The paper describes the design of a wearable and wireless system that allows the real-time identification of some gestures performed by basketball players. This system is specifically designed as a support for coaches to track the activity of two or more players simultaneously. Each wearable device is composed of two separate units, positioned on the wrists of the user, connected to a personal computer (PC) via Bluetooth. Each unit comprises a triaxial accelerometer and gyroscope, a microcontroller, installed on a TinyDuino platform, and a battery. The concept of activity recognition chain is investigated and used as a reference for the gesture recognition process. A sliding window allows the system to extract relevant features from the incoming data streams: mean values, standard deviations, maximum values, minimum values, energy, and correlations between homologous axes are calculated to identify and differentiate the performed actions. Machine learning algorithms are implemented to handle the recognition phase.
Issue Section:
Research Papers
References
1.
Lightman
, K.
, 2016
, “Silicon Gets Sporty: Next-Gen Sensors Make Golf Clubs, Tennis Rackets, and Baseball Bats Smarter Than Ever
,” IEEE Spectrum
, 53
(3), pp. 48
–53
.https://spectrum.ieee.org/consumer-electronics/gadgets/nextgen-sensors-make-golf-clubs-tennis-rackets-and-baseball-bats-smarter-than-ever2.
Park
, S.
, Park
, J.
, Al-masni
, M.
, Al-antari
, M.
, Uddin
, M. Z.
, and Kim
, T.-S.
, 2016
, “A Depth Camera-Based Human Activity Recognition Via Deep Learning Recurrent Neural Network for Health and Social Care Services
,” Procedia Comput. Sci.
, 100
, pp. 78
–84
.3.
Ahmadi
, A.
, Rowlands
, D.
, and James
, D. A.
, 2010
, “Towards a Wearable Device for Skill Assessment and Skill Acquisition of a Tennis Player During the First Serve
,” Sports Eng.
, 2
(3–4
), pp. 129
–136
.4.
Mitchell
, E.
, Monaghan
, D.
, and O'Connor
, N. E.
, 2013
, “Classification of Sporting Activities Using Smartphone Accelerometers
,” Sensors (Basel, Switz.)
, 13
(4
), pp. 5317
–5337
.5.
Bai
, L.
, Efstratiou
, C.
, and Ang
, C. S.
, 2016
, “WeSport: Utilising Wrist-Band Sensing to Detect Player Activities in Basketball Games
,” IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops
), Sydney, NSW, Australia, Mar. 14–18.6.
Fox
, J. L.
, Scanlan
, A. T.
, and Stanton
, R.
, 2017
, “A Review of Player Monitoring Approaches in Basketball: Current Trends and Future Directions
,” J. Strength Cond. Res.
, 31
(7
), pp. 2021
–2029
.7.
Staunton
, C.
, Wundersitz
, D.
, Gordon
, B.
, and Kingsley
, M.
, 2017
, “Construct Validity of Accelerometry-Derived Force to Quantify Basketball Movement Patterns
,” Int. J. Sports Med.
, 38
(14
), pp. 1090
–1096
.8.
Kok
, M.
, Hol
, J. D.
, and Schön
, T. B.
, 2017
, “Using Inertial Sensors for Position and Orientation Estimation
,” Found. Trends Signal Process.
, 11
(1–2
), pp. 1
–153
.9.
Altun
, K.
, and Barshan
, B.
, 2010
, “Human Activity Recognition Using Inertial/Magnetic Sensor Units
,” International Workshop on Human Behavior Understanding
, Amsterdam, The Netherlands, Oct. 15–19, pp. 38
–51
.10.
Aminian
, K.
, Robert
, P.
, Buchser
, E. E.
, Rutschmann
, B.
, Hayoz
, D.
, and Depairon
, M.
, 1999
, “Physical Activity Monitoring Based on Accelerometry: Validation and Comparison With Video Observation
,” Med. Biol. Eng. Comput.
, 37
(3
), pp. 304
–308
.11.
Roetenberg
, D.
, Slycke
, P. J.
, and Veltink
, P. H.
, 2007
, “Ambulatory Position and Orientation Tracking Fusing Magnetic and Inertial Sensing
,” IEEE Trans. Biomed. Eng.
, 54
(5
), pp. 883
–890
.12.
Najafi
, B.
, Aminian
, K.
, Paraschiv-Ionescu
, A.
, Loew
, F.
, Büla
, C. J.
, and Robert
, P.
, 2003
, “Ambulatory System for Human Motion Analysis Using a Kinematic Sensor: Monitoring of Daily Physical Activity in the Elderly
,” IEEE Trans. Biomed. Eng.
, 50
(6
), pp. 711
–723
.13.
Tao
, Y.
, Hu
, H.
, and Zhou
, H.
, 2007
, “Integration of Vision and Inertial Sensors for 3D Arm Motion Tracking in Home-Based Rehabilitation
,” Int. J. Rob. Res.
, 26
(6
), pp. 607
–624
.14.
Bao
, L.
, and Intille
, S.
, 2004
, “Activity Recognition From User-Annotated Acceleration Data
,” Pervasive Computing. Pervasive, Lecture Notes in Computer Science
, Vol. 3001, A. Ferscha and F. Mattern, eds., Springer, Berlin, pp. 1
–17
.15.
Ermes
, M.
, Pärkkä
, J.
, Mäntyjärvi
, J.
, and Korhonen
, I.
, 2008
, “Detection of Daily Activities and Sports With Wearable Sensors in Controlled and Uncontrolled Conditions
,” IEEE Trans. Inf. Technol. Biomed.
, 12
(1
), pp. 20
–26
.16.
Leutheuser
, H.
, Schuldhaus
, D.
, and Eskofier
, B. M.
, 2013
, “Hierarchical, Multi-Sensor Based Classification of Daily Life Activities: Comparison With State-of-the-Art Algorithms Using a Benchmark Dataset
,” PLoS One
, 8
(10
), p. e75196
.17.
Ugulino
, W.
, Cardador
, D.
, Vega
, K.
, Velloso
, E.
, Milidiú
, R.
, and Fuks
, H.
, 2012
, “Wearable Computing: Accelerometers' Data Classification of Body Postures and Movements
,” Advances in Artificial Intelligence
(SBIA 2012), Curitiba, Brazil, Oct. 20–25, pp. 52
–61
.18.
Sebestyen
, G.
, Stoica
, I.
, and Hangan
, A.
, 2016
, “Human Activity Recognition and Monitoring for Elderly People
,” IEEE 12th International Conference on Intelligent Computer Communication and Processing
(ICCP
), Cluj-Napoca, Romania, Sept. 8–10, pp. 341
–347
.19.
Bagalà
, F.
, Becker
, C.
, Cappello
, A.
, Chiari
, L.
, Aminian
, K.
, Hausdorff
, J. M.
, Zijlstra
, W.
, and Klenk
, J.
, 2012
, “Evaluation of Accelerometer-Based Fall Detection Algorithms on Real-World Falls
,” PLoS One
, 7
(5
), p. e37062
.20.
Lindemann
, U.
, Hock
, A.
, Stuber
, M.
, Keck
, W.
, and Becker
, C.
, 2005
, “Evaluation of a Fall Detector Based on Accelerometers: A Pilot Study
,” Med. Biol. Eng. Comput.
, 43
(5
), pp. 548
–551
.21.
Lapinski
, M.
, Berkson
, E.
, Gill
, T.
, Reinold
, M.
, and Paradiso
, J. A.
, 2009
, “A Distributed Wearable, Wireless Sensor System for Evaluating Professional Baseball Pitchers and Batters
,” International Symposium on Wearable Computers
(ISWC
), Linz, Austria, Sept. 4–7, ISWC, pp. 131
–138
.22.
Ghasemzadeh
, H.
, Loseu
, V.
, Guenterberg
, E.
, and Jafari
, R.
, 2009
, “Sport Training Using Body Sensor Networks: A Statistical Approach to Measure Wrist Rotation for Golf Swing
,” Fourth International Conference on Body Area Networks
(BodyNets '09
), Los Angeles, CA, Apr. 1–3.23.
James
, D. A.
, Leadbetter
, R. I.
, Neeli
, M. R.
, Burkett
, B. J.
, Thiel
, D. V.
, and Lee
, J. B.
, 2011
, “An Integrated Swimming Monitoring System for the Biomechanical Analysis of Swimming Strokes
,” Sports Technol.
, 4
(3–4
), pp. 141
–150
.24.
Lecoutere
, J.
, and Puers
, R.
, 2014
, “Wireless Communication With Miniaturized Sensor Devices in Swimming
,” Procedia Eng.
, 72
, pp. 398
–403
.25.
Kelly
, D.
, Coughlan
, G. F.
, Green
, B. S.
, and Caulfield
, B.
, 2012
, “Automatic Detection of Collisions in Elite Level Rugby Union Using a Wearable Sensing Device
,” Sports Eng.
, 15
(2
), pp. 81
–92
.26.
Kelly
, D.
, Mc Donald
, J.
, and Markham
, C.
, 2011
, “Weakly Supervised Training of a Sign Language Recognition System Using Multiple Instance Learning Density Matrices
,” IEEE Trans. Syst. Man Cybern., Part B (Cybern.)
, 41
(2
), pp. 526
–541
.27.
Li
, Z.
, and Zhang
, G.
, 2011
, “A Gait Recognition System for Rehabilitation Based on Wearable Micro Inertial Measurement Unit
,” IEEE International Conference on Robotics and Biomimetics
(ROBIO
), Karon Beach, Phuket, Thailand, Dec. 7–11, pp. 1678
–1682
.28.
Gafurov
, D.
, and Snekkenes
, E.
, 2009
, “Gait Recognition Using Wearable Motion Recording Sensors
,” EURASIP J. Adv. Signal Process.
, 2009
, p. 415817
.29.
Yanco
, H. A.
, and Drury
, J.
, 2004
, “Classifying Human-Robot Interaction: An Updated Taxonomy
,” IEEE
International Conference on Systems, Man and Cybernetics
, The Hague, Netherlands, Oct. 10–13, pp. 2841
–2846
.30.
Schubö
, A.
, Vesper
, C.
, Wiesbeck
, M.
, and Stork
, S.
, 2007
, Movement Coordination in Applied Human-Human and Human-Robot Interaction
, Springer
, Berlin
, pp. 143
–154
.31.
Schelling
, X.
, and Torres
, L.
, 2016
, “Accelerometer Load Profiles for Basketball-Specific Drills in Elite Players
,” J. Sports Sci. Med.
, 15
(4
), pp. 585
–591
.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5131211/32.
Nguyen
, L. N. N.
, Rodríguez-Martín
, D.
, Català
, A.
, Pérez-López
, C.
, Samà
, A.
, and Cavallaro
, A.
, 2015
, “Basketball Activity Recognition Using Wearable Inertial Measurement Units
,” XVI International Conference on Human Computer Interaction
(Interacción '15
), Vilanova i la Geltrú, Spain, Sept. 7–9, p. 60
.33.
Bulling
, A.
, Blanke
, U.
, and Schiele
, B.
, 2014
, “A Tutorial on Human Activity Recognition Using Body-Worn Inertial Sensors
,” ACM Comput. Surv. (CSUR)
, 46
(3
), pp. 33:1
–33:33
.34.
Okeyo
, G.
, Chen
, L.
, Wang
, H.
, and Sterritt
, R.
, 2014
, “Dynamic Sensor Data Segmentation for Real-Time Knowledge-Driven Activity Recognition
,” Pervasive Mobile Comput.
, 10
, pp. 155
–172
.35.
Zhou
, S.
, Shan
, Q.
, Fei
, F.
, Li
, W. J.
, Kwong
, C. P.
, Wu
, P. C. K.
, Meng
, B.
, Chan
, C. K. H.
, and Liou
, J. Y. J.
, 2009
, “Gesture Recognition for Interactive Controllers Using MEMS Motion Sensors
,” Fourth IEEE
International Conference on Nano/Micro Engineered and Molecular Systems
, Shenzhen, China, Jan. 5–8, pp. 935
–940
.36.
Dellaserra
, C. L.
, Gao
, Y.
, and Ransdell
, L.
, 2014
, “Use of Integrated Technology in Team Sports: A Review of Opportunities, Challenges, and Future Directions for Athletes
,” J. Strength Amp; Conditioning Res.
, 28
(2
), pp. 556
–573
.37.
Junker
, H.
, Amft
, O.
, Lukowicz
, P.
, and Tröster
, G.
, 2008
, “Gesture Spotting With Body-Worn Inertial Sensors to Detect User Activities
,” Pattern Recognit.
, 41
(6
), pp. 2010
–2024
.38.
Amft
, O.
, Junker
, H.
, and Troster
, G.
, 2005
, “Detection of Eating and Drinking Arm Gestures Using Inertial Body-Worn Sensors
,” Ninth IEEE
International Symposium on Wearable Computers
, Osaka, Japan, Oct. 18–21, pp. 160
–163
. Copyright © 2019 by ASME
You do not currently have access to this content.
