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The development and application of inertial sensors for sports performance assessment: Successes, failures and emerging technologies
Abstracts / Journal of Science and Medicine in Sport 12S (2009) S1–S83
71 Swimming intra-stroke metric identification using wrist mounted inertial sensors N. Davey 1,2,∗ , D. James 1,3 1 Griffith School of Engineering, Griffith University, Australia 2 Centre
of Excellence for Applied Sport Science Research, Queensland Academy of Sport, Australia 3 Centre for Wireless Monitoring and Applications, Griffith University, Australia Introduction: In swimming the analysis and metrics of a stroke require the stroke observation in real time or on video, with subsequent interpretation and feedback. Using synchronised inertial sensors attached to the swimmers wrists movement patterns can be recorded. The inertial sensor data can be used in the analysis of stroke metrics. Prior work with body mounted inertial sensors for stroke type identification is extended to consider stroke and intra-stroke relationships. Methodology: A dry land experiment was conducted using a Qualysis motion capture system and swimming ergometer in parallel with the inertial sensors to provide reference and validation data. The swimming ergometer measured stroke length and force. The subject performed three sets of freestyle, butterfly and breaststroke at easy, medium and race pace. Results: Analysis of the inertial data shows that stroke timing metrics such as stroke frequency and stroke rate are obtainable when compared to ergometer data. Elements of the intra-stroke phases can also be obtained using the gyroscope data rotation axis defined by the lateral and medial wrist positions. This is validated against the motion capture system. Intra-stroke phases such as pull/propulsion and timing between left and right side can also be obtained. Conclusions: Results indicate that stroke and intra-stroke metrics can be obtained from wrist mounted inertial sensors. This provides an alternate method for obtaining such metrics. As dry land does not replicate inwater conditions, further in-water testing is required to fully validate the results. doi:10.1016/j.jsams.2008.12.072 72 The development and application of inertial sensors for sports performance assessment: Successes, failures and emerging technologies D. James 1,3,∗ , Y. Ohgi 2 1 Centre for Wireless Monitoring and Applications, Griffith University, Australia 2 School of Media and Governance, Keio University, Japan 3 Centre of Excellence for Applied Sport Science Research, Queensland Academy of Sport, Australia
The use of inertial sensors for human activity monitoring and sports performance analysis has enjoyed considerable
S31
attention in recent years. The increasing availability of micro sensors coupled with increasingly powerful wearable computing power has lead these sensors to being applied to a number of sports in both the training and competition environments. This paper describes the use of and limitations of these sensors for monitoring the human body. Linear and angular accelerations from these sensors represent derivative quantities of what is commonly associated with motion. However interpretation of this data into typical measures suitable for use by the sports community is something of a challenge. Instead the data needs to be interpreted as a new data type with complimentary contributions through feature recognition, signal processing and creative visualisations. Results from discrete and a custom ‘single chip’ monitoring platform for a range of sports will highlight the challenges of using these sensors together with the successes they can bring, such as allowing multipoint monitoring of an athlete, with minimal biomechanical loading an associated artifact. doi:10.1016/j.jsams.2008.12.073 73 The accuracy of kinematic whole body centre of mass location estimation W. McKinon ∗ , C. Hartford, G. Rogers University of The Witwatersrand Medical School, South Africa Introduction: Measurements of location of the human whole body centre of mass (COM) are becoming more important in many fields, but show particular value in clinical gait analysis and various sport science applications. To assess the accuracy of the commonly used kinematic (segmental) method of COM location modelling we compared two such optically-based models against direct suspension-based COM location measurements. Methodology: The two popular conventional models to estimate COM location were derived from either direct measurements made on cadavers or indirect gamma scanning methods in live humans. In a group of fifteen healthy male subjects the two kinematic model estimation s of COM location were statistically significantly different to simultaneous direct measurements (suspended sitting positions). Results: The cadaver based kinematic model was statistically significantly more similar to the direct suspension method than the human based kinematic model (mean differences 31 ± 13 mm and 92 ± 17 mm differences, respectively). Differences were not correlated to whole body mass, body fat or body water. In conclusion, kinematic (segmental) estimations of COM location differ significantly from simultaneous direct suspension measurements. Conclusions: Additional research to understand the factors behind the differences between known and estimated COM locations, shown in this study will facilitate improvements in the accuracy of kinematic estimations of COM
71 Swimming intra-stroke metric identification using wrist mounted inertial sensors N. Davey 1,2,∗ , D. James 1,3 1 Griffith School of Engineering, Griffith University, Australia 2 Centre
of Excellence for Applied Sport Science Research, Queensland Academy of Sport, Australia 3 Centre for Wireless Monitoring and Applications, Griffith University, Australia Introduction: In swimming the analysis and metrics of a stroke require the stroke observation in real time or on video, with subsequent interpretation and feedback. Using synchronised inertial sensors attached to the swimmers wrists movement patterns can be recorded. The inertial sensor data can be used in the analysis of stroke metrics. Prior work with body mounted inertial sensors for stroke type identification is extended to consider stroke and intra-stroke relationships. Methodology: A dry land experiment was conducted using a Qualysis motion capture system and swimming ergometer in parallel with the inertial sensors to provide reference and validation data. The swimming ergometer measured stroke length and force. The subject performed three sets of freestyle, butterfly and breaststroke at easy, medium and race pace. Results: Analysis of the inertial data shows that stroke timing metrics such as stroke frequency and stroke rate are obtainable when compared to ergometer data. Elements of the intra-stroke phases can also be obtained using the gyroscope data rotation axis defined by the lateral and medial wrist positions. This is validated against the motion capture system. Intra-stroke phases such as pull/propulsion and timing between left and right side can also be obtained. Conclusions: Results indicate that stroke and intra-stroke metrics can be obtained from wrist mounted inertial sensors. This provides an alternate method for obtaining such metrics. As dry land does not replicate inwater conditions, further in-water testing is required to fully validate the results. doi:10.1016/j.jsams.2008.12.072 72 The development and application of inertial sensors for sports performance assessment: Successes, failures and emerging technologies D. James 1,3,∗ , Y. Ohgi 2 1 Centre for Wireless Monitoring and Applications, Griffith University, Australia 2 School of Media and Governance, Keio University, Japan 3 Centre of Excellence for Applied Sport Science Research, Queensland Academy of Sport, Australia
The use of inertial sensors for human activity monitoring and sports performance analysis has enjoyed considerable
S31
attention in recent years. The increasing availability of micro sensors coupled with increasingly powerful wearable computing power has lead these sensors to being applied to a number of sports in both the training and competition environments. This paper describes the use of and limitations of these sensors for monitoring the human body. Linear and angular accelerations from these sensors represent derivative quantities of what is commonly associated with motion. However interpretation of this data into typical measures suitable for use by the sports community is something of a challenge. Instead the data needs to be interpreted as a new data type with complimentary contributions through feature recognition, signal processing and creative visualisations. Results from discrete and a custom ‘single chip’ monitoring platform for a range of sports will highlight the challenges of using these sensors together with the successes they can bring, such as allowing multipoint monitoring of an athlete, with minimal biomechanical loading an associated artifact. doi:10.1016/j.jsams.2008.12.073 73 The accuracy of kinematic whole body centre of mass location estimation W. McKinon ∗ , C. Hartford, G. Rogers University of The Witwatersrand Medical School, South Africa Introduction: Measurements of location of the human whole body centre of mass (COM) are becoming more important in many fields, but show particular value in clinical gait analysis and various sport science applications. To assess the accuracy of the commonly used kinematic (segmental) method of COM location modelling we compared two such optically-based models against direct suspension-based COM location measurements. Methodology: The two popular conventional models to estimate COM location were derived from either direct measurements made on cadavers or indirect gamma scanning methods in live humans. In a group of fifteen healthy male subjects the two kinematic model estimation s of COM location were statistically significantly different to simultaneous direct measurements (suspended sitting positions). Results: The cadaver based kinematic model was statistically significantly more similar to the direct suspension method than the human based kinematic model (mean differences 31 ± 13 mm and 92 ± 17 mm differences, respectively). Differences were not correlated to whole body mass, body fat or body water. In conclusion, kinematic (segmental) estimations of COM location differ significantly from simultaneous direct suspension measurements. Conclusions: Additional research to understand the factors behind the differences between known and estimated COM locations, shown in this study will facilitate improvements in the accuracy of kinematic estimations of COM