1. Lecture 3 Wednesday February 8 Dr. Moran

2. Lecture Outline Assignment #1 »Class Presentations of Research Articles Problems with Excel Practice Calculations Further explanation of Assignment #2 Data Manipulation »Normalization »Missing Data Points Angular Kinematic Data Presentation 3D Kinematics - Introduction

3. Data Manipulation How does a researcher average data across numerous trials? »Problem: each trial does not take the same amount of time so computing the mean for each frame would not be correct »Solution: Steps to Compute Ensemble Average 1.) Normalize: Ex (Gait): from right-foot toe-off to right-foot toe-off is considered one full cycle 2.) Data Interpolation: What data frames could we use to match trials from the vertical jump kinematic analysis?

4. Normalizing Data Picking Out Event Markers Trial #1: Frame 63 LEFT HEEL STRIKE Trial #1: Frame 91 LEFT HEEL STRIKE

5. Normalizing Data (Continued) Event #1Event #2 Trial #16391 Trial #25483 Sampling Frequency = 60 Hz (60 frames/second) s s MS Excel Tutorial

6. Linear Interpolation Assumption: that the data between collected data points is linear. That may be acceptable when »Ex: Data Point #1 (x,y)0.310s1.185m Data Point #2 (x,y)0.315s1.190m Linear Equation: So: f(3.11) = 0.311 + 0.875 = 1.186 f(3.12) = 0.312 + 0.875 = 1.187 …

7. Linear Interpolation (continued) For movements that occur rapidly and the sampling rate is not high, a spline interpolation is warranted. MS Excel Add-In: cubic spline interpolationcubic spline interpolation These methods would also be used to deal with missing data points. Missing data points can occur in kinematic analysis when markers are blocked during a movement sequence.

8. Angular Kinematics Presentation Presentation Form Joint Angle vs. Time Angle-Angle Diagram »Aids visual understanding of a movement sequence »Handout  distance running Phase Plot »Motor Control Field 

9. Angle-Angle Plots Running A Drill Running B Drill Sprinting Online Abstract

10. 3D Kinematics Introduction to Matrix Algebra Hand notes