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This work proposes a Common Spatial Pattern with Polarity Check (CSPPC) to facilitate Movement Related Cortical Potential (MRCP) detection. The algorithm was compared with the Locality Preserving Projection (LPP) algorithm in the context of detecting foot dorsiflexion within a group of thirteen subjects. It has been shown that CSPPC achieved a significantly reduced delay latency compared to LPP (−25...
Dual tasking refers to the simultaneous execution of two tasks with different demands. In this study, we aimed to investigate the effect of a second task on a main task of motor execution and on the ability to detect the cortical potential related to the main task from non-invasive electroencephalographic (EEG). Participants were asked to perform a series of cue-based ankle dorsiflexions as the primary...
This paper presents a polynomial ridge regression algorithm with substantial improvements in computational efficiency compared with the polynomial kernel ridge regression and the standard polynomial regression. This regression algorithm was combined with a Kalman Filter (KF) to yield the Directly Weighted Polynomial Ridge Regression KF (DWPRR-KF). Experiments conducted offline from data collected...
Recently the number of people with swallowing disorders (dysphagia) is increasing. Therefore, efforts are needed to support the swallowing process of dysphagia patients. In order to assist the swallowing process, understanding the initial phase is important. As the first step of development, we analyzed muscle activities related to the initial phase of the swallowing process. In this research, muscle...
Denoising, noise or interferences are removed from recorded signal to enhance the signal-to-noise ratio (SNR), is a crucial and ubiquitous step in the procedure of signal processing, especially for neurophysiological signal. This step facilitates following processing, such as feature extraction, classification, and data analyses. Conventional methods are based on the principle of separating noise...
Recently, we proposed a musculoskeletal model to simultaneously predict motion along metacarpophalangeal (MCP) and wrist flexion/extension degrees-of-freedom (DOFs) from surface electromyography (EMG) signals. Since wrist pronation/supination is also functionally important, we extended the musculoskeletal model to simultaneously estimate wrist pronation/supination in addition to wrist and MCP flexion/extension...
In this study, we propose a novel method to explore the relationship between grip force and forearm muscle thickness during isometric contraction. One-directional ultrasound was used to detect the depth of muscle-bone interface. By tracking the movement of this interface, the change of muscle thickness can be calculated. A dynamometer was used to measure force. Three able-bodied subjects were asked...
Understanding how multiple muscles are recruited across a joint has typically been approached from relating muscle activity to resultant forces. New tools are now available to look deeper into a muscle's recruitment by observing groups of single motor units. Identifying changes in the motor unit activity both within a muscle and between muscles the redundancies in motor control can be better understood...
We assessed the impact of different motor unit action potential (MUAP) components in dynamic muscle contractions on decomposition of high-density surface electromyograms (hdEMG). In particular, hypothesis that nontravelling MUAP components, originating from the tendon regions, are less sensitive to changes in geometry of fusiform muscles than travelling MUAP components has been tested on synthetic...
This paper investigates whether the movement intent of an amputee can be detected and classified in real-time as the individual moved his/her phantom hand. We present a method to detect movement intent using neural signals from the peripheral nervous system (PNS). In addition, we classify eight types of individual hand movements using 300 ms signal segments beginning with our detected starting time...
Three muscle activation estimators: a linear mean-absolute value filter, a recursive Bayesian method, and a kurtosis filter were compared as control approaches for an abstract myoelectric-controlled interface. The linear filter outperformed both the Bayesian and kurtosis methods with respect to participants' overall scores. Despite significantly less efficient trajectories, the Bayesian filter showed...
It is of great significance to detect and predict muscle fatigue for avoiding muscle injury and the negative effects on human-machine interface. This paper presents a novel approach to obtain reliable information about muscle fatigue by analyzing surface electromyography (sEMG) and near-infrared spectroscopy (NIRS) simultaneously. Muscle fatigue was induced via sustained isometric contraction at 50%...
To effectively restore the fine motor functions of the forearm and hand of stroke survivors and patients with traumatic brain injury (TBI), recent studies have proposed an active rehabilitation concept based on the pattern recognition of electromyography (EMG) signals to decode the motor intent of the patients. The results from these studies suggested that pattern recognition of EMG signals associated...
This study sought to investigate two-electrode montages for the application of anodal transcranial direct current stimulation (atDCS) over ipsilateral cerebellar hemisphere during visuomotor learning of myoelectric visual pursuit using electromyogram (EMG) from gastrocnemius (GAS) muscle. The atDCS montages were selected based on computational modeling to target electric field strength at the anterior...
The corticospinal tract (CST) is one of the descending tracts that carry the forelimb volitional information. Using flexible multi-electrode arrays (MEAs), the CST signals were recorded in rats during active and resting states. The power spectral density (PSD) of CST signals during the active state were notably higher than those observed during resting or anesthesia. Average inter-channel coherences...
Active lower limb exoskeletons can provide assistance to the lower extremities and may drastically improve the walking abilities of millions of individuals with gait impairments. However, most currently available control systems for these devices cannot predict the user's intended movements and have yet to enable walking with seamless transitions. Recent developments in intent recognition for active...
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