research-article

Are we synchronized? Measure synchrony in team sports using a network of wireless accelerometers

Authors:

Daniel Cesarini,

Giovanni Lelli,

Marco AvvenutiAuthors Info & Claims

IWWISS '14: Proceedings of the 2014 International Workshop on Web Intelligence and Smart Sensing

Pages 1 - 6

https://doi.org/10.1145/2637064.2637104

Published: 01 September 2014 Publication History

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Abstract

Movements synchronism is a key parameter for team sports. To determine whether human movements in rowing are synchronous or not, we developed a system that acquires signals through accelerometers and compares those signals using correlation. System components are tuned to reduce the delay between the time at which the action occurs and the one the system produces the output. We present an application to help training synchronized movements and use it to test the system with elite rowing athletes. The system generates the output within 500 ms from the moment of the movement.

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Cited By

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Prakash NRamakrishnan AVader DGoodill SBeardall NMoore RShim M(2025)Two ways to measure interpersonal synchrony in dance/movement therapy: Comparing accelerometer data with observational dataThe Arts in Psychotherapy10.1016/j.aip.2024.10224592(102245)Online publication date: Mar-2025
https://doi.org/10.1016/j.aip.2024.102245
Wang Z(2024)Methodology for Human Activity Recognition Based on Wearable Sensor NetworksActivity Recognition and Prediction for Smart IoT Environments10.1007/978-3-031-60027-2_2(19-46)Online publication date: 27-May-2024
https://doi.org/10.1007/978-3-031-60027-2_2
Liu LLiu JQiu SWang ZZhao HHabib MWang Y(2023)Kinematics Analysis of Arms in Synchronized Canoeing With Wearable Inertial Measurement UnitIEEE Sensors Journal10.1109/JSEN.2023.323492923:5(4983-4993)Online publication date: 1-Mar-2023
https://doi.org/10.1109/JSEN.2023.3234929
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Index Terms

Are we synchronized? Measure synchrony in team sports using a network of wireless accelerometers
1. Human-centered computing
  1. Human computer interaction (HCI)

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Information

Published In

IWWISS '14: Proceedings of the 2014 International Workshop on Web Intelligence and Smart Sensing

September 2014

109 pages

ISBN:9781450327473

DOI:10.1145/2637064

Editors:
Pierre Maret,
Satoshi Honda,
Program Chairs:
Rajendra Akerkar
Western Norway Research Institute, Norway
,
Fuyuki Ishikawa
National Institute of Informatics, Japan
,
Takuro Yonezawa
Keio University, Japan
,
Till Riedel
University of Karlsruhe, Germany
,
Publications Chair:
Martin Alexander Neumann
University of Karlsruhe, Germany

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].

In-Cooperation

Keio University: Keio University
WNRI: Western Norway Research Institute

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2014

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IWWISS '14

IWWISS '14: International Workshop on Web Intelligence and Smart Sensing

September 1 - 2, 2014

Saint Etienne, France

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IWWISS '14 Paper Acceptance Rate 12 of 18 submissions, 67%;

Overall Acceptance Rate 12 of 18 submissions, 67%

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Cited By

View all

Prakash NRamakrishnan AVader DGoodill SBeardall NMoore RShim M(2025)Two ways to measure interpersonal synchrony in dance/movement therapy: Comparing accelerometer data with observational dataThe Arts in Psychotherapy10.1016/j.aip.2024.10224592(102245)Online publication date: Mar-2025
https://doi.org/10.1016/j.aip.2024.102245
Wang Z(2024)Methodology for Human Activity Recognition Based on Wearable Sensor NetworksActivity Recognition and Prediction for Smart IoT Environments10.1007/978-3-031-60027-2_2(19-46)Online publication date: 27-May-2024
https://doi.org/10.1007/978-3-031-60027-2_2
Liu LLiu JQiu SWang ZZhao HHabib MWang Y(2023)Kinematics Analysis of Arms in Synchronized Canoeing With Wearable Inertial Measurement UnitIEEE Sensors Journal10.1109/JSEN.2023.323492923:5(4983-4993)Online publication date: 1-Mar-2023
https://doi.org/10.1109/JSEN.2023.3234929
Worsey MEspinosa HShepherd JThiel D(2019)A Systematic Review of Performance Analysis in Rowing Using Inertial SensorsElectronics10.3390/electronics81113048:11(1304)Online publication date: 7-Nov-2019
https://doi.org/10.3390/electronics8111304
Wang ZYang NGuo MZhao H(2019)Human-Human Interactional Synchrony Analysis Based on Body Sensor NetworksIEEE Transactions on Affective Computing10.1109/TAFFC.2017.272594910:3(407-416)Online publication date: 1-Jul-2019
https://doi.org/10.1109/TAFFC.2017.2725949
Ciuti GRicotti LMenciassi ADario P(2015)MEMS Sensor Technologies for Human Centred Applications in Healthcare, Physical Activities, Safety and Environmental Sensing: A Review on Research Activities in ItalySensors10.3390/s15030644115:3(6441-6468)Online publication date: 17-Mar-2015
https://doi.org/10.3390/s150306441

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