Journal of Medical Engineering and Technology最新文献

In different studies in the field of healthcare, big data analytics technology has been shown to be effective in observing the behaviour of data, of which analysed to allow the discovery of relevant insights for strategy and decision making. The objective of this study is to present the results of a systematic review of the literature on big data analytics in healthcare, focussing in technologies, main areas and purposes of adoption. To reach its objective, the study conducts an exploratory research, through a systematic review of the literature, using the Methodi Ordinatio protocol supported by content analysis. The results reveal that the use of tools implies work performance at the clinical and managerial level, improving the cost-benefit ratio and reducing the time factor in the practice of the workforce in health services. Thus, this study hopes to contribute to the technological advancement of computational intelligence applied to healthcare.

Understanding the relationship between mechanobiology and the biosynthetic activities of the valve interstitial cells (VICs) in health and disease under severe dynamic loading conditions is of particular interest. The purpose of this study is to further understand the mechanobiology of heart valve leaflet tissue and the VICs under impact forces. Two novel computational and experimental platforms were developed to study the effect of impact load on the VICs to monitor for apoptosis. The first objective was to design and develop an apparatus to experimentally study viability (apoptosis) of the porcine heart valve leaflet tissue VICs in the aortic position under controlled impact forces. Apoptosis was assessed based on terminal transferase dUTP nick end-labelling (TUNEL) assay. The second objective was to develop a computational platform to estimate the stress and strain fields in the vicinity of VICs when the tissue experiences impact forces. A nonlinear finite element (FE) model with an anisotropic, hyperelastic and heterogeneous material model for the matrix and cells was developed. Preliminary results confirm that interstitial cells are successfully resistant to impact loads up to 30 times more than normal physiological conditions. Additionally, the structure and composition of heart valve leaflet tissue provides a mechanical shield for VICs protecting them from excessive mechanical forces such as impact loads. Although, the entire tissue may experience excessive stresses, which may lead to structural damage, the stresses around and near VICs remain consistency low. Results of this study may be used for heart valve leaflet tissue-engineering, as well as further understanding the mechanobiology of the VICs in health and disease.

Dementia is a general term used to indicate any disorder related to human memory. The various memory-related problems severely affect the human brain and so the individual feels difficulty in doing their normal physical as well as mental activities. There are different types of dementia that exist, but the commonly seen and fatal types of dementia are Alzheimer's disease (AD) and Parkinson's disease (PD). In this paper different efficient Machine Learning Techniques are selected analysed their behaviours in the diagnosis of AD and PD using Positron Emission Tomography (PET). The PET image dataset used in this work consists of 1050 images with AD, PD and Healthy Brain images. The total number of images is split into two different categories in the ratio of 7:3 for training and testing respectively. The different machine learning classifiers used are Bagged Ensemble, ID3, Naive Bayes and Multiclass Support Vector Machine. The classification of the AD and PD with the reference of a healthy brain is done by comparing the input image with the trained samples in the PET image database. In the comparison of trained samples with the input image for the PET images, the bagged ensemble learning classifier worked better than the other classification algorithms and yielded an accuracy of 90.3%.

Autistic children have difficulty communicating wants, needs, and thoughts. In cases of low functioning autism, an individual can have serious speech and language disabilities. In response to the need of parents and therapists dealing with autistic children, social robots have been developed and incorporated into assisting children with autism. Research studies have proved the possibility of improving autistic children's lives using social robots. However, not any social robot can successfully fulfil this task, since autistic children are sensitive to certain behaviours, shapes, and colours. The proposed integrated application and humanoid robot, Otisma has been designed and developed after an intensive literature research. Otisma can be used as an educational and communicational tool with autistic children. Otisma aids educators by using applied behaviour analysis (ABA) which is a scientifically validated method that helps autistic children work through areas of severe developmental delay, like language and nonverbal communication. Different lessons can be explored using an application that is controlled by the therapist. Otisma is an efficient educational tool that facilitates the learning process to maximise social skills for children with autism. Otisma is portable, affordable, user friendly, and can be equally used by therapists in clinics or parents at home.

Wearable technology is a promising and revolutionary technology that is changing some aspects of our standard of living to a great extent, including health monitoring, sport and fitness, performance tracking, education, and entertainment. This article presents a comprehensive literature review of over 160 articles related to state-of-the-art human wearable technologies. We provide a thorough understanding of the materials, power sources, sensors, and manufacturing processes, and the relationships between these to capture opportunities for enhancement and challenges to overcome in wearables. As a result of our review, we have determined the need for the development of a comprehensive, robust manufacturing system alongside specific standards and regulations that take into account wearables' unique characteristics. Seeing the whole picture will provide a frame reference and road map for researchers and industries through the design, manufacturing, and commercialisation of effective, portable, self-powered, multi-sensing ultimate future wearable devices and create opportunities for new innovations and applications.

Diabetes mellitus is one of the fastest-growing lifestyle disorders in the world. While numerous regimes have been developed to manage diabetes, there continue to be high numbers of diabetes-related deaths worldwide. The review gives a brief introduction to the pathology and aetiology of the disorder, different solutions developed over time with their advantages and disadvantages, and highlights the technological components and challenges of the latest technologies: artificial pancreas and regenerative medicine. The study is restricted to a set of high-quality publications from the last decade.

Pressure ulcers have been part of tissue damage without effectiveness in medical, surgical, and intensive care units. This study aims to focus on developing lateral tilt positions for effective pressure ulcer relief for bedridden patients. A repositioning mattress was placed in the side-lying left lateral tilt position (15°, 30°, 45°), sheering (0.680, 1.323, 1.870), interface pressure (2.550, 2.290, 2.830), and placed at 1.5 m long piece of polyethylene rubber. The design strength was set at 6000 N and 2100 mm x 1105 mm (${\sigma }_{t,0,d}$ = 42, ${\sigma }_{c,0,d}$ = 34). The design shows the greatest supine position at 30°, 1.323, 2.290, pressure load ($\Delta p_0$ = 1.125 (1820) $\approx$ 2050 psi, $\Delta p_{3000}$ = 1.125 (620) $\approx$ 700 psi), tensile stress (${\sigma }_{t,0,d}$ (MPa) = 42), compressive stress (${\sigma }_{c,0,d}$ (MPa) = 34), and FOS (${\sigma }_{t,0,d}$ = 42, ${\sigma }_{c,0,d}$ = 34). The factor of safety illustrated that the 30° lateral tilt position is more consistent in repositioning for pressure ulcer prevention compared to the supine-to-tilt region. Further, an application of repositioning mattresses was developed to test in bedridden patients with tissue ulcers in nursing homes.

The knee joint is frequently exposed to injuries in people of all ages. In some cases, physical therapy is prescribed to recover the strength and mobility of a patient. The robotic assistance devices are gaining community attention and aim to improve the quality of life of people. In this work, we present the kinematic and dynamic modelling of a five-bar-linkage assistive device for knee rehabilitation according to anthropometric data from Latin-American population. We obtain a dynamic model of the proposed rehabilitation system and compare the knee trajectories with obtained using the assistive system to evaluate appropriate control strategies in the future. For this purpose, we present the kinematic formulation of the device, and then we derive the dynamics using two approaches to validate the model; we obtain the motion equation using the Lagrange approach and an algebraic method that simplifies modelling. Both approaches yield a unique model, which is validated either in simulation and by experimental trials, showing the functionality of the system and the validity of the models when performing rehabilitation routines.