Demo: Drumming application using commodity wearable devices

• Main Authors: DWIVEDI, Bharat, MISRA, Archan, LEE, Youngki
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: SmartPhone; smart watch; Hidden Markov Model (HMM); Computer Sciences; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3277; https://ink.library.smu.edu.sg/context/sis_research/article/4279/viewcontent/9923527.pdf
• Institution: Singapore Management University

We aim to develop a drumming application in which individual can play drums using multiple wearable and mobile devices. Our vision is to tap out different rythms in the air using smart watches as a virtual drum stick and smart phone would act as a drum kit. Same user interface can be visualized in smart glasses. Here, our prime target is to use multiple commodity wearable devices (non-commodity i.e. Myo arm band) and smart phones for recognizing new (or same type of here) types of multi limb gestural context and building an adaptive application interface and allow such gesture recognition and interface to be easily integrated into a new multi device applications. We describe our initial exploration of our aim in multi wrist gesture recognition. We have designed and modified the traditional HMM [2] and discussed the problems faced in multi device interaction. We explore how same type of tapping gestures in drumming context gives the technical challenges and discuss the problems of developing the application and our research direction. The combined multi device ecosystem as a whole can enable not just a variety of new applications but also radically foster new forms of user interaction.