Personal Stress-Level Clustering and Decision-Level Smoothing to Enhance the Performance of Ambulatory Stress Detection With Smartwatches

Personal Stress-Level Clustering and Decision-Level Smoothing to Enhance the Performance of Ambulatory Stress Detection With Smartwatches

Researchers strive hard to develop effective ways to detect and cope with enduring high-level daily stress as early as possible to prevent serious health consequences. Although research has traditionally been conducted in laboratory settings, a set of new studies have recently begun to be conducted...

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Bibliographic Details
Main Authors: Yekta Said Can, Niaz Chalabianloo, Deniz Ekiz, Javier Fernandez-Alvarez, Giuseppe Riva, Cem Ersoy
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Stress recognition
machine learning
wearable sensors
smart-phone
smartwatch
photoplethysmography
Online Access:https://ieeexplore.ieee.org/document/9004470/

Internet

https://ieeexplore.ieee.org/document/9004470/

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