CONCLUSIONS RESEARCH PURPOSE Background This study used Kinematic Data from 2 Subject Groups (Classified by Physicians as those with Symmetric Motion Patterns.

Slides:



Advertisements
Similar presentations
Motivation and diabetes self-management *Cheryl L. Shigaki, PhD, ABPP, **Robin L. Kruse, PhD, MSPH, **David Mehr, MD, MS, † Kennon M. Sheldon, PhD, ‡ Bin.
Advertisements

3-Dimensional Gait Measurement Really expensive and fancy measurement system with lots of cameras and computers Produces graphs of kinematics (joint.
ADVANCED STATISTICS FOR MEDICAL STUDIES Mwarumba Mwavita, Ph.D. School of Educational Studies Research Evaluation Measurement and Statistics (REMS) Oklahoma.
College Student Identity and Emotional Intelligence Abstract This research examines the longitudinal relationship between identity and emotional intelligence.
Attitudes toward Hearing Aids and Cochlear Implants for Older Adults among Ear, Nose and Throat (ENT) Physicians Patthida Maroongroge, D.D.S.*, Rose L.
Exploring the Utility of a Single-item Measure of the Readiness Ruler in Brief Interventions: Can We Determine Stage of Change? Introduction Motivational.
Copyright (c) Li Zhu Biostatistics and Its Role in Public Health Li Zhu, PhD Assistant Professor of Biostatistics Department of Epidemiology and.
Effect of Physician Asthma Education on Health Care Utilization of Children at Different Income Levels Randall Brown, Noreen Clark, Niko Kaciroti, Molly.
Method IntroductionResults Discussion Effects of Plans and Workloads on Academic Performance Mark C. Schroeder University of Nebraska – Lincoln College.
Kingdom of Saudi Arabia King Saud University College of Engineering Industrial Engineering department ERGONOMICALLY DESIGN, DEVELOPMENT, AND IMPLEMENTATION.
In the name of Allah. Development and psychometric Testing of a new Instrument to Measure Affecting Factors on Women’s Behaviors to Breast Cancer Prevention:
Chapter 12 Inferring from the Data. Inferring from Data Estimation and Significance testing.
Multivariate Data and Matrix Algebra Review BMTRY 726 Spring 2012.
Hypothesis 1: Narrow roadways and roadways with higher speed limits will increase risk of vehicle/bicycle crash Hypothesis 2: Bicycle lanes and signage.
® Introduction Mental Health Predictors of Pain and Function in Patients with Chronic Low Back Pain Olivia D. Lara, K. Ashok Kumar MD FRCS Sandra Burge,
® Introduction Low Back Pain Remedies and Procedures: Helpful or Harmful? Lauren Lyons, Terrell Benold, MD, Sandra Burge, PhD The University of Texas Health.
Chapter 9 Two-Sample Tests Part II: Introduction to Hypothesis Testing Renee R. Ha, Ph.D. James C. Ha, Ph.D Integrative Statistics for the Social & Behavioral.
Estimation and Confidence Intervals
Student Engagement Survey Results and Analysis June 2011.
® Introduction Back Pain Flare Ups, Physical Function, and Opioid Use Adriana Gonzalez, Darryl White MD, Sandra Burge PhD The University of Texas Health.
Comparison of Knee Kinematics during Anticipated and Unanticipated Landings Tony Moreno PhD CSCS School of Health Promotion and Human Performance Eastern.
Week 8 Chapter 8 - Hypothesis Testing I: The One-Sample Case.
Evaluating a Research Report
Chapter 3: Introductory Linear Regression
RESULTS INTRODUCTION Laurentian_University.svgLaurentian_University.svg‎ (SVG file, nominally 500 × 87 pixels, file size: 57 KB) Comparison of the ASQ.
Patterns of Event Causality Suggest More Effective Corrective Actions Abstract: The Occurrence Reporting and Processing System (ORPS) has used a consistent.
EVIDENCE ABOUT DIAGNOSTIC TESTS Min H. Huang, PT, PhD, NCS.
Chapter 4 Linear Regression 1. Introduction Managerial decisions are often based on the relationship between two or more variables. For example, after.
METHODS Setting Wichita State University Physician Assistant Program Study population WSU PA graduating class of 2003 and 2004 (n=84) Study design Retrospective.
Changing With The Seasons: Does vitamin D affect mood? Dave G. Downing & David C. R. Kerr, Ph.D. School of Psychological Science, College of Liberal Arts.
Marian Abowd, Dr. Cindy Trowbridge, Dr. Mark Ricard EFFECTS OF PATTERNED ELECTRICAL NEUROMUSCULAR STIMULATION ON KNEE JOINT STABILIZATION AbstractResultsConclusion.
Table 2: Correlation between age and readiness to change Table 1: T-test relating gender and readiness to change  It is estimated that 25% of children.
Do Instrumental Activities of Daily Living Predict Dementia at 1- and 2- Year Follow-Up? Findings from the Development of Screening Guidelines and Diagnostic.
IB Lab Check list Data Collection Assignment Due 9/30 □ Neatly drawn with ruler or on the computer □ One data table for qualitative data and one data table.
Journal Report The Effect of Listening To Classical Music On Students’ Performance, Motivation and Focus In Math Summarized by : Valentin Quanti S. MPd.
Relational Discord at Conclusion of Treatment Predicts Future Substance Use for Partnered Patients Wayne H. Denton, MD, PhD; Paul A. Nakonezny, PhD; Bryon.
© 2006 by The McGraw-Hill Companies, Inc. All rights reserved. 1 Chapter 12 Testing for Relationships Tests of linear relationships –Correlation 2 continuous.
How To Design a Clinical Trial
Chapter 6: Analyzing and Interpreting Quantitative Data
Instructors’ General Perceptions on Students’ Self-Awareness Frances Feng-Mei Choi HUNGKUANG UNIVERSITY DEPARTMENT OF ENGLISH.
ABSTRACT The purpose of the present study was to investigate the test-retest reliability of force-time derived parameters of an explosive push up. Seven.
Chapter 5: Introductory Linear Regression
European Patients’ Academy on Therapeutic Innovation The Purpose and Fundamentals of Statistics in Clinical Trials.
Course: Research in Biomedicine and Health III Seminar 5: Critical assessment of evidence.
Trouble? Can’t type: F11 Can’t hear & speakers okay or can’t see slide? Cntrl R or Go out & come back in 1 Sridhar Rajappan.
Aron, Aron, & Coups, Statistics for the Behavioral and Social Sciences: A Brief Course (3e), © 2005 Prentice Hall Chapter 10 Introduction to the Analysis.
Dr. Wang Xingbo QQ: Homepage: wxbstudio.home4u.china.com Fall , 2005 Mathematical & Mechanical Method in Mechanical.
Data Analytics Framework for A Game-based Rehabilitation System Jiongqian (Albert) Liang*, David Fuhry*, David Maung*, Alexandra Borstad +, Roger Crawfis*,
Chapter 5: Introductory Linear Regression. INTRODUCTION TO LINEAR REGRESSION Regression – is a statistical procedure for establishing the relationship.
Inferential Statistics Psych 231: Research Methods in Psychology.
Printed by Kendall M, Zanetti K & Hoshizaki TB. School of Human Kinetics, University of Ottawa. Ottawa, Canada A Novel Protocol for.
Literacy, Knowledge, Health Beliefs, and Self-efficacy among Urban, Low-income, Obese African American Women Feleta L. Wilson, PhD, RN 1 May T. Dobal,
Inferential Statistics Psych 231: Research Methods in Psychology.
M Eltoukhy, M Ziff, S Elmasry, F Travascio and S Asfour
How To Design a Clinical Trial
Melissa Ferlo [Mentor: Eric Scibek] College of Health Professions
Comparison of Nurse Mentor and Instructor
Clemson University Department of Bioengineering Clemson, SC 29634
From Action Representation to Action Execution: Exploring the Links Between Mental Representation and Movement William Land1,2,3 Dima Volchenkov3 & Thomas.
AN INTRODUCTION TO EDUCATIONAL RESEARCH.
INTERPRETATION OF RESULTS & CONCLUSIONS
Courtesy from Dr. McNutt
Sampling Distribution
Threat signals of pain modulate defensive responses in observers: development of an experimental paradigm Goubert, L.1*, PhD, Caes, L. 1, MSc, Uzieblo,
School of Behavioral Sciences
CHAPTER 10 Comparing Two Populations or Groups
Static Foot Structure May Predict Midfoot Mechanics
Chapter 10 Introduction to the Analysis of Variance
Quantifying Movement Agreement between Therapist and Patient
Normal as Approximation to Binomial
Presentation transcript:

CONCLUSIONS RESEARCH PURPOSE Background This study used Kinematic Data from 2 Subject Groups (Classified by Physicians as those with Symmetric Motion Patterns & Asymmetric Patterns exhibiting Neck Pain) to drive a Cervical Computer Model (See Figure 1 ). Hypothesis Kinematic patterns for the symmetric subject group will yield differences in muscle activities (predicted by the compute model) as compared to the asymmetric/pain group. Motivation To move toward an era of evidenced base medicine, it will be necessary to develop computer models that are more representative of the human body. Purpose Evaluate Potential of Cervical Computer Model (AnyBody) to Assist in Correlating Objective Measures (Kinematic Data) & Clinical Findings (Physician Classification). ANYBODY Cervical Model Figure 1 Computer Model Analysis of Cervical Lateral Function for Symmetric and Asymmetric/Symptomatic Subject Groups Emily Wandell, B.S. 1, Nicholas Beechnau, B.S. 1, William Smits, B.S. 1, Seungik Baek, Ph.D. 1, Jongeun Choi, Ph. D. 1, Mark de Zee, Ph.D. 2,3, Tamara Reid Bush, Ph.D. 1 1 Department of Mechanical Engineering, Michigan State University, East Lansing, MI Center for Sensory-Motor Interaction, Dept. of Health Science and Technology, Aalborg University, Denmark 3 AnyBody Research Group, Institute of Mechanical Engineering, Aalborg University, Denmark RESULTS PROCEDURE No agreement, subjects not invited to participate in the Kinematic test 1. Screening Two examiners screened subjects by performing a standard palpatory motion test of cervical lateral flexion. (See Figure 2) Examiner Agreement Subjects Classified as: 1)Symmetric (10 Subjects) 2)Asymmetric/Pain (Self Marked Score of 4 or higher on a Pain Scale) (9 Subjects) 4. Output 3D Kinematic Data: Position of neck given by 3 Angles of Neck Motion over the data collection time. (See Figure 4) Figure 4 3. Kinematic Test/ Data Collection Subjects had markers placed on their head & sternum. Examiners performed the same lateral motions used in screening Kinematic data was collected using 5-camera Qualisys system (See Figure 3). Figure 3 Figure 2 5) AnyBody Model 3-D Movement Patterns for each subject was inputted into the Cervical Model (AnyBody) & used to drive the model. By solving the muscle recruitment problem, the model provided a % of max muscle force for muscle groups used in the activity Figure 5 (Left) Experimental Data Collection (Right) Model Driven with Actual Kinematic Data  Higher Activity for Symmetric Subjects might be Expected *Because as a Group had a Larger Range of Primary Motion*  Strong Trend: Symmetric Subjects had Higher Levels of Muscle Activity (See Table 1)  Statistics (t-test at 95% confidence level): Trapezius Activity had Significant Difference (p=0.03) Between Groups Other Muscle Groups (Sternocleidomastoid, Longus Colli, Scalenus Medius, & Scalenus Posterior) had Low p Values & with a Larger Sample May Show Significant Differences 1)1 Challenge: (in Biomechanical Assessments of humans) Large Range of Variability! *Model can Provide Estimations for Mainstream Populations* 2) 2 Challenge: controlling specific parameters. *Predictive Scenarios could be studied with a computer model to shed insight into how parameters affect the kinematics or the muscle forces associated with an activity* Thus, a Model can Help Refine Studies IMPLICATIONS A model increasingly more representative of the human cervical region can be used in combination with biomedical/clinical assessments to facilitate the move toward evidence-based strategies! RELEVANCE