This paper proposes and tests on able-bodied subjects a control strategy that can be practically applied in unilateral transradial amputees for simultaneous proportional of multiple degrees-of-freedom (DOFs). We used artificial neural networks to estimate kinematics the complex wrist/hand from high-density surface electromyography (EMG) signals contralateral limb during mirrored bilateral movements free space. The tested involved concurrent activation wrist flexion/extension, radial/ulnar...

This study examined the effect of experimental neck muscle pain on EMG-force relationship cervical agonist and antagonist muscles. Surface EMG signals were detected from sternomastoid, splenius capitis, upper trapezius muscles bilaterally 14 healthy subjects during flexion extension contractions linearly increasing force 0 to 60% maximum voluntary contraction (MVC). Measurements performed before after injection 0.5 ml hypertonic isotonic saline into either sternomastoid or capitis in two...

This paper presents the fully automatic identification of motor unit spike trains from high-density surface electromyograms (EMG) in pathological tremor. First, a mathematical derivation is provided to theoretically prove possibility decomposing noise-free EMG signals into with high correlation, which are typical tremor contractions. Further, proposed decomposition method tested on simulated different levels noise and experimental 14 tremor-affected patients. In case central frequency...

This study details the development and validation of a graphene-based ice detection system, designed to enhance flight safety by monitoring accumulation on aircraft surfaces. The system employs semiconductive polymer (PEDOT:PSS) with graphene electrodes, interpreting resistance changes detect water impact formation in real time. sensor's performance was rigorously tested wind tunnel under various temperature airflow conditions, focusing signal dependency air phase change. results demonstrate...

The study investigated the possibility of identifying speed an imagined movement from EEG recordings in amyotrophic lateral sclerosis (ALS) patients. signals were acquired four ALS patients during imagination wrist extensions at two speeds (fast and slow), each repeated up to 100 times random order. movement-related cortical potentials (MRCPs) averaged sensorimotor rhythm associated with tasks obtained recordings. Moreover, offline single-trial classification was performed discrete wavelet...

Abstract Ice formation detection is important in telecommunications and aeronautics, e.g., ice on the wings of an aircraft affects its aerodynamic performance leads to fatal accidents. While many types sensors exist, resistive for have been poorly explored. They are however attractive because their simplicity possibility install array large areas map wings. Hygroscopic ionic conductors demonstrated sensing but high resistance prevents readout sensor arrays. In this work, mixed...

The purpose of this study was to investigate the amplitude properties artifact generated on recorded surface electromyography (EMG) signals during transcutaneous electrical muscle stimulation. factors which were investigated are shape stimulation waveform, distance stimulating electrode from recording system, interelectrode detection spatial filter used for signal detection, and current amplitude. Surface EMG biceps brachii motor point with a linear adhesive array eight electrodes....

Tremor is the most prevalent movement disorder, and its incidence increasing with aging. In spite of numerous therapeutic solutions available, 65% those suffering from upper limb tremor report serious difficulties during their daily living. This gives rise to research on different treatment alternatives, amongst which wearable robots that apply selective mechanical loads constitute an appealing approach. this context, current work presents a multimodal human-robot interface drive...

We describe a new method for the estimation of muscle fiber conduction velocity (CV) from surface electromyography (EMG) signals. The is based on detection two EMG signals with different spatial filters and compensation filtering operations by temporal (with CV as unknown parameter) applied to transfer functions may have magnitudes phases, thus detected not necessarily same shape. are first spatially then temporally filtered ideally equal when value selected parameter in corresponds...

The study developed a novel multi-scale model for simulating the surface electromyogram (EMG) of an antagonistic pair muscles during pathological tremor. By combining and expanding mathematical descriptions from motor units to limb kinematics, constitutes first attempt simulate EMG individual unit activity under influence descending voluntary command, oscillatory noise in signal, afferent feedback when controlling freely moving achieve predefined angular trajectory. was adjusted various...

In the context of improving aircraft safety, this work focuses on creating and testing a graphene-based ice detection system in an environmental chamber. This research is driven by need for more accurate efficient methods, which are crucial mitigating in-flight icing hazards. The methodology employed involves flat sensors controlled environment, simulating variety climatic conditions that could be experienced during its entire flight. chamber enabled precise manipulation temperature humidity...

Intramuscular electromyography (EMG) signals are usually decomposed with semiautomatic procedures that involve the interaction an expert operator. In this paper, a Bayesian statistical model and maximum posteriori (MAP) estimator used to solve problem of multiunit EMG decomposition in fully automatic way. The MAP estimation exploits both likelihood reconstructed signal some physiological constraints, such as discharge pattern regularity refractory period muscle fibers, prior information...

An increase to above‐baseline levels of electromyography (EMG) mean power spectral frequency (MPF) has been observed previously during muscle recovery following fatiguing contractions and explained by membrane hyperpolarization due increased activation the Na + –K pump. It is hypothesized that this mechanism impaired fiber damage eccentric exercise. Thus, aim study was investigate surface EMG signal characteristics from fatigue after Ten healthy subjects performed sustained isometric knee...

This paper focus on SFIT platforms for rehabilitations and FES therapy. Two systems will be described, one developed to support patients during motor therapy, when they are still hospitalized, after discharge, at home; the other is a sleeve integrating multi-electrodes patches, designed allow therapy EMG acquisition affected by tremor. These examples prove that it possible combine fabric electrodes biomechanical textile sensors conceive where gesture recognition function can combined with...

In the context of improving aircraft safety, this study focuses on development and evaluation a graphene-based ice detection system using an environmental chamber. The research is driven by need for more accurate efficient methods, crucial in mitigating in-flight icing hazards. methodology employed involves testing flat sensors controlled environment, simulating variety climatic conditions that could be experienced during its entire flight. chamber enabled precise manipulation temperature...

ABSTRACT We introduce NeuroNella, an automated algorithm developed for the identification of neuronal activity from multichannel electrode arrays. In evaluations conducted on recordings implanted probes in nervous system rodents and primates, demonstrated remarkable accuracy, showcasing error rate less than 1% compared to ground-truth patch clamp signals. Notably, proposed handles large datasets efficiently without necessity a GPU system. The results highlighted algorithm’s efficacy...

Ice formation on aircraft surfaces poses significant safety risks, and current detection systems often struggle to provide accurate, real-time predictions. This paper presents the development comprehensive evaluation of a smart ice control system using suite machine learning models. The utilizes various sensors detect temperature anomalies signal potential formation. We trained tested supervised models (Logistic Regression, Support Vector Machine, Random Forest), unsupervised (K-Means...