Unified digital biomarker platform for wearable devices assuring integrity, heterogeneity, and scalability

This study presents a cloud-based platform for managing personal digital biomarker data collected from wearable and mobile devices. The platform aims to address four essential challenges for personalized healthcare: ensuring data integrity, supporting various biomarker data types, maintaining measurement reliability, and enabling system scalability. To protect data integrity and privacy, the platform uses private blockchain technology. It also supports heterogeneous data formats, such as time-series ECG signals and dietary images, through standardized interfaces. Measurement reliability is ensured by Gaussian mixture model that successfully detect faulty data with 100% recall. In real-world clinical tests with patients, the platform detects all attempts of data tampering and processes diverse biomarker data with an average latency of less than 1.76 s. The platform’s scalability maintains stable performance under high data loads, and practical use is demonstrated through integration with our mobile application and biomarker web server. We validate the platform by measuring actual biomarker data from real-world atrial fibrillation patients and demonstrate its capability to securely and efficiently integrate wearable biomarker data for personalized healthcare.

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Publication Details

Journal
Scientific Reports
Published
2026-07-27
DOI
https://doi.org/10.1038/s41598-026-63514-y
Primary Topic
ECG Monitoring and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Unified digital biomarker platform for wearable devices assuring integrity, heterogeneity, and scalability

Junseok Lee, Chuck Yoo, Gyeongsik Yang, Yeonho Yoo et al.
Scientific Reports
ECG Monitoring and Analysis
article

Unified digital biomarker platform for wearable devices assuring integrity, heterogeneity, and scalability

Junseok Lee, Chuck Yoo, Gyeongsik Yang, Yeonho Yoo, Seungwoo Jung, Youngpil Kim, Dosun Lim, Yunkyung Kang
article en

Abstract

This study presents a cloud-based platform for managing personal digital biomarker data collected from wearable and mobile devices. The platform aims to address four essential challenges for personalized healthcare: ensuring data integrity, supporting various biomarker data types, maintaining measurement reliability, and enabling system scalability. To protect data integrity and privacy, the platform uses private blockchain technology. It also supports heterogeneous data formats, such as time-series ECG signals and dietary images, through standardized interfaces. Measurement reliability is ensured by Gaussian mixture model that successfully detect faulty data with 100% recall. In real-world clinical tests with patients, the platform detects all attempts of data tampering and processes diverse biomarker data with an average latency of less than 1.76 s. The platform’s scalability maintains stable performance under high data loads, and practical use is demonstrated through integration with our mobile application and biomarker web server. We validate the platform by measuring actual biomarker data from real-world atrial fibrillation patients and demonstrate its capability to securely and efficiently integrate wearable biomarker data for personalized healthcare.

Scientific Reports
Incheon National University (KR), Korea University (KR), Dongguk University (KR), Korea University (JP)
Openalex Percentile: Top 9%
ECG Monitoring and Analysis
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