Reference: A Wixted, W Spratford, M Davis, M Portus, D James, Wearable Sensors for On FIeld Near Real Time Detection of Illegal Bowling Actions, 1 of 1-Conference of Science, Medicine & Coaching in Cricket 2010, 165 Introduction: A well-developed and legal bowling action is of enormous importance to developing cricket athletes and teams both nationally and internationally. Good bowlers can make the headlines, but so do the controversial ones. The bowling action can currently only be measured with accuracy in a few specialist laboratories around the world. Testing requires a break in a player’s schedule, travel to a distant testing centre and players are then asked to bowl in an unnatural environment. This testing is therefore somewhat expensive and not routinely accessible, but this process is the best method currently available. Recently developed micro technologies have been used in athlete performance monitoring, biomechanical monitoring and physiological monitoring in other sports such as swimming (Kavanagh et.al. 2006, James et.al. 2007, Davey et.al. 2008), snowboarding (Harding 2008), running (Wixted et.al 2007, 2010) and also in cricket (Rowlands et.al. 2009). These technologies offer the promise of wearable alternatives to laboratory testing that would be inexpensive enough to be used routinely by elite and developmental players and coaches. In light of the above, real time, non-laboratory monitoring of the bowling arm-action by miniature sensors is a potential solution to the disruptive issues caused by the processes currently in-place to assess perceived or actual throwing. Current and future miniature sensors are achieving, or will soon achieve, the sensitivity and range of operation necessary to monitor athletes operating at the elite levels of many sports. In the case of monitoring the arm action of bowlers, a number of checkpoints needed to be achieved to verify that miniature sensors could supply the required level of monitoring. The verification process involved testing with actual sensors and the use of “virtual” sensors generated from the existing library of Cricket Australia motion capture data (Vicon). These combined tests identified some of the sensor operational ranges and the feasibility of identifying the illegal arm actions using miniature sensors. Sensor systems have a very restricted view of the world and this limits their ability to identify activities that seem obvious to an onlooker. Sport involves movement and the sensors predominately used for measuring kinematic activities are accelerometers and rate gyroscopes (to measure rotation). These sensors are often arranged on three orthogonal axes to capture activity in three dimensions (3D). The accelerometers and rate-gyroscopes are usually Micro-Electro Mechanical Systems (MEMS) and are manufactured, along with support electronics, directly in silicon with sizes of 3D accelerometers as small as 5x3x1mm. Gyroscopes have similar sizes. The combination of 3D accelerometers and gyroscopes and the fast sampling rate of sensor systems allow the sensor systems to capture information about a small segment of the physical world yet this small segment is often sufficient to determine the parameters of interest. To monitor a bowler for illegal bowling it is necessary that the sensor can identify specific points of the arm action, in particular the start and end of the arm action. The start of the arm action occurs when the elbow is level with the shoulder, the end of the arm action occurs when the ball is released. Between these two points the sensor needs to monitor the critical aspect of elbow extension. Although stationary 3D accelerometers can detect orientation, the complex forces affecting a moving limb prevent the direct extraction of orientation therefore; a simple orientation based detection of start of arm action is not possible. The ball release point appears to occur around 120 degrees after the start of arm action. Other than some sort of finger tip pressure sensor there does not appear to be any obvious sensor measure that can detect ball release. Finally, the detection of elbow extension: this does appear amenable to detection by miniature sensors. Using data from multiple accelerometers or multiple gyroscopes, elbow extension should be detectable as a centrifugal acceleration phase difference or a rotation rate phase difference between upper arm and forearm mounted sensors. To ascertain the feasibility of MEMS based sensor monitoring of bowling arm elbow extension, the dynamics of the bowling arm were investigated using ‘virtual’ sensors. The virtual sensors were also used to determine the working range required for physical sensors. Virtual Sensors: 120 Hz Vicon motion capture data from numerous bowlers performing a range of deliveries was processed to generate the output of virtual sensors. This process involved selecting specific Vicon markers and converting their position data from an external ‘cricket-pitch’ based Frame of Reference (FOR) to acceleration data and angular velocity data in a sensor based FOR. The markers involved were part of a semi rigid technical marker set. The process of creating the virtual sensors involved double differentiation of the position information to convert it to acceleration. For each frame of Vicon data the orientation of the technical marker relative to the external FOR was extracted and the orientation used to transform the external FOR acceleration into sensor FOR acceleration. As the process of transforming acceleration from one FOR to another involved generating rotation angles, the sequence of rotation angles was differentiated to give rotation rates (angular velocity). The data from the virtual sensors represented the outputs of accelerometers and rate-gyroscopes had they been fitted in the location of the technical marker when the original motion capture data was collected. This data was analysed and a very clear ball-release signature was identified indicating that real sensors should be able to identify the ball release point (Fig.1(a)). Not included in Fig.1(a) were two illegal bowls where there was a distinctive phase difference between the upper-arm and forearm peak acceleration. No specific start of arm-action was initially identified in 120Hz Vicon data but when data from a 250 Hz Vicon system was processed many deliveries showed a spike of very high angular velocity on or about the start of the bowling action (Fig.1(b)). Video replay indicated that this was associated with the elbow extension and shoulder rotation that brings the ball into the upward facing direction (a supination action) just prior to the start of the arm action. This shoulder rotation is necessary to prepare the shoulder joint for the delivery action.  Figure 1: (a) Centrifugal Acceleration for right arm bowlers at ball release, (b) Example of two axes of angular velocity with a spike of angular velocity at the start of the arm action. Despite the apparent confirmation of the existence of potential arm-action start and end signatures, the Vicon data is subject to its own processing errors and these signatures need to be confirmed with actual sensors. The Vicon data does give indicative acceleration and angular velocity: • Forearm Centrifugal Acceleration: > 70g ( ~ 700ms-2) • Forearm Angular Velocity: > 3500 deg/s Both these values are achievable by current technology. Physical Sensor: The positions of the Vicon technical markers were not the optimal positions for actual sensors attempting to detect elbow extension. In a separate experiment rate-gyroscopes were used to synchronously collect data from either side of the elbow joint. Elbow extension and flexion was performed through a bowling action. From the gyroscopes, an arm starting in the already flexed position and extending through the bowl showed peak rotation rates for the forearm occurring prior to the upper-arm peak rotation (figure 2). An arm staying straight through the bowling action and then flexing after release showed the gyroscopes for the upper arm and forearm tracking together until the flexing started (figure 3). The gyroscope output for an arm starting straight but flexing through the action showed the sensors not even tracking together with the forearm’s sensors peaking sometime after the upper arm sensor (figure 4)  Figure 2: Exaggerated stick figure representation and gyroscope output for an arm starting the bowling action flexed and extending through to release.  Figure 3: Exaggerated stick figure representation and gyroscope output for an arm starting the bowling action straight and beginning to flex at release.  Figure 4: Exaggerated stick figure representation and gyroscope output for an arm starting the bowling action straight and flexing through the bowl. Where the arm remains straight through the bowling action it appeared that the outputs of the sensors tracked together. If a single flexion or extension occurred the phase relationship between the forearm and upper arm sensors was distinctly different. At this time the effect of a complete flexion-extension action during the bowling has not been analysed although study of the historical data indicates that this type of action occurs for some bowlers. Similar data has been collected from accelerometers and although the accelerometers used for these experiments were overloaded by the bowling action, the phase shifting between upper-arm sensors and forearm sensors for flexion-extension was identified in the output. Summary: Analysis from virtual sensors indicated that arm action start and end points have identifiable signatures that can be utilised by miniature sensors. The virtual sensors also indicated the signal magnitudes. For some types of illegal bowling action, the virtual accelerometers identified a phase shift between forearm and upper-arm acceleration. Analysis of the output of physical sensors indicated that changing elbow extension during the bowling arm action is identifiable in the sensor output. These factors have become the input to the development of sensors specifically designed to capture the bowling action and extract elbow extension. The next phase of this development is the confirmation of sensor operation using simultaneously collection of data from both the sensors and the motion capture system. This step will also begin the development of the mapping from sensor phase shift to elbow angle Acknowledgements: The authors acknowledge the funding for this project from the ICC and the Marylebone Cricket Club (MCC) as well as the support and historical data from CA and the AIS References: Kavanagh JJ, Morrison S, James DA, Barrett R, Reliability of segmental accelerations measured using a new wireless gait analysis system, Journal of Biomechanics, Vol 39, pp2863-72, 2006 James DA, Davey N, Hayes J, From conception to reality: A wearable device for automated swimmer performance analysis, Japan Society for Sciences in Swimming and Water Exercise 11th Annual Conference proceedings, pp101-109. 2007 Davey N, Anderson M, James DA, Validation trial of an accelerometer-based sensor platform for swimming, Sports Technology, 2008; 1 (4) pp 202-207 Harding JW, Macintosh CG, Martin DT, James DA, Classification of aerial acrobatics in elite halfpipe snowboarding using body mounted inertial sensors, The Engineering of Sport, 2008, Estivalet, Brisson Ed. pp447-456 Paris: Springer Wixted AJ, Thiel DV, Hahn A, Gore C, Pyne D, James DA, Measurement of Energy Expenditure in Elite Athletes using MEMS based inertial sensors, IEEE Sensors Journal, Vol 7, No4, pp481-8, April 2007 Wixted AJ, Billing DC, James DA, Validation of trunk mounted inertial sensors for analysing running biomechanics under field conditions, using synchronously collected foot contact data. Sports Engineering, 2010, In Press. Rowlands D, James DA, Thiel DV, Bowler Analysis in Cricket using Centre of Mass Inertial Monitoring, Sports Technology, 2009, (21-2), pp39-42. |
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