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Entropy, as a measure of randomness in time-varying signals, is widely used in areas such as thermodynamics, statistical mechanics and information theory. This paper investigates the use of two commonly employed entropy measures, namely Wavelet Entropy and Approximate Entropy, as a predictor of tremor reappearance in Essential Tremor patients; the predictor input is a raw surface-electromyographic...
The control of powered upper limb prostheses using the surface electromyogram (EMG) is an important clinical option for amputees. There have been considerable recent improvements in prosthetic hands, but these currently lack a control scheme that can decode movement intent from the EMG to exploit their mechanical dexterity. Pattern recognition based control has the potential to decode many classes...
Lower-limb prostheses are rapidly advancing with greater computing power and sensing modalities. This paper is an attempt to begin exploring the trade-off between extrinsic and intrinsic control modalities. In this case, between electromyographic (extrinsic) and several internal sensors that can be used for intrinsic control. We propose a method that will identify the particular features, taken from...
Neuromuscular electrical stimulation (NMES) can alter the functioning of muscles and even assist muscle rehabilitation. In this paper, we evaluate the effect of NMES on the conduction velocity (CV) of the brachial biceps' motor units. We used a linear array of electrodes to acquire electromyographic signals, as different subjects perform isometric voluntary contractions (IVCs), with and without prior...
Parkinson's disease (PD) is characterized by motor disabilities that can be alleviated reasonably with appropriate medication. However, there is a lack of objective methods for quantifying the efficacy of treatment in PD. We applied here an objective method for quantifying the effects of medication in PD using EMG and acceleration measurements and analysis. In the method, four signal features were...
Many stroke patients are subject to limited hand functions in the paretic arm due to a significant loss of Corticospinal Tract (CST) fibers. A possible solution for this problem is to classify surface Electromyography (EMG) signals generated by hand movements and uses that to implement Functional Electrical Stimulation (FES). However, EMG usually presents an abnormal muscle coactivation pattern shown...
Rigorous analyses of the mechanisms human-human physical interaction are only possible if corresponding means of systematically classifying dyad strategies are in place. Previous suggestions for classification of strategies neglect the high level of redundancy that is present when attenuation of external disturbances is required. To address this, we propose a quantitative classification system based...
This paper presents a real-time implementation of an intent recognition system on one transfemoral (TF) amputee. Surface Electromyographic (EMG) signals recorded from residual thigh muscles and the ground reaction forces/moments collected from the prosthetic pylon were fused to identify three locomotion modes (level-ground walking, stair ascent, and stair descent) and tasks such as sitting and standing...
Monitoring patients' physiological signals during their daily activities in the home environment is one of the challenge of the health care. New ultra-low-power wireless technologies could help to achieve this goal. In this paper we present a low-power, multi-modal, wearable sensor platform for the simultaneous recording of activity and physiological data. First we provide a description of the wearable...
In order to improve the quality of life of persons who lost their limb due to an accident or a sickness, many myoelectric artificial arms have been proposed. To control the motion of the elbow joint of the myoelectric arm, the EMG signals of the biceps brachii and the triceps brachii muscles are frequently used as input signals. However, since both muscles are the biarticular muscles between the shoulder...
In this paper we present surface electromyo-graphic (EMG) data collected from 16 channels on five unimpaired subjects and one transradial amputee performing 12 individual finger movements and a rest class. EMG were processed using a traditional Time Domain feature-set and classifiers: a Linear Discriminant Analysis (LDA) a k-Nearest Neighbors (k-NN) and Support Vector Machine (SVM). Using continuous...
Since the 1970s, various automatic sleep spindles procedures have been implemented and presented in the literature. Unfortunately, their results are not easily comparable because the databases, the assessment methods and the terminologies employed are often radically different. In this study, we propose a systematic assessment method for any automatic sleep spindles detection algorithm. We apply this...
The rough entropy (RoughEn) is developed based on the rough set theory. It has the advantage of low computational complexity, because there is no parameter to set in RoughEn. In this paper, we characterized the feature of surface electromyography (SEMG) signal with RoughEn and then used support vector machine to classify six different hand motions. The sample entropy, wavelet entropy and approximate...
A new, automated way to obtain signatures of active motor units (MUs) from high density surface EMG recordings during voluntary contractions is presented. It relies on clustering of repetitive shapes corresponding to different MU action potentials (MUAPs) present. The number of clusters and the mean shapes of the MUAPs as observed on the electrode grid, are estimated in a fast way without user interaction...
This study describes the design and feasibility testing of a hand rehabilitation system that provides haptic assistance for hand opening in moderate to severe hemiplegia while subjects attempt to perform bilateral hand movements. A cable-actuated exoskeleton robot assists the subjects in performing impaired finger movements but is controlled by movement of the unimpaired hand. In an attempt to combine...
A novel method for detecting muscle contraction is presented. This method is further developed for identifying four different gestures to facilitate a hand gesture controlled robot system. It is achieved based on surface Electromyograph (EMG) measurements of groups of arm muscles. The cross-information is preserved through a simultaneous processing of EMG channels using a recent multivariate extension...
Essential Tremor (ET) refers to involuntary movements of a part of the body. ET patients have serious difficulties in performing daily living activities. Our ultimate goal is to develop a system that can enable ET patients to perform daily living activities. We have been developing an exoskeleton robot for ET patients. We make use of the electromyogram (EMG) signal to control this robot. However,...
This paper presents an adaptive least squares algorithm for estimating the power line interference in surface electromyography (sEMG) signals. The algorithm estimates the power line interference, without the need for a reference input. Power line interference can be removed by subtracting the estimate from the original sEMG signal. The algorithm is evaluated with simulated sEMG based on its ability...
Muscle force estimation while a dynamic motor task is carried out still presents open questions. In particular, concerning locomotion, although the inverse dynamic based static optimization has been widely accepted as a suitable method to obtain reliable results, appropriate modifications of the object function may improve results. This paper was aimed at analyzing the sensitivity of estimated muscle...
A calibration method is proposed to compensate for the changes in the surface electromyogram (SEMG) amplitude level of the biceps brachii at different joint angles due to the movement of the muscle bulk under the EMG electrodes for a constant force level. To this end, an experiment was designed, and SEMG and force measurements were collected from 5 subjects. The fast orthogonal search (FOS) method...
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