I currently perform signal quality assessment for collaborators who are exploring physiological correlates of intervention effects observed in children and adolescents with autism. In the Computational Behavioral Science Lab, I lead the following projects.
Wearable sensor systems allow electrocardiograph (ECG) data to
be collected less obtrusively, especially from populations
who may present with behavioral or attentional difficulties.
However, given the ambulatory and high sampling frequencies
of these systems, raw ECG data is often noisy and requires
pre-processing that is typically time-consuming and
non-standardized due to non-transparent reporting of
closed-source pipelines. In this project, I am developing an
open-source pipeline with an accompanying
web-based dashboard that can perform signal quality
assessment on ambulatory physiological data from ECG,
photoplethysmograph (PPG), and electrodermal activity (EDA)
devices.
doi: 10.1007/978-3-031-59717-6_8
Dyadic synchrony is the temporal coordination of behavioral
and physiological processes between two individuals. This
coordination has important consequences for social
and relational processes, which appear atypical in
individuals with autism. Moreover, research on autism has
seen a growing trend towards finding potential genetic,
neurological, and physiological markers, with the rationale
that biomarkers could better identify clinical subgroups and
guide more personalized treatment planning.
I am interested in exploring how sociobehavioral and cardiac
signals interact synchronously (or asynchronously) during
dyadic interactions between children with autism and their
caregivers.
doi: 10.17605/OSF.IO/4FN8R