In recent years, there has been major interest in the exposure to physical therapy during
rehabilitation. Several publications have demonstrated its usefulness in clinical/medical and …

Analysis of biomedical signals is a very challenging task involving implementation of various
advanced signal processing methods. This area is rapidly develo**. This paper is a Part III …

Objective Local field potential (LFP) recordings from deep brain stimulation (DBS)
electrodes are often contaminated with electrocardiographic (ECG) artifacts that hinder the …

Transcutaneous electromyography (tc-EMG) has been used to measure the electrical activity
of respiratory muscles during inspiration in various studies. Processing the raw tc-EMG …

Electromyographic (EMG) measurements of the respiratory muscles provide a convenient
and noninvasive way to assess respiratory muscle function and detect patient activity during …

Sensing-enabled neurostimulators are an advanced technology for chronic observation of
brain activities, and show great potential for closed-loop neuromodulation and as …

Motion artifact removal (MR) is one of the essential issues in processing raw ECG signals
since it could not be simply solved by using classic filtering. In this paper, a QRS detection …

Objective. Brain–Computer Interfaces targeting post-stroke recovery of the upper limb
employ mainly electroencephalography to decode movement-related brain activation …

Electromyograms (EMG signals) may be contaminated by electrocardiographic (ECG)
signals that cannot be easily separated with traditional filters, because both signals have …

A new algorithm based on singular value decomposition (SVD) to remove cardiac
contamination from trunk electromyography (EMG) is proposed. Its performance is compared …