arXiv subjects

Jorge

Publications and source records attributed to Jorge.

3 recordsLinked to original sources

arXiv2023

Sparse electrophysiological source imaging predicts aging-related gait speed slowing

Objective: We seek stable Electrophysiological Source Imaging (ESI) biomarkers associated with Gait Speed (GS) as a measure of functional decline. Towards this end we determine the predictive value of ESI activation and connectivity patterns of resting-state EEG Theta rhythm on physical performance decline measured by a slowing GS in aging individuals. Methods: As potential biomarkers related to GS changes, we estimate ESI using flexible sparse/smooth/non-negative models (NN-SLASSO), from which activation ESI (aESI) and connectivity ESI (cESI) features are selected using the Stable Sparse Classifier method. Results and Conclusions: Novel sparse aESI models outperformed traditional methods such as the LORETA family. The models combining aESI and cESI features improved the predictability of GS changes. Selected biomarkers from activation/connectivity patterns were localized to orbitofrontal and temporal cortical regions. Significance: The proposed methodology contributes to understanding the activation and connectivity of ESI complex patterns related to GS, providing potential biomarker features for GS slowing. Given the known relationship between GS decline and cognitive impairment, this preliminary work suggests it might be applied to other, more complex measures of healthy and pathological aging. Importantly, it might allow an ESI-based evaluation of rehabilitation programs.

q-bio.QM↗

arXiv2020

CrimAnalyzer: Understanding Crime Patterns in S\~ao Paulo City

S\~ao Paulo is the largest city in South America, with high criminality rates. The number and type of crimes varies considerably around the city, assuming different patterns depending on urban and social characteristics. In this scenario, enabling tools to explore particular locations of the city is very important for domain experts to understand how urban features as to mobility, passersby behavior, and urban infrastructures can influence the quantity and type of crimes. In present work, we present CrimAnalyzer, a visualization assisted analytic tool that allows users to analyze crime behavior in specific regions of a city, providing new methodologies to identify local crime hotspots and their corresponding patterns over time. CrimAnalyzer has been developed from the demand of experts in criminology and it deals with three major challenges: i) flexibility to explore local regions and understand their crime patterns, ii) Identification of not only prevalent hotspots in terms of number of crimes but also hotspots where crimes are frequent but not in large amount, and iii) understand the dynamic of crime patterns over time. The effectiveness and usefulness of the proposed system are demonstrated by qualitative/quantitative comparisons as well as case studies involving real data and run by domain experts.

stat.AP↗

arXiv2019

Enhanced Robot Speech Recognition Using Biomimetic Binaural Sound Source Localization

Inspired by the behavior of humans talking in noisy environments, we propose an embodied embedded cognition approach to improve automatic speech recognition (ASR) systems for robots in challenging environments, such as with ego noise, using binaural sound source localization (SSL). The approach is verified by measuring the impact of SSL with a humanoid robot head on the performance of an ASR system. More specifically, a robot orients itself toward the angle where the signal-to-noise ratio (SNR) of speech is maximized for one microphone before doing an ASR task. First, a spiking neural network inspired by the midbrain auditory system based on our previous work is applied to calculate the sound signal angle. Then, a feedforward neural network is used to handle high levels of ego noise and reverberation in the signal. Finally, the sound signal is fed into an ASR system. For ASR, we use a system developed by our group and compare its performance with and without the support from SSL. We test our SSL and ASR systems on two humanoid platforms with different structural and material properties. With our approach we halve the sentence error rate with respect to the common downmixing of both channels. Surprisingly, the ASR performance is more than two times better when the angle between the humanoid head and the sound source allows sound waves to be reflected most intensely from the pinna to the ear microphone, rather than when sound waves arrive perpendicularly to the membrane.

cs.SD↗