Papers by Sashi Thapaliya
Autism Spectrum Disorder is a developmental disorder that often impairs a child's normal developm... more Autism Spectrum Disorder is a developmental disorder that often impairs a child's normal development of the brain. Early Diagnosis is crucial in the long term treatment of ASD, but this is challenging due to the lack of a proper objective measures. Subjective measures often take more time, resources, and have false positives or false negatives. There is a need for efficient objective measures that can help in diagnosing this disease early as possible with less effort. This paper presents EEG and Eye movement data for the diagnosis of ASD using machine learning algorithms. There are number of studies on classification of ASD using EEG or Eye tracking data. However, all of them simply use either Eye movements or EEG data for the classification. In our study we combine Eye movements and EEG data to develop an efficient methodology for diagnosis. This paper presents several models based on EEG, and eye movements for the diagnosis of ASD.
An Empirical Evaluation of Machine Learning Approaches for Species Identification through Bioacoustics
In this paper, we investigate a complete system for identifying species from audio files. Audio d... more In this paper, we investigate a complete system for identifying species from audio files. Audio data from both high quality and low quality sound files with varying degrees of background noise are collected and preprocessed for enhancing the learning capability of machine learning models. Then, fine-scale features are extracted to quantify acoustic properties of audio streams. Based on the proposed system, we evaluate a set of popular machine learning approaches on audio data from the cat and dog families. The experimental results show that the use of appropriate quality data and machine learning models yield compelling identification accuracy of species with limited user assistance.
Advances in bioinformatics and biomedical engineering book series, 2019
Autism Spectrum Disorder (ASD) is a developmental disorder that often impairs a child's normal de... more Autism Spectrum Disorder (ASD) is a developmental disorder that often impairs a child's normal development of the brain. According to CDC, it is estimated that 1 in 6 children in the US suffer from development disorders, and 1 in 68 children in the US suffer from ASD. This condition has a negative impact on a person's ability to hear, socialize and communicate. Overall, ASD has a broad range of symptoms and severity; hence the term spectrum is used. One of the main contributors to ASD is known to be genetics. Up to date, no suitable cure for ASD has been found. Early diagnosis is crucial for the long-term treatment of ASD, but this is challenging due to the lack of a proper objective measures. Subjective measures often take more time, resources, and have false positives or false negatives. There is a need for efficient objective measures that can help in diagnosing this disease early as possible with less effort. EEG measures the electric signals of the brain via electrodes placed on various places on the scalp. These signals can be used to study complex neuropsychiatric issues. Studies have shown that EEG has the potential to be used as a biomarker for various neurological conditions including ASD. This chapter will outline the usage of EEG measurement for the classification of ASD using machine learning algorithms.
2018 IEEE International Conference on Big Data (Big Data), 2018
Autism Spectrum Disorder is a developmental disorder that often impairs a child's normal developm... more Autism Spectrum Disorder is a developmental disorder that often impairs a child's normal development of the brain. Early Diagnosis is crucial in the long term treatment of ASD, but this is challenging due to the lack of a proper objective measures. Subjective measures often take more time, resources, and have false positives or false negatives. There is a need for efficient objective measures that can help in diagnosing this disease early as possible with less effort. This paper presents EEG and Eye movement data for the diagnosis of ASD using machine learning algorithms. There are number of studies on classification of ASD using EEG or Eye tracking data. However, all of them simply use either Eye movements or EEG data for the classification. In our study we combine Eye movements and EEG data to develop an efficient methodology for diagnosis. This paper presents several models based on EEG, and eye movements for the diagnosis of ASD.
An Empirical Evaluation of Machine Learning Approaches for Species Identification through Bioacoustics
2017 International Conference on Computational Science and Computational Intelligence (CSCI), 2017
In this paper, we investigate a complete system for identifying species from audio files. Audio d... more In this paper, we investigate a complete system for identifying species from audio files. Audio data from both high quality and low quality sound files with varying degrees of background noise are collected and preprocessed for enhancing the learning capability of machine learning models. Then, fine-scale features are extracted to quantify acoustic properties of audio streams. Based on the proposed system, we evaluate a set of popular machine learning approaches on audio data from the cat and dog families. The experimental results show that the use of appropriate quality data and machine learning models yield compelling identification accuracy of species with limited user assistance.
Autism spectrum disorder (ASD) is a developmental disorder that often impairs a child’s normal de... more Autism spectrum disorder (ASD) is a developmental disorder that often impairs a child’s normal development of the brain. According to CDC, it is estimated that 1 in 6 children in the US suffer from development disorders, and 1 in 68 children in the US suffer from ASD. This condition has a negative impact on a person’s ability to hear, socialize, and communicate. Subjective measures often take more time, resources, and have false positives or false negatives. There is a need for efficient objective measures that can help in diagnosing this disease early as possible with less effort. EEG measures the electric signals of the brain via electrodes placed on various places on the scalp. These signals can be used to study complex neuropsychiatric issues. Studies have shown that EEG has the potential to be used as a biomarker for various neurological conditions including ASD. This chapter will outline the usage of EEG measurement for the classification of ASD using machine learning algorith...
Evaluating the EEG and Eye Movements for Autism Spectrum Disorder
2018 IEEE International Conference on Big Data (Big Data)
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Papers by Sashi Thapaliya