NDLI: Energy-aware embedded classifier design for real-time emotion analysis

Content Provider	IEEE Xplore Digital Library
Author	Padmanabhan, M. Murali, S. Rincon, F. Atienza, D.
Copyright Year	2015
Description	Author affiliation: Embedded Syst. Lab., EPFL, Lausanne, Switzerland (Padmanabhan, M.; Atienza, D.) \|\| SmartCardia Inc., Ltd., Switzerland (Murali, S.; Rincon, F.)
Abstract	Detection and classification of human emotions from multiple bio-signals has a wide variety of applications. Though electronic devices are available in the market today that acquire multiple body signals, the classification of human emotions in real-time, adapted to the tight energy budgets of wearable embedded systems is a big challenge. In this paper we present an embedded classifier for real-time emotion classification. We propose a system that operates at different energy budgeted modes, depending on the available energy, where each mode is constrained by an operating energy bound. The classifier has an offline training phase where feature selection is performed for each operating mode, with an energy-budget aware algorithm that we propose. Across the different operating modes, the classification accuracy ranges from 95% - 75% and 89% - 70% for arousal and valence respectively. The accuracy is traded off for less power consumption, which results in an increased battery life of up to 7.7 times (from 146.1 to 1126.9 hours).
Starting Page	2275
Ending Page	2278
File Size	828271
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7318846
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Real-time systems Biomedical monitoring Batteries Electrocardiography Training Algorithm design and analysis
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Improvement of emotional healthcare system with stress detection from ECG signal

Real-time wearable telecardiology from representative signals

Context-aware Sensing of Physiological Signals

An embedded reconfigurable architecture for patient-specific multi-paramater medical monitoring

A portable real-time ECG recognition system based on smartphone

Wearable real-time ecg monitoring with emergency alert system for scuba diving

Real-time implementation of a self-recovery EMG pattern recognition interface for artificial arms

A time domain based classifier for ECG pattern recognition

Stability of MEG for real-time neurofeedback

Energy-aware embedded classifier design for real-time emotion analysis

Similar Documents

Improvement of emotional healthcare system with stress detection from ECG signal

Real-time wearable telecardiology from representative signals

Context-aware Sensing of Physiological Signals

An embedded reconfigurable architecture for patient-specific multi-paramater medical monitoring

A portable real-time ECG recognition system based on smartphone

Wearable real-time ecg monitoring with emergency alert system for scuba diving

Real-time implementation of a self-recovery EMG pattern recognition interface for artificial arms

A time domain based classifier for ECG pattern recognition

Stability of MEG for real-time neurofeedback

Energy-aware embedded classifier design for real-time emotion analysis