A portable fetal heart monitor and its adaption to the detection of certain prenatal abnormalities

There were three primary objectives for this task: (1) The investigation of the feasibility of making the fetal heart rate monitor portable, using a laptop computer; (2) Improvements in the signal processing for the monitor; and (3) Implementation of a real-time hardware software system. These tasks have been completed as discussed in the following section

Towards an Automated Screening Tool for Pediatric Speech Delay

Speech delay is a childhood language problem that sometimes is resolved on its own but sometimes may cause more serious language difficulties later. This leads therapists to screen children for detection at early ages in order to eliminate future problems. Using the Goldman-Fristoe Test of Articulation (GFTA) method, therapists listen to a child\u27s pronunciation of certain phonemes and phoneme pairs in specified words and judge the child\u27s stage of speech development. The goal of this paper is to develop an Automatic Speech Recognition (ASR) tool and related speech processing methods which emulate the knowledge of speech therapists. In this paper two methods of feature extraction (MFCC and DCTC) were used as the baseline for training an HMM-based utterance verification system which was later used for testing the utterances of 63 young children (ages 4-10), both typically developed and speech delayed. The ASR results show the value of augmenting static spectral information with spectral trajectory information for better prediction of therapist\u27s judgments

A new robust algorithm for isolated word endpoint detection

Teager Energy and Energy-Entropy Features are two approaches, which have recently been used for locating the endpoints of an utterance. However, each of them has some drawbacks for speech in noisy environments. This paper proposes a novel method to combine these two approaches to locate endpoint intervals and yet make a final decision based on energy, which requires far less time than the feature based methods. After the algorithm description, an experimental evaluation is presented, comparing the automatically determined endpoints with those determined by skilled personnel. It is shown that the accuracy of this algorithm is quite satisfactory and acceptable

Passive fetal heart rate monitoring apparatus and method with enhanced fetal heart beat discrimination

An apparatus for acquiring signals emitted by a fetus, identifying fetal heart beats and determining a fetal heart rate. Multiple sensor signals are outputted by a passive fetal heart rate monitoring sensor. Multiple parallel nonlinear filters filter these multiple sensor signals to identify fetal heart beats in the signal data. A processor determines a fetal heart rate based on these identified fetal heart beats. The processor includes the use of a figure of merit weighting of heart rate estimates based on the identified heart beats from each filter for each signal. The fetal heart rate thus determined is outputted to a display, storage, or communications channel. A method for enhanced fetal heart beat discrimination includes acquiring signals from a fetus, identifying fetal heart beats from the signals by multiple parallel nonlinear filtering, and determining a fetal heart rate based on the identified fetal heart beats. A figure of merit operation in this method provides for weighting a plurality of fetal heart rate estimates based on the identified fetal heart beats and selecting the highest ranking fetal heart rate estimate

Speech Processing Approach for Diagnosing Dementia in an Early Stage

The clinical diagnosis of Alzheimer’s disease and other dementias is very challenging, especially in the early stages. Our hypothesis is that any disease that affects particular brain regions involved in speech production and processing will also leave detectable finger prints in the speech. Computerized analysis of speech signals and computational linguistics have progressed to the point where an automatic speech analysis system is a promising approach for a low-cost non-invasive diagnostic tool for early detection of Alzheimer’s disease.We present empirical evidence that strong discrimination between subjects with a diagnosis of probable Alzheimer’s versus matched normal controls can be achieved with a combination of acoustic features from speech, linguistic features extracted from an automatically determined transcription of the speech including punctuation, and results of a mini mental state exam (MMSE). We also show that discrimination is nearly as strong even if the MMSE is not used, which implies that a fully automated system is feasible. Since commercial automatic speech recognition (ASR) tools were unable to provide transcripts for about half of our speech samples, a customized ASR system was developed

Passive fetal heart rate monitoring apparatus and method with enhanced fetal heart beat discrimination

An apparatus for acquiring signals emitted by a fetus, identifying fetal heart beats and determining a fetal heart rate is presented. Multiple sensor signals are outputted by a passive fetal heart rate monitoring sensor. Multiple parallel nonlinear filters filter these multiple sensor signals to identify fetal heart beats in the signal data. A processor determines a fetal heart rate based on these identified fetal heart beats. The processor includes the use of a figure of merit weighting of heart rate estimates based on the identified heart beats from each filter for each signal. The fetal heart rate thus determined is outputted to a display, storage, or communications channel. A method for enhanced fetal heart beat discrimination includes acquiring signals from a fetus, identifying fetal heart beats from the signals by multiple parallel nonlinear filtering, and determining a fetal heart rate based on the identified fetal heart beats. A figure of merit operation in this method provides for weighting a plurality of fetal heart rate estimates based on the identified fetal heart beats and selecting the highest ranking fetal heart rate estimate

Personal Computer Software Vowel Training Aid for lhe Hearing Impaired”,

ABSTRACT A vowel training aid system for hearing impaired persons which uses a Windows-based multimedia computer has been developed. The system provides two main displays which give visual feedback for vowels spoken in isolation and short word contexts. Feature extraction methods and neural network processing techniques provide a high degree of accuracy for speaker independent vowel training. The system typically provides correct classification of over 85% of steady state vowels spoken by adult male, adult female and child (both genders combined) speakers. Similar classification accuracy is also observed for vowels spoken in short words. Low cost and good performance make this system potentially useful for speech training at home

Knowledge Maps for Intelligent Questioning Systems in Engineering Education

The development of a hierarchical knowledge map with an intelligent questioning system to improve the educational process in engineering courses is discussed. Knowledge map represents the architecture of the entire curriculum and each course as an interconnection of modules. The knowledge system provides the necessary framework to allow a questioning system to select appropriate questions. It will also give immediate feedback and assistance to the student for improving the delays with classical assessment

An Instrument for Assessing Knowledge Gain in a First Course in Circuit Theory

Although there has been considerable research on the development and use of assessment instruments to measure the effectiveness of various pedagogical approaches to teaching introductory physics classes (Hestenes et al. 1, Hestenes et al 2, Hake 3, Saul et al. 4) and other science courses (for example, see Vosniadou 5), there is relatively little similar work that has been done to develop assessment instruments for the first circuit theory course that is taught in electrical and computer engineering. Given the large numbers of students nationwide who take such a course, the challenge this course presents to beginning engineering students, and the introduction of new approaches to teach this material, an instrument similar to those available for physics is needed to identify student misconceptions at the beginning of the class and to measure the normalized learning gain at the end of the class (Hake 3). These gains and other metrics can then be used to compare the effect of different teaching methods. In addition, this same instrument or portions of it can be offered at later times in the curriculum to measure retention and reinforcement from other courses. This concept-based testing approach is useful to examine the overall effectiveness of the circuit component of a curriculum and could thus be used as part of the continuous self-improvement process required under the ABET 2000 rules