MASC: Wearable Design for Infectious Disease Detection Through Machine Learning
We present an innovative approach for designing a wearable solution that utilizes machine learning to systematically optimize the monitoring of vital signs for early detection of COVID-19 infections in symptomatic patients. This approach correlates sensor data trends with disease predictions, utiliz...
Saved in:
Main Authors: | Sumaiya Afroz Mila, Bhagawat Baanav Yedla Ravi, Md Rafiul Kabir, Sandip Ray |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10870051/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Research progress and application prospects of flexible wearable sensor in spacesuit
by: Aiming Bu, et al.
Published: (2025-02-01) -
Integrating Wearable Sensor Signal Processing with Unsupervised Learning Methods for Tremor Classification in Parkinson’s Disease
by: Serena Dattola, et al.
Published: (2025-01-01) -
Wearable Sensors for Plants: Status and Prospects
by: Xuexin Yan, et al.
Published: (2025-01-01) -
Stretchable and body conformable electronics for emerging wearable therapies
by: Benzhao Huang, et al.
Published: (2025-01-01) -
Graphene-Based, Flexible, Wearable Piezoresistive Sensors with High Sensitivity for Tiny Pressure Detection
by: Rui Li, et al.
Published: (2025-01-01)