13,565 research outputs found

    Neural coding of high-frequency tones

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    Available evidence was presented indicating that neural discharges in the auditory nerve display characteristic periodicities in response to any tonal stimulus including high-frequency stimuli, and that this periodicity corresponds to the subjective pitch

    The role of motion analysis in elite soccer

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    The optimal physical preparation of elite soccer (association football) players has become an indispensable part of the professional game especially due to the increased physical demands of match-play. The monitoring of players’ work-rate profiles during competition is now feasible through computer-aided motion analysis. Traditional methods of motion analysis were extremely labour intensive and were largely restricted to university- based research projects. Recent technological developments have meant that sophisticated systems, capable of quickly recording and processing the data of all players’ physical contributions throughout an entire match, are now being used in elite club environments. In recognition of the important role motion analysis now plays as a tool for measuring the physical performance of soccer players, this review critically appraises various motion analysis methods currently employed in elite soccer and explores research conducted using these methods. This review therefore aims to increase the awareness of both practitioners and researchers of the various motion analysis systems available, identify practical implications of the established body of knowledge, while highlighting areas that require further exploration

    Extraction of vocal-tract system characteristics from speechsignals

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    We propose methods to track natural variations in the characteristics of the vocal-tract system from speech signals. We are especially interested in the cases where these characteristics vary over time, as happens in dynamic sounds such as consonant-vowel transitions. We show that the selection of appropriate analysis segments is crucial in these methods, and we propose a selection based on estimated instants of significant excitation. These instants are obtained by a method based on the average group-delay property of minimum-phase signals. In voiced speech, they correspond to the instants of glottal closure. The vocal-tract system is characterized by its formant parameters, which are extracted from the analysis segments. Because the segments are always at the same relative position in each pitch period, in voiced speech the extracted formants are consistent across successive pitch periods. We demonstrate the results of the analysis for several difficult cases of speech signals

    Uses of the pitch-scaled harmonic filter in speech processing

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    The pitch-scaled harmonic filter (PSHF) is a technique for decomposing speech signals into their periodic and aperiodic constituents, during periods of phonation. In this paper, the use of the PSHF for speech analysis and processing tasks is described. The periodic component can be used as an estimate of the part attributable to voicing, and the aperiodic component can act as an estimate of that attributable to turbulence noise, i.e., from fricative, aspiration and plosive sources. Here we present the algorithm for separating the periodic and aperiodic components from the pitch-scaled Fourier transform of a short section of speech, and show how to derive signals suitable for time-series analysis and for spectral analysis. These components can then be processed in a manner appropriate to their source type, for instance, extracting zeros as well as poles from the aperiodic spectral envelope. A summary of tests on synthetic speech-like signals demonstrates the robustness of the PSHF's performance to perturbations from additive noise, jitter and shimmer. Examples are given of speech analysed in various ways: power spectrum, short-time power and short-time harmonics-to-noise ratio, linear prediction and mel-frequency cepstral coefficients. Besides being valuable for speech production and perception studies, the latter two analyses show potential for incorporation into speech coding and speech recognition systems. Further uses of the PSHF are revealing normally-obscured acoustic features, exploring interactions of turbulence-noise sources with voicing, and pre-processing speech to enhance subsequent operations

    Acoustic cues to tonal contrasts in Mandarin: Implications for cochlear implants

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    The present study systematically manipulated three acoustic cues-fundamental frequency (f0), amplitude envelope, and duration-to investigate their contributions to tonal contrasts in Mandarin. Simplified stimuli with all possible combinations of these three cues were presented for identification to eight normal-hearing listeners, all native speakers of Mandarin from Taiwan. The f0 information was conveyed either by an f0-controlled sawtooth carrier or a modulated noise so as to compare the performance achievable by a clear indication of voice f0 and what is possible with purely temporal coding of f0. Tone recognition performance with explicit f0 was much better than that with any combination of other acoustic cues (consistently greater than 90% correct compared to 33%-65%; chance is 25%). In the absence of explicit f0, the temporal coding of f0 and amplitude envelope both contributed somewhat to tone recognition, while duration had only a marginal effect. Performance based on these secondary cues varied greatly across listeners. These results explain the relatively poor perception of tone in cochlear implant users, given that cochlear implants currently provide only weak cues to f0, so that users must rely upon the purely temporal (and secondary) features for the perception of tone. (c) 2008 Acoustical Society of America

    Fog Computing in Medical Internet-of-Things: Architecture, Implementation, and Applications

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    In the era when the market segment of Internet of Things (IoT) tops the chart in various business reports, it is apparently envisioned that the field of medicine expects to gain a large benefit from the explosion of wearables and internet-connected sensors that surround us to acquire and communicate unprecedented data on symptoms, medication, food intake, and daily-life activities impacting one's health and wellness. However, IoT-driven healthcare would have to overcome many barriers, such as: 1) There is an increasing demand for data storage on cloud servers where the analysis of the medical big data becomes increasingly complex, 2) The data, when communicated, are vulnerable to security and privacy issues, 3) The communication of the continuously collected data is not only costly but also energy hungry, 4) Operating and maintaining the sensors directly from the cloud servers are non-trial tasks. This book chapter defined Fog Computing in the context of medical IoT. Conceptually, Fog Computing is a service-oriented intermediate layer in IoT, providing the interfaces between the sensors and cloud servers for facilitating connectivity, data transfer, and queryable local database. The centerpiece of Fog computing is a low-power, intelligent, wireless, embedded computing node that carries out signal conditioning and data analytics on raw data collected from wearables or other medical sensors and offers efficient means to serve telehealth interventions. We implemented and tested an fog computing system using the Intel Edison and Raspberry Pi that allows acquisition, computing, storage and communication of the various medical data such as pathological speech data of individuals with speech disorders, Phonocardiogram (PCG) signal for heart rate estimation, and Electrocardiogram (ECG)-based Q, R, S detection.Comment: 29 pages, 30 figures, 5 tables. Keywords: Big Data, Body Area Network, Body Sensor Network, Edge Computing, Fog Computing, Medical Cyberphysical Systems, Medical Internet-of-Things, Telecare, Tele-treatment, Wearable Devices, Chapter in Handbook of Large-Scale Distributed Computing in Smart Healthcare (2017), Springe

    Direct observation of a "devil's staircase'' in wave-particle interaction

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    We report the experimental observation of a "devil's staircase'' in a time dependent system considered as a paradigm for the transition to large scale chaos in the universality class of hamiltonian systems. A test electron beam is used to observe its non-self-consistent interaction with externally excited wave(s) in a Travelling Wave Tube (TWT). A trochoidal energy analyzer records the beam energy distribution at the output of the interaction line. An arbitrary waveform generator is used to launch a prescribed spectrum of waves along the slow wave structure (a 4 m long helix) of the TWT. The resonant velocity domain associated to a single wave is observed, as well as the transition to large scale chaos when the resonant domains of two waves and their secondary resonances overlap. This transition exhibits a "devil's staircase'' behavior for increasing excitation amplitude, due to the nonlinear forcing by the second wave on the pendulum-like motion of a charged particle in one electrostatic wave.Comment: remplacement des figures 7, 8, 9 par rapport au premier depo

    Objective dysphonia quantification in vocal fold paralysis: comparing nonlinear with classical measures

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    Clinical acoustic voice recording analysis is usually performed using classical perturbation measures including jitter, shimmer and noise-to-harmonic ratios. However, restrictive mathematical limitations of these measures prevent analysis for severely dysphonic voices. Previous studies of alternative nonlinear random measures addressed wide varieties of vocal pathologies. Here, we analyze a single vocal pathology cohort, testing the performance of these alternative measures alongside classical measures.

We present voice analysis pre- and post-operatively in unilateral vocal fold paralysis (UVFP) patients and healthy controls, patients undergoing standard medialisation thyroplasty surgery, using jitter, shimmer and noise-to-harmonic ratio (NHR), and nonlinear recurrence period density entropy (RPDE), detrended fluctuation analysis (DFA) and correlation dimension. Systematizing the preparative editing of the recordings, we found that the novel measures were more stable and hence reliable, than the classical measures, on healthy controls.

RPDE and jitter are sensitive to improvements pre- to post-operation. Shimmer, NHR and DFA showed no significant change (p > 0.05). All measures detect statistically significant and clinically important differences between controls and patients, both treated and untreated (p < 0.001, AUC > 0.7). Pre- to post-operation, GRBAS ratings show statistically significant and clinically important improvement in overall dysphonia grade (G) (AUC = 0.946, p < 0.001).

Re-calculating AUCs from other study data, we compare these results in terms of clinical importance. We conclude that, when preparative editing is systematized, nonlinear random measures may be useful UVFP treatment effectiveness monitoring tools, and there may be applications for other forms of dysphonia.
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