ABSTRACT
The rise of smart rings enables for ubiquitous control of computers that are wearable or mobile. We developed a ring interface using a 9 DOF IMU for detecting microgestures that can be executed while performing another task that involve hands, e.g. riding a bicycle. For the gesture classification we implemented 4 classifiers that run on the Android operating system without the need of clutch events. In a user study, we compared the success of 4 classifiers in a cycling scenario. We found that Random Forest (RF) works better for microgesture detection on Android than Dynamic Time Warping (DTW), K-Nearest-Neighbor (KNN), and than a Threshold (TH)-based approach as it has the best detection rate while it runs in real-time on Android. This work shell encourages other researchers to develop further mobile applications for using remote microgesture control in encumbered contexts.
- Gilles Bailly, Jörg Müller, Michael Rohs, Daniel Wigdor, and Sven Kratz. 2012. ShoeSense: A New Perspective on Gestural Interaction and Wearable Applications. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '12). ACM, New York, NY, USA, 1239--1248. DOI: http://dx.doi.org/10.1145/2207676.2208576 Google ScholarDigital Library
- Masaaki Fukumoto and Yoshinobu Tonomura. 1997. "Body Coupled FingerRing": Wireless Wearable Keyboard. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI '97). ACM, New York, NY, USA, 147--154. DOI: http://dx.doi.org/10.1145/258549.258636 Google ScholarDigital Library
- Chris Harrison, Desney Tan, and Dan Morris. 2010. Skinput: Appropriating the Body As an Input Surface. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '10). ACM, New York, NY, USA, 453--462. DOI: http://dx.doi.org/10.1145/1753326.1753394 Google ScholarDigital Library
- Bruce Howard and Susie Howard. 2001. Light-glove: Wrist-Worn Virtual Typing and Pointing. In Proceedings of the 5th IEEE International Symposium on Wearable Computers (ISWC '01). IEEE Computer Society, Washington, DC, USA, 172--173. http://dl.acm.org/citation.cfm?id=580581.856559 Google ScholarDigital Library
- Howell Istance, Richard Bates, Aulikki Hyrskykari, and Stephen Vickers. 2008. Snap Clutch, a Moded Approach to Solving the Midas Touch Problem. In Proceedings of the 2008 Symposium on Eye Tracking Research; Applications (ETRA '08). ACM, New York, NY, USA, 221--228. DOI: http://dx.doi.org/10.1145/1344471.1344523 Google ScholarDigital Library
- Robert J. K. Jacob. 1990. What You Look at is What You Get: Eye Movement-based Interaction Techniques. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '90). ACM, New York, NY, USA, 11--18. DOI: http://dx.doi.org/10.1145/97243.97246 Google ScholarDigital Library
- Lei Jing, Zixue Cheng, and Wang Junbo. 2011. A recognition method for one-stroke finger gestures using a MEMS 3D accelerometer. IEICE transactions on information and systems 94.5, 1062--1072.Google Scholar
- Hamed Ketabdar, Peyman Moghadam, and Mehran Roshandel. 2012. Pingu: A New Miniature Wearable Device for Ubiquitous Computing Environments. 2014 Eighth International Conference on Complex, Intelligent and Software Intensive Systems 0 (2012), 502--506. DOI: http://dx.doi.org/10.1109/CISIS.2012.123 Google ScholarDigital Library
- David Kim, Otmar Hilliges, Shahram Izadi, Alex D. Butler, Jiawen Chen, Iason Oikonomidis, and Patrick Olivier. 2012. Digits: Freehand 3D Interactions Anywhere Using a Wrist-worn Gloveless Sensor. In Proceedings of the 25th Annual ACM Symposium on User Interface Software and Technology (UIST '12). ACM, New York, NY, USA, 167--176. DOI: http://dx.doi.org/10.1145/2380116.2380139 Google ScholarDigital Library
- Jun Rekimoto. 2001. GestureWrist and GesturePad: Unobtrusive Wearable Interaction Devices. In Proceedings of the 5th IEEE International Symposium on Wearable Computers (ISWC '01). IEEE Computer Society, Washington, DC, USA, 21--. http://dl.acm.org/citation.cfm?id=580581.856565 Google ScholarDigital Library
- T. Scott Saponas. 2009. Enabling Always-available Input: Through On-body Interfaces. In CHI '09 Extended Abstracts on Human Factors in Computing Systems (CHIEA '09). ACM, New York, NY, USA, 3117--3120. DOI: http://dx.doi.org/10.1145/1520340.1520441 Google ScholarDigital Library
- Koji Tsukadaa and Michiaki Yasumurab. 2001. Ubifinger: Gesture input device for mobile use. In Proceedings of Ubicomp. 11.Google Scholar
- A. Vardy, J. Robinson, and Li-Te Cheng. 1999. The WristCam as input device. In Wearable Computers, 1999. Digest of Papers. The Third International Symposium on. 199--202. DOI: http://dx.doi.org/10.1109/ISWC.1999.806928 Google ScholarDigital Library
- Katia Vega and Hugo Fuks. 2013. Beauty Technology As an Interactive Computing Platform. In Proceedings of the 2013 ACM International Conference on Interactive Tabletops and Surfaces (ITS '13). ACM, New York, NY, USA, 357--360. DOI: http://dx.doi.org/10.1145/2512349.2512399 Google ScholarDigital Library
- MarkWeiser. 1991. The computer for the 21st century. Scientific american 265, 3 (1991), 94--104.Google Scholar
- Katrin Wolf, Anja Naumann, Michael Rohs, and Jörg Müller. 2011. Taxonomy of Microinteractions: Defining Microgestures Based on Ergonomic and Scenario-dependent Requirements. In Proceedings of the 13th IFIP TC 13 International Conference on Human-computer Interaction - Volume Part I (INTERACT'11). Springer-Verlag, Berlin, Heidelberg, 559--575. http://dl.acm.org/citation.cfm?id=2042053.2042111 Google ScholarDigital Library
- Katrin Wolf, Robert Schleicher, Sven Kratz, and Michael Rohs. 2013. Tickle: A Surface-independent Interaction Technique for Grasp Interfaces. In Proceedings of the 7th International Conference on Tangible, Embedded and Embodied Interaction (TEI '13). ACM, New York, NY, USA, 185--192. DOI: http://dx.doi.org/10.1145/2460625.2460654 Google ScholarDigital Library
Index Terms
- Microgesture detection for remote interaction with mobile devices
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