Adaptive Data Extractor for Wearable Health Data Integration

Poster Number: P26
Presentation Time: 05:00 PM - 06:30 PM

Abstract Keywords: Patient / Person Generated Health Data (Patient Reported Outcomes), Machine Learning, Workflow
Primary Track: Applications

With growing interest in leveraging wearable health data, standardized pipelines are developed to process such data efficiently. However, these tools depend on a rigid input schema, making it challenging to adapt evolving data schemas of wearable devices, thus limiting their scalability. In response, this study explored the feasibility of building an adaptive wearable health data extractor to facilitate data pre-processing and integration, irrespective of changes in data labels and formats.

Speaker(s):
Sunghoon Kang, B.A.
Seoul National University

Author(s):
Hyeoneui Kim, PhD - Seoul National University;