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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
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Posts
Future Blog Post
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Blog Post number 4
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Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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portfolio
Portfolio item number 1
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publications
Tenets Towards Smartphone-based Medical Tricorder
Published in MobiSys 2021: DigiBiom, Workshop on the Future of Digital Biomarkers, 2021
This paper presents a vision for smartphone based medical tricorders and draws out the challenges to realizing successful smartphone-based medical sensing solutions.
Recommended citation: Colin Barry, Tauhidur Rahman, and Edward J. Wang. 2021. "Tenets towards smartphone-based medical tricorders. " In Proceedings of the 2021 Workshop on Future of Digital Biomarkers (DigiBiom 2021). Association for Computing Machinery, New York, NY, USA, 12–18. DOI:https://doi.org/10.1145/3469266.3469880 https://dl.acm.org/doi/proceedings/10.1145/3469266
talks
Smartphone-based Alzheimer’s Disease Risk Screening
Published:
Presentation of ongoing research to develop an effective digital biomarker for screening of Alzheimer’s Disease using smartphones.
Tenets Towards Smartphone-based Medical Tricorders
Published:
The challenges and motifs inherent to realizing the vision of smartphone-based medical sensing solutions.
At-home Pupillometry Using Smartphone Facial Identification Cameras
Published:
With recent developments in medical and psychiatric research surrounding pupillary response, cheap and accessible pupillometers could enable medical benefits from early neurological disease detection to measurements of cognitive load. In this paper, we introduce a novel smartphone-based pupillometer to allow for future development in clinical research surrounding at-home pupil measurements. Our solution utilizes a NIR front-facing camera for facial recognition paired with the RGB selfie camera to perform tracking of absolute pupil dilation with sub-millimeter accuracy. In comparison to a gold standard pupillometer during a pupillary light reflex test, the smartphone-based system achieves a median MAE of 0.27mm for absolute pupil dilation tracking and a median error of 3.52% for pupil dilation change tracking. Additionally, we remotely deployed the system to older adults as part of a usability study that demonstrates promise for future smartphone deployments to remotely collect data in older, inexperienced adult users operating the system themselves.
New Eye Scanning Smartphone App
Published:
https://omny.fm/shows/ched-mid-morning/new-eye-scanning-app-can-screen-people-for-alzheim
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.