Related papers: A Weak Monotonicity Based Muscle Fatigue Detection…
We present a hybrid brain-machine interface (BMI) that integrates steady-state visually evoked potential (SSVEP)-based EEG and facial EMG to improve multimodal control and mitigate fatigue in assistive applications. Traditional BMIs relying…
In sensitive scenarios, such as meetings, negotiations, and team sports, messages must be conveyed without detection by non-collaborators. Previous methods, such as encrypting messages, eye contact, and micro-gestures, had problems with…
We consider the extent to which we can learn from a completely randomized experiment whether all individuals have treatment effects that are weakly of the same sign, a condition we call monotonicity. From a classical sampling perspective,…
This paper studies the problem of testing whether a function is monotone from a nonparametric Bayesian perspective. Two new families of tests are constructed. The first uses constrained smoothing splines, together with a hierarchical…
Hands are used for communicating with the surrounding environment and have a complex structure that enables them to perform various tasks with their multiple degrees of freedom. Hand amputation can prevent a person from performing their…
Using shear wave elastography, we measure the changes in the wave speed with the stress produced by a striated muscle during isometric voluntary contraction. To isolate the behaviour of an individual muscle from complementary or…
This paper describes method for detecting the early signs of fatigue in train drivers. As soon as the train driver is falling in symptoms of fatigue immediate message will be transfer to the control room indicating the status of the…
Upper limb based neuromuscular interfaces aim to provide a seamless way for humans to interact with technology. Among noninvasive interfaces, surface electromyogram (EMG) signals hold significant promise. However, their sensitivity to…
This study investigates the application of surface-enhanced Raman spectroscopy (SERS) as a diagnostic tool for myasthenia gravis, a severe neuromuscular disorder characterized by muscle weakness and fatigue. Blood serum samples were…
Analysing electrocardiograms (ECGs) is an inexpensive and non-invasive, yet powerful way to diagnose heart disease. ECG studies using Machine Learning to automatically detect abnormal heartbeats so far depend on large, manually annotated…
sEMG pattern recognition algorithms have been explored extensively in decoding movement intent, yet are known to be vulnerable to changing recording conditions, exhibiting significant drops in performance across subjects, and even across…
In universal environment, a patient-friendly inexpensive method is needed to realize the early diagnosis of depression, which is believed to be an effective way to reduce the mortality of depression. The purpose of this study is only to…
Epilepsy is a well-known neuronal disorder that can be identified by interpretation of the electroencephalogram (EEG) signal. Usually, the length of an EEG signal is quite long which is challenging to interpret manually. In this work, we…
The Electromyography (EMG) signal is the electrical activity produced by cells of skeletal muscles in order to provide a movement. The non-invasive prosthetic hand works with several electrodes, placed on the stump of an amputee, that…
Introduction. Low-cost health monitoring devices are increasingly being used for mental health related studies including stress. While cortisol response magnitude remains the gold standard indicator for stress assessment, a growing number…
Sleep abnormalities can have severe health consequences. Automated sleep staging, i.e. labelling the sequence of sleep stages from the patient's physiological recordings, could simplify the diagnostic process. Previous work on automated…
Identifying stress levels can provide valuable data for mental health analytics as well as labels for annotation systems. Although much research has been conducted into stress detection models using heart rate variability at a higher cost…
Mental fatigue related behavioral performance decline precipitates catastrophic accidents in sustained attention tasks. While existing neurophysiological systems effectively detect current behavioral performance, they often lack the…
Surface electromyography (sEMG) is a widely employed bio-signal that captures human muscle activity via electrodes placed on the skin. Several studies have proposed methods to remove sEMG contaminants, as non-invasive measurements render…
Seizure onset detection in electroencephalography (EEG) signals is a challenging task due to the non-stereotyped seizure activities as well as their stochastic and non-stationary characteristics in nature. Joint spectral-temporal features…