Spectrogram-Based Audio Classification of Nutrition Intake

被引：0

作者：

Kalantarian, Haik ^{[1
]}

Alshurafa, Nabil ^{[1
]}

Pourhomayoun, Mohammad ^{[1
]}

Sarin, Shruti ^{[1
]}

Le, Tuan ^{[1
]}

Sarrafzadeh, Majid ^{[1
]}

机构：

[1] Univ Calif Los Angeles, Dept Comp Sci, Los Angeles, CA 90024 USA

来源：

2014 IEEE HEALTHCARE INNOVATION CONFERENCE (HIC) | 2014年

关键词：

nutrition; swallow detection; spectrogram;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Acoustic monitoring of food intake in an unobtrusive, wearable form-factor can encourage healthy dietary choices by enabling individuals to monitor their eating patterns, maintain regularity in their meal times, and ensure adequate hydration levels. In this paper, we describe a system capable of monitoring food intake by means of a throat microphone, classifying the data based on the food being consumed among several categories through spectrogram analysis, and providing user feedback in the form of mobile application. We are able to classify sandwich swallows, sandwich chewing, water swallows, and none, with an F-Measure of 0.836.

引用

页码：161 / 164

页数：4

共 50 条

[21] Spectrogram-based formant tracking via particle filters
Shi, Y
Chang, E
2003 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL I, PROCEEDINGS: SPEECH PROCESSING I, 2003, : 168 - 171
[22] Grid-tuned ensemble models for 2D spectrogram-based autism classification
Ullah, Muhammad Zakir
Yu, Dongchuan
BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2024, 93
[23] Learning Temporal Resolution in Spectrogram for Audio Classification
Liu, Haohe
Liu, Xubo
Kong, Qiuqiang
Wang, Wenwu
Plumbley, Mark D.
THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 12, 2024, : 13873 - 13881
[24] Spectrogram-based efficient perceptual hashing scheme for speech identification
Zhang, Qiu-Yu
Zhang, Tao
Qiao, Si-Bin
Wu, Dong-Fang
International Journal of Network Security, 2019, 21 (02) : 259 - 268
[25] Classification of Affective Sound Quality Characteristics of Spectrogram-based Vehicle Driving Sounds Using Data Augmentation
Ha Kim, Dong
Lee, Jongsoo
TRANSACTIONS OF THE KOREAN SOCIETY OF MECHANICAL ENGINEERS A, 2022, 46 (05) : 487 - 494
[26] Cough Classification Using Audio Spectrogram Transformer
Habashy, Karim
Valdes, Julio
Cohen-McFarlane, Madison
Xi, Pengcheng
Wallace, Bruce
Goubran, Rafik
Knoefel, Frank
2022 IEEE SENSORS APPLICATIONS SYMPOSIUM (SAS 2022), 2022,
[27] Multi-frequency exciting and spectrogram-based ECT method
Chady, T
Enokizono, M
JOURNAL OF MAGNETISM AND MAGNETIC MATERIALS, 2000, 215 : 700 - 703
[28] A Spectrogram-based Voiceprint Recognition Using Deep Neural Network
Li, Penghua
Chen, Minglong
Hu, Fangchao
Xu, Yang
2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 2947 - 2951
[29] Spectrogram-Based Automatic Modulation Recognition Using Convolutional Neural Network
Jeong, Sinjin
Lee, Uhyeon
Kim, Suk Chan
2018 TENTH INTERNATIONAL CONFERENCE ON UBIQUITOUS AND FUTURE NETWORKS (ICUFN 2018), 2018, : 843 - 845
[30] Emotional sounds of crowds: spectrogram-based analysis using deep learning
Franzoni, Valentina
Biondi, Giulio
Milani, Alfredo
MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (47-48) : 36063 - 36075

← 1 2 3 4 5 →