Smart Toothbrushes: Inertial Measurement Sensors Fusion with Visual Tracking
A proper toothbrushing is a crucial aspect to preserve person’s dental health. Furthermore different brushing techniques have been defined for kids, adults and people with different dental appliances, prostheses, partial dentures or oral pathologies. In o
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Abstract. A proper toothbrushing is a crucial aspect to preserve person’s dental health. Furthermore different brushing techniques have been defined for kids, adults and people with different dental appliances, prostheses, partial dentures or oral pathologies. In order to provide a realtime feedback to the user there are, mainly, two approaches: the first one is based on intelligent toothbrushes (called smart toothbrushes) where Inertial Measurement Units, bristles pressure sensor, and also cameras are placed on the toothbrush; data acquired is then transmitted and processed on a smartphone or tablet that monitor the user’s habit and provide him/her with brushing statistics together with suggestions to tune brushing timing and technique. The second approach simplifies the toothbrush device transferring the computational efforts to the handheld device: from the onboard camera it has to track both user’s face and toothbrush in order to extract brushing parameters. In this paper we compare the two approaches concluding that only a fusion of their data can produce an all-around exhaustive analysis of the tooth brushing technique. Keywords: Dental care
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· Target tracking · Toothbrushing analysis
Introduction
Intelligent Toothbrush systems, or, as the are commonly called, Smart Toothbrushes (ST) represent a novel technology in the Cyber Physical Systems context for human healthcare. ST can be equipped with a wide variety of sensors, from IMU [12], to bristles pressure detectors [2], from timers [20] to cameras for teeth analysis [18]. Lot of companies are investing in advanced ST technologies and apps in order to improve toothbrushing habits of everyone; e.g. in order to make the procedure more attractive for kids, usually gamification techniques are adopted: [4,11,17]. A different approach is presented in [5,7] and in our previous work [13] where the toothbrush motion analysis is performed through the camera available on the smartphone or tablet. In this last case a target, that can be easily recognized and tracked, is applied on the toothbrush, and, usually, the face and the facial parts of the used are also tracked. In this paper we compare the two approaches in order to find advantages and disadvantages and to c Springer International Publishing Switzerland 2016 G. Hua and H. J´ egou (Eds.): ECCV 2016 Workshops, Part II, LNCS 9914, pp. 480–494, 2016. DOI: 10.1007/978-3-319-48881-3 33
Smart Toothbrushes: Inertial Measurement Sensors Fusion
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cross-check their accuracy and reliability. We want to underline that the aim of this work is not to compare the manual toothbrush with the electric one but to assert how oral care for kids, adults and people with dental diseases can take great advantage from the next generation of STs.
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Experimental Setup
We equipped a manual toothbrush with a coloured target, according to [13] and with a battery powered G-Module from ST Microelectronics. A picture of the adopted setup is visible in Fig. 1. The G-Module and the Li-ion battery can be easily placed inside the toothbrush han
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