corresponding rate is 44 percent.

The project was based on the need for aids to perform blood sampling. The need was identified and recognised by the taskmasters Frida Svensson and Lisa Eliasson during their degree project in 2021. The project group’s aim was to continue the taskmasters work developing a medical technology product that facilitates blood sampling and to bring the product one step closer to the market.

Text removed due to confidentiality. The text mentions the functionality of the product. The product's effect is to increase the chance of succeeding with the blood sampling at the first try. This not only increases the patient’s comfort, but also is timesaving and decreases the need of disposable materials. In the long run this contributes to large financial savings for the healthcare department.

The result of the project was a prototype that embodies the product Blood Simpling II.  The product’s functions reduce the risk of complications when blood sampling is performed. At the same time, the product increases the chance of succeeding with the blood sampling at the first attempt. The project group’s successful result resulted in its purpose of bringing the product one step closer to the market. Text removed due to confidentiality. The text mentions the functionality of the product. 

With the continued growth of digitalization and ICT (Information and communicationtechnology) new healthcare solutions for both patients and healthcare providers have been made readily available. During the recent outbreak of the Covid-19 virus the necessity for digital healthcare options have been made apparent. Services such as MinDoktor, Kry and 1177’s healthcare app have all seen an increase in use. In this study we have conducted research on what patients on digital healthcare apps thought was necessary for them to create and strengthen trust for these applications. The study was conducted with eleven participating respondents who had previously used a digital healthcare app. The empirical data was then analyzed to enable a representation of the participants opinions and thoughts. This study contributes with insights on how trust for digital healthcare can be created and strengthenedfor patients through access to personal contact, video consultations and company reputation.

The project was initiated by dental personnel at the Specialist dentistry in Halmstad, Sweden, because they experienced problems when working with oral prosthetics. There is a risk that components are dropped and due to gravity and the patient's position, being inhaled or swallowed. This means stress and concerns, contributing to the deterioration of the psychosocial work environment for dental personnel.

The Swedish dental State support was introduced in 2008, which gives the patient a reduced cost for dental prosthetic procedures. This allows more people to afford oral prosthetics. Therefore, the problem becomes more and more prevalent and the demand for a solution is requiered.

 The project has implemented dynamic product development with a major focus on the involvement of future users. The project was based on literature reviews, observation and survey, which was performed in the product definition phase. Different concept generation methods and evaluation methods were applied and resulted in a final prototype. A continuous dialogue and testing with the clients where performed throughout the project.

This product development project resulted in an instrument that facilitates for dental personnel and increase safety for the patient during oral prosthetics. The solution is a specially designed forceps which slips onto the screwdriver and secures components.

Healthy gait requires a balance between various neuro-physiological systems and is considered an important indicator of a subject's physical and cognitive health status. As such, health-related applications would immensely benefit by performing long-term or continuous monitoring of subjects' gait in their natural environment and everyday lives. In contrast to stationary sensors such as motion capture systems and force plates, inertial sensors provide a good alternative for such gait analysis applications as they are miniature, cheap, mobile and can be easily integrated into wearable systems.

This thesis focuses on improving overall gait analysis using inertial sensors by providing a methodology for detecting gait events in real-world settings. Although the experimental protocols for such analysis have been restricted to only highly-controlled lab-like indoor settings; this thesis presents a new gait database that consists of data from gait activities carried out in both, indoor and outdoor environments. The thesis shows how domain knowledge about gait could be formulated and utilized to develop methods that are robust and can tackle real-world challenges. It also shows how the proposed approach can be generalized to estimate gait events from multiple body locations. Another aspect of this thesis is to demonstrate that the traditionally used temporal error metrics are not enough for presenting the overall performance of gait event detection methods. The thesis introduces how non-parametric tests can be used to complement them and provide a better overview.

The results of comparing the proposed methodology to state-of-the-art methods showed that the approach of incorporating domain knowledge into the time-frequency analysis of the signal was robust across different real-world scenarios and outperformed other methods, especially for the scenario involving variable gait speeds in outdoor settings. The methodology was also benchmarked on publicly available gait databases yielding good performance for estimating events from different body locations. To conclude, this thesis presents a road map for the development of gait analysis systems in real-world settings.

Many gait analysis applications involve long-term or continuous monitoring which require gait measurements to be taken outdoors. Wearable inertial sensors like accelerometers have become popular for such applications as they are miniature, low-powered and inexpensive but with the drawback that they are prone to noise and require robust algorithms for precise identification of gait events. However, most gait event detection algorithms have been developed by simulating physical world environments inside controlled laboratories. In this paper, we propose a novel algorithm that robustly and efficiently identifies gait events from accelerometer signals collected during both, indoor and outdoor walking of healthy subjects. The proposed method makes adept use of prior knowledge of walking gait characteristics, referred to as expert knowledge, in conjunction with continuous wavelet transform analysis to detect gait events of heel strike and toe off. It was observed that in comparison to indoor, the outdoor walking acceleration signals were of poorer quality and highly corrupted with noise. The proposed algorithm presents an automated way to effectively analyze such noisy signals in order to identify gait events.

The following report is a description of the process, result and reflections of the project that was carried out in cooperation with Medarca AB from the fall of 2020 to the spring semester of 2021. 

The project has been aimed at the elderly care, specifically special housing. An important part of the care given at these elderly care facilities is managing the patient's medicine. And when it comes to managing the medicine it’s of utmost importance that it’s done in a safe manner. A single mistake in the medication process can have life-threatening consequences. There are over 90.000 beds just in Sweden and over 4 million across Europe. This means that there are many people in need of a safe and secure elderly care. 

The problems that the elderly care facilities face are, among others, medicine waste by theft and errors in giving medication. There's also the problem of messy medicine cabinets that make it hard to find the right medicine and personnel running around unnecessarily since a patient's medicine can’t be stored all in one place. And finally outdated processes that need digitalization. 

The project group was given the task to examine Medarca’s product Meddibox to see if any improvements could be made. After the preparatory work was done several ideas aimed at improving Meddibox were presented. Among them was an idea that led to a completely new concept product being developed. The result was MeddiGuard, a digital medicine cabinet that minimizes the risks for all the aforementioned problems and that also streamlines the processes related to the caregiving sector. MeddiGuard works seamlessly together with Medarca’s other products which leads to a safer and more secure health care for everyone involved. And saves money for both the caregivers and society as a whole.

Relying on the commonsense knowledge that the trajectory of any physical entity in the spatio-temporal domain is continuous, we propose a heuristic data association technique. The technique is used in conjunction with an Extended Kalman Filter (EKF) for human tracking under occlusion. Our method is capable of tracking moving objects, maintain their state hypothesis even in the period of occlusion, and associate the target reappeared from occlusion with the existing hypothesis. The technique relies on the estimation of the reappearance event both in time and location, accompanied with an alert signal that would enable more intelligent behavior (e.g. in path planning). We implemented the proposed method, and evaluated its performance with real-world data. The result validates the expected capabilities, even in case of tracking multiple humans simultaneously.

To ensure that medical instruments and fluids maintain a high safety standard for use in healthcare, it requires a sterilization process that entails high energy consumption and cooling water. With increased environmental requirements from the government, it becomes increasingly important for companies to report and minimize their climate impact. Therefore, the company Getinge Sterilization, aimed to develop a method that could present consumption values of their new steam sterilizer.

The aim of the project thus became for Getinge’s customers to easily document and report how much energy and water the autoclave consumes. The project group therefore developed a system that, through theoretical calculations, calculates the volume flowing through each valve in the machine since pressure, temperature and pipe size are known. 

The outcome of the algorithms implies a system that does not require external hardware, where the calculation average on water consumption is 2,22% compared to actual consumption, with an approved result of plus/minus 15%. Whereupon the electricity consumption corresponds to reality. 

Today, Getinge estimates how much the autoclaves consume, but with the new system, customers get almost exact values without external hardware, leading to saving on materials and lower costs. 

The aim of this study is a transparent tool for analysis of voice (sustained phonation /a/) and query data capable of providing support in screening for laryngeal disorders. In this work, screening is concerned with identification of potentially pathological cases by classifying subject’s data into ’healthy’ and ’pathological’ classes as well as visual exploration of data and automatic decisions. A set of association rules and a decision tree, techniques lending themselves for exploration, were generated for pathology detection. Data pairwise similarities, estimated in a novel way, were mapped onto a 2D metric space for visual inspection and analysis. Accurate identification of pathological cases was observed on unseen subjects using the most discriminative query parameter and six audio parameters routinely used by otolaryngologists in a clinical practice: equal error rate (EER) of 11.1% was achieved using association rules and 10.2% using the decision tree. The EER was further reduced to 9.5% by combining results from these two classifiers. The developed solution can be a useful tool for Otolaryngology departments in diagnostics, education and exploratory tasks. © 2017 by the authors.

Introduction

Microfluidic reactionware allows small volumes of reagents to be utilized for highly controlled flow chemistry applications. By integrating these microreactors with onboard analytical systems, the devices change from passive ones to active ones, increasing their functionality and usefulness. A pressing application for these active microreactors is the monitoring of reaction progress and intermediaries with respect to time, shedding light on important information about these real-time synthetic processes.

Objective

In this multi-disciplinary study the objective was to utilise advanced digital fabrication to research metallic, active microreactors with integrated fibre optics for reaction progress monitoring of solvent based liquids, incompatible with previously researched polymer devices, in combination with on-board Ultraviolet-visible spectroscopy for real-time reaction monitoring.

Method

A solid-state, metal-based additive manufactured system (Ultrasonic Additive Manufacturing) combined with focussed ion beam milling, that permitted the accurate embedment of delicate sensory elements directly at the point of need within aluminium layers, was researched as a method to create active, metallic, flow reactors with on-board sensing. This outcome was then used to characterise and correctly identify concentrations of UV-active water-soluble B-vitamin nicotinamide and fluorescein. A dilution series was formed from 0.01–1.75 mM; which was pumped through the research device and monitored using UV-vis spectroscopy.

Results

The results uniquely showed the in-situ ion milling of ultrasonically embedded optical fibres resulted in a metallic microfluidic reaction and monitoring device capable of measuring solvent solutions from 18 μM to 18 mM of nicotinamide and fluorescein, in real time. This level of accuracy highlights that the researched device and methods are capable of real-time spectrographic analysis of a range of chemical reactions outside of those possible with polymer devices.

Alzheimer’s Disease (AD) is a widespread neurodegenerative disease. The disease causes brain atrophy, resulting in memory loss, decreased cognitive ability, and eventually death. There is currently no cure for the disease, but treatment may delay the onset. Therefore, it is crucial to detect the disease at an early stage. Medical imaging techniques, such as Positron Emission Tomography (PET), are heavily applied for this task. In recent years, machine learning approaches have shown success in identifying AD from such images.

The thesis presents a pipeline approach to detect, extract and evaluate Region of Interest (ROI) for prioritization of informative regions in PET scans for classification of Alzheimer’s disease. The pipeline applies data acquired from Alzheimer’s Disease Neuroimaging Initiative (ADNI). An analysis of Weakly-Supervised Object Localization (WSOL) is discussed for detection of informative regions particularly indicative of AD. WSOL analyse the original full-volume 18F-fluorodeoxyglucose (18F-FDG)-PET scan to categorize the informative regions on subjects into Cognitively Normal (CN), Mild Cognitive Impairment (MCI), or AD. The detection of informative regions are processed to two approaches to extract ROI on the full-volume 18F-FDG-PET scan: Bounding-Box (BBox) Generatio nand Automated Anatomical Labeling (AAL) Generation. BBoxes Generation restricts the 18F-FDG-PET scans for Convolutional Neural Network (CNN) to BBox proposal swith particularly informative regions. The second approach ranks the anatomical regions of the brain through brain parcellation with the pre-defined atlas AAL3, and restricts a CNN to the highest-ranked regions.

The results evaluate if ROIs increase the robustness for classification in relationto full-volume 18F-FDG-PET scan.

The results suggest that full-volume 18F-FDG-PET with heavily restricted image size does not decrease classification performance. Instead, the BBox Generation results in a significant classification performance improvement on the test set from an Area under the ROC Curve (AuC) score of 70.08% to 97.73% and accuracy from 51.79% to 88.03%. AAL Generation suggests that the middle and inferior regions of the temporal lobe and the fusiform are essential to the classification. In addition, several regions of the frontal lobe were found to be highly important but could not alone discriminate between CN, MCI, and AD. 

As the population grows and gets older, the need for health care increases, both withinprimary care but also within home care. Being able to carry out smaller examinations to obtain the vital values without a trip to the hospital or that healthcare professionals travel to each patient gives great value to both partners. The care situation in Sweden in 2020 is an understaffed and periodically heavily strained. With the help of digitalisation and the advancement of technology, healthcare can be streamlined and at not least, improved. One of the companies working on a vision of a better healthcare situation is Detectivio. Detectivio was founded by Stefan Malmgren, a physician who saw a clear need for streamlining care when working at the emergency room. Together with researcher Taha Kahn, they have developed a product that can scan a face and in ten seconds get five vital values such as bloodpressure, respiratory rate, heart rate, body temperature and oxygen level in the blood. However, the product is not complete or ready to meet the market and this is where we, as a project group, step in to formulate, develop and complete the products functional aspects into a product ready to be placed on the market. The purpose of the project is to outline possible target groups, their needs and requirementsfor the product. Creating a prototype to test the user experience. The effect of this project will be to offer comfort and safety in the form of high-quality healthcare through time-efficientmeans. The primary target groups were categorized as "technical person", "tool" and "medical reason". The technician wants a product for his or her own use, the group “tools” is meant those who want a product for preventative purposes or as a supplement to existing healthcare products. Finally, we have those in need of medical treatment or supervision. It may be someone who is conically ill and sees a great need to be able to measure their vital values in the home. The result is a fully automated product that enables safe and secure healthcare in the home. The product is activated with the help of sensors that sense movement. Through clear visual means such as a display and lights, the product communicates with the user. All functions are controlled by an Arduino whose code is written by the project team. Since the product does not require user contact, it can contribute to reduced infection risk. The product is a rectangular box of 250 x 176 x 160 mm made in PLA and plexiglass with holes for two cameras, two distance readers, a display and power cable output. The product weighs just over 4 kilos which makes it easy to move. With a simple and unobtrusive design, this product can become part of the everyday interior of the smart home of the future.

The field of hematology involves the analysis of blood and its components like platelets, red blood cells, white blood cells. The outcome of this analysis can be vital in determining the condition of the human body and it is important to obtain accurate results. A deep learning algorithm scans over the given input data for unique features and learns them. Then it identifies these features and correlates them to give the result. This can save a significant amount of time and manual work. In contrast, a traditional machine learning algorithm requires the developer to carry-out the feature engineering. This thesis involves the analysis of white blood cells (WBC) using deep learning techniques. In collaboration with a hematology company HemoCue AB based in Angelholm, we will be developing deep learning algorithms for the analysis of white blood cells in the HemoCue R WBC DIFF System. Predominantly, there are two stages in this thesis. The first stage is white blood cell identification, which is used to calculate the number of white blood cells in the given blood sample. The next stage is to identify the different types of white blood cells with which the concentration of each type of WBC in the given blood sample is calculated. We have explored different classification approaches like ’one vs all’ and ’4-class classifier’, and have developed two CNN architectural designs i.e. ’multi-input’ and ’multi-channel’. On comparing the performance of all these design approaches, a final integrated model is put forth for the analysis of WBCs in the company’s device. The proposed ’one vs all’ classification approach combined with a 3-class CNN classifier has yielded very promising results with a combined accuracy 95.45% in WBC identification and 90.49% in WBC differential classification.

Volvo Group is one of the Worlds leading manufacturer in the categories trucks, busses, construction equipment and engines for the marine and industrial applications. Volvo Group consist of many different brands 10 in total, these are: Volvo Trucks, UD Trucks, Renault Trucks, Mack Trucks, Group Trucks Asia & JVs, Volvo Construction Equipment, Volvo Bus, Volvo Penta, Volvo Financial Services and Governmental Sales. The initiative for the project came from Method and Process Development within Volvo Trucks Tuve Plant, department at Volvo Group Trucks Operations (GTO), which is the part of Volvo Group performing the actual production of the trucks.

Volvo GTO is located worldwide in several different countries, which leads to different work processes. To standardize a method where the designer (component owner) together with the geometry architect can make a first ergonomics analysis of the concerned component. To make this possible, the project presented a manual on how the component owner should proceed to obtain as good and correct analysis of ergonomics as possible.

This bachelor thesis makes suggestions for how VR would be helpful in the design phase as an evaluation tool during development of a new product/component or whether improvements should be made to an existing component. The thesis has focused mostly on how the designer and geometry architect can evaluate the ergonomics aspects with VR as a help, already in the design phase.

The project has investigated two user cases. One of them is presented in this report. This applies to the installation of heat shield, the reason that this particular assembly was chosen is due to its poor ergonomics and accessibility. The project chose to do a RULA-analysis and PLIBEL-analysis. The RULA analysis gave a high total score, 7 out of 7, while PLIBEL was an analysis at the workplace. Both proved to be a good basis for continued work. 

The study shows that VR is a great tool for analysis of the ergonomics aspects in early design phase. It gives relevant results and has the potential for savings in resources and cost in product development process.

To improve the results of the thesis, there have been visits on ESI-Group which has sponsored the thesis in the form of VR equipment and workshop. This gave the project members an insight into the possibilities of VR.