Forearm surface EMG signals recognition and muscoloskeletal system dynamics identification using intelligent computational methods

Biosignals processing, Biological Nonlinear and time-varying systems identification, Electomyograph signals recognition, Pattern classification, Fuzzy logic and neural networks methods

Prediction of difficult intubation with advanced face recognition techniques: a preliminary study

Introduction: Difficult tracheal intubation remains a constant and significant source of morbidity and mortality in anaesthetic practice. Insufficient airway assessment in the preoperative period continues to be a major cause of unanticipated difficult intubation. Although many risk factors have already been identified, preoperative airway evaluation is not always regarded as a standard procedure and the respective weight of each risk factor remains unclear. Moreover the predictive scores available are not sensitive, moderately specific and often operator-dependant. In order to improve the preoperative detection of patients at risk for difficult intubation, we developed a system for automated and objective evaluation of morphologic criteria of the face and neck using video recordings and advanced techniques borrowed from face recognition. Method and results: Frontal video sequences were recorded in 5 healthy volunteers. During the video recording, subjects were requested to perform maximal flexion-extension of the neck and to open wide the mouth with tongue pulled out. A robust and real-time face tracking system was then applied, allowing to automatically identify and map a grid of 55 control points on the face, which were tracked during head motion. These points located important features of the face, such as the eyebrows, the nose, the contours of the eyes and mouth, and the external contours, including the chin. Moreover, based on this face tracking, the orientation of the head could also be estimated at each frame of the video sequence. Thus, we could infer for each frame the pitch angle of the head pose (related to the vertical rotation of the head) and obtain the degree of head extension. Morphological criteria used in the most frequent cited predictive scores were also extracted, such as mouth opening, degree of visibility of the uvula or thyreo-mental distance. Discussion and conclusion: Preliminary results suggest the high feasibility of the technique. The next step will be the application of the same automated and objective evaluation to patients who will undergo tracheal intubation. The difficulties related to intubation will be then correlated to the biometric characteristics of the patients. The objective in mind is to analyze the biometrics data with artificial intelligence algorithms to build a highly sensitive and specific predictive test.

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

A genotypic mutation system measuring mutations in restriction recognition sequences.

The RFLP/PCR approach (restriction fragment length polymorphism/polymerase chain reaction) to genotypic mutation analysis described here measures mutations in restriction recognition sequences. Wild-type DNA is restricted before the resistant, mutated sequences are amplified by PCR and cloned. We tested the capacity of this experimental design to isolate a few copies of a mutated sequence of the human c-Ha-ras1 gene from a large excess of wild-type DNA. For this purpose we constructed a 272 bp fragment with 2 mutations in the PvuII recognition sequence 1727-1732 and studied the rescue by RFLP/PCR of a few copies of this 'PvuII mutant standard'. Following amplification with Taq-polymerase and cloning into lambda gt10, plaques containing wild-type sequence, PvuII mutant standard or Taq-polymerase induced bp changes were quantitated by hybridization with specific oligonucleotide probes. Our results indicate that 10 PvuII mutant standard copies can be rescued from 10(8) to 10(9) wild-type sequences. Taq polymerase errors originating from unrestricted, residual wild-type DNA were sequence dependent and consisted mostly of transversions originating at G.C bp. In contrast to a doubly mutated 'standard' the capacity to rescue single bp mutations by RFLP/PCR is limited by Taq-polymerase errors. Therefore, we assessed the capacity of our protocol to isolate a G to T transversion mutation at base pair 1698 of the MspI-site 1695-1698 of the c-Ha-ras1 gene from excess wild-type ras1 DNA. We found that 100 copies of the mutated ras1 fragment could be readily rescued from 10(8) copies of wild-type DNA.

A Writer Identification System For Handwritten Malayalam Documents

Handwriting is an acquired tool used for communication of one's observations or feelings. Factors that inuence a person's handwriting not only dependent on the individual's bio-mechanical constraints, handwriting education received, writing instrument, type of paper, background, but also factors like stress, motivation and the purpose of the handwriting. Despite the high variation in a person's handwriting, recent results from different writer identification studies have shown that it possesses sufficient individual traits to be used as an identification method. Handwriting as a behavioral biometric has had the interest of researchers for a long time. But recently it has been enjoying new interest due to an increased need and effort to deal with problems ranging from white-collar crime to terrorist threats. The identification of the writer based on a piece of handwriting is a challenging task for pattern recognition. The main objective of this thesis is to develop a text independent writer identification system for Malayalam Handwriting. The study also extends to developing a framework for online character recognition of Grantha script and Malayalam characters

The Koundoum sheep breed in Niger: morpho-biometric study and description of the production system

The diffusion of highly productive breeds across developing countries goes along with a neglect of indigenous breeds, which are well suited to their environment but often show low yields. Thus, in Niger, the flock of Koundoum sheep are rapidly decreasing. The Koundoum is one of the few wool sheep breeds of Africa and shows important adaptive feature to its native environment, i.e. the humid pastures on the banks of the Niger River. To characterise the breed and to understand its production context, a survey has been conducted in 104 herds in four communes along the Niger River (Kollo, Tillabery, Say and Tera). Nine body measurements, including live weight, were taken on 180 adult sheep (101 females and 79 males). The herds varied from 2 to 60 heads, with a median size of eight animals and two thirds of the herds having less than 10 animals. Mainly fed on natural pastures, 85.6% of the herds received crop residues. Only natural mating was practiced. Veterinary care was restricted to anti-helminthic and some indigenous treatments. The frequent affiliation of breeders to professional unions appeared as favourable to the implementation of a collective conservation program. The Koundoum sheep were white or black coated, with the black colour being most frequent (75.6%). Wattles were present in both sexes at similar frequencies of around 14%. All biometric variables were significantly and positively correlated between them. The thoracic perimeter showed the best correlation with live weight in both males and females. Three variables were selected for live weight prediction: thoracic perimeter, height at withers and rump length. From the present study, it is expected that the in situ conservation of the Koundoum sheep will be highly problematic, due to lack of market opportunities for wool and the willingness of smallholders to get involved in pure Koundoum rearing.

A video-based biometric authentication for e-learning web applications

In the last years there was an exponential growth in the offering of Web-enabled distance courses and in the number of enrolments in corporate and higher education using this modality. However, the lack of efficient mechanisms that assures user authentication in this sort of environment, in the system login as well as throughout his session, has been pointed out as a serious deficiency. Some studies have been led about possible biometric applications for web authentication. However, password based authentication still prevails. With the popularization of biometric enabled devices and resultant fall of prices for the collection of biometric traits, biometrics is reconsidered as a secure remote authentication form for web applications. In this work, the face recognition accuracy, captured on-line by a webcam in Internet environment, is investigated, simulating the natural interaction of a person in the context of a distance course environment. Partial results show that this technique can be successfully applied to confirm the presence of users throughout the course attendance in an educational distance course. An efficient client/server architecture is also proposed. © 2009 Springer Berlin Heidelberg.

Enhancing Activity Recognition by Fusing Inertial and Biometric Information

Activity recognition is an active research field nowadays, as it enables the development of highly adaptive applications, e.g. in the field of personal health. In this paper, a light high-level fusion algorithm to detect the activity that an individual is performing is presented. The algorithm relies on data gathered from accelerometers placed on different parts of the body, and on biometric sensors. Inertial sensors allow detecting activity by analyzing signal features such as amplitude or peaks. In addition, there is a relationship between the activity intensity and biometric response, which can be considered together with acceleration data to improve the accuracy of activity detection. The proposed algorithm is designed to work with minimum computational cost, being ready to run in a mobile device as part of a context-aware application. In order to enable different user scenarios, the algorithm offers best-effort activity estimation: its quality of estimation depends on the position and number of the available inertial sensors, and also on the presence of biometric information.

Quantitative assessment of enzyme specificity in vivo: P2 recognition by Kex2 protease defined in a genetic system

The specificity of the yeast proprotein-processing Kex2 protease was examined in vivo by using a sensitive, quantitative assay. A truncated prepro-α-factor gene encoding an α-factor precursor with a single α-factor repeat was constructed with restriction sites for cassette mutagenesis flanking the single Kex2 cleavage site (-SLDKR↓EAEA-). All of the 19 substitutions for the Lys (P2) residue in the cleavage site were made. The wild-type and mutant precursors were expressed in a yeast strain lacking the chromosomal genes encoding Kex2 and prepro-α-factor. Cleavage of the 20 sites by Kex2, expressed at the wild-type level, was assessed by using a quantitative-mating assay with an effective range greater than six orders of magnitude. All substitutions for Lys at P2 decreased mating, from 2-fold for Arg to >106-fold for Trp. Eviction of the Kex2-encoding plasmid indicated that cleavage of mutant sites by other cellular proteases was not a complicating factor. Mating efficiencies of strains expressing the mutant precursors correlated well with the specificity (kcat/KM) of purified Kex2 for comparable model peptide substrates, validating the in vivo approach as a quantitative method. The results support the conclusion that KM, which is heavily influenced by the nature of the P2 residue, is a major determinant of cleavage efficiency in vivo. P2 preference followed the rank order: Lys > Arg > Thr > Pro > Glu > Ile > Ser > Ala > Asn > Val > Cys > AsP > Gln > Gly > His > Met > Leu > Tyr > Phe > Trp.