Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Extracellular Matrix-Mimetic Intrinsic Versatile Coating Derived from Marine Adhesive Protein Promotes Diabetic Wound Healing through Regulating the Microenvironment.

ACS nano·2024

Same author

Learning dynamic graph representations through timespan view contrasts.

Neural networks : the official journal of the International Neural Network Society·2024

Same author

Corrigendum: Tree-shrub-grass composite woodland better facilitates emotional recovery in college students emotion better than other plant communities.

Frontiers in psychology·2024

Same author

Statins improve cardiac endothelial function to prevent heart failure with preserved ejection fraction through upregulating circRNA-RBCK1.

Nature communications·2024

Same author

WITHDRAWN: Impact of a Clinical Nursing Teaching Model Based on Institutional Cooperation on Teaching Quality of Nursing Programs in Colleges and Universities and Effectiveness of Internship for Undergraduate Nurses.

Alternative therapies in health and medicine·2024

Same author

Spatially resolved single-cell atlas of ascidian endostyle provides insight into the origin of vertebrate pharyngeal organs.

Science advances·2024

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 19, 2026

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

Wearable Networked Sensing for Human Mobility and Activity Analytics: A Systems Study.

Bo Dong¹, Subir Biswas¹

¹Electrical and Computer Engineering, Michigan State University, East Lansing, MI.

International Conference on Communication Systems and Networks : [Proceedings]. International Conference on Communication Systems and Networks

|December 23, 2014

Summary

This summary is machine-generated.

This study demonstrates that wearable sensor networks can efficiently analyze human activities, even with limited on-body processing power and energy constraints. Machine learning algorithms achieve accurate activity detection, optimizing performance for wearable human activity analytics.

Keywords:

Activity Analytics Machine Learning Neural Network On-body Processing Wearable Sensor Network

More Related Videos

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

Home-Based Monitor for Gait and Activity Analysis

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

Related Experiment Videos

Last Updated: Apr 19, 2026

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data

Published on: July 27, 2018

Home-Based Monitor for Gait and Activity Analysis

Home-Based Monitor for Gait and Activity Analysis

Published on: August 8, 2019

Area of Science:

Computer Science
Biomedical Engineering
Machine Learning

Background:

Wearable sensor networks are increasingly used for human activity analysis.
Energy consumption and limited processing capabilities are key challenges for on-body sensors.
Accurate human activity recognition is crucial for various applications, including healthcare and fitness.

Purpose of the Study:

To present the implementation, characterization, and performance of a wearable sensor network for human activity analysis.
To investigate the impact of energy consumption on activity detection accuracy with out-of-body processing.
To characterize the effects of limited on-body processing abilities on detection accuracy.

Main Methods:

Implementation of a wearable sensor network for human activity analysis.
Application of machine learning mechanisms for activity recognition using both out-of-body and on-body processing.
Analysis of energy consumption impacts on activity detection accuracy.
Characterization of processing limitations on sensor units by varying background load.

Main Results:

Machine learning algorithms successfully recognize target activities with both processing arrangements.
Energy consumption analysis shows its impact on activity detection accuracy for out-of-body processing.
Limited on-body processing abilities were characterized, showing effects on detection accuracy.
The system demonstrated efficient human activity analytics under energy and processing constraints.

Conclusions:

An efficient human activity analytics system can be designed and operated using tiny on-body wearable sensors.
The study validates the feasibility of on-body processing for activity recognition despite resource limitations.
Wearable sensor networks offer a viable solution for human activity analysis even under strict energy and processing constraints.