Experimental Analysis of Handcart Pushing and Pulling Safety in an Industrial Environment by Using IoT Force and EMG Sensors: Relationship with Operators' Psychological Status and Pain Syndromes.

Non-ergonomic execution of repetitive physical tasks represents a major cause of work-related musculoskeletal disorders (WMSD). This study was focused on the pushing and pulling (P&P) of an industrial handcart (which is a generic physical task present across many industries), with the aim to investigate the dependence of P&P execution on the operators' psychological status and the presence of pain syndromes of the upper limbs and spine. The developed acquisition system integrated two three-axis force sensors (placed on the left and right arm) and six electromyography (EMG) electrodes (placed on the chest, back, and hand flexor muscles).

The compliance of head-mounted industrial PPE by using deep learning object detectors.

The compliance of industrial personal protective equipment (PPE) still represents a challenging problem considering size of industrial halls and number of employees that operate within them. Since there is a high variability of PPE types/designs that could be used for protecting various body parts and physiological functions, this study was focused on assessing the use of computer vision algorithms to automate the compliance of head-mounted PPE. As a solution, we propose a pipeline that couples the head ROI estimation with the PPE detection.

A Noninvasive Assistant System in Diagnosis of Lumbar Disc Herniation.

The purpose of this study is the application of pressure sensors in diagnostics and evaluation of the accuracy diagnostics of lumbar disc herniation at levels L4/L5 and L5/S1 using the aforementioned platform. The motivation behind the idea to apply the pressure measurement platform is the fact that the motor weakness of plantar and dorsal flexia of the feet is one of the absolute indications for the operative treatment of patients with lumbar disc herniation at the indicated levels. In patients, MRI diagnosis of the lumbosacral spine served as the ground truth in the diagnosis of herniation at L4/L5 and L5/S1 levels.

An Early Disc Herniation Identification System for Advancement in the Standard Medical Screening Procedure Based on Bayes Theorem.

The aim of this research was to analyze objectively the process of disc herniation identification using Bayes Theorem. One of the symptoms of discus hernia is muscle weakness on the foot that is caused by displaced discs in the space of two vertebrae. This fact is used by experts in initial diagnosis of herniated discs and we used it to create non-invasive platform for the same purposes by measuring force values from four sensors placed on both feet (first, second, and fourth metatarsal head as well as the heel).

Comfort level classification during patients transport.

Background: Passenger comfort is affected by many factors. Patient comfort is even more specific due to its mental and physical health condition.

Objective: Developing a system for monitoring patient transport conditions with the comfort level classification, which is affected by the patient parameters.

Non-invasive improved technique for lumbar discus hernia classification based on fuzzy logic.

This paper presents the improved technique for classification of the type of lumbar discus hernia based on fuzzy logic. The reduced mobility of the foot is one of the symptoms of the disease that occurs because of the displaced discs in the space of two vertebrae. This fact was used for non-invasive discus hernia diagnosis by measuring force values from four sensors placed on both feet (first, second and fourth metatarsal head as well as the heel).

Family and Personality Predictors of Clinical Depression and Anxiety in Emerging Adults: Common, Distinctive, or a Vulnerability Continuum?

There is an ongoing debate on the relationship between depression and anxiety, but data on similarities and differences in their predictor profiles are scarce. The aim of our study was to compare family and personality predictors of these disorders among 220 "emerging adults." As such, two clinical groups with noncomorbid depressive and anxiety disorders, and one healthy control group were assessed by sociodemographic questionnaires, Structured Clinical Interview for DSM-IV Disorders and NEO Personality Inventory, Revised.

Anxiety-like behavioural effects of extremely low-frequency electromagnetic field in rats.

In recent years, extremely low-frequency electromagnetic field (ELF-EMF) has received considerable attention for its potential biological effects. Numerous studies have shown the role of ELF-EMF in behaviour modulation. The aim of this study was to investigate the effect of short-term ELF-EMF (50 Hz) in the development of anxiety-like behaviour in rats through change hypothalamic oxidative stress and NO.

Acceleration of Image Segmentation Algorithm for (Breast) Mammogram Images Using High-Performance Reconfigurable Dataflow Computers.

Image segmentation is one of the most common procedures in medical imaging applications. It is also a very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages.

Multicomponent Treatment in a Day Hospital for Adolescents: A Case of Good Practice.

The dynamics of adolescence require adjustments in psychiatric treatment because of the challenges of this developmental stage in life. This column describes the Day Hospital for Adolescents (DHA) of the Institute of Mental Health in Belgrade, Serbia, which was established in December 2007. The DHA is a holistic program for the treatment of youths ages 15-25 with emotional disorders.

Parameter optimization of a computer-aided diagnosis system for detection of masses on digitized mammograms.

Background: Reading mammograms is a difficult task and for this reason any development that may improve the performance in breast cancer screening is of great importance.

Objective: We proposed optimized computer aided diagnosis (CAD) system, equipped with reliability estimate module, for mass detection on digitized mammograms.

Methods: Proposed CAD system consists of four major steps: preprocessing, segmentation, feature extraction and classification.

Comparative analysis of breast cancer detection in mammograms and thermograms.

In this paper, we present a system based on feature extraction techniques for detecting abnormal patterns in digital mammograms and thermograms. A comparative study of texture-analysis methods is performed for three image groups: mammograms from the Mammographic Image Analysis Society mammographic database; digital mammograms from the local database; and thermography images of the breast. Also, we present a procedure for the automatic separation of the breast region from the mammograms.

Numerical and experimental analysis of factors leading to suture dehiscence after Billroth II gastric resection.

The main goal of this study was to numerically quantify risk of duodenal stump blowout after Billroth II (BII) gastric resection. Our hypothesis was that the geometry of the reconstructed tract after BII resection is one of the key factors that can lead to duodenal dehiscence. We used computational fluid dynamics (CFD) with finite element (FE) simulations of various models of BII reconstructed gastrointestinal (GI) tract, as well as non-perfused, ex vivo, porcine experimental models.

Segmentation for the enhancement of microcalcifications in digital mammograms.

Microcalcification clusters appear as groups of small, bright particles with arbitrary shapes on mammographic images. They are the earliest sign of breast carcinomas and their detection is the key for improving breast cancer prognosis. But due to the low contrast of microcalcifications and same properties as noise, it is difficult to detect microcalcification.

Thermography based breast cancer detection using texture features and minimum variance quantization.

In this paper, we present a system based on feature extraction techniques and image segmentation techniques for detecting and diagnosing abnormal patterns in breast thermograms. The proposed system consists of three major steps: feature extraction, classification into normal and abnormal pattern and segmentation of abnormal pattern. Computed features based on gray-level co-occurrence matrices are used to evaluate the effectiveness of textural information possessed by mass regions.

ARTreat Project: three-dimensional numerical simulation of plaque formation and development in the arteries.

Atherosclerosis is a progressive disease characterized by the accumulation of lipids and fibrous elements in arteries. It is characterized by dysfunction of endothelium and vasculitis, and accumulation of lipid, cholesterol, and cell elements inside blood vessel wall. In this study, a continuum-based approach for plaque formation and development in 3-D is presented.

Transient finite element modeling of functional electrical stimulation.

Transcutaneous functional electrical stimulation is commonly used for strengthening muscle. However, transient effects during stimulation are not yet well explored. The effect of an amplitude change of the stimulation can be described by static model, but there is no differency for different pulse duration.

Noninvasive determination of knee cartilage deformation during jumping.

The purpose of this investigation was to use a combination of image processing, force measurements and finite element modeling to calculate deformation of the knee cartilage during jumping. Professional athletes performed jumps analyzed using a force plate and high-speed video camera system. Image processing was performed on each frame of video using a color recognition algorithm.