Thesis - Instituto de Telecomunicações

28 CHAPTER 2. STATE OF THE ARTreported with 2% of FAR and 14% of FRR.In [11] the authors extract a different set of features from the eye gaze behavior, suchas the pupil size dynamics. They obtain very low performances in a group of 12 subjects,obtaining classification results with 40% of error, but stating that these features have someinformation related to the user.Advantages and disadvantages The proposed systems lack, at the current researchstage, good performance to be usable as a standalone biometric system. Nevertheless themethod described has gained some interest, given that at least one patent is known concerningthis biometric trait [140].The necessary hardware already exists in some of the regular computer systems or insome image based biometric systems. We also state that the physiologic characteristics thatexist in the non-voluntary control of the eye are complex and difficult to mimic. The systemis easy to extend to a continuous verification mode. Meanwhile more evidence should becollected and presented to understand the real value of the technique and its capacity toscale to larger populations. Some usability questions are yet to be addressed, such as thetolerance to changes in the lighting and the robustness of the system to subjects wearingglasses.2.3.7 HeartOne of the most vital organs of our body has been extensively studied to detect its normaland abnormal behavior. The ECG signal was one of the early physiological signals measuredelectrically. Recently the electrical signal coming from the heart neural enervation has beenused to identify the user [109]. In [17], 20 persons were submitted to a 12 leads ECGrecording where signal processing and classification provided a 5% error rate even usingonly one of the electrodes.In [215, 214] the authors studied 20 subjects and provided an algorithm that correctlyclassified all the subjects using only one ECG lead.We address this trait in the present work by searching for individual features [220, 219],in a case study of 27 users. Preliminary results were based on a feature selection approachon data from a mean heart beat collected as a one-lead ECG. The results using 90 seconds