The SPLENDID chewing detection challenge

Vasileios Papapanagiotou, Christos Diou, Lingchuan Zhou, Janet van den Boer, Monica Mars, Anastasios Delopoulos

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

6 Citations (Scopus)

Abstract

Monitoring of eating behavior using wearable technology is receiving increased attention, driven by the recent advances in wearable devices and mobile phones. One particularly interesting aspect of eating behavior is the monitoring of chewing activity and eating occurrences. There are several chewing sensor types and chewing detection algorithms proposed in the bibliography, however no datasets are publicly available to facilitate evaluation and further research. In this paper, we present a multi-modal dataset of over 60 hours of recordings from 14 participants in semi-free living conditions, collected in the context of the SPLENDID project. The dataset includes raw signals from a photoplethysmography (PPG) sensor and a 3D accelerometer, and a set of extracted features from audio recordings; detailed annotations and ground truth are also provided both at eating event level and at individual chew level. We also provide a baseline evaluation method, and introduce the 'challenge' of improving the baseline chewing detection algorithms. The dataset can be downloaded from http: //dx.doi.org/10.17026/dans-zxw-v8gy, and supplementary code can be downloaded from https://github. com/mug-auth/chewing-detection-challenge.git.

Original languageEnglish
Title of host publication2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Proceedings
Subtitle of host publicationSmarter Technology for a Healthier World
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages817-820
ISBN (Electronic)9781509028092
DOIs
Publication statusPublished - 14 Sep 2017
Event39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of
Duration: 11 Jul 201715 Jul 2017

Conference

Conference39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
CountryKorea, Republic of
CityJeju Island
Period11/07/1715/07/17

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  • Datasets

    The SPLENDID chewing detection challenge

    Delopoulos, A. D. (Creator), Papapanagiotou, V. P. (Creator), Diou, C. D. (Creator), Zhou, L. Z. (Creator), van den Boer, J. H. W. (Creator) & Mars, M. (Creator), Aristotle University of Thessaloniki, 18 Feb 2017

    Dataset

    The SPLENDID chewing detection challenge (Version 2)

    Delopoulos, A. D. (Creator), Papapanagiotou, V. P. (Creator), Diou, C. D. (Creator), Zhou, L. Z. (Creator), van den Boer, J. H. W. (Creator) & Mars, M. (Creator), Aristotle University of Thessaloniki, 21 Sep 2017

    Dataset

    Projects

    BigO: Big data against childhood Obesity

    1/12/1630/11/20

    Project: EU research project

    Cite this

    Papapanagiotou, V., Diou, C., Zhou, L., van den Boer, J., Mars, M., & Delopoulos, A. (2017). The SPLENDID chewing detection challenge. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Proceedings: Smarter Technology for a Healthier World (pp. 817-820). [8036949] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2017.8036949