Noninvasive automatic detection of Alzheimer's disease from spontaneous speech: a review
X Qi, Q Zhou, J Dong, W Bao - Frontiers in Aging Neuroscience, 2023 - frontiersin.org
Alzheimer's disease (AD) is considered as one of the leading causes of death among
people over the age of 70 that is characterized by memory degradation and language …
people over the age of 70 that is characterized by memory degradation and language …
[HTML][HTML] Paradigm shift toward digital neuropsychology and high-dimensional neuropsychological assessments
T Parsons, T Duffield - Journal of medical Internet research, 2020 - jmir.org
Neuropsychologists in the digital age have increasing access to emerging technologies. The
National Institutes of Health (NIH) initiatives for behavioral and social sciences have …
National Institutes of Health (NIH) initiatives for behavioral and social sciences have …
Predicting MCI status from multimodal language data using cascaded classifiers
KC Fraser, K Lundholm Fors, M Eckerström… - Frontiers in aging …, 2019 - frontiersin.org
Recent work has indicated the potential utility of automated language analysis for the
detection of mild cognitive impairment (MCI). Most studies combining language processing …
detection of mild cognitive impairment (MCI). Most studies combining language processing …
[PDF][PDF] Detecting Signs of Dementia Using Word Vector Representations.
Recent approaches to word vector representations, eg,'w2vec'and 'GloVe', have been
shown to be powerful methods for capturing the semantics and syntax of words in a text. The …
shown to be powerful methods for capturing the semantics and syntax of words in a text. The …
[PDF][PDF] Automatic Detection of Autism Spectrum Disorder in Children Using Acoustic and Text Features from Brief Natural Conversations.
Abstract Autism Spectrum Disorder (ASD) is increasingly prevalent [1], but long waitlists
hinder children's access to expedient diagnosis and treatment. To begin addressing this …
hinder children's access to expedient diagnosis and treatment. To begin addressing this …
Combining voice and language features improves automated autism detection
Variability in expressive and receptive language, difficulty with pragmatic language, and
prosodic difficulties are all features of autism spectrum disorder (ASD). Quantifying language …
prosodic difficulties are all features of autism spectrum disorder (ASD). Quantifying language …
[HTML][HTML] Identification of digital voice biomarkers for cognitive health
Aim: Human voice contains rich information. Few longitudinal studies have been conducted
to investigate the potential of voice to monitor cognitive health. The objective of this study is …
to investigate the potential of voice to monitor cognitive health. The objective of this study is …
How technology is reshaping cognitive assessment: Lessons from the Framingham Heart Study.
R Au, RJ Piers, S Devine - Neuropsychology, 2017 - psycnet.apa.org
Objective: This article elucidates how the Boston process approach (BPA) can amplify the
role of neuropsychology in the study of preclinical and clinical dementia, particularly …
role of neuropsychology in the study of preclinical and clinical dementia, particularly …
A mobile application using automatic speech analysis for classifying Alzheimer's disease and mild cognitive impairment
Speech and language disturbances have been observed from the early stages of
Alzheimer's disease (AD), including mild cognitive impairment (MCI), and speech analysis …
Alzheimer's disease (AD), including mild cognitive impairment (MCI), and speech analysis …
Self-supervised neural factor analysis for disentangling utterance-level speech representations
Self-supervised learning (SSL) speech models such as wav2vec and HuBERT have
demonstrated state-of-the-art performance on automatic speech recognition (ASR) and …
demonstrated state-of-the-art performance on automatic speech recognition (ASR) and …