A5037490912- Autism Spectrum Disorder Research
- Child Development and Digital Technology
- Digital Mental Health Interventions
- Emotion and Mood Recognition
- Virology and Viral Diseases
- Mental Health Research Topics
- Infant Health and Development
- Mobile Crowdsensing and Crowdsourcing
- Mobile Health and mHealth Applications
- Genomics and Phylogenetic Studies
- Genetics and Neurodevelopmental Disorders
- Data-Driven Disease Surveillance
- Scientific Computing and Data Management
- Innovative Human-Technology Interaction
- Parkinson's Disease Mechanisms and Treatments
- Chemical Reaction Mechanisms
- Assistive Technology in Communication and Mobility
- Heart Rate Variability and Autonomic Control
- Molecular Junctions and Nanostructures
- History and advancements in chemistry
- Machine Learning in Healthcare
- Artificial Intelligence in Healthcare and Education
- Data Stream Mining Techniques
- Speech and Audio Processing
- Behavioral and Psychological Studies
University of Hawaiʻi at Mānoa
2021-2025
University of California, San Francisco
2024-2025
University of Hawaii System
2023-2024
Honolulu University
2024
Stanford University
2016-2023
Bioengineering Center
2020-2022
Palo Alto University
2016-2021
Rice University
2013-2015
Menlo School
1973-1976
ATUM (United States)
1976
Background The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors take several hours complete. This has in part contributed long wait times for a diagnosis subsequent delays access therapy. We hypothesize that the use of machine learning analysis on home video can speed without compromising accuracy. have analyzed item-level records from 2 diagnostic instruments construct classifiers optimized sparsity, interpretability, In present study,...
Autism behavioral therapy is effective but expensive and difficult to access. While mobile technology-based can alleviate wait-lists scale for increasing demand, few clinical trials exist support its use autism spectrum disorder (ASD) care.To evaluate the efficacy of Superpower Glass, an artificial intelligence-driven wearable intervention improving social outcomes children with ASD.A randomized trial in which participants received Glass plus standard care applied analysis control only...
Autism spectrum disorder (ASD) is a neurodevelopmental characterized by repetitive behaviors, narrow interests, and deficits in social interaction communication ability. An increasing emphasis being placed on the development of innovative digital mobile systems for their potential therapeutic applications outside clinical environments. Due to recent advances field computer vision, various emotion classifiers have been developed, which play significant role screening therapy developmental...
Autism spectrum disorder (ASD) is currently diagnosed using qualitative methods that measure between 20-100 behaviors, can span multiple appointments with trained clinicians, and take several hours to complete. In our previous work, we demonstrated the efficacy of machine learning classifiers accelerate process by collecting home videos US-based children, identifying a reduced subset behavioral features are scored untrained raters classifier determine children's "risk scores" for autism. We...
We have developed a system for automatic facial expression recognition running on Google Glass, delivering real-time social cues to children with Autism Spectrum Disorder (ASD). The includes multiple mechanisms engage and their parents, who administer this technology within the home. completed an at-home design trial 14 families that used learning aid over 3-month period. found ASD generally respond well wearing at home opt most expressive feedback choice. further evaluated app usage,...
Abstract Although standard behavioral interventions for autism spectrum disorder (ASD) are effective therapies social deficits, they face criticism being time-intensive and overdependent on specialists. Earlier starting age of therapy is a strong predictor later success, but waitlists can be 18 months long. To address these complications, we developed Superpower Glass, machine-learning-assisted software system that runs Google Glass an Android smartphone, designed use during interactions....
Over 1 million children under the age of 17 in US have been identified with Autism Spectrum Disorder (ASD). These struggle to recognize facial expressions, make eye contact, and engage social interactions. Gaining these skills requires intensive behavioral interventions that are often expensive, difficult access, inconsistently administered.nWe developed a system automate expression recognition runs on wearable glasses delivers real time cues, goal creating aid for ASD maximizes feedback...
Autism spectrum disorder (ASD) is a neurodevelopmental that results in altered behavior, social development, and communication patterns. In recent years, autism prevalence has tripled, with 1 44 children now affected. Given traditional diagnosis lengthy, labor-intensive process requires the work of trained physicians, significant attention been given to developing systems automatically detect autism. We toward this goal by analyzing audio data, as prosody abnormalities are signal autism,...
Abstract The unmapped readspace of whole genome sequencing data tends to be large but is often ignored. We posit that it contains valuable signals both human infection and contamination. Using poorly aligned reads from sequences (WGS) over 1000 families nearly 5000 individuals, we present insights into common viral, bacterial, computational contamination plague studies. several notable results: (1) In addition known contaminants such as Epstein-Barr virus phiX, blood lymphocyte cell lines...
Background There are a wide range of potential adverse health effects, ranging from headaches to cardiovascular disease, associated with long-term negative emotions and chronic stress. Because many indicators stress imperceptible observers, the early detection remains pressing medical need, as it can enable intervention. Physiological signals offer noninvasive method for monitoring affective states recorded by growing number commercially available wearables. Objective We aim study...
We have developed a system for automatic facial expression recognition, which runs on Google Glass and delivers real-time social cues to the wearer. evaluate as behavioral aid children with Autism Spectrum Disorder (ASD), who can greatly benefit from non-invasive emotional are more sensitive sensory input than neurotypically developing children. In addition, we present mobile application that enables users of wearable review their videos along auto-curated information video playback bar....
In this paper, we describe challenges in the development of a mobile charades-style game for delivery social training to children with Autism Spectrum Disorder (ASD). Providing real-time feedback and adapting difficulty response child's performance necessitates integration emotion classifiers into system. Due limited existing recognition platforms ASD, propose novel technique automatically extract emotion-labeled frames from video acquired sessions, which hypothesize can be used train new...
Background Recent advances in computer vision and wearable technology have created an opportunity to introduce mobile therapy systems for autism spectrum disorders (ASD) that can respond the increasing demand therapeutic interventions; however, feasibility questions must be answered first. Objective We studied of a prototype tool children with ASD using Google Glass, examining whether would wear such device, if providing emotion classification will improve recognition, how recognition...
Autism affects 1 in every 59 children the United States, according to estimates from Centers for Disease Control and Prevention's Developmental Disabilities Monitoring Network 2018. Although similar rates of autism are reported rural urban areas, families report greater difficulty accessing resources. An overwhelming number experience long waitlists diagnostic therapeutic services.
Autism spectrum disorder (ASD) is a developmental characterized by deficits in social communication and interaction, restricted repetitive behaviors interests. The incidence of ASD has increased recent years; it now estimated that approximately 1 40 children the United States are affected. Due part to increasing prevalence, access treatment become constrained. Hope lies mobile solutions provide therapy through artificial intelligence (AI) approaches, including facial emotion detection AI...
Mobilized telemedicine is becoming a key, and even necessary, facet of both precision health medicine. In this study, we evaluate the capability potential crowd virtual workers—defined as vetted members popular crowdsourcing platforms—to aid in task diagnosing autism. We workers when providing categorical ordinal behavioral ratings to unstructured public YouTube videos children with autism neurotypical controls. To emerging patterns that are consistent across independent crowds, target from...
Activity recognition computer vision algorithms can be used to detect the presence of autism-related behaviors, including what are termed "restricted and repetitive behaviors", or stimming, by diagnostic instruments. Examples stimming include hand flapping, spinning, head banging. One most significant bottlenecks for implementing such classifiers is lack sufficiently large training sets human behavior specific pediatric developmental delays. The data that do exist usually recorded with a...
Many children with autism cannot receive timely in-person diagnosis and therapy, especially in situations where access is limited by geography, socioeconomics, or global health concerns such as the current COVD-19 pandemic. Mobile solutions that work outside of traditional clinical environments can safeguard against gaps to quality care.The aim study examine engagement level therapeutic feasibility a mobile game platform for autism.We designed application, GuessWhat, which, its form,...
Background Autism spectrum disorder (ASD) is a widespread neurodevelopmental condition with range of potential causes and symptoms. Standard diagnostic mechanisms for ASD, which involve lengthy parent questionnaires clinical observation, often result in long waiting times results. Recent advances computer vision mobile technology hold speeding up the process by enabling computational analysis behavioral social impairments from home videos. Such techniques can improve objectivity contribute...
Background A formal autism diagnosis can be an inefficient and lengthy process. Families may wait several months or longer before receiving a for their child despite evidence that earlier intervention leads to better treatment outcomes. Digital technologies detect the presence of behaviors related scale access pediatric diagnoses. strong indicator is self-stimulatory such as hand flapping. Objective This study aims demonstrate feasibility deep learning detection flapping from unstructured...
Automated emotion classification could aid those who struggle to recognize emotions, including children with developmental behavioral conditions such as autism. However, most computer vision recognition models are trained on adult and therefore underperform when applied child faces.
Background Referred to as the “silent killer,” elevated blood pressure (BP) often goes unnoticed due absence of apparent symptoms, resulting in cumulative harm over time. Chronic stress has been consistently linked increased BP. Prior studies have found that BP arises a stressful lifestyle, although effect exact stressors varies drastically between individuals. The heterogeneous nature both and response multitude lifestyle decisions can make it difficult if not impossible pinpoint most...