short-paper

ISwimCoach: A Smart Coach guiding System for Assisting Swimmers Free Style Strokes: ISwimCoach

Authors:

Hossam Mohamed,

Mostafa Hammad,

Ayman AtiaAuthors Info & Claims

ICMI '20 Companion: Companion Publication of the 2020 International Conference on Multimodal Interaction

Pages 265 - 269

https://doi.org/10.1145/3395035.3425314

Published: 27 December 2020 Publication History

Abstract

In sports, coaching remains an essential aspect of the efficiency of the athlete's performance. This paper proposes a wrist wearable assistant for the swimmer called iSwimCoach. The key aim behind the system is to detect and analyze incorrect swimming patterns in a free crawl swimming style using an accelerometer sensor. iSwimCoach collects patterns of a swimmer's stream which enables it to detect the strokes to be analyzed in real-time. Therefore, introducing quick and efficient self-coaching feature for mid-level athlete to enhance their swimming style. In our research, we were able to monitor athlete strokes underwater and hence assist swimming coaches. The proposed system was able to classify four types of strokes done by mid-level players (correct strokes, wrong recovery, wrong hand entry and wrong high elbow). The system informs both the swimmer and the coach when an incorrect movement is detected. iSwimCoach achieved 91% accuracy for the detection and classification of incorrect strokes by a fast non expensive dynamic time warping algorithm. These readings analyzed in real-time to automatically generate reports for the swimmer and coach.

References

[1]

[n.d.]. 25 Great Reasons to Start Swimming Now. https://www.thespruce.com/great-reasons-to-swim-2736611

[2]

Inc Advanced Solutions International. [n.d.]. Preventing Swimming Injuries. https://www.stopsportsinjuries.org/STOP/STOP/Prevent_Injuries/Swimming_Injury_Prevention.aspx

[3]

A. Akl and S. Valaee. 2010. Accelerometer-based gesture recognition via dynamic-time warping, affinity propagation, amp; compressive sensing. In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. 2270--2273. https://doi.org/10.1109/ICASSP.2010.5495895

[4]

Marc Bachlin, Kilian Förster, and Gerhard Tröster. 2009. SwimMaster: A Wearable Assistant for Swimmer. Proceedings of the 11th International Conference on Ubiquitous Computing, Vol. 53, 10 (2009), 215--224.

Digital Library

[5]

Amos Binks and J. R. Green. 2013. Calibration Interface for the Electronic Swim Coach. CMBES Proceedings, Vol. 36, 1 (May 2013). https://proceedings.cmbes.ca/index.php/proceedings/article/view/413

[6]

Farzin Dadashi, Florent Crettenand, Grégoire P. Millet, Ludovic Seifert, John Komar, and Kamiar Aminian. 2013. Automatic front-crawl temporal phase detection using adaptive filtering of inertial signals. Journal of Sports Sciences, Vol. 31, 11 (2013), 1251--1260. https://doi.org/10.1080/02640414.2013.778420 23560703.

[7]

Neil Davey, Megan Anderson, and Daniel A. James. 2008. Validation trial of an accelerometer-based sensor platform for swimming. Sports Technology, Vol. 1, 4--5 (2008), 202--207.

[8]

Sander Ganzevles, Rik Vullings, Peter Jan Beek, Hein A. M. Daanen, and Martin Truijens. 2017. Using Tri-Axial Accelerometry in Daily Elite Swim Training Practice. Rehabilitation Research and Development (2017).

[9]

R. M. Hagem, S. G. O'Keefe, T. Fickenscher, and D. V. Thiel. 2013. Self Contained Adaptable Optical Wireless Communications System for Stroke Rate During Swimming. IEEE Sensors Journal, Vol. 13, 8 (2013), 3144--3151.

[10]

D. A. James, Norman Davey, and Theora Rice. 2004. An accelerometer based sensor platform for insitu elite athlete performance analysis. Proceedings of IEEE Sensors, 2004. (2004), 1373--1376 vol.3.

[11]

Yoshihisa Kon, Yuto Omae, Kazuki Sakai, Hirotaka Takahashi, Takuma Akiduki, Chikara Miyaji, Yoshihisa Sakurai, Nobuo Ezaki, and Kazufumi Nakai. 2015. Toward Classification of Swimming Style by Using Underwater Wireless Accelerometer Data. ACM (2015), 85--88.

Digital Library

[12]

Joe Marshall. 2013. Smartphone Sensing for Distributed Swim Stroke Coaching and Research. In Proceedings of the 2013 ACM Conference on Pervasive and Ubiquitous Computing Adjunct Publication (Zurich, Switzerland) (UbiComp '13 Adjunct). ACM, New York, NY, USA, 1413--1416. https://doi.org/10.1145/2494091.2496036

Digital Library

[13]

Robert Mooney, Gavin Corley, Alan Godfrey, Conor Osborough, John Newell, Leo Quinlan, and Gearóid ÓLaighin. 2015a. Analysis of swimming performance: perceptions and practices of US-based swimming coaches. Journal of sports sciences, Vol. 34 (09 2015), 1--9. https://doi.org/10.1080/02640414.2015.1085074

[14]

Robert Mooney, Gavin Corley, Alan Godfrey, Leo R. Quinlan, and Gearóid ÓLaighin. 2015b. Inertial sensor technology for elite swimming performance analysis: A systematic review. Sensors, Vol. 16, 1 (25 dec 2015). https://doi.org/10.3390/s16010018

[15]

NSRE. 2000. National Survey on Recreation and the Environment 2000--2002. The Interagency National Survey Consortium Coordinated by the USDA Forest Service Recreation Wilderness and Demographics Trends Research Group and the University of Tennessee Human Dimensions Research Laboratory. University of Tennessee; Knoxville, TN: 2004. (2000).

[16]

Department of Health & Human Services. 2013. Swimming - health benefits. Better Health Channel (Aug 2013). https://www.betterhealth.vic.gov.au/health/healthyliving/swimming-health-benefits

[17]

Yuji Ohgi, Hiroshi Ichikawa, and Chikara Miyaji. 2002. Microcomputer-based acceleration sensor device for swimming stroke monitoring. JSME International Journal, Series C: Mechanical Systems, Machine Elements and Manufacturing, Vol. 45, 4 (12 2002), 960--966. https://doi.org/10.1299/jsmec.45.960

[18]

M L Sein, J Walton, J Linklater, R Appleyard, B Kirkbride, D Kuah, and G A Murrell. 2010. Shoulder pain in elite swimmers: primarily due to swim-volume-induced supraspinatus tendinopathy. https://www.ncbi.nlm.nih.gov/ /18463295

[19]

S E Slawson, L M Justham, P P Conway, T Le-Sage, and A A West. 2011. Characterizing the swimming tumble turn using acceleration data. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, Vol. 226, 1 (2011), 3--15. https://doi.org/10.1177/1754337111428395

[20]

S. E. Slawson, L. M. Justham, A. A. West, P. P. Conway, M. P. Caine, and R. Harrison. 2008. Accelerometer Profile Recognition of Swimming Strokes (P17). In The Engineering of Sport 7. Springer Paris, Paris, 81--87.

[21]

Andy Stamm and David Thiel. 2015. Investigating Forward Velocity and Symmetry in Freestyle Swimming Using Inertial Sensors. Procedia Engineering, Vol. 112 (12 2015), 522--527. https://doi.org/10.1016/j.proeng.2015.07.236

[22]

D. Tarasevi?ius and A. Serackis. 2020. Deep Learning Model for Sensor based Swimming Style Recognition. In 2020 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream). 1--4.

[23]

I Yustres, R Mart'in, L Fernández, and JM González-Ravé. 2017. Swimming championship finalist positions on success in international swimming competitions. PloS one, Vol. 12, 11 (2017), e0187462.

Cited By

Vec VTomažič SKos AUmek A(2024)Trends in real-time artificial intelligence methods in sports: a systematic reviewJournal of Big Data10.1186/s40537-024-01026-011:1Online publication date: 26-Oct-2024
https://doi.org/10.1186/s40537-024-01026-0
Dobiasch MOppl SStöckl MBaca A(2023)Pegasos: a framework for the creation of direct mobile coaching feedback systemsJournal on Multimodal User Interfaces10.1007/s12193-023-00411-y18:1(1-19)Online publication date: 12-Sep-2023
https://doi.org/10.1007/s12193-023-00411-y
Hamidi Rad MGremeaux VMassé FDadashi FAminian K(2022)SmartSwim, a Novel IMU-Based Coaching AssistanceSensors10.3390/s2209335622:9(3356)Online publication date: 27-Apr-2022
https://doi.org/10.3390/s22093356
Show More Cited By

Index Terms

ISwimCoach: A Smart Coach guiding System for Assisting Swimmers Free Style Strokes: ISwimCoach
1. Applied computing
2. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction techniques
      1. Gestural input

Index terms have been assigned to the content through auto-classification.

Recommendations

Technical Support System for Baseball Beginners by Analyzing Batting Stance with Sensors
MoMM2018: Proceedings of the 16th International Conference on Advances in Mobile Computing and Multimedia

Recently a support system that improves sports skills using sensor or video camera data is attracting great attention. Since most of these systems are developed for professional athletes, few are available for beginners. In baseball, hitting skills are ...
A multi-sensor deep learning approach for complex daily living activity recognition
DigiBiom '22: Proceedings of the 2022 Workshop on Emerging Devices for Digital Biomarkers

With the ever increasing elderly population, human activity trackers can help monitor the daily physical activities performed by the elderly in order to contribute towards improvements in independent living and quality of life.

Little activity ...
Dungeons & swimmers: designing an interactive exergame for swimming
UbiComp '13 Adjunct: Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication

We propose Dungeons & Swimmers, an interactive audio- and motion-based exergame for swimming. As the first of its kind, we explore its design considerations and opportunities stemming from swimming. We gamify the four different stroke types with an ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

ICMI '20 Companion: Companion Publication of the 2020 International Conference on Multimodal Interaction

October 2020

548 pages

ISBN:9781450380027

DOI:10.1145/3395035

General Chairs:
Khiet Truong
University of Twente, the Netherlands
,
Dirk Heylen
University of Twente, the Netherlands
,
Mary Czerwinski
Microsoft Research, USA
,
Program Chairs:
Nadia Berthouze
University College London, United Kingdom
,
Mohamed Chetouani
Sorbonne University, France
,
Mikio Nakano
C4A Research Institute, Japan

Copyright © 2020 ACM.

© 2020 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

Sponsors

SIGCHI: ACM Special Interest Group on Computer-Human Interaction

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 December 2020

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Short-paper

Conference

ICMI '20

Sponsor:

SIGCHI

ICMI '20: INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION

October 25 - 29, 2020

Virtual Event, Netherlands

Acceptance Rates

Overall Acceptance Rate 453 of 1,080 submissions, 42%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
96
Total Downloads

Downloads (Last 12 months)9
Downloads (Last 6 weeks)1

Reflects downloads up to 01 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Vec VTomažič SKos AUmek A(2024)Trends in real-time artificial intelligence methods in sports: a systematic reviewJournal of Big Data10.1186/s40537-024-01026-011:1Online publication date: 26-Oct-2024
https://doi.org/10.1186/s40537-024-01026-0
Dobiasch MOppl SStöckl MBaca A(2023)Pegasos: a framework for the creation of direct mobile coaching feedback systemsJournal on Multimodal User Interfaces10.1007/s12193-023-00411-y18:1(1-19)Online publication date: 12-Sep-2023
https://doi.org/10.1007/s12193-023-00411-y
Hamidi Rad MGremeaux VMassé FDadashi FAminian K(2022)SmartSwim, a Novel IMU-Based Coaching AssistanceSensors10.3390/s2209335622:9(3356)Online publication date: 27-Apr-2022
https://doi.org/10.3390/s22093356
Dobiasch MOppl SStöckl MBaca A(2022)Direct Mobile Coaching as a Paradigm for the Creation of Mobile Feedback SystemsApplied Sciences10.3390/app1211555812:11(5558)Online publication date: 30-May-2022
https://doi.org/10.3390/app12115558
Tamer SAtia A(2022)Recognition of Butterfly strokes using different Machine Learning Models2022 International Conference on Electrical, Computer and Energy Technologies (ICECET)10.1109/ICECET55527.2022.9872896(1-6)Online publication date: 20-Jul-2022
https://doi.org/10.1109/ICECET55527.2022.9872896

View Options

Login options

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

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents