Predicting maximal strength: Difference between revisions
From JSXGraph Wiki
A WASSERMANN (talk | contribs) No edit summary |
A WASSERMANN (talk | contribs) No edit summary |
||
(8 intermediate revisions by 2 users not shown) | |||
Line 6: | Line 6: | ||
1RM = w\cdot(0.988+0.0104\cdot x+0.00190\cdot x^2-0.0000584\cdot x^3) | 1RM = w\cdot(0.988+0.0104\cdot x+0.00190\cdot x^2-0.0000584\cdot x^3) | ||
</math> | </math> | ||
The | The horizontal axis denotes the number of repetitions, the vertical axis denotes the ratio 1RM/RTF. | ||
'''How to use this graphical calculator?''' | |||
Suppose you managed to do 9 repetitions with a weight of 80 kilograms. In the graphical calculator below you have to drag the black dot to r=9 and the blue dot to weight=80. Now, you can read of the 1RM prediction of 95.43. | |||
var w = brd. | <jsxgraph width="700" height="500"> | ||
var brd = JXG.JSXGraph.initBoard('jxgbox',{boundingbox:[-1,1.8,30,0.8], axis: true}); | |||
var w = brd.create('slider',[[24,0.92],[24,1.7],[0,50,200]],{name:'weight w',snapWidth:1}); | |||
f = function(x){ return (0.988+0.0104*x+0.00190*x*x-0.0000584*x*x*x); }; | f = function(x){ return (0.988+0.0104*x+0.00190*x*x-0.0000584*x*x*x); }; | ||
var c = brd. | var c = brd.create('functiongraph',[ | ||
f, | f, | ||
1,22 | 1,22 | ||
Line 23: | Line 24: | ||
); | ); | ||
var r = brd. | var r = brd.create('glider',[10,1,c],{name:'',fillColor:'black',strokeColor:'black',style:6}); | ||
var t = brd. | var t = brd.create('text',[function(){return r.X()+1;}, | ||
function(){return r.Y();}, | function(){return r.Y();}, | ||
function(){return "repetitions r = " + Math.floor(r.X());}]); | function(){return "repetitions r = " + Math.floor(r.X());}]); | ||
brd. | brd.create('text',[5,1.6, | ||
function(){return "predicted 1RM = " + (w.Value()*f(Math.floor(r.X()))).toFixed(2);}], | |||
{fontSize:24,strokeColor:'red'}); | |||
</jsxgraph> | </jsxgraph> | ||
Line 37: | Line 38: | ||
* W. Kemmler, D. Lauber, J. Mayhew, and A. Wassermann: "Predicting Maximal Strength in Trained Postmenopausal Woman", ''Journal of Strength and Conditioning Research'' 20(4), (2006), pp. 838-842. | * W. Kemmler, D. Lauber, J. Mayhew, and A. Wassermann: "Predicting Maximal Strength in Trained Postmenopausal Woman", ''Journal of Strength and Conditioning Research'' 20(4), (2006), pp. 838-842. | ||
=== The underlying JavaScript code === | |||
<source lang="javascript"> | |||
var brd = JXG.JSXGraph.initBoard('jxgbox',{boundingbox:[-1,1.8,30,0.8], axis: true}); | |||
var w = brd.create('slider',[[24,0.92],[24,1.7],[0,50,200]],{name:'weight w',snapWidth:1}); | |||
f = function(x){ return (0.988+0.0104*x+0.00190*x*x-0.0000584*x*x*x); }; | |||
var c = brd.create('functiongraph',[ | |||
f, | |||
1,22 | |||
], {strokeColor:'black', highlightStrokeColor:'black'} | |||
); | |||
var r = brd.create('glider',[10,1,c],{name:'',fillColor:'black',strokeColor:'black',style:6}); | |||
var t = brd.create('text',[function(){return r.X()+1;}, | |||
function(){return r.Y();}, | |||
function(){return "repetitions r = " + Math.floor(r.X());}]); | |||
brd.create('text',[5,1.6, | |||
function(){return "predicted 1RM = " + (w.Value()*f(Math.floor(r.X()))).toFixed(2);}], | |||
{fontSize:24,strokeColor:'red'}); | |||
</source> | |||
[[Category:Examples]] | [[Category:Examples]] |
Latest revision as of 15:45, 20 February 2013
This little application tries to predict the maximal strength (1RM) based on a repetitions to fatigue (RTF) value.
The calculation is based on the so called KLW formula:
- [math]\displaystyle{ 1RM = w\cdot(0.988+0.0104\cdot x+0.00190\cdot x^2-0.0000584\cdot x^3) }[/math]
The horizontal axis denotes the number of repetitions, the vertical axis denotes the ratio 1RM/RTF.
How to use this graphical calculator? Suppose you managed to do 9 repetitions with a weight of 80 kilograms. In the graphical calculator below you have to drag the black dot to r=9 and the blue dot to weight=80. Now, you can read of the 1RM prediction of 95.43.
References
- W. Kemmler, D. Lauber, J. Mayhew, and A. Wassermann: "Predicting Maximal Strength in Trained Postmenopausal Woman", Journal of Strength and Conditioning Research 20(4), (2006), pp. 838-842.
The underlying JavaScript code
var brd = JXG.JSXGraph.initBoard('jxgbox',{boundingbox:[-1,1.8,30,0.8], axis: true});
var w = brd.create('slider',[[24,0.92],[24,1.7],[0,50,200]],{name:'weight w',snapWidth:1});
f = function(x){ return (0.988+0.0104*x+0.00190*x*x-0.0000584*x*x*x); };
var c = brd.create('functiongraph',[
f,
1,22
], {strokeColor:'black', highlightStrokeColor:'black'}
);
var r = brd.create('glider',[10,1,c],{name:'',fillColor:'black',strokeColor:'black',style:6});
var t = brd.create('text',[function(){return r.X()+1;},
function(){return r.Y();},
function(){return "repetitions r = " + Math.floor(r.X());}]);
brd.create('text',[5,1.6,
function(){return "predicted 1RM = " + (w.Value()*f(Math.floor(r.X()))).toFixed(2);}],
{fontSize:24,strokeColor:'red'});