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In this study, the power spectral density of simulated data which contain neuromuscular diseases and normal motor unit (i.e. control group) scenarios was calculated using Welch's method. Furthermore, the effect of Welch's method on differential diagnosis was investigated. Data were recorded both near innervation zone which is the area that motor unit action potential occurs and near tendon. Multi-layer...
UF-EMG test, in which non-invasive uroflowmetry (UF) and electromyography (EMG) signals are simultaneously recorded, is frequently used in children diagnosed with lower urinary tract dysfunction disease (AUSD) and its treatment. In the literature, independent (single) UF signals and integrated (dual) UF-EMG signals are graded many times but there is no classification study of UF-EMG integrated signals...
The need for diagnostic tools for the characterization of progressive movement disorders — as the Parkinson Disease (PD) — aiming to early detect and monitor the pathology is getting more and more impelling. The parallel request of wearable and wireless solutions, for the real-time monitoring in a non-controlled environment, has led to the implementation of a Quantitative Gait Analysis platform for...
Among other applications, electromyography (EMG) is used in the assessment of locomotion pathologies to quantitatively document abnormal muscle activation patterns during walking. However, EMG cyclic patterns are affected by high cycle-to-cycle variability. Previous research introduced a clustering approach (CIMAP) to recognize gait cycles with similar EMG onset/offset timings, reducing variability...
The information present in the electromyogram (EMG) signals can be used for the diagnosis of the neuro-muscular abnormalities such as: amyotrophic lateral sclerosis (ALS) and myopathy. In this paper, a technique for detection of ALS and myopathy is presented, which is based on tunable-Q wavelet transform (TQWT). For the purpose of detection of these abnormalities, motor unit action potentials (MUAPs)...
Electromyogram (EMG) signals contain a lot of information about the neuromuscular diseases like amyotrophic lateral sclerosis (ALS). ALS progressively degenerates the motor neurons in spinal cord. In this study, a new technique for the analysis of normal and ALS EMG signals is proposed. EMG signals are decomposed into narrow band intrinsic mode functions (IMFs) by using empirical mode decomposition...
This study includes a classification structure consisting of second part for the automatic diagnosis of the neuromuscular disease of ALS (Amyotrophic Lateral Sclerosis) and myopathy being a muscular disease. In this study feature vectors containing time domain parameters, frequency domain parameters (a total of 25 feature vectors) as well as feature vectors composed of combination of these parameters...
This study includes a classification structure consisting of first three stages for the automatic diagnosis of the neuromuscular disease of ALS (Amyotrophic Lateral Sclerosis) and myopathy being a muscular disease. In this study; EMG mark representing best MUAP will be determined for the right to comment sign EMG. After the first stage of the raw EMG data eliminated by noise the segmentation stage...
In this contribution, classification of two main neuromuscular diseases namely Myopathy and Neuropathy and Healthy signals is performed using cross-correlation based feature extraction technique. For this purpose, cross-correlation of Healthy, Myopathy and Neuropathy disease EMG signal is done with a reference Healthy signal. Selective features like Hjorth, Adaptive Autoregressive and statistical...
Correlation size together with Lyapunov exponents estimated from both electroencephalography (EEG) and electromyography (EMG) signals, are the crucial variables in the classification of mental tasks using an artificial neural network (ANN) classifier for patients suffering from neurological disorders/diseases. The above parameters vary according to the status of the patient, for example: depending...
In this study, we intended to differentiate patients with essential tremor (ET) from tremor dominant Parkinson disease (PD). Accelerometer and electromyographic signals of hand movement from standardized upper extremity movement tests (resting, holding, carrying weight) were extracted from 13 PD and 11 ET patients. The signals were filtered to remove noise and non-tremor high frequency components...
In this paper, an efficient technique for the analysis of Myopathy and normal electromyography (EMG) signals is proposed. Empirical mode decomposition (EMD) technique has been used to decompose non-stationary EMG signals in some set of narrow band intrinsic mode functions (IMFs). Hilbert transform of IMFs provides analytic signals, which are used for extraction of instantaneous frequency and instantaneous...
Electromyography (EMG) signals collected from skeletal muscles, can be used for diagnosis of ALS and myopathy diseases. This paper presents a new technique based on five features and Extreme learning machine (ELM) classifier for the diagnosis of ALS and myopathy diseases. Bispectrum based features with mean plosion index, and fractal dimension features are extracted from EMG signals. For the purpose...
Chronic obstructive pulmonary disease (COPD) is a type of obstructive lung disease which affects 329 million people or nearly 5% of the population in the worldwide. The respiratory training robot proposed in this paper, which is designed for using in a bed, aims to assist in COPD patients' respiratory activities and achieve rehabilitation goals on respiration through chest and respiratory muscle training...
Different physiological parameters of a human being are measured to accurately diagnose the related disease. Though there are numerous physiological parameters this paper emphasizes on some of the most common physiological parameters such as blood pressure, EMG, sEMG, heart rate and ECG which are of primary importance to elderly people. Accurate measurement and analysis of these parameters can lead...
Objectives: The inaccurate implantation of deep brain stimulation electrode could cause in-effective therapy and varied side-effects. This study aims to intra-operatively localise the subthalamic nucleus (STN) using voluntary movement related local field potentials (LFPs) to improve the electrode implantation accuracy. Methods: STN LFPs were recorded during auditory cued clicking motor task in twelve...
Spinal Muscular Atrophy (SMA) is a progressive neuromuscular disorder. Usually, this condition is considered genetically induced with no known cure to date. Children are born with the condition and develop muscular weakness progressively as they grow. The weakness ultimately encompasses the whole muscular function rendering the limbs dysfunctional or paralyzed. Many children with SMA, if they do not...
Swallowing difficulty is also called dysphasia. It is usually a sign related to the problems of your throat or oesophagus the muscular tube that moves food and liquids from the back of your mouth to your stomach. These diseases are the common problem in people who have problems of the brain or nervous system. Surface electromyography (sEMG) signals provide the valuable information about the changes...
In this work, an attempt has been made to differentiate sEMG signals under muscle fatigue and non-fatigue conditions using multiscale features. Signals are recorded from biceps brachii muscle of 50 normal adults during repetitive dynamic contractions. After prescribed preprocessing, each signal is divided into six segments out of which first and last segments are considered in this analysis. Multiscale...
The aim of the present study is to analyse changes in the diaphragmatic electromyography integral, as a direct expression of the patients inspiratory effort and index of neural respiratory drive, and parameters associated with ventilatory function in patients with prolonged weaning under Pressure Support Ventilation (PSV) and Neurally Adjusted Ventilatoy Assist (NAVA). Five patients affected by neuromuscular...
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