Muscle Network Connectivity Study in Diabetic Peripheral Neuropathy Patients.

Diabetic peripheral neuropathy (DPN) is a prevalent complication of chronic diabetes mellitus and has a significant impact on quality of life. DPN typically manifests itself as a symmetrical, length-dependent sensorimotor polyneuropathy with severe effects on gait. Surface electromyography (sEMG) is a valuable low-cost tool for assessing muscle activation patterns and precise identification of abnormalities.

Automatic semantic segmentation of EHG recordings by deep learning: An approach to a screening tool for use in clinical practice.

Background And Objective: Preterm delivery is an important factor in the disease burden of the newborn and infants worldwide. Electrohysterography (EHG) has become a promising technique for predicting this condition, thanks to its high degree of sensitivity. Despite the technological progress made in predicting preterm labor, its use in clinical practice is still limited, one of the main barriers being the lack of tools for automatic signal processing without expert supervision, i.

Vectorgastrogram: dynamic trajectory and recurrence quantification analysis to assess slow wave vector movement in healthy subjects.

Functional gastric disorders entail chronic or recurrent symptoms, high prevalence and a significant financial burden. These disorders do not always involve structural abnormalities and since they cannot be diagnosed by routine procedures, electrogastrography (EGG) has been proposed as a diagnostic alternative. However, the method still has not been transferred to clinical practice due to the difficulty of identifying gastric activity because of the low-frequency interference caused by skin-electrode contact potential in obtaining spatiotemporal information by simple procedures.

Assessment of Muscle Coordination Changes Caused by the Use of an Occupational Passive Lumbar Exoskeleton in Laboratory Conditions.

The introduction of exoskeletons in industry has focused on improving worker safety. Exoskeletons have the objective of decreasing the risk of injury or fatigue when performing physically demanding tasks. Exoskeletons' effect on the muscles is one of the most common focuses of their assessment.

Assessment of a Passive Lumbar Exoskeleton in Material Manual Handling Tasks under Laboratory Conditions.

Manual material handling tasks in industry cause work-related musculoskeletal disorders. Exoskeletons are being introduced to reduce the risk of musculoskeletal injuries. This study investigated the effect of using a passive lumbar exoskeleton in terms of moderate ergonomic risk.

Optimized Feature Subset Selection Using Genetic Algorithm for Preterm Labor Prediction Based on Electrohysterography.

Electrohysterography (EHG) has emerged as an alternative technique to predict preterm labor, which still remains a challenge for the scientific-technical community. Based on EHG parameters, complex classification algorithms involving non-linear transformation of the input features, which clinicians found difficult to interpret, were generally used to predict preterm labor. We proposed to use genetic algorithm to identify the optimum feature subset to predict preterm labor using simple classification algorithms.

A Surface Electromyogram Evaluation of the Postural Freedom Effects in Laparoscopic Surgery.

It has been demonstrated that laparoscopic procedures benefit patients in terms of recovery time, exposure to infections and trauma. Nevertheless, it increases the number of problems for the surgeons, including the frequency and duration of awkward postures for surgeons. The repetition of these movements is considered the main cause for musculoskeletal disorders in surgeons' upper limbs.

Active concentric ring electrode for non-invasive detection of intestinal myoelectric signals.

Although the surface electroenterogram (EEnG) is a weak signal contaminated by strong physiological interference, such as ECG and respiration, abdominal surface recordings of the EEnG could provide a non-invasive method of studying intestinal activity. The goal of this work was to develop a modular, active, low-cost and easy-to-use sensor to obtain a direct estimation of the Laplacian of the EEnG on the abdominal surface in order to enhance the quality of bipolar surface monitoring of intestinal activity. The sensor is made up of a set of 3 concentric dry Ag/AgCl ring electrodes and a battery-powered signal-conditioning circuit.

Discrete Laplacian recordings of the electroenterogram from abdominal surface in humans.

The first aim of this study was to obtain the discrete Laplacian of the myoelectric small intestine signal (electroenterogram, EEnG) from bipolar recordings on the abdominal surface in humans. In addition, the objective was to identify the slow wave (SW) component of the EEnG in the estimated Laplacian, as well as to compare this signal with the bipolar surface recordings. It was carried out 8 recording sessions in 6 healthy volunteers.

Signal noise ratio of small intestine myoelectrical signal recorded from external surface.

Electroenterogram (EEnG), which is the myoelectrical activity of the small bowel, can be non-invasively recorded from abdominal external surface. However, this bioelectrical signal is weak and noisy compared to internal recording from bowel serous layers, because of bioelectric transmission through abdominal layers. Furthermore, it is contaminated with several interferences from other biological activities as cardiac muscle (ECG), skeletal muscles (EMG), or respiration movements.

Identification of the slow wave component of the electroenterogram from Laplacian abdominal surface recordings in humans.

The electroenterogram (EEnG) is a surface recording of the myoelectrical activity of the smooth muscle layer of the small intestine. It is made up of two signals: a low-frequency component, known as the slow wave (SW), and high-frequency signals, known as spike bursts (SB). Most methods of studying bowel motility are invasive due to the difficult anatomic access of the intestinal tract.

Adaptive filtering of ECG interference on surface EEnGs based on signal averaging.

An external electroenterogram (EEnG) is the recording of the small bowel myoelectrical signal using contact electrodes placed on the abdominal surface. It is a weak signal affected by possible movements and by the interferences of respiration and, principally, of the cardiac signal. In this paper an adaptive filtering technique was proposed to identify and subsequently cancel ECG interference on canine surface EEnGs by means of a signal averaging process time-locked with the R-wave.

Noninvasive measurement and analysis of intestinal myoelectrical activity using surface electrodes.

Intestinal myoelectrical activity (IMA), which determines bowel mechanical activity, is the result of two components: a low-frequency component [slow wave (SW)] that is always present, and a high-frequency component [spike bursts (SB)] which is associated with bowel contractions. Despite of the diagnostic significance of internal recordings of IMA, clinical application of this technique is limited due to its invasiveness. Thus, surface recording of IMA which is also called electroenterogram (EEnG) could be a solution for noninvasive monitoring of intestinal motility.