skip to main content
research-article

FinDroidHR: Smartwatch Gesture Input with Optical Heartrate Monitor

Authors Info & Claims
Published:26 March 2018Publication History
Skip Abstract Section

Abstract

We present FinDroidHR, a novel gesture input technique for off-the-shelf smartwatches. Our technique is designed to detect 10 hand gestures on the hand wearing a smartwatch. The technique is enabled by analysing features of the Photoplethysmography (PPG) signal that optical heart-rate sensors capture. In a study with 20 participants, we show that FinDroidHR achieves 90.55% accuracy and 90.73% recall. Our work is the first study to explore the feasibility of using optical sensors on the off-the-shelf wearable devices to recognise gestures. Without requiring bespoke hardware, FinDroidHR can be readily used on existing smartwatches.

References

  1. Gregory D Abowd. 2012. What next, ubicomp?: celebrating an intellectual disappearing act. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing. ACM, 31--40. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Nasimuddin Ahmed, Rohan Banerjee, Avik Ghose, and Arijit Sinharay. 2015. Feasibility Analysis for Estimation of Blood Pressure and Heart Rate using a Smart Eye Wear. In Proc. WearSys 2015. ACM Press, 9--14. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Nazneen Akhter, Sumegh Tharewal, Vijay Kale, Ashish Bhalerao, and K.V. Kale. 2016. Heart-Based Biometrics and Possible Use of Heart Rate Variability in Biometric Recognition Systems. Advances in Intelligent Systems and Computing 395 (2016), 15--29.Google ScholarGoogle ScholarCross RefCross Ref
  4. Daniel Ashbrook, Kent Lyons, and Thad Starner. 2008. An Investigation into Round Touchscreen Wristwatch Interaction. In Proc. MobileHCI 2008. ACM Press, 311--314. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. IEEE Standards Association. 2003. IEEE Standard for Transitions, Pulses, and Related Waveforms. In IEEE Std. 181-2003. IEEE Press.Google ScholarGoogle Scholar
  6. Hamed Azami, Karim Mohammadi, and Behzad Bozorgtabar. 2012. An Improved Signal Segmentation Using Moving Average and Savitzky-Golay Filter. Journal of Signal and Information Processing 3 (2012), 39--44.Google ScholarGoogle ScholarCross RefCross Ref
  7. Nick Barnes. 2005. Improved Signal To Noise Ratio And Computational Speed For Gradient-Based Detection Algorithms. In International Conference on Robotics and Automation 2005. IEEE Press, 4661--4667.Google ScholarGoogle Scholar
  8. Patrick Baudisch and Gerry Chu. 2009. Back-of-Device Interaction Allows Creating Very Small Touch Devices. In Proc. CHI 2009. ACM Press, 1923--1932. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Jorge Blasco, Thomas M. Chen, Juan Tapiador, and Pedro Peris-Lopez. 2016. A Survey of Wearable Biometric Recognition Systems. In Proc. CSUR 2016. ACM Press.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Liwei Chan, Rong-Hao Liang, Ming-Chang Tsai, Kai-Yin Cheng, Chao-Huai Su, Mike Y. Chen, Wen-Huang Cheng, and Bing-Yu Chen. 2013. FingerPad: Private and Subtle Interaction Using Fingertips. In Proc. UIST 2013. ACM Press, 255--260. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Jikai Chen, Yanhui Dou, Yang Li, and Jiang Li. 2016. Application of Shannon Wavelet Entropy and Shannon Wavelet Packet Entropy in Analysis of Power System Transient Signals. Entropy 2016 18 (2016), 14.Google ScholarGoogle Scholar
  12. Ke-Yu Chen, Kent Lyons, Sean White, and Shwetak Patel. 2013. uTrack: 3D Input Using Two Magnetic Sensors. In Proc. UIST 2013. ACM Press, 237--244. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Sangita Das, Saurabh Pal, and Madhuchhanda Mitra. 2016. Real Time Heart Rate Detection from PPG Signal in Noisy Environment. In Proc. ICICPI 2016. IEEE Press, 70--73.Google ScholarGoogle ScholarCross RefCross Ref
  14. Artem Dementyev and Joseph A. Paradiso. 2014. WristFlex: Low-Power Gesture Input with Wrist-Worn Pressure Sensors. In Proc. UIST 2014. ACM Press, 161--166. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Tizen Developers. 2017. Heart Rate Monitor LED Green Sensor. (2017). https://developer.tizen.org/development/guides/native-application/location-and-sensors/device-sensors#hrm_irGoogle ScholarGoogle Scholar
  16. Florian Grutzmacher, Johann-Peter Wolff, and Christian Haubelt. 2015. Exploiting Thread-Level Parallelism in Template-Based Gesture Recognition with Dynamic Time Warping. In Proc. WOAR 2015. ACM Press, 6. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Sidhant Gupta, Dan Morris, Shwetak N Patel, and Desney Tan. 2012. SoundWave: Using the Doppler Effect to Sense Gestures. In Proc. CHI 2012. ACM Press, 1911--1914. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Da-Yuan Huang, Liwei Chan, Shuo Yang, Fan Wang, Rong-Hao Liang, De-Nian Yang, Yi-Ping Hung, and Bing-Yu Chen. 2016. DigitSpace: Designing Thumb-to-Fingers Touch Interfaces for One-Handed and Eyes-Free Interactions. In Proc. CHI 2016. ACM Press, 1526--1537. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Bryce Kellogg, Vamsi Talla, and Shyamnath Gollakota. 2014. Bringing gesture recognition to all devices. In Proc. NSDI 2014. ACM Press, 303--316. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Frederic Kerber, Markus Lochtefeld, Antonio Kruger, Jess Mcintosh, Charlie McNeill, and Mike Fraser. 2016. Understanding Same-Side Interactions with Wrist-Worn Devices. In Proc. NordiCHI 2016. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Jungsoo Kim, Jiasheng He, Kent Lyons, and Thad Starner. 2007. The Gesture Watch: A Wireless Contact-free Gesture based Wrist Interface. In Proc. ISWC 2007. IEEE Press, 1--8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Min Sik Kim, Taekhyun Kim, Yong-June Shin, Simon S. Lam, and Edward J. Powers. 2008. A wavelet-based approach to detect shared congestion. In IEEE/ACM Trans. Netw 2008. IEEE Press, 763--776. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Vassilis Kostakos and Mirco Musolesi. 2017. Avoiding Pitfalls When Using Machine Learning in HCI Studies. INTERACTIONS (2017). Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Sven Kratz and Michael Rohs. MobileHCI. Hoverflow: Exploring Around-Device Interaction with IR Distance Sensors. In Proc. MobileHCI 2009. ACM Press, 4. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Gierad Laput, Robert Xiao, Xiang Anthony' Chen, Scott E. Hudson, and Chris Harrison. 2014. Skin Buttons: Cheap, Small, Low-Power and Clickable Fixed-Icon Laser Projections. In Proc. UIST 2014. ACM Press, 389--394. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. YANN LECUN, LEON BOTTOU, YOSHUA BENGIO, and PATRICK HAFFNER. 1998. Gradient-Based Learning Applied to Document Recognition. In Proc. IEEE 1998. IEEE Press, 2278--2324.Google ScholarGoogle Scholar
  27. Zhiyuan Lu, Xiang Chen, Qiang Li, Xu Zhang, and Ping Zhou. 2014. A Hand Gesture Recognition Framework and Wearable Gesture-Based Interaction Prototype for Mobile Devices. In Proc. HUMAN-MACHINE SYSTEMS 2014. IEEE Press, 293--299.Google ScholarGoogle ScholarCross RefCross Ref
  28. Yuka Maeda, Masaki Sekine, and Toshiyo Tamura. 2011. Relationship Between Measurement Site and Motion Artifacts in Wearable Reflected Photoplethysmography. Journal of Medical Systems 39, 5(2011), 969--976. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. HENRY MARTIN, PAUL GROVES, and MARK NEWMAN. 2016. The Limits of In-Run Calibration of MEMS Inertial Sensors and Sensor Arrays. NAVIGATION: Journal of The Institute of Navigation 63 (2016).Google ScholarGoogle Scholar
  30. Jess Mcintosh, Asier Marzo, Mike Fraser, and Carol Phillips. 2017. EchoFlex: Hand Gesture Recognition using Ultrasound Imaging. In Proc. CHI 2017. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Kei Nakatsuma, Hiroyuki Shinoda, Yasutoshi Makino, Katsunari Sato, and Takashi Maeno. 2011. Touch Interface on Back of the Hand. In Proc. SIGGRAPH 2011. ACM Press, 1. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Rajalakshmi Nandakumar, Vikram Iyer, Desney Tan, and Shyamnath Gollakota. 2016. FingerIO: Using Active Sonar for Fine-Grained Finger Tracking. In Proc. CHI 2016. ACM Press, 1515--1525. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Simon T. Perrault, Eric Lecolinet, James Eagan, and Yves Guiard. 2013. WatchIt: Simple Gestures and Eyes-free Interaction for Wristwatches and Bracelets. In Proc. CHI 2013. ACM Press, 1451--1460. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Raj Rakshit, V Ramu Reddy, and Parijat Deshpande. 2016. Emotion Detection and Recognition using HRV Features Derived from Photoplethysmogram Signals. In Proc. ERM4CT 2016. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Marko Robnik-Sikonja and Igor Kononenko. 2003. Theoretical and Empirical Analysis of ReliefF and RReliefF. In Machine Learning, 53, 2003. 23--69. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. T. Scott Saponas, Chris Harrison, and Hrvoje Benko. 2011. PocketTouch: Through-Fabric Capacitive Touch Input. In Proc. UIST 2011. ACM Press, 303--308. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. T. Scott Saponas, Desney S. Tan, Dan Morris, Jim Turner, and James A. Landay. 2010. Making Muscle-Computer Interfaces More Practical. In Proc. CHI 2010. ACM Press, 851--854. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Mads Soegaard and Rikke Friis Dam. 2013. The Encyclopedia of Human-Computer Interaction, 2nd Ed. (2nd ed.). The Interaction Design Foundation.Google ScholarGoogle Scholar
  39. Li Sun, Souvik Sen, Dimitrios Koutsonikolas, and Kyu-Han Kim. 2015. WiDraw: Enabling Hands-free Drawing in the Air on Commodity WiFi Devices. In Proc. Mobicom 2015. ACM Press, 77--89. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. S.K. Deric Tang, Y.Y. Sebastian Goh, M.L. Dennis Wong, and Y.L. Eileen Lew. 2016. PPG signal reconstruction using a combination of discrete wavelet transform and empirical mode decomposition. In Proc. ICIAS 2016. IEEE Press.Google ScholarGoogle Scholar
  41. H. Emrah Tasli, Amogh Gudi, and Marten den Uyl. 2014. Integrating Remote PPG in Facial Expression Analysis Framework. In Proc. ICMI 2014. ACM Press, 74--75. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. Ihor Vasyltsov and Seunghwan Lee. 2015. Entropy Extraction from Bio-Signals in Healthcare IoT. In Proc. IoTPTS 2015. ACM Press, 11--17. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Martin Weigel, Tong Lu, Gilles Bailly, Antti Oulasvirta, Carmel Majidi, and Jurgen Steimle. 2015. iSkin: Flexible, Stretchable and Visually Customizable On-Body Touch Sensors for Mobile Computing. In Proc. CHI 2015. ACM Press, 2991--3000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Martin Weigel, Aditya Shekhar, Nittala1 Alex Olwal, and Jurgen Steimle. 2017. SkinMarks: Enabling Interactions on Body Landmarks Using Conformal Skin Electronics. In Proc. CHI 2017. ACM Press, 3095--3105. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. Hongyi Wen, Julian Ramos Rojas, and Anind K. Dey. 2016. Serendipity: Finger Gesture Recognition using an Off-the-Shelf Smartwatch. In Proc. CHI 2016. ACM Press, 3847--3851. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. Robert Xiao, Gierad Laput, and Chris Harrison. 2014. Expanding the Input Expressivity of Smartwatches with Mechanical Pan, Twist, Tilt and Click. In Proc. CHI 2014. ACM Press, 193--196. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Liu Xing and Qian Feng. 2016. Measuring and optimizing android smartwatch energy consumption: poster. In Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking. ACM, 421--423. Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. Chao Xu, Parth H. Pathak, and Prasant Mohapatra. 2014. Finger-writing with Smartwatch: A Case for Finger and Hand Gesture Recognition using Smartwatch. In Proc. HotMobile 2015. ACM Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. Yalan Ye, Wenwen He, Yunfei Cheng, Wenxia Huang, and Zhilin Zhang. 2017. A Robust Random Forest-Based Approach for Heart Rate Monitoring Using Photoplethysmography Signal Contaminated by Intense Motion Artifacts. MDPI 385 (2017).Google ScholarGoogle Scholar
  50. Xiaobo Zhang and Xiangchu Feng. 2014. A New Gradient-based Nonlinear Diffusion Method Applied to Image Denoising. In Proc. PIC 2014. IEEE Press, 321--315.Google ScholarGoogle ScholarCross RefCross Ref
  51. Yang Zhang, Junhan Zhou, Gierad Laput, and Chris Harrison. 2016. SkinTrack: Using the Body as an Electrical Waveguide for Continuous Finger Tracking on the Skin. In Proc. CHI 2016. ACM Press, 1491--1503. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. FinDroidHR: Smartwatch Gesture Input with Optical Heartrate Monitor

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in

          Full Access

          • Published in

            cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
            Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies  Volume 2, Issue 1
            March 2018
            1370 pages
            EISSN:2474-9567
            DOI:10.1145/3200905
            Issue’s Table of Contents

            Copyright © 2018 ACM

            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 26 March 2018
            • Accepted: 1 January 2018
            • Revised: 1 November 2017
            • Received: 1 August 2017
            Published in imwut Volume 2, Issue 1

            Permissions

            Request permissions about this article.

            Request Permissions

            Check for updates

            Qualifiers

            • research-article
            • Research
            • Refereed

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader