Sensor node acceleration signatures and electromyography in synchronisation and sequencing analysis in sports: A rowing perspective

Abstract

Please note: Changes made as a result of publishing processes such as copy-editing, formatting and page numbers may not be reflected in this version. For the definitive version of this publication, please refer to the published source. You are advised to consult the publisher's version if you wish to cite this paper.This version is being made available in accordance with publisher policies. See http://orca.cf.ac.uk/policies.html for usage policies. Copyright and moral rights for publications made available in ORCA are retained by the copyright holders.Sensor node acceleration signatures and electromyography in synchronisation and sequencing analysis in sports: a rowing perspective Sian Armstrong, Leonard DM Nokes AbstractFollowing a review of the key determinants of successful rowing, a wireless body sensor network (BSN) was developed to monitor boat and body segment acceleration, and surface electromyography in major muscles recruited during the rowing stroke cycle. Its design was optimised to yield maximum information about the rowing stroke cycle from fewest sensors, and minimise the power consumption of the nodes. The system was validated against the Qualisys motion capture and high speed camera system with most Pearson correlation coefficients in excess of r=0.8.On land ergometer experimentation allowed muscle recruitment over the stroke cycle to be studied, with multiple experiments combined using correlation of the acceleration signatures of back and thigh nodes (r=0.95). It was demonstrated that it was possible to identify one of the common rowing errors of "shooting-the-slide" from the data collected, and that a marked decrease in correlation of good-to-bad technique over the drive phase of the stroke (0.95 reducing to 0.34 in the experiment undertaken) could be used to indicate the presence of this error.Extension of the wireless BSN to encompass boat and two oarsmen was demonstrated, allowing correlation of their rowing signatures to be studied, indicating their cohesion as a crew.

A Systematic Review of Performance Analysis in Rowing Using Inertial Sensors

“…Despite the obvious differences in the biomechanical processes of an athlete when transferring from an ergometer to a scull, it will provide a baseline measurement with golden standard data to validate against. [12] Rowing × × [13] Rowing…”

“…Signal processing algorithms used on data, KNN (K-nearest Neighbours); DTW (Dynamic Time Warping); SVM (Support Vector Machine). [12] Rowing × × × [13] Rowing × × × [14] Rowing × × [15] Rowing × × × [16] Rowing…”

“…Kayaking/Canoeing Citation Sport Validation Technology [12] Rowing Optical motion capture [14] Rowing Coach qualitative assessment [17] Rowing Manual feature labelling [18] Rowing Controlled laboratory validation test [20] Rowing Force plates [25] Rowing GPS [27] Rowing GPS [30] Rowing GPS [32] Rowing Navilock-550 ERS [33] Rowing Optical motion capture [38] Rowing GPS [39] Rowing GPS [40] Rowing Optical motion capture [41] Rowing Optical motion capture [42] Canoeing Video Camera [43] Rowing GPS and stroke coach monitor [44] Rowing GPS [46] Rowing Reference measures from rowing simulator [47] Rowing Peach innovations measurement oarlock…”

“…Seven of the reviewed papers (7/36-19.4%) investigated rowing athletes' physiological and physicality parameters using inertial sensors. Four of these records (5/7-71.4%) analysed crew synchronicity [12,14,20,23,32]. An elite rower has high special fitness; high coordination, motor control and functional strength [52].…”

“…Thus, being able to use inertial sensor data as a measure of synchronicity between rowers can aid coaches in having a more informed understanding of their rowing crew's interactions during training and competition. Armstrong and Nokes [12] investigated synchronization through acceleration signatures and electromyography signals. This demonstrated the muscle recruitment requirements for different boat positions (stroke, bow).…”