Abstracts from the 6th international conference on the Engineering of Sport, 10–14 July 2006, Olympic Hall, Munich, Germany

Please download to get full document.

View again

of 6
All materials on our website are shared by users. If you have any questions about copyright issues, please report us to resolve them. We are always happy to assist you.
Categories
Published
Download Abstracts from the 6th international conference on the Engineering of Sport, 10–14 July 2006, Olympic Hall, Munich, Germany
  Validation of a Full-Body Computer Simulation of the Golf Drive for Clubs of Differing Length Ian C. Kenny 1 , Eric S. Wallace 1 , Desmond Brown 1 , Steve R. Otto 2   1  University of Ulster, i.kenny@ulster.ac.uk 2  R&A Rules Limited Abstract.  The aim of the present study was to validate a full-body computer simulation of a golfer’s swing for driving clubs. An elite male golfer performed 24 shots in a laboratory, comprised of 8 trials using each of three drivers of different shaft length (46  , 48   & 50  ). A 5-camera MAC™ system operating at 240Hz collected kinematic data which was subsequently used to drive the model utilising ADAMS/LifeMOD software. Additional skin markers were used for model validation. A large-scale musculoskeletal human model was constructed, with a parametric model of a driver. Inverse and forward dynamics calculations were performed with the imported experimental motion data in order to generate model movement. A commercially available launch monitor recorded experimental clubhead and launch conditions. There was a very high level of agreement (r=0.995) between experimental kinematic data and the predicted trajectory splines of the model. There was also a high level of correlation (r=0.989) between the model predicted mean values for clubhead speed and the experimental values for each of the club lengths, both demonstrating increased clubhead velocity as club length increased. Muscle contraction force output by the model showed a significant difference (p  0.001) between driver simulations, demonstrating its capability to illustrate the link between gross muscle force production and club length, as evidenced by the increased force output for the longest shafted club. 1 Introduction Computer simulation models permit the study of the complex interactions between biomechanical variables, yet their application to the scientific study of the golf swing is still in an early phase of development. There exists a number of research papers that have focused on kinematic and kinetic variations in the golf swing, with some papers examining club dimensional properties. However, few researchers have developed full-body computer models of the golf swing. Nesbit (2005) utilised ADAMS software to develop a rigid-body model of a golfer and parametric model of a golf club to investigate kinematics and kinetics throughout the swing. The latest edition of the Rules of Golf, as approved by the R&A Rules Limited and the United States Golf Association (30 th  Edition, Appendix II, 1c (length), effective 1 st  January 2004) states that the overall maximum club length (excluding putters) must not exceed 48   (1.2192m). Reyes & Mittendorf (1999)   have discussed the significance of  Ian Kenny, Eric Wallace, Desmond Brown and Steve Otto 10altering club length for the golf swing, concluding that there would be an increase in drive length as club length increased, and that a 47   driver would produce optimum performance in terms of shot distance and accuracy. Several researchers have concentrated on clubhead and ballspeed as an indication of improved performance when using longer shafted clubs, for example Egret, Vincent, Weber, Dujardin and Chollet (2003), and Mizoguchi and Hashiba (2002). Both experimental and mathematical modelling studies have ascertained that increasing club length is associated with greater drive distance. 2 Methods 2.1 Experimental Procedures The current study used one category 1 golfer to infer the effects of using drivers of different shaft length (single-subject analysis, Bates, Rodger and Dufek 2004). Hatze (2005) stressed the importance and need for subject-specific models to be developed. The subject (25yrs, 1.80m, 91.3kg, +1 handicap) signed an informed consent approved by the University of Ulster and completed an activity and medical history questionnaire. Full-body motion data during the golf swing were captured at 240Hz, using a 5-camera MAC™ Falcon Analogue motion analysis system. Image verification was carried out as instructed by the MAC™ Falcon instruction manual, and the camera system indicated a maximum residual error of 2mm for each camera. The calibrated volume (3m x 3m x 2.5m high) was greater than that exhibited by the motion of the markers during the swing. An adaptation of Mitchell, Banks, Morgan and Sugaya’s (2003) 26 marker setup was used. Reflective passive surface markers were placed on the subject by a trained physiologist. In addition to the 26 body markers and 1 shaft marker the MAC™ computer stick model included a further 16 markers to aid model validation. Three drivers were constructed specifically for the tests (Table 1). Table 1.  Test clubs physical properties Club length (   /m) 46/1.17 48/1.22 50/1.27 Assembled frequency (Hz) 332.2 323.8 300.4 Shaft type Grafalloy Prolite Alida Longwood 50/50 Alida Longwood 50/50 Flex Stiff Stiff Stiff Shaft mass (g) 63.0 63.0 63.0 Swingweight D9 E4 F4 Head volume (cc) 350 350 350 Head mass (g) 200.9 199.7 199.8 Loft (˚) 9.0 9.0 9.0 Premium balls and a Golftek Pro V Swing Analyser were used for the present study. After performing their usual pre-game warm-up the subject hit a maximum of 8 shots with each randomly assigned driver. For each shot the MAC™ system tracked the complete swing, the launch monitor tracked clubhead and ball launch conditions, and an   Validation of a full-body computer simulation of the golf drive 11 investigator recorded any anecdotal information offered by the subject relating to the quality of the shot. The subject was instructed to aim along a target line into netting hanging 4.5m away. Reconstructed co-ordinates of the markers to infer joint centre location and segment COM were transferred from the capture software EvaRT to KinTrak. Data were smoothed using a low-pass Butterworth filter at 12Hz and an order of 2 (Mitchell et al. 2003). Data were analysed using SPSS with variables (velocity, angles) tested for variance using different drivers by means of a 1-way ANOVA. Pearson’s test for correlation was applied during the validation procedure. A significance level of p<0.05 was set. To test for combined effects of club length, and muscle force production, Friedman’s 2-way ANOVA was applied. 2.2 Modelling Techniques The base segment set comprised 19 segments. The model was initially scaled for the subject’s height and body mass, with an additional 54 subject-specific measures input. The model in the present study was constructed with a total of 42 degrees-of-freedom. MAC™ kinematic data was used to drive the model and a forward dynamics simulation replicated the swing. A full-body set of 111 muscles were generated. The muscles learned shortening/lengthening patterns whilst the model was being driven in an inverse dynamics simulation. Contact forces between the body segments and the environment or objects (ground and club grip) were created using ellipsoid-plate contact elements. A clubhead shell with titanium material properties was created, of 350cc volume and 200g mass. A flexible 8-segment graphite shaft connected the clubhead hosel to the grip. The additional markers that were attached to the subject during experimentation were used for validation purposes. Their 3D kinematic trajectory data were compared to virtual markers placed on the same anatomical landmarks in the model. To verify that muscle force output by the model was correct, grip force exerted by the hands on the club grip was derived during forward dynamics simulations, and compared to force transducer experimental data previously published by other researchers. 3 RESULTS 3.1 Validation Correlations between model virtual marker kinematics and experimental additional marker kinematics were all greater than 0.99, as illustrated in Table 2 for 4 selected markers. Experimentally determined clubhead velocity was compared to peak linear velocity for a virtual marker placed on the toe of the modelled clubhead. Pearson’s correlation (r) for mean values for all club lengths was 0.989. Figure 1 illustrates mean peak clubhead velocity values for experimental and modelled data. Clubhead velocity  Ian Kenny, Eric Wallace, Desmond Brown and Steve Otto 12was found to increase as club length increased with the greatest increase noted for the 46   and 48   driver comparison. Table 2.  Select virtual marker/experimental marker kinematics correlation  Marker/ anatomical landmark Correlation (Pearson’s r) Left medial malleolus 0.991 Left greater trochanter 0.993 Right medial malleolus 0.996 Right greater trochanter 0.998 The final method of model validation focused on the capability of the model to accurately predict muscle force output. Grip force exerted at points on the hands with the club grip were compared with previously published experimental force transducer research. In the present study the average force exerted by the left 4th finger on the club throughout the swing was shown to be 13.2N, which lies within the range of 8-17N reported recently by Nikonovas, Harrison, Hoult and Sammut (2004). 3.2 Muscle force production Table 3 shows the peak force output for 4 selected muscles. Figures shown represent the means and standard deviations of 24 forward dynamics simulations for each driver length. Muscles were chosen which are deemed ‘prime movers’ for the golf swing. It can be seen that for all muscles, force output significantly increases to maintain swing kinematics as club length increases.  Fig. 1.  Model and experimental mean peak clubhead velocity Model Vs Experimental peak clubhead velocity 50.351.6 52.050.149.748.340.045.050.055.060.046.0 48.0 50.0 Club length (")    V  e   l  o  c   i   t  y   (  m  s   -   1    ) ExperimentModel   Validation of a full-body computer simulation of the golf drive 13 Table 3.  Select optimised muscle average peak force output Soft tissue peak force output (N) Muscle 46 48 50 R extensor carpi ulnaris* 0.89 ± 0.05 3.77 ± 0.09 4.41 ± 0.08 R pectoralis minor* 1.50 ± 0.01 6.63 ± 0.01 10.51 ± 0.02 R gluteus medius* 228.00 ± 1.37 291.3 ± 1.4 305.21 ± 1.71 R vastus medialis* 30.20 ± 1.76 115.28 ± 1.03 497.23 ± 1.34 R = right *   2 = 16.02, p    0.001 4 Discussion The aim of the present study was to validate a full-body computer simulation of a golfer’s swing for driving clubs, and to investigate the effect of club length on swing kinematics and kinetics. Previous studies have indicated that increasing driver length is associated with an increase in drive distance, inferred via increases in peak clubhead velocity. Through validation of    the model, we have been confident in predicting clubhead velocity, swing kinematics and internal peak muscle force production during the golf swing. A model is as good as its verifiable predictions. All correlations performed relating to swing kinematics were higher than 0.99. Thus the trajectory splines of all 42 markers placed on the subject were perfectly replicated by the model. Furthermore, a correlation of 0.989 between experimental and predicted clubhead velocity for all club lengths demonstrate the ability of the model to predict clubhead peak velocity. The effect of club length on clubhead velocity was in agreement with Egret et al. (2003) and Mizoguchi et al. (2002) in that clubhead peak velocity increases as club length increases. In the present study an extra 4   club length (46   - 50  ) produced only an average 1.74ms -1  greater peak clubhead velocity. A measure of the accuracy loss, if any, would be needed to enable an objective conclusion to be made on the benefits or consequences of using a club of greater length than that normally used. Several studies have been concerned with the prediction of muscle forces in humans, including Heller, Bergman, Deuretzbacher, Durselen, Pohl, Claes, Haas and Duda (2001) who made a direct comparison between calculated hip contact forces and measured contact forces, with good agreement reported. The redundancy and indeterminancy problems have led to inaccuracies in muscle force output prediction for humans performing a given motor task. With a greater number of muscles available in the human body than is necessary to complete the movement, it leads to model underestimation of the force used. A common method employed is to decrease the overall number of muscles applied to the model and to use either direct comparisons with experimental ground reaction forces (GRFs) or object grip forces. The present study made a direct comparison of modelled grip force with previously reported force transducer results for the left 4th finger peak point force. We found that the average force exerted by the left 4th finger on the club through the swing lay within the range reported recently by Nikonovas et al. (2004). The 4 muscles shown in Table 3 demonstrate an increase in muscle force output needed to move the body segments when long shafted drivers are
Similar documents
View more...
We Need Your Support
Thank you for visiting our website and your interest in our free products and services. We are nonprofit website to share and download documents. To the running of this website, we need your help to support us.

Thanks to everyone for your continued support.

No, Thanks
SAVE OUR EARTH

We need your sign to support Project to invent "SMART AND CONTROLLABLE REFLECTIVE BALLOONS" to cover the Sun and Save Our Earth.

More details...

Sign Now!

We are very appreciated for your Prompt Action!

x