Nathan Starliper

College of Engineering

Works (1)

Updated: April 5th, 2024 11:57

2019 journal article

Activity-Aware Wearable System for Power-Efficient Prediction of Physiological Responses

SENSORS, 19(3).

By: N. Starliper n, F. Mohammadzadeh n, T. Songkakul n , M. Hernandez *, A. Bozkurt n & E. Lobaton n 

author keywords: wearable health; physiological prediction; activity clustering; multi-modal data; Body Sensor Networks; sensor selection; power efficient sensing
MeSH headings : Accelerometry / statistics & numerical data; Actigraphy / instrumentation; Cluster Analysis; Electric Power Supplies / economics; Humans; Telemedicine / economics; Wearable Electronic Devices / economics; Wearable Electronic Devices / standards
TL;DR: This article proposes a method for context aware dynamic sensor selection for power optimized physiological prediction using multi-modal wearable data streams, and finds the optimal reduced set of groups of sensor features, in turn reducing power usage by duty cycling these and optimizing prediction accuracy. (via Semantic Scholar)
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7. Affordable and Clean Energy (OpenAlex)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: March 18, 2019

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