Hi,
I have had an extensive search of the net but am having trouble solving my predicament.
I am running into a dilemma with my research. Its regarding gait analysis.
I want to be able to present joint angles at a percentage of gait cycle in increments of 1 or 2%.
Right now, through normalization, I am able to present data with relative to gait cycle percentage, but the increments are all different for each trial. e.g. trial 1 has cycle percentage going up in 0.6 and trial 2 going up in 0.4 etc. (this is as each trial ends up giving different number of frames for one gait cycle)
I have a certain number of datapoints, and I want to be able to reduce this to another number so i can compare multiple trials easily. But I don't want to lose any datapoints, so want to average in a certain way.
For example,
1st trial: 124 data points but want to evenly spread out these points to 100 points.
2nd trial: 128 data points but want to evenly spared out these points to 100 points.
3rd trial: and so on...
I want to do this as I want to be able to calculate the mean and standard deviation at each point i.e. at 1% or 2% of gait cycle.
It is kinda like keeping the same trendline/shape of the original graph (that had 124 points) but instead intrapolating 100 new points from that trendline that would represent the original data just the same.
Is there a way of achieving this?
Thanks in advance
I have had an extensive search of the net but am having trouble solving my predicament.
I am running into a dilemma with my research. Its regarding gait analysis.
I want to be able to present joint angles at a percentage of gait cycle in increments of 1 or 2%.
Right now, through normalization, I am able to present data with relative to gait cycle percentage, but the increments are all different for each trial. e.g. trial 1 has cycle percentage going up in 0.6 and trial 2 going up in 0.4 etc. (this is as each trial ends up giving different number of frames for one gait cycle)
I have a certain number of datapoints, and I want to be able to reduce this to another number so i can compare multiple trials easily. But I don't want to lose any datapoints, so want to average in a certain way.
For example,
1st trial: 124 data points but want to evenly spread out these points to 100 points.
2nd trial: 128 data points but want to evenly spared out these points to 100 points.
3rd trial: and so on...
I want to do this as I want to be able to calculate the mean and standard deviation at each point i.e. at 1% or 2% of gait cycle.
It is kinda like keeping the same trendline/shape of the original graph (that had 124 points) but instead intrapolating 100 new points from that trendline that would represent the original data just the same.
Is there a way of achieving this?
Thanks in advance
