Toothbrushing Performance Evaluation Using Smartphone Audio Based on Hybrid HMM-recognition/SVM-regression Model

• Joseph, Korpela

• Ryosuke, Miyaji

• Takuya, Maekawa

• Kazunori, Nozaki

• Hiroo, Tamagawa

抄録

This paper presents a method for evaluating toothbrushing performance using audio data collected by a smartphone. This method first conducts activity recognition on the audio data to classify segments of the data into several classes based on the brushing location and type of brush stroke. These recognition results are then used to compute several independent variables which are used as input to an SVM regression model, with the dependent variables for the SVM model derived from evaluation scores assigned to each session of toothbrushing by a dentist who specializes in dental care instruction. Using this combination of audio-based activity recognition and SVM regression, our method is able to take smartphone audio data as input and output evaluation score estimates that closely correspond to the evaluation scores assigned by the dentist participating in our research.\n------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.24(2016) No.2 (online)DOI　http://dx.doi.org/10.2197/ipsjjip.24.302------------------------------

This paper presents a method for evaluating toothbrushing performance using audio data collected by a smartphone. This method first conducts activity recognition on the audio data to classify segments of the data into several classes based on the brushing location and type of brush stroke. These recognition results are then used to compute several independent variables which are used as input to an SVM regression model, with the dependent variables for the SVM model derived from evaluation scores assigned to each session of toothbrushing by a dentist who specializes in dental care instruction. Using this combination of audio-based activity recognition and SVM regression, our method is able to take smartphone audio data as input and output evaluation score estimates that closely correspond to the evaluation scores assigned by the dentist participating in our research.\n------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.24(2016) No.2 (online)DOI　http://dx.doi.org/10.2197/ipsjjip.24.302------------------------------

収録刊行物

• 情報処理学会論文誌

  情報処理学会論文誌 57 (3), 2016-03-15

キーワード

• [特集：学生・若手研究者論文] toothbrushing, healthcare, smartphone, audio

詳細情報

• CRID: 1050282812883759488
• NII論文ID: 170000130898
• NII書誌ID: AN00116647
• ISSN: 18827764
• Web Site: http://id.nii.ac.jp/1001/00158085/
• 本文言語コード: en
• 資料種別: journal article
• データソース種別:
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