In this paper the need for employing a data reduction algorithm in using digital graphic systems to display biomedical signals is firstly addressed and then, some such algorithms are compared from different points of view (such as complexity, real time feasibility, etc.). Subsequently, it is concluded that Turning Point algorithm can be a suitable one for real time implementation on a microproc...

background: this paper proposes a new emotional stress assessment system using multi-modal bio-signals. electroencephalogram (eeg) is the reflection of brain activity and is widely used in clinical diagnosis and biomedical research. methods: we design an efficient acquisition protocol to acquire the eeg signals in five channels (fp1, fp2, t3, t4 and pz) and peripheral signals such as blood volu...

Previous work in biomedical signal processing area, especially in the area of cardiology indicates that most of the disorders in heart can be completely captured in an Electrocardiogram (ECG) signal and then can be classified using a classifying tool. A pulse signal (Nadi, in Ayurvedic terms) can also extract similar disorders along with the arterial blockages in the body. Similar methodology, ...

Introduction In order to improve the quality of life of amputees, biomechatronic researchers and biomedical engineers have been trying to use a combination of various techniques to provide suitable rehabilitation systems. Diverse biomedical signals, acquired from a specialized organ or cell system, e.g., the nervous system, are the driving force for the whole system. Electromyography(EMG), as a...

Abstract A wide range of signs are acquired from the human body called biomedical or biosignals, and they can be at cell level, organ sub-atomic level. Electroencephalogram is electrical activity cerebrum, electrocardiogram heart, action muscle sound signals referred to as electromyogram, electroretinogram eye, so on. Studying these helpful for doctors, it help them examine predict cure many di...