skip to main content
research-article

MicroCam: Leveraging Smartphone Microscope Camera for Context-Aware Contact Surface Sensing

Published: 27 September 2023 Publication History

Abstract

The primary focus of this research is the discreet and subtle everyday contact interactions between mobile phones and their surrounding surfaces. Such interactions are anticipated to facilitate mobile context awareness, encompassing aspects such as dispensing medication updates, intelligently switching modes (e.g., silent mode), or initiating commands (e.g., deactivating an alarm). We introduce MicroCam, a contact-based sensing system that employs smartphone IMU data to detect the routine state of phone placement and utilizes a built-in microscope camera to capture intricate surface details. In particular, a natural dataset is collected to acquire authentic surface textures in situ for training and testing. Moreover, we optimize the deep neural network component of the algorithm, based on continual learning, to accurately discriminate between object categories (e.g., tables) and material constituents (e.g., wood). Experimental results highlight the superior accuracy, robustness and generalization of the proposed method. Lastly, we conducted a comprehensive discussion centered on our prototype, encompassing topics such as system performance and potential applications and scenarios.

Supplementary Material

hu (hu.zip)
Supplemental movie, appendix, image and software files for, MicroCam: Leveraging Smartphone Microscope Camera for Context-Aware Contact Surface Sensing

References

[1]
Chadia Abras, Diane Maloney-Krichmar, Jenny Preece, et al. 2004. User-centered design. Bainbridge, W. Encyclopedia of Human-Computer Interaction. Thousand Oaks: Sage Publications 37, 4 (2004), 445--456.
[2]
Raghav Bansal, Gaurav Raj, and Tanupriya Choudhury. 2016. Blur image detection using Laplacian operator and Open-CV. In 2016 International Conference System Modeling & Advancement in Research Trends (SMART). 63--67. https://doi.org/10.1109/SYSMART.2016. 7894491
[3]
P. Buzzega, M. Boschini, A. Porrello, and S. Calderara. 2021. Rethinking Experience Replay: a Bag of Tricks for Continual Learning. In 2020 25th International Conference on Pattern Recognition (ICPR). IEEE Computer Society, Los Alamitos, CA, USA, 2180--2187. https://doi.org/10.1109/ICPR48806.2021.9412614
[4]
Rajkumar Darbar and Debasis Samanta. 2015. SurfaceSense: Smartphone Can Recognize Where It Is Kept. In Proceedings of the 7th International Conference on HCI, IndiaHCI 2015 (Guwahati, India) (IndiaHCI'15). Association for Computing Machinery, New York, NY, USA, 39--46. https://doi.org/10.1145/2835966.2835971
[5]
Antonella De Angeli, Alistair Sutcliffe, and Jan Hartmann. 2006. Interaction, Usability and Aesthetics: What Influences Users' Preferences?. In Proceedings of the 6th Conference on Designing Interactive Systems (University Park, PA, USA) (DIS '06). Association for Computing Machinery, New York, NY, USA, 271--280. https://doi.org/10.1145/1142405.1142446
[6]
Shohreh Deldari, Hao Xue, Aaqib Saeed, Daniel V. Smith, and Flora D. Salim. 2022. COCOA: Cross Modality Contrastive Learning for Sensor Data. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6, 3, Article 108 (sep 2022), 28 pages. https://doi.org/10.1145/3550316
[7]
Android Developers. 2021. BatteryHistorian. https://developer.android.com/topic/performance/power/setup-battery-historian Accessed: 2021-07-17.
[8]
Anind K Dey. 2001. Understanding and using context. Personal and ubiquitous computing 5, 1 (2001), 4--7.
[9]
Andrew Dillon. 1987. A PSYCHOLOGICAL VIEW OF "USER-FRIENDLINESS". In Human--Computer Interaction--INTERACT '87, H.-J. BULLINGER and B. SHACKEL (Eds.). North-Holland, Amsterdam, 157--163. https://doi.org/10.1016/B978-0-444-70304-0.50034-0
[10]
Zackory Erickson, Sonia Chernova, and Charles C. Kemp. 2017. Semi-Supervised Haptic Material Recognition for Robots using Generative Adversarial Networks. In Proceedings of the 1st Annual Conference on Robot Learning (Proceedings of Machine Learning Research, Vol. 78), Sergey Levine, Vincent Vanhoucke, and Ken Goldberg (Eds.). PMLR, 157--166. https://proceedings.mlr.press/v78/erickson17a.html
[11]
Zackory Erickson, Nathan Luskey, Sonia Chernova, and Charles C. Kemp. 2019. Classification of Household Materials via Spectroscopy. IEEE Robotics and Automation Letters 4, 2 (April 2019), 700--707. https://doi.org/10.1109/LRA.2019.2892593
[12]
Zackory Erickson, Eliot Xing, Bharat Srirangam, Sonia Chernova, and Charles C. Kemp. 2020. Multimodal Material Classification for Robots using Spectroscopy and High Resolution Texture Imaging. In 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 10452--10459. https://doi.org/10.1109/IROS45743.2020.9341165
[13]
Euan Freeman, Gareth Griffiths, and Stephen A. Brewster. 2017. Rhythmic Micro-Gestures: Discreet Interaction on-the-Go. In Proceedings of the 19th ACM International Conference on Multimodal Interaction (Glasgow, UK) (ICMI '17). Association for Computing Machinery, New York, NY, USA, 115--119. https://doi.org/10.1145/3136755.3136815
[14]
Florian Fuchs, Andreas Koenig, David Poppitz, and Sebastian Hahnel. 2020. Application of macro photography in dental materials science. Journal of Dentistry 102 (2020), 103495.
[15]
Kaori Fujinami, Satoshi Kouchi, and Yuan Xue. 2012. Design and Implementation of an On-body Placement-aware Smartphone. In 2012 32nd International Conference on Distributed Computing Systems Workshops. IEEE, 69--74.
[16]
Susan Gasson. 2003. Human-centered vs. user-centered approaches to information system design. Journal of Information Technology Theory and Application (JITTA) 5, 2 (2003), 5.
[17]
Hans W Gellersen, Albrecht Schmidt, and Michael Beigl. 2002. Multi-sensor context-awareness in mobile devices and smart artifacts. Mobile Networks and Applications 7, 5 (2002), 341--351.
[18]
Tiago Guerreiro, Ricardo Gamboa, and Joaquim Jorge. 2009. Mnemonical Body Shortcuts for Interacting with Mobile Devices. Springer-Verlag, Berlin, Heidelberg, 261--271. https://doi.org/10.1007/978-3-540-92865-2_29
[19]
Xiansheng Guo, Shilin Zhu, Lin Li, Fangzi Hu, and Nirwan Ansari. 2019. Accurate WiFi Localization by Unsupervised Fusion of Extended Candidate Location Set. IEEE Internet of Things Journal 6, 2 (2019), 2476--2485. https://doi.org/10.1109/JIOT.2018.2870659
[20]
Chris Harrison and Scott E. Hudson. 2008. Lightweight Material Detection for Placement-Aware Mobile Computing. In Proceedings of the 21st Annual ACM Symposium on User Interface Software and Technology (Monterey, CA, USA) (UIST '08). Association for Computing Machinery, New York, NY, USA, 279--282. https://doi.org/10.1145/1449715.1449761
[21]
Tatsuhito Hasegawa, Satoshi Hirahashi, and Makoto Koshino. 2016. Determining a Smartphone's Placement by Material Detection Using Harmonics Produced in Sound Echoes. In Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Hiroshima, Japan) (MOBIQUITOUS 2016). Association for Computing Machinery, New York, NY, USA, 246--253. https://doi.org/10.1145/2994374.2994389
[22]
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 770--778. https://doi.org/10.1109/CVPR.2016.90
[23]
Shruthi K. Hiremath, Yasutaka Nishimura, Sonia Chernova, and Thomas Plötz. 2022. Bootstrapping Human Activity Recognition Systems for Smart Homes from Scratch. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6, 3, Article 119 (sep 2022), 27 pages. https://doi.org/10.1145/3550294
[24]
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam. 2017. Mobilenets: Efficient convolutional neural networks for mobile vision applications. arXiv preprint arXiv:1704.04861 (2017).
[25]
Sungjae Hwang and Kwangyun Wohn. 2013. VibroTactor: Low-Cost Placement-Aware Technique Using Vibration Echoes on Mobile Devices. In Proceedings of the Companion Publication of the 2013 International Conference on Intelligent User Interfaces Companion (Santa Monica, California, USA) (IUI '13 Companion). Association for Computing Machinery, New York, NY, USA, 73--74. https://doi.org/10.1145/2451176.2451206
[26]
Wendy Ju. 2015. The design of implicit interactions. Synthesis Lectures on Human-Centered Informatics 8, 2 (2015), 1--93.
[27]
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al. 2017. Overcoming catastrophic forgetting in neural networks. Proceedings of the national academy of sciences 114, 13 (2017), 3521--3526.
[28]
Sunmin Lee, Jinah Kim, and Nammee Moon. 2019. Random forest and WiFi fingerprint-based indoor location recognition system using smart watch. Human-centric Computing and Information Sciences 9, 1 (2019), 1--14.
[29]
Hang Li, Xi Chen, Ju Wang, Di Wu, and Xue Liu. 2022. DAFI: WiFi-Based Device-Free Indoor Localization via Domain Adaptation. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5, 4, Article 167 (dec 2022), 21 pages. https://doi.org/10.1145/3494954
[30]
Nicolai Marquardt, Ken Hinckley, and Saul Greenberg. 2012. Cross-Device Interaction via Micro-Mobility and f-Formations. In Proceedings of the 25th Annual ACM Symposium on User Interface Software and Technology (Cambridge, Massachusetts, USA) (UIST '12). Association for Computing Machinery, New York, NY, USA, 13--22. https://doi.org/10.1145/2380116.2380121
[31]
Alexander J. Medeiros, Lee Stearns, Leah Findlater, Chuan Chen, and Jon E. Froehlich. 2017. Recognizing Clothing Colors and Visual Textures Using a Finger-Mounted Camera: An Initial Investigation. In Proceedings of the 19th International ACM SIGACCESS Conference on Computers and Accessibility (Baltimore, Maryland, USA) (ASSETS '17). Association for Computing Machinery, New York, NY, USA, 393--394. https://doi.org/10.1145/3132525.3134805
[32]
Florian Floyd Mueller, Pedro Lopes, Paul Strohmeier, Wendy Ju, Caitlyn Seim, Martin Weigel, Suranga Nanayakkara, Marianna Obrist, Zhuying Li, Joseph Delfa, Jun Nishida, Elizabeth M. Gerber, Dag Svanaes, Jonathan Grudin, Stefan Greuter, Kai Kunze, Thomas Erickson, Steven Greenspan, Masahiko Inami, Joe Marshall, Harald Reiterer, Katrin Wolf, Jochen Meyer, Thecla Schiphorst, Dakuo Wang, and Pattie Maes. 2020. Next Steps for Human-Computer Integration. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI '20). Association for Computing Machinery, New York, NY, USA, 1--15. https://doi.org/10.1145/3313831.3376242
[33]
José Ramón Padilla-López, Alexandros Andre Chaaraoui, and Francisco Flórez-Revuelta. 2015. Visual privacy protection methods: A survey. Expert Systems with Applications 42, 9 (2015), 4177--4195.
[34]
Brice Parilusyan, Marc Teyssier, Valentin Martinez-Missir, Clément Duhart, and Marcos Serrano. 2022. Sensurfaces: A Novel Approach for Embedded Touch Sensing on Everyday Surfaces. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6, 2, Article 67 (jul 2022), 19 pages. https://doi.org/10.1145/3534616
[35]
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019. PyTorch: An Imperative Style, High-Performance Deep Learning Library. In Advances in Neural Information Processing Systems 32. Curran Associates, Inc., 8024--8035. http://papers.neurips.cc/paper/9015- pytorch-an-imperative-style-high-performance-deep-learning-library.pdf
[36]
Jennifer Pearson, Simon Robinson, Matt Jones, Anirudha Joshi, Shashank Ahire, Deepak Sahoo, and Sriram Subramanian. 2017. Chameleon Devices: Investigating More Secure and Discreet Mobile Interactions via Active Camouflaging. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI '17). Association for Computing Machinery, New York, NY, USA, 5184--5196. https://doi.org/10.1145/3025453.3025482
[37]
Massimo Piccardi. 2004. Background subtraction techniques: a review. In 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No. 04CH37583), Vol. 4. IEEE, 3099--3104.
[38]
Henning Pohl, Andreea Muresan, and Kasper Hornbæk. 2019. Charting Subtle Interaction in the HCI Literature. Association for Computing Machinery, New York, NY, USA, 1--15. https://doi.org/10.1145/3290605.3300648
[39]
Hongmei Qian, Meng Xu, Xiaowei Li, Muwei Ji, Lei Cheng, Anwer Shoaib, Jiajia Liu, Lan Jiang, Hesun Zhu, and Jiatao Zhang. 2016. Surface micro/nanostructure evolution of Au--Ag alloy nanoplates: Synthesis, simulation, plasmonic photothermal and surface-enhanced Raman scattering applications. Nano Research 9, 3 (2016), 876--885.
[40]
Aaron Quigley. 2010. From GUI to UUI: Interfaces for ubiquitous computing. Ubiquitous Computing Fundamentals (2010), 237--283.
[41]
A. Quigley, B. Ward, C. Ottrey, D. Cutting, and R. Kummerfeld. 2004. BlueStar, a privacy centric location aware system. In PLANS 2004. Position Location and Navigation Symposium (IEEE Cat. No.04CH37556). 684--689. https://doi.org/10.1109/PLANS.2004.1309060
[42]
Aaron Quigley and David West. 2005. Proximation: Location-awareness though sensed proximity and gsm estimation. In International Symposium on Location-and Context-Awareness. Springer, 363--376.
[43]
Vaskar Raychoudhury, Jiannong Cao, Mohan Kumar, and Daqiang Zhang. 2013. Middleware for pervasive computing: A survey. Pervasive and Mobile Computing 9, 2 (2013), 177--200. https://doi.org/10.1016/j.pmcj.2012.08.006 Special Section: Mobile Interactions with the Real World.
[44]
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy Lillicrap, and Gregory Wayne. 2019. Experience replay for continual learning. Advances in Neural Information Processing Systems 32 (2019).
[45]
Munehiko Sato, Shigeo Yoshida, Alex Olwal, Boxin Shi, Atsushi Hiyama, Tomohiro Tanikawa, Michitaka Hirose, and Ramesh Raskar. 2015. SpecTrans: Versatile Material Classification for Interaction with Textureless, Specular and Transparent Surfaces. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (Seoul, Republic of Korea) (CHI '15). Association for Computing Machinery, New York, NY, USA, 2191--2200. https://doi.org/10.1145/2702123.2702169
[46]
Albrecht Schmidt. 2000. Implicit human computer interaction through context. Personal technologies 4, 2 (2000), 191--199.
[47]
Maximilian Schrapel, Philipp Etgeton, and Michael Rohs. 2021. SpectroPhone: Enabling Material Surface Sensing with Rear Camera and Flashlight LEDs. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3411763.3451753
[48]
Barış Serim and Giulio Jacucci. 2019. Explicating "Implicit Interaction": An Examination of the Concept and Challenges for Research. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI '19). Association for Computing Machinery, New York, NY, USA, 1--16. https://doi.org/10.1145/3290605.3300647
[49]
Dai Shi, Dan Tao, Jiangtao Wang, Muyan Yao, Zhibo Wang, Houjin Chen, and Sumi Helal. 2021. Fine-Grained and Context-Aware Behavioral Biometrics for Pattern Lock on Smartphones. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5, 1, Article 33 (mar 2021), 30 pages. https://doi.org/10.1145/3448080
[50]
Lee Stearns, Leah Findlater, and Jon E. Froehlich. 2018. Applying Transfer Learning to Recognize Clothing Patterns Using a Finger-Mounted Camera. In Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility (Galway, Ireland) (ASSETS '18). Association for Computing Machinery, New York, NY, USA, 349--351. https://doi.org/10.1145/3234695.3241015
[51]
Lee Stearns, Uran Oh, Leah Findlater, and Jon E. Froehlich. 2018. TouchCam: Realtime Recognition of Location-Specific On-Body Gestures to Support Users with Visual Impairments. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 4, Article 164 (jan 2018), 23 pages. https://doi.org/10.1145/3161416
[52]
Constantine Stephanidis, Gavriel Salvendy, Margherita Antona, Jessie YC Chen, Jianming Dong, Vincent G Duffy, Xiaowen Fang, Cali Fidopiastis, Gino Fragomeni, Limin Paul Fu, et al. 2019. Seven HCI grand challenges. International Journal of Human--Computer Interaction 35, 14 (2019), 1229--1269.
[53]
Hossein Taheri and Ahmed Arabi Hassen. 2019. Nondestructive ultrasonic inspection of composite materials: A comparative advantage of phased array ultrasonic. Applied Sciences 9, 8 (2019), 1628.
[54]
Sasha Targ, Diogo Almeida, and Kevin Lyman. 2016. Resnet in resnet: Generalizing residual architectures. arXiv preprint arXiv:1603.08029 (2016).
[55]
Format Team. 2020. The Beginners Guide to Macro Photography. https://www.format.com/magazine/resources/photography/macro-photography-beginners-guide
[56]
Ian Tenney, Dipanjan Das, and Ellie Pavlick. 2019. BERT rediscovers the classical NLP pipeline. arXiv preprint arXiv:1905.05950 (2019).
[57]
Manfred Thüring and Sascha Mahlke. 2007. Usability, aesthetics and emotions in human--technology interaction. International journal of psychology 42, 4 (2007), 253--264.
[58]
Garreth W. Tigwell and Michael Crabb. 2020. Household Surface Interactions: Understanding User Input Preferences and Perceived Home Experiences. Association for Computing Machinery, New York, NY, USA, 1--14. https://doi.org/10.1145/3313831.3376856
[59]
Lesley Trenner. 1987. How to win friends and influence people: definitions of user-friendliness in interactive computer systems. Journal of information science 13, 2 (1987), 99--107.
[60]
Jason Wiese, T. Scott Saponas, and A.J. Bernheim Brush. 2013. Phoneprioception: Enabling Mobile Phones to Infer Where They Are Kept. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Paris, France) (CHI '13). Association for Computing Machinery, New York, NY, USA, 2157--2166. https://doi.org/10.1145/2470654.2481296
[61]
Fuyong Xing, Yuanpu Xie, Hai Su, Fujun Liu, and Lin Yang. 2017. Deep learning in microscopy image analysis: A survey. IEEE transactions on neural networks and learning systems 29, 10 (2017), 4550--4568.
[62]
Susu Xu, Shijia Pan, and Tong Yu. 2020. CML-IOT 2020: The Second Workshop on Continual and Multimodal Learning for Internet of Things. In Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers (Virtual Event, Mexico) (UbiComp-ISWC '20). Association for Computing Machinery, New York, NY, USA, 616--618. https://doi.org/10.1145/3410530.3414613
[63]
Xing-Dong Yang, Tovi Grossman, Daniel Wigdor, and George Fitzmaurice. 2012. Magic finger: always-available input through finger instrumentation. In Proceedings of the 25th annual ACM symposium on User interface software and technology. 147--156.
[64]
Jiung yao Huang and Chung-Hsien Tsai. 2008. Improve GPS positioning accuracy with context awareness. In 2008 First IEEE International Conference on Ubi-Media Computing. 94--99. https://doi.org/10.1109/UMEDIA.2008.4570872
[65]
Hui-Shyong Yeo, Gergely Flamich, Patrick Schrempf, David Harris-Birtill, and Aaron Quigley. 2016. RadarCat: Radar Categorization for Input & Interaction. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology (Tokyo, Japan) (UIST '16). Association for Computing Machinery, New York, NY, USA, 833--841. https://doi.org/10.1145/2984511.2984515
[66]
Hui-Shyong Yeo, Juyoung Lee, Andrea Bianchi, David Harris-Birtill, and Aaron Quigley. 2017. SpeCam: Sensing Surface Color and Material with the Front-Facing Camera of a Mobile Device. In Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services (Vienna, Austria) (MobileHCI '17). Association for Computing Machinery, New York, NY, USA, Article 25, 9 pages. https://doi.org/10.1145/3098279.3098541
[67]
Friedemann Zenke, Ben Poole, and Surya Ganguli. 2017. Continual learning through synaptic intelligence. In International conference on machine learning. PMLR, 3987--3995.

Cited By

View all
  • (2023)LiT: Fine-grained Toothbrushing Monitoring with Commercial LED ToothbrushProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3613287(1-16)Online publication date: 2-Oct-2023

Index Terms

  1. MicroCam: Leveraging Smartphone Microscope Camera for Context-Aware Contact Surface Sensing

    Recommendations

    Comments

    Information & Contributors

    Information

    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 7, Issue 3
    September 2023
    1734 pages
    EISSN:2474-9567
    DOI:10.1145/3626192
    Issue’s Table of Contents
    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: 27 September 2023
    Published in IMWUT Volume 7, Issue 3

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. Sensing
    2. macro-camera
    3. microscope camera
    4. mobile interaction
    5. surface sensing

    Qualifiers

    • Research-article
    • Research
    • Refereed

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)342
    • Downloads (Last 6 weeks)27
    Reflects downloads up to 15 Sep 2024

    Other Metrics

    Citations

    Cited By

    View all
    • (2023)LiT: Fine-grained Toothbrushing Monitoring with Commercial LED ToothbrushProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3613287(1-16)Online publication date: 2-Oct-2023

    View Options

    Get Access

    Login options

    Full Access

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media