Fluid Intake Recognition using Inertial Sensors

被引:9
作者
Wellnitz, Arne [1 ]
Wolff, Johann-Peter [1 ]
Haubelt, Christian [1 ]
Kirste, Thomas [1 ]
机构
[1] Univ Rostock, Rostock, Germany
来源
6TH INTERNATIONAL WORKSHOP ON SENSOR-BASED ACTIVITY RECOGNITION AND INTERACTION (IWOAR 2019) | 2019年
关键词
D O I
10.1145/3361684.3361688
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
As one of many uses of body-worn inertial sensors, health monitoring applications can have a significant impact on the quality of life for a user even with inexpensive consumer electronics. In this paper, we address fluid intake monitoring as an activity recognition problem and conduct a user-study with 41 participants. We show that while an approach with a wrist-mounted sensor outperforms an approach with a head-mounted sensor, they can both be considered viable options for such a system. Furthermore we compare the classification performance of a hybrid CNN-LSTM artificial neural network with simpler baseline classifiers.
引用
收藏
页数:7
相关论文
共 17 条
[1]  
Amft Oliver, 2010, 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), P298, DOI 10.1109/PERCOMW.2010.5470653
[2]   A Hierarchical Approach in Food and Drink Intake Recognition Using Wearable Inertial Sensors [J].
Anderez, Dario Ortega ;
Lotfi, Ahmad ;
Langensiepen, Caroline .
11TH ACM INTERNATIONAL CONFERENCE ON PERVASIVE TECHNOLOGIES RELATED TO ASSISTIVE ENVIRONMENTS (PETRA 2018), 2018, :552-557
[3]  
[Anonymous], P 25 INT JOINT C ART, DOI DOI 10.48550/ARXIV.1604.08880
[4]  
[Anonymous], 2014, P 5 AUGM HUM INT C N
[5]   A Tutorial on Human Activity Recognition Using Body-Worn Inertial Sensors [J].
Bulling, Andreas ;
Blanke, Ulf ;
Schiele, Bernt .
ACM COMPUTING SURVEYS, 2014, 46 (03)
[6]  
Chiu MC, 2009, UBICOMP'09: PROCEEDINGS OF THE 11TH ACM INTERNATIONAL CONFERENCE ON UBIQUITOUS COMPUTING, P185
[7]  
Gomes Diana, 2019, SENSORS, V19, P9
[8]   Food Intake Detection from Inertial Sensors Using LSTM Networks [J].
Kyritsis, Konstantinos ;
Diou, Christos ;
Delopoulos, Anastasios .
NEW TRENDS IN IMAGE ANALYSIS AND PROCESSING - ICIAP 2017, 2017, 10590 :411-418
[9]  
Mengistu Y, 2016, 2016 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2016), P1857, DOI 10.1109/IROS.2016.7759295
[10]   Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition [J].
Ordonez, Francisco Javier ;
Roggen, Daniel .
SENSORS, 2016, 16 (01)