**8. References**


308 Real-Time Systems, Architecture, Scheduling, and Application

Aim of this chapter was to merge the well-assessed design procedure of RF exposure systems (Kuster & Schönborn, 2000; Paffi et al., 2010) with the requirements emerging from real-time investigations, thus providing a reference work on this segment of knowledge.

The exposure system, defined as the complex structure used for allocating the biological samples (cell cultures for the *in vitro* experiments, animals for the *in vivo* ones) during the exposure phase of a biological experiment, is a fundamental device in the whole experimental setup. Indeed, a well-designed and characterized exposure system is a prerequisite for obtaining reproducible and scientifically meaningful results useful in the process of health risk assessment. Therefore, moving from the analysis of both biological and EM requirements (Kuster et al., 2000), a standardized procedure for the design of the

Due to the great variety of biological protocols and exposure parameters (dose, duration, frequency and waveform of the EM signal), different exposure systems can be found in the literature, based on radiating (antennas), propagating (waveguides), and resonant (resonant cavities) structures. From an accurate review of them, it emerges that real-time systems, in almost all cases, were designed for *in vitro* investigations on the electrophysiological activity of excitable cells. Such systems generally require modifications of standard RF structures to allow the continuous monitoring of the sample while avoiding RF coupling and interference with the recording apparatus (Paffi et al., 2010). Different solutions can be found in the literature, almost all based on propagating structures. They are mostly open planar structures or semi-open and closed structures modified with holes to allow the access to the sample for the data acquisition. The proposed systems, tailored for the particular biological endpoint and protocol, often result from the trade-off between the two conflicting requirements: the easy access to the sample and the avoidance of interference with the laboratory equipment. Therefore, in these cases, guidelines to design the optimal and most

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**0**

**15**

*Poland*

**Real–Time Low–Latency Estimation of the**

Electrooculography biosignals (EOG) are very important for the eye orientation and eyelid movements (blinking) estimation. There are many applications of the EOG signals. Most important applications are related to the medical applications [Duchowski (2007)]. The EOG signal is used for the analysis of eye movement in the selected medical test of the eye related health problems. It is also important for the sleep analysis. The EOG signal has much higher level than the important EEG (electroencephalography) signals and should be removed from the EEG measurements [Duchowski (2007); Shayegh & Erfanian (2006)]. The reduction of the EOG artifacts from EEG is considered by many researchers and it is also important for the

The EOG and blinking signals are used in Human–Computer Interfaces in: the ergonomics, the advertisement analysis [Poole & Ball (2005)], the human–computer interaction (HCI) systems (e.g. a virtual keyboard [Usakli at al. (2010)], the vehicle control [Barea et al. (2002); Firoozabadi (2008)], the wearable computers [Bulling et al. (2009)]), and the video compression

Many alternative oculography techniques are available. The applications of the EOG signals for the HCI applications should be considered as one of the available techniques. The most important disadvantage is the long–time stability of the measurements and the influences of the other factors like light sources. The video–oculography (VOG) is interesting alternative, but the long–time influence of the infrared illuminators usually used on the eye has not been well tested. The infrared oculography (IROG) applies a small set of the illuminators (IR LEDs)

The recent application of the EOG signal is the computer animation. The estimated orientation and blinking signals are used for the control of eye and eyelid of the human–generated avatar [Deng et al. (2008)]. This is specific for the motion capture technique [Duchowski (2007); Krupi ´nski & Mazurek (2009)] that, for instance, was used successfully in Beowulf movie [Sony et al. (2006); Warner Brothers (2008)]. Such a motion capture technique is alternative to the

A measured biosignal has two important subsignals: electrooculography and blinking. Both of them should be separated and the interesting parameters should be estimated. The

practical applications of the EEG–based Human–Computer Interfaces.

driven by eye–interest [Khan & Komogortsev (2004)].

and IR sensors for the estimation of eye movements.

video–based motion capture systems fixed to the human head.

**1. Introduction**

**Blinking and EOG Signals**

Robert Krupi ´nski and Przemysław Mazurek

*West Pomeranian University of Technology, Szczecin*

*Department of Signal Processing and Multimedia Engineering*

