Smoking recognition with smartwatch sensors in different postures and impact of user’s height-Reference-Cited by-同舟云学术

Smoking recognition with smartwatch sensors in different postures and impact of user’s height

Published:2020-05-22 Issue:3 Volume:12 Page:239-261
ISSN:1876-1372
Container-title:Journal of Ambient Intelligence and Smart Environments
language:
Short-container-title:AIS

Author:

Agac Sumeyye¹,Shoaib Muhammad²,Durmaz Incel Ozlem¹

Affiliation:

1. Department of Computer Engineering, Galatasaray University, Ciragan Cd. No:36, 34349, Istanbul, Turkey. E-mails: konaksumeyye@gmail.com, odincel@gsu.edu.tr

2. Pervasive Systems Research Group, University of Twente, Enschede, The Netherlands. E-mail: m.shoaib@utwente.nl

Publisher

IOS Press

Subject

Software

Reference30 articles.

1. F. Alharbi and K. Farrahi, A convolutional neural network for smoking activity recognition, in: 2018 IEEE 20th International Conference on E-Health Networking, Applications and Services (Healthcom), IEEE, 2018, pp. 1–6.

2. A.A. Ali, S.M. Hossain, K. Hovsepian, M.M. Rahman, K. Plarre and S. Kumar, mPuff: Automated detection of cigarette smoking puffs from respiration measurements, in: Proceedings of the 11th International Conference on Information Processing in Sensor Networks, ACM, 2012, pp. 269–280.

3. Detecting Smoking Events Using Accelerometer Data Collected Via Smartwatch Technology: Validation Study

4. Phone position/placement detection using accelerometer: Impact on activity recognition

5. Preprocessing techniques for context recognition from accelerometer data;Figo;Personal and Ubiquitous Computing,2010

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1. Human Activity Recognition with Smart Watches Using Federated Learning;Lecture Notes in Networks and Systems;2022

2. Quantification of Smoking Characteristics Using Smartwatch Technology: Pilot Feasibility Study of New Technology;JMIR Formative Research;2021-02-05

3. Quantification of Smoking Characteristics Using Smartwatch Technology: Pilot Feasibility Study of New Technology (Preprint);2020-05-26