Problem 3064. Cycling — Normalized Power

Created by goc3

Solve Later

{"relationships":[{"relationshipType":"http://schemas.mathworks.com/matlab/code/2013/relationships/document","targetMode":"","relationshipId":"rId1","target":"/matlab/document.xml"},{"relationshipType":"http://schemas.mathworks.com/matlab/code/2013/relationships/output","targetMode":"","relationshipId":"rId2","target":"/matlab/output.xml"}],"parts":[{"partUri":"/matlab/document.xml","relationship":[],"contentType":"application/vnd.mathworks.matlab.code.document+xml","content":"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<w:document xmlns:w=\"http://schemas.openxmlformats.org/wordprocessingml/2006/main\"><w:body><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:t>In cycling, a power meter is an indispensable tool to record power output (in Watts) and measure fitness gains and performance metrics. When analyzing the data though, many different workouts can yield approximately the same average power, despite major differences between workouts (e.g., a long steady effort vs. sprints or intervals). Normalized power (NP) is a method to measure the effect of more intense efforts on the overall workout. NP is calculated by the following four steps (from Training and Racing with a Power Meter by Allen and Coggan):</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"ListParagraph\"/><w:numPr><w:numId w:val=\"2\"/></w:numPr></w:pPr><w:r><w:t>Calculate a 30-second rolling average of the power data</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"ListParagraph\"/><w:numPr><w:numId w:val=\"2\"/></w:numPr></w:pPr><w:r><w:t>Raise these values to the fourth power</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"ListParagraph\"/><w:numPr><w:numId w:val=\"2\"/></w:numPr></w:pPr><w:r><w:t>Average the resulting values</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"ListParagraph\"/><w:numPr><w:numId w:val=\"2\"/></w:numPr></w:pPr><w:r><w:t>Take the fourth root of the result</w:t></w:r></w:p><w:p><w:pPr><w:pStyle w:val=\"text\"/></w:pPr><w:r><w:t>You will be provided with the 30-second rolling average power data set (vector). Write a function to return the average power (using the rolling average data) and the normalized power using steps 2–4 above. Round the values to the nearest integer.</w:t></w:r></w:p></w:body></w:document>"},{"partUri":"/matlab/output.xml","contentType":"text/xml","content":"<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\" ?><embeddedOutputs><metaData><evaluationState>manual</evaluationState><layoutState>code</layoutState><outputStatus>ready</outputStatus></metaData><outputArray type=\"array\"/><regionArray type=\"array\"/></embeddedOutputs>"}]}

<p>In cycling, a power meter is an indispensable tool to record power output (in Watts) and measure fitness gains and performance metrics. When analyzing the data though, many different workouts can yield approximately the same average power, despite major differences between workouts (e.g., a long steady effort vs. sprints or intervals). Normalized power (NP) is a method to measure the effect of more intense efforts on the overall workout. NP is calculated by the following four steps (from Training and Racing with a Power Meter by Allen and Coggan):</p><ol><li>Calculate a 30-second rolling average of the power data</li><li>Raise these values to the fourth power</li><li>Average the resulting values</li><li>Take the fourth root of the result</li></ol><p>You will be provided with the 30-second rolling average power data set (vector). Write a function to return the average power (using the rolling average data) and the normalized power using steps 2–4 above. Round the values to the nearest integer.</p>

Solve

Solution Stats

128 Solutions
28 Solvers

Last Solution submitted on Apr 19, 2021

Last 200 Solutions

Problem Comments

1 Comment

1 Comment

Richard Livingston on 27 Apr 2018

I don't understand what I'm looking at, Ive attempted to add the code from a solution, but it seems like I'm missing something crutial...

function [P_avg,NP] = cycling_norm_power(power)
P_avg = 0;
NP = 0;

%% steady
power = 200*ones(1,3600);
P_avg_corr = 200;
NP_corr = 200;
[P_avg,NP] = cycling_norm_power(power);
assert(isequal(P_avg_corr,P_avg))
assert(isequal(NP_corr,NP))

Solution Comments

Solution 830802

2 Comments

2 Comments

M. on 17 Feb 2016

??????????? really? 4 correct and 5 not?

goc3 on 18 Feb 2016

Same problem as noted in the other comment. You get the correct P_avg here but not NP because the sprint is so short that the 30-second rolling average (applied twice) is rounded to the same answer. Unrounded P_avg answers for this routine and the correct routine are 131.3638 and 131.1111, respectively. Given that answers are being rounded, it may look wrong since the P_avg calculation appears to be right (due to rounding) while NP was wrong when both were actually wrong.

Solution 830776

2 Comments

2 Comments

M. on 17 Feb 2016

Maybe I'm wrong, but for sure the results in test 4 and 5 is NOT CORRECT

goc3 on 18 Feb 2016

Note in the last paragraph of the explanation: "You will be provided with the 30-second rolling average power data set (vector)." In essence, your solution is calculating the 30-second rolling average of a 30-second rolling average data set.

Problem Recent Solvers28

Problem Tags

analysis cycling data meter normalized power

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Problem 3064. Cycling — Normalized Power

Solution Stats

Last 200 Solutions

Problem Comments

Solution Comments

Problem Recent Solvers28

Suggested Problems

More from this Author139

Problem Tags

Community Treasure Hunt

Problem 3064. Cycling — Normalized Power

Solution Stats

Last 200 Solutions

Problem Comments

Solution Comments

Problem Recent Solvers28

Suggested Problems

More from this Author139

Problem Tags

Community Treasure Hunt

Players