1 Introduction EducationBinghamton University, The State University of New York, NY, USA Doctor of Philosophy in Industrial and Systems Engineering , GPA (3.7/4.00) Embry Riddle Aeronautical University, FL, USA Master of Aeronautical Science, (Human Factors in Aviation ), GPA (4.00/4.00) Central Michigan University, MI,USA Master of Science in Administration, (Acquisition Admin ), GPA (3.82/4.00) Jordan University of Science & Technology(JUST) BSc, Mechanical Engineering (Dual Concentrations: Aeronautical and Thermal Power Engineering) Joint Services Command and Staff College (JSCSC) Diploma, UK Intermediate Command and Staff Course - (ICSC) (Shrivenham, Royal Air Force / United Kingdom) Command and Staff School Diploma Leader Ship and Intermediate Command and Staff Course (Royal Air Force) CERTIFICATIONS & TECHNICAL SKILLS Green Belt & Black Belt Six Sigma Certificate -General Electric, Cincinnati /U.S.A. Management Information System (SAMIS) Course, Wright Patterson AFB (USA). LRQA Total Quality Management Course, (LLOYD’S Register Quality Assurance Com). Quality Control Course for officers, (Royal Jordanian Air Force), Jordan. Federal Aviation Administration license (FAA) (Mechanic Airframe and Power Plant), U.S.A. EASA, Civil Aviation Authority License (CAA) (Mechanic Airframe and Power Plant), Jordan. Project Management Professional Certificate, Electrical and Instrument aircraft components, Depot Level Course (Republic Of Taiwan). Aviation Maintenance Officer Certificate (Royal Air Force). Defense Institution for Security Assistance Management (DISAM), WPAFB, (USA). Air Force Security Assistance Centre (AFSAC) (USA).

2 Introduction GRADUATE COURSEWORK Industrial EngineeringIndustrial Engineering Advanced Integrated Manufacturing Production Concepts Applied Experimental Design (DOE) Applied Multivariate Data Analysis Supply Chain Management Human Factors /Ergonomics Advanced Human Factors Engineering And Design Human Factors in the Aviation/Aerospace Industry Aviation/Aerospace Psychology Memory and Cognition Human Computer Interaction Quality Management Management and Control of Quality Statistical Quality Control Quality Assurance for Engineers Six Sigma Courses (BB ) Business/Admin, Management Integrative Analysis of Admn Managerial Accounting Concepts Purchasing Strategy Financial Management Marketing Administration Program Analysis and Evaluation Regulatory Processes and Administrative Law Aviation Industry Air Transportation Systems Aircraft and Spacecraft Development Aircraft Maintenance Management Administrative Research and Reporting Methods Systems Engineering Applied Soft Computing Fuzzy Logic and Fuzzy System Systems Problem Solving Quantitative Applications in Admin and Decision Making

3 Introduction PROFESSIONAL EXPERIENCEBinghamton University, State University of New York (Watson School of Engineering) Teaching Assistant Al-Balqa' Applied University (Prince Faisal Aeronautical Technical College) Amman, Jordan Dean Assistant & Chairman of Mechanical Engineering Department Aug 2008-March 2010 Royal Jordanian Air Force Royal Air Force, Jordan Quality Control Courses Techer/Trainer Directorate of Maintenance/Royal Jordanian Air Force Amman, Jordan Chief of American military aircraft maintenance & Quality Control Division March Dec 2011 United States Air Force, Air Force Security Assistance Centre (AFSAC) Wright Patterson AFB.USA Supply Chain, Logistic and Maintenance (Manager) Foreign Liaison Officer (FLO) Oct Jan 2007 King Hussein Air College, Royal Air Force Mafraq, Jordan Chief of Aircraft Maintenance Wing March2008-Aug 2010 Directorate of Maintenance/Royal Air Force Amman, Jordan chief of Munitions and Armament Systems Division March 2011-Aug 2014 Jet Engine Intermediate Maintenance Depot /Moufaq Salti Air Base Azraq, Jordan Commander of the Jet Engine Intermediate Maintenance Depot Feb 2007-March 2008 Directorate of Supply/ Royal Air Force Amman, Jordan Supply chain Manager for Military aircraft Jan 1998-Nov2004 Aircraft Component Maintenance Depot / Royal Air Force Safawi, Jordan Aircraft Components Depot Maintenance Chief Aug Dec 1995

4 Introduction HIGHLIGHTS OF QUALIFICATION, SKILLS & INTERESTSIndustrial engineering (education, operations, quality, manufacturing and production, assembly lines. Etc) System engineering (Strong analytically skills, statistical analysis, artificial intelligence and soft computing). Management of undergraduate educational institutes (assistant deanship and mechanical department chair at Al-Balqa' Applied University. Human Factors & Ergonomics Engineering. Quality management, control and assurance expert (Highest education, trainer, practitioner and long expertize). Black and Green Belt Certification in Six Sigma from first leading aviation engines company (General Electric) Management and business Science, professional project and program management, business development, acquisition administration, supply chain management, purchasing, marketing, contractor global program administration, managerial financial cost analysis. Aviation Systems expert, aircraft assembly, maintenance management, engineering analysis in aviation Systems, and aircraft armament systems. Universal Aviation licenses (American (FAA) Federal aviation administration (USA) and European / EISA Approved/ (CAA) Civil aviation Administration (Jordan). I have led high tech projects where I assembled Hughes MD500 A/C first time in Jordan with no prior experience A Security Assistance and Foreign Military Sales Program Expert. PROFESSIONAL EXPERIENCE Binghamton University, State University of New York (Watson School of Engineering) Binghamton, NY Teaching Assistant Aug Dec 2015 Al-Balqa' Applied University (Prince Faisal Aeronautical Technical College) Amman, Jordan Dean Assistant & Chairman of Mechanical Engineering Department Aug 2008-March 2010 Royal Jordanian Air Force Royal Air Force, Jordan Quality Control Courses Techer/Trainer Directorate of Maintenance/Royal Jordanian Air Force Amman, Jordan Chief of American military aircraft maintenance & Quality Control Division March Dec 2011 United States Air Force, Air Force Security Assistance Centre (AFSAC) Wright Patterson AFB.USA Supply Chain, Logistic and Maintenance (Manager) Foreign Liaison Officer (FLO) Oct Jan 2007 King Hussein Air College, Royal Air Force Mafraq, Jordan Chief of Aircraft Maintenance Wing March2008-Aug 2010 Directorate of Maintenance/Royal Air Force Amman, Jordan Chief of Munitions and Armament Systems Division March 2011-Aug 2014 Jet Engine Intermediate Maintenance Depot /Moufaq Salti Air Base Azraq, Jordan Commander of the Jet Engine Intermediate Maintenance Depot Feb 2007-March 2008 Directorate of Supply/ Royal Air Force Amman, Jordan Supply chain Manager for Military aircraft Jan 1998-Nov2004 Aircraft Component Maintenance Depot / Royal Air Force Safawi, Jordan Aircraft Components Depot Maintenance Chief Aug Dec 1995

5 A Psychophysical Approach for Measuring Isometric and Isotonic Hand Muscles Strength in the Aviation Industry Hesham A. Al-momani Ph.D. Candidate Systems Science & Industrial Engineering Department State University Of New York at Binghamton Dissertation Defense Presentation November 25 , 2015

6 Agenda Introduction Motivation Literature Review Research ObjectivesUniqueness and Significance Methodology Results and Discussion Conclusions and Future Work

7 Introduction Started with non-medical applications“Hand represents the identity of  human, they are the only primates known to be able to form a fist” (David Carrier, 2013) Started with non-medical applications Transitioned to medical applications Various cultures Hand reflexology clinics are available in many countries.

8 Introduction (cont’d)Vitals (Royal College of Physicians of London, 2013) Are used to measure the body’s basic functions Help assess the general physical health of a person Give clues to possible diseases Show progress toward recovery Vital signs vary with age, weight, gender, and overall health Four primary vital signs: body temperature, blood pressure, pulse, and breathing rate Fifth vital sign (Pain, Glasgow Coma Scale, Pulse Oximetry & Blood Glucose level) (Neff, 1988) Sixth vital sign (End-tidal CO2, Functional status, Shortness of breath and Gait speed (Studenski et al., 2003) Seventh (Future): Grip Strength Many Names & Many Definitions: according to World Health Organisation. & Canadian Centre for Occupational Health and Safety & National Institute of Occupational Safety and Health (NIOSH)

9 Work-Related Musculoskeletal Disorders (WMSDs)Group of painful disorders Muscular discomfort, hurt and pain, exhibited in muscles, tendons, and nerves (Canadian Centre for Occupational Health and Safety, 1998) Diseases and injuries that affect the musculoskeletal system That are caused or aggravated by occupational exposure to ergonomic hazards (NIOSH, 1997) Characterized Multi Factorial /Work-Related Complaints (WHO, 1985) Depends on Individual Capabilities, Physical Limitations & Work Organizational Policies (WHO, 1985) Many Names & Many Definitions: according to World Health Organisation. & Canadian Centre for Occupational Health and Safety & National Institute of Occupational Safety and Health (NIOSH)

10 WMSDs – Classification & Cost1. Risk Factors (HSE, 2002) Task-Related Factors Environment-Related Factors Psychosocial Factors Worker-Related Factors 2. Distinct Features (NIOSH, 1997) Body Parts (Muscles, Joints) Event (Slip Or Fall) Intensity (Persistent) Special or Distinctive (Carpel Tunnel Syn) Occasional Disorders (Events) Very Difficult To Classify I go with this classification The National Institute for Occupational Health and Safety

11 Hand Grip Strength Grip strength Types of Hand Grip (Bookfield, 2008)Most used body parts (consist of 35 different muscles) Hand grip does not act by itself, its related to hand muscles strength (Gonzalez et al., 1997) Hand Grip Main muscles Forearm muscles (3) Hand muscles (6) Grip strength Force applied by the hand to pull on or suspend from objects (Koley et al., 2009) Types of Hand Grip (Bookfield, 2008) Crush Grip Pinch Grip Support Grip

12 Importance of Hand Grip StrengthIndicator Tool where strong handshake correlation can indicate (Sanderson et al., 2014 ) Power, confidence, health, or aggression Measure true age (** More educated men had aged more slowly) Diagnostic and Screening Tool (Sirajudeen et al., 2012) Human overall health and upper body general strength Quality of life among critical patients General body health (Mital et al., 1989; Mital & Faard, 1990) Predictive Tool Future events such as “post-operative complications” (Sirajudeen et al., 2012) Capability and ability to battle the deadly disease (Kilgour et al., 2013) Ability to recover from hospital stays (Sanderson & Scherbov, 2014) Human population aging “future mortality, cognitive decline” (Sanderson & Scherbov, 2014)

13 Importance of Hand Grip Strength (Cont’d)Disease Correlations Cancer rates survival (Kilgour et al., 2009) Nutritional status, bone mineral content (Sirajudeen et al., 2012) Chronic kidney disease patients (Gerontology Department, Ain Shams University, Cairo, 2013) Risk of stroke in people over age 65 (American Academy of Neurology's, 2014) Dementia & walking speed (Sanderson et al., 2014; American Academy of Neurology's, 2014) Sports General muscle strength, athletes training, strengthen hand muscles for athletes (e.g., wrestlers, golfers, tennis players (Bohan, 2004; Wind et al., 2009) Pre-Employment Tool The grip tests used as pre-requirement for workers give both the general body health and strength indication (Keyserling et al., 1980; Chaffin, 1975; Jackson, 1994)

14 Human Strength Types Isometric Muscle StrengthCapacity to produce torque or force by a maximal voluntary isometric muscular exertion (Chaffin, 1975) Isotonic Muscle Strength Capacity to produce torque or force while the muscle changes length during contraction and cause movement of the body (Knapik & Wright, 1983) Divided into Two Types Eccentric Isotonic: Muscle length extended during the contraction Concentric Isotonic: Muscle length shortened during the contraction Isokinetic Muscle Strength Ability to exert maximum force with producing movement with constant Velocity (Jackson, 1994) Isometric Muscle Strength :(Capacity To Produce Torque Or Force By A Maximal Voluntary Isometric Muscular Exertion) & Static Measurement Of Strength ) B. Isotonic Muscle Strength: (capacity to produce torque or force while the muscle changes length during contraction or ext) & wher muscle length changed in none constant speed during movement of the body parts ). Isotonic Muscle Strength divided into two types (length of muscle) : Eccentric Isotonic (muscle length extended during the contraction) Concentric Isotonic (Muscle length shortened during the contraction). C. Isokinetic Muscle Strength (The ability to exert maximum force with producing movement) where Muscle Strength the muscle changes its length in constant rate/ manner.

15 Human Muscle Fatigue Definitions Endurance Limit Human Fatigue TypesState which is characterized by a feeling, the feeling of fatigue, combined with the feeling of a reduction in activity (Rohmert, 1966) Endurance Limit Defined as force and time relationship where the muscles capability and ability to sustain the whole or percentage a mount level of maximum voluntary contraction (MVC) (Force) over time (Kumar et al., 1991) Human Fatigue Types Physical Fatigue (Vollestad, 1997) Mental Fatigue (Baumeister, 2002) Human Fatigue Causes (Kumar and Faga, 2003) Human Capabilities and limitations Task (Worker)-Related factors Environment-Related Factors Psychosocial Factors Difference Material and Human factors ) that includes (doing a certain job repeatedly( Repetition), Posture, extended Duration, Recovery time,Extra repetitive motions , Psychosocial factors,excessive physical work , Workload and pacing,extended use of human muscle , Hand-Arm vibration, Cold stress,uncomfortable awkward postures ,Force, Velocity/Acceleration and mechanical stress caused by or over a long period that exceeds worker body limits), Heavy loads over short time job tasks or small load over an extended period of time beside the repetitive tasks and directly proportional with the amount of load force , load exertion time, , and abnormal postures and inversely proportional with rest time.

16 Human Muscle Fatigue (cont’d)(Human Capital Review, 2015) Difference Material and Human factors ) that includes (doing a certain job repeatedly( Repetition), Posture, extended Duration, Recovery time,Extra repetitive motions , Psychosocial factors,excessive physical work , Workload and pacing,extended use of human muscle , Hand-Arm vibration, Cold stress,uncomfortable awkward postures ,Force, Velocity/Acceleration and mechanical stress caused by or over a long period that exceeds worker body limits), Heavy loads over short time job tasks or small load over an extended period of time beside the repetitive tasks and directly proportional with the amount of load force , load exertion time, , and abnormal postures and inversely proportional with rest time.

17 Various Measurement ApproachesPhysiological Approach (Dempsey, 1998) Measure “The amount of oxygen intake, energy spending rate, and heart rate” to design a task within human body physiological measures and will be within acceptable limits Biomechanical Approach (Jorgensen et al., 1999) Measure joint moment, joint torque, compression force on the spine, and shear forces on the lumber spine against human physical structure Psychophysical Approach (Nook, 1978; Jorgensen et al., 1999; Al-Meanazel, 2013) It depends on human subject judgment of stress and strain on human joints and muscles

18 Motivation Aviation: Assist aviation industry pilot and mechanic training, aviation trades Diseases Correlations (Kilgour et al., 2009; Sirajudeen et al., 2012; Sanderson et al., 2014) Sports (General Muscle Strength, Athletes Training) Strengthen hand muscles for athletes (wrestlers, golfers, tennis players) (Bohan, 2004; Wind et al., 2009) Industries (Task Design): Provide guidelines for type, duration, operation of drilling and other tools (Dubrowski et al, 2004) Healthcare and Clinical Settings (Boissey et al., 1999) Human Overall Health and Physical Factors Studies Attitude, disability and mortality, survival rates of diseases Battle deadly diseases, relationship with sickness, nutrition (Sanderson & Scherbov, 2014) Job Strength Performance Requirements/Measurement: Fire departments, police (Ruiz et al., 2002; Dubrowski et al., 2004) Diagnostic Tool: To gauge strength and quality of life among critical patients and population aging (Sirajudeen et al., 2012) One of the most-discussed topics at aviation safety seminars is the so-called "human factor", and it's also a fundamental subject during pilot and mechanic training. Yet, despite widespread awareness of the importance of human factors in safety, the FAA says it continues to play a key role in a majority of today's aircraft incidents and accidents. Brittle and sickness

19 Research Objectives Objective 1: Conduct a comprehensive literature review to develop a comprehensive understanding of the factors that impact grip strength Objective 2: Perform an experimental using psychophysical approach to investigate the effect of static/dynamic forces on the hand grip strength, MVC, and fatigue A- Aviation trades experts (middle age subjects) B- Medertrainian (Jordan) race C- High number of smokers D- Use high precision apparatus (Digital dynamometer) E- Include forearm circumference F- Posture (Seated, Standing) Objective 3: Assess and evaluate the effectiveness of various models to predict the maximum voluntary contraction, the maximum isometric endurance limit for holding submaximal of maximum voluntary contraction and predict maximum number of frequency for isotonic muscle fatigue Mathematical/Statistical Models Artificial Neural Networks (ANNs) Adaptive Neuro-fuzzy Inference System (ANFIS)

20 Uniqueness and SignificanceAviation Industry No formal research on the effect of the combined forces on muscle fatigue Pilots and different trades mechanics use a combination of isometric & dynamic isotonic forces New Factors and More Comprehensive and Detailed Models New accurate apparatus digital dynamometer, forearm grip circumference,  Mediterranean race, posture, larger smoker’s sample, older ages, young and middle ages subject Various mathematical/statistical and artificial intelligence model Verification of Hand Grip Literature Using A Psychophysical Approach Because Biomechanical and physiological approaches were extensively used to predict the endurance and fatigue limits, only to determine the fatigue limits (Marley & Fernandes, 2012) Set Standard Procedure For more accuracy, researches output comparison and future research Relevant to industry (more realistic Industrial settings), where workers use combination of static (isometric) as well as dynamic (isotonic) forces

21 Research Methodology

22 Overall Framework Collect DataRecruit aviation subjects Get personal data (age, smoking effect, hand volume, and dominant hand) Descriptive analysis is presented (anthropometry measurement) Design & Perform Experiment Three tests will be conducted in this research: Maximum voluntary contraction test (MVC) test Isometric muscle fatigue test Isotonic muscle fatigue Analysis and Modeling Descriptive Statistics Regression Analysis to analyze the data Design comprehensive model using Artificial Neural Network models Use adaptive neuro-fuzzy inference system (ANFIS) Conclusion and Recommendations List effect of each factor/combination of factors on the endurance limit Summarize all the preliminary findings Make recommendations Assign future work

23 Participants & Descriptive Statistics132 (Active Duty & Retired) Royal Jordanian Air Force (RJAF) participants All Males Variable Mean StDev Median Minimum Maximum Age (Y) 41.71 7.83 42.50 25.00 65.00 Weight (Kg) 82.60 12.85 84.00 55.00 114.00 Height (M) 1.75 0.07 1.83 1.55 1.93 BMI 26.67 3.60 27.42 18.71 37.42 HGC (CM) 22.52 1.33 25.5 19.50 25.50 FAC (CM) 29.34 2.44 35.00 23.00 Subjects group ages started from 25 to 60 years Five trades 60% smokers HGC (Hand Grip Circumference ) FAC *Forearm Circumference)

24 Experimental ApparatusDigital Hand Grip Dynamometer Gollehon Extendable Goniometer Measuring Tape Digital Stop Watch Digital Weighing Scale Digital Hand grip dynamometer ( used to determine the MVC). suitable hand held device that measures hand strength using an analog gauge, as shown in Figure ..-.. Analogue Hand grip dynamometer ( used to determine the MVC). suitable hand held device that measures hand strength using an analog gauge, as shown in Figure ..-.. 2. Gollehon extendable goniometer.. (accurate and reliable tool to assess joint angles. This tool used to obtain three 90˚ joint angles (Elbow flexion, Knee, and hip). 3 . Measuring tape was also used to measure the height and the hand GC. 4. Digital stop watch To record the endurance limit, the time was recorded to the nearest second. 5. Overflow Vessel and a measuring cylinder to measure Hand volume measurement 6. Digital scale used to measure weight , with the weight rounded to the nearest 0.1 kg.

25 Experimental VariablesDependent Variables  Independent Variables Treatment Levels MVC Isometric Fatigue (Time to Fatigue) at Load Range (20%, 40%, 60%, 80%) Isotonic Fatigue (Time to Fatigue) with both movements Slow & High Speed Fixed Factors: Race (Jordanian) Gender (Male) Apparatuses: Digital Dynamometer Age (years) A0: (25-<30) A1: (30- <35) A2: (35-<40) A3: (40-<45) A4: (45-<50) A5: Above 50 Trade APG: (Airplane General) E&I: (Electrical and Instrument) COMNAV: (Communication & Navigation) Eng: (Engine ) GSE: (Ground Support Equipment) Smoking Smokers Non Smokers Body Mass Index (BMI)  Small : S (19 - <25) Medium: M (25-<30) Large: L above =<30 Hand Grip Circumference (CM) Small : S (=< 21.5) Medium: M (> ) Large: above 23.5 Hand Dominancy D: Dominant ND: Non-Dominant Forearm Circumference (CM) Small: S (<= 27.5) Medium: M (> ) Large: above 31 Posture Sitting: SIT (Sitting) Standing: STD (Standing) Height (M) Short: S (<= 1.70) Medium: M (> ) Tall: above 1.81

26 Methodology – Experimental RunGet Anthropometric Data (subjects) Height Weight Hand grip circumference GC Gender Forearm circumference GC 6. Smoking Condition 7. Dominant Hand 8. Trade 9. BMI MVC Test Seated with 90 joint angles (hip, knees and elbow) Hand grip Dynamometer adjusted to fit the GC Each subject to exert maximum force on the Dynamometer Do three Maximum Grip strength (MVC) for 5 sec each for dominant and 5 minutes rest and record results Repeat for non-dominant hand Repeat for Seating & Standing Isometric Endurance Limit Test Seated with 90 joint angles (hip, knees and elbow) Hand grip Dynamometer adjusted to fit the GC Hold at 20%, 40%, 60% and 80% of MVC until fatigue Rest for 5 minutes Repeat for non-dominant Repeat for Seating & Standing Isotonic Endurance Limit Test Seated with 90 joint angles (hip, knees and elbow) Hand grip Dynamometer adjusted to fit the GC Move pointer hand grip Dynamometer between 20%, and , 60% slowly and then high speed until fatigue Rest for 5 minutes Repeat for non-dominant Repeat for Seating & Standing

27 Methodology – AnalysisData MVC Data Isometric Endurance Limit Isotonic Muscle Fatigue Statistical Analysis: MANOVA and ANOVA Develop Linear Regression Models (LR) Develop Non-Linear regression Models (NLR) Perform Neural Network Models Perform ANFIS

28 Pilot Study 21 Male Subjects (Engineers and Technicians) from Royal Jordanian Air force Ages range of years (10 of them are non-smokers) and used digital hand grip dynamometer

29 Normality & Outliers Test

30 Correlation Analysis

31 Correlation Analysis (cont’d)Correlation effect appears as expected correlations between physical factors of human body (FAC with (HGC, BMI & Weight)) Other high correlated variables are expected since they are terms in BMI calculations Negative correlation noticed Between MVC & Isotonic Endurance limit Terms (Low & High Speed) Between age and height of subjects Positive correlation noticed MVC values with isometric endurance limit 4. Experiment correlation factors considered suitable for this human-subjects experiment Correlation, normality and outlier analysis Conclusion: This is human subject experiment with many independent factors related together for the experiment subject’s human body. Covariance as measure of linear association test the relationship between two or more dependent factors (responses), can be done in two ways, run a covariance test or a correlation test and since correlation coefficients are function of the covariance, positive covariance will result in a positive correlation and vice versa.

32 MANOVA Maximum Voluntary Contraction (MVC)ANALYSIS FACTOR Wilk’s Lawley-Hotelling Pillai’s Maximum Voluntary Contraction (MVC) Age 0.000 Height Trade 0.036 HGC BMI 0.001 FAC 0.00 Isometric Endurance Limit (20%) (40%) (60%) (80%) Isotonic Endurance Limit (20%-60%) 0.002 0.027 .000 0.019 (MANOVA)  procedure used to investigate multiple responses (dependent variables) versus multiple independent factors Can increase chances for finding a group difference It might find out differences that do not detected under ANOVA, and decrease the type I error (rejection of a true null hypothesis) In this experiment we have three main subjects with nine detailed dependent factors special cases, MINITAB displays MANOVA table that consist of four multivariate tests (Wilks' test, Lawley- Hoteling , Pillai's and Roy's test . The hypothesis is that none of the independent variables have any effect on the responses. The MANOVA The results indicated that all of the factors (independent variables) have an effect on the responses. The MANOVA chart indicates that further analysis by ANOVA is necessary on these factors (or combination of factors) for evaluation of effect of each factor on the responses. **HGC (Hand Grip Circumference ) ** FAC (Forearm Circumference)

33 ANOVA Experiment has categorical & continuous factorsIndependent factors interaction terms up to two interactions may be four!!. ANOVA performed through design of experiment procedure in Minitab 17 with full factorial general linear method since experiment has different independent factors with more than two levels Using both general (normal) and stepwise procedure Compare significant factors output results with prior knowledge from literature review. Stepwise procedure highly considered because its more accurate, mostly used in the exploratory stages of building the regression model to find out the best a useful subset of dependent factors (predictors) include only variables needed in the model (Prost et al., 2008) Stepwise procedure always include the most significant (independent factor) variable and eliminates the least significant (independent factor) variable through each step It has both forward and backward selection where forward selection starts with assumption no predictors in the model and backwards elimination starts with assumption all predictors in the model But Stepwise procedure has pitfalls Because of high independent variables correlation issues (which is expected in this human subject experiment) where model can include only one factor even though other correlated factor may be important, and this will be solved by the prior knowledge as mentioned above. Stepwise procedure also may not end with the highest R2 value model for an experiment given number of dependent factors (predictors), do not include the special knowledge the data. Make calculations by chance.

34 Residual Plot Example Pattern correlation

35 General Linear RegressionMVC = AGE(Y) HEIGHT(M) BMI HGC(CM) FAC(CM) RMSE: R-Sq: R-Sq,(Adj) 0.443 Isometric End Limit (Avg) = AGE(Y) HEIGHT(M) BMI HGC(CM) FAC(CM) RMSE: R-Sq: R-Sq,(Adj) Isometric (20%) = AGE(Y) HEIGHT(M) BMI HGC(CM) FAC(CM) RMSE: R-Sq: R-Sq,(Adj) 0.104 Isometric (40%) = AGE(Y) HEIGHT(M) BMI HGC(CM) FAC(CM) RMSE: 33.4 R-Sq: R-Sq,(Adj) 0.118 Isometric (60%) = AGE(Y) HEIGHT(M) BMI HGC(CM) FAC(CM) RMSE: 21 R-Sq: R-Sq,(Adj) Isometric (80%) = AGE(Y) HEIGHT(M) BMI HGC(CM) FAC(CM) RMSE: 13.2 R-Sq: R-Sq,(Adj) Isotonic End Limit = AGE(Y) HEIGHT(M) BMI HGC(CM) FAC(CM) RMSE: R-Sq: R-Sq,(Adj) linear regression (LR) modelling (Minitab 17 & Mat lab 15) Extracted for both the significant factors received from ANOVA & MANOVA analysis. but because of nature of the experiment and expected multicollinearity issue general linear model will be extracted. General and stepwise regression model used to find out predicted model .Stepwise regression model generally works by selecting a subgroup of explanatory variables using statistical principles.

36 General Non-Linear RegressionMVC= * AGE(Y)^ *HEIGHT(M)^ *BMI^ *HGC(CM)^ *FAC(CM)^2 RMSE: 6.3 R-Sq: R-Sq,(Adj) 0.445 Isotonic , End, Limit = * AGE(Y)^ *HEIGHT(M)^ *BMI^ *HGC(CM)^ *FAC(CM)^2 RMSE: 16.9 R-Sq: R-Sq,(Adj) Isometric End Limit(Avg) = * AGE(Y)^ *HEIGHT(M)^ *BMI^ *HGC(CM)^ *FAC(CM)^2 RMSE: 23.8 R-Sq: R-Sq,(Adj) 0.101 Isometric (20%) = * AGE(Y)^ *HEIGHT(M)^ *BMI^ *HGC(CM)^ *FAC(CM)^2 RMSE: 58.4 R-Sq: R-Sq,(Adj) 0.107 Isometric (40%) = * AGE(Y)^ *HEIGHT(M)^ *BMI^ *HGC(CM)^ *FAC(CM)^2 RMSE: 33.5 R-Sq: R-Sq,(Adj) 0.109 Isometric (60%) = b2* AGE(Y)^ *HEIGHT(M)^ *BMI^ *HGC(CM)^ *FAC(CM)^2 RMSE: 21 R-Sq: R-Sq,(Adj) Isometric (80%) = * AGE(Y)^ *HEIGHT(M)^ *BMI^ *HGC(CM)^ *FAC(CM)^2 RMSE: 13.1 R-Sq: R-Sq,(Adj) Non -linear regression (LR) modelling (SAS and Mat lab 15) It is used to get a the best (good) fit with linear regression mode lining technique and cant model the specific curve that exists in experiment data, it can fit any model, including a linear regression which is considered as special case of nonlinear modeling or regression, in this approach the independent factors data are modeled by using function that represents a nonlinear combination of the experiment independent variables parameters. Improve model accuracy , make the line or curve come as close as possible to the data by extracting the Non -linear regression (LR) models and minimizing experiment error I will use quadratic nonlinear approach since its recently used by latest researchers and sometimes has the lowest possible model error among all Non Linear dissimilar forms

37 RMSE & R-Sq Values (Linear & Non-Linear) RegressionRMSE Linear Regression RMSE Non-Linear Regression R-Sq Linear R-Sq Non-Linear Sitting Posture (Avg) 6.01 6.02 0.49 Standing Posture (Avg) 6.25 6.23 0.47 0.52 Dominant Hand (Avg) 5.81 5.76 0.44 Non Dominant Hand (Avg) 6.445 6.49 0.48 Avg 6.129 6.125 0.482  Term RMSE Linear Regression RMSE Non-Linear Regression R-Sq Linear R-Sq Non-Linear ISOMETRIC END LIMIT (20%) 59.6 59.5 0.117 0.119 ISOMETRIC END LIMIT (40%) 34 34.2 0.129 0.0917 ISOMETRIC END LIMIT (60%) 21.5 0.0817 0.0844 ISOMETRIC END LIMIT (80%) 13.4 13.3 0.0825 0.0945 Avg 32.12 32.125 0.0974  Term RMSE Linear Regression RMSE Non-Linear Regression R-Sq Linear R-Sq Non-Linear Isoto End 20-60% LS, RH 15.7 0.0493 0.0514 Isoto End, 20-60% HS,RH 14.1 14 0.179 0.191 Isoto End, 20-60% HS, LH 20.7 20.6 0.183 0.185 Isoto End, 20-60% lS, LH 13.6 0.102 0.104 Avg 16.02 15.98

38 MVC Relationships Linear Relationship: MVC and Ages (Chatterjee & Chowdhuri, 1991) Non-linear Relationship Strength-time curve relationship between (maximum strength and length-time) that has an early peak followed by gradual decrease in strength (Kamimura & Ikuta, 2001) Relationship between MVC% and endurance limit with different postures for a given elbow flexion angle (Garg et al., 2002) Max MVC MVC at 20 years old (Chatterjee & Chowdhuri, 1991) Companies Charts, Highest exerted MVC was for young subjects ages between (25-29 years old) (Clerke, 2005) Chatterjee & Chowdhuri, 1991

39 Grip Strength Models – MVC[Chatterjee & Chowdhuri, 1991] 39

40 MVC Fractions MVC Fraction Conclusion Researcher(s) 5%Curve Does Not Become Asymptotic even at 5% of MVC and Different MVC%s Garg et al., 2002 10-15% Holding time did not vary between high and Low BMI persons MVC & the muscle fatigue rate increasing rapidly when muscle contraction tension go beyond the (10%-15% envelope) Funderburk et al., 1974 Rohmert, 1960a,b; Merton, 1654; Funderburk et al., 1974 30% Up To Of MVC%, Uniform Increase At 30% MVC other researchers models get altered values (lower or higher) Garg et al., 2002 Eksioglu, 2011 30-90% Slower rate decrease in endurance limit with uniform increase in MVC% 40% Extra endurance limit average of 16 seconds more than the non- dominant hand Independent of gender and age Chatterjee & Chowdhuri, 1991 General Non-linear relationship (Decrease endurance limits during increase MVC%) Maximum endurance limit results for non smoker male that have both (higher BMI and grip circumference) Al Meanazel, 2013

41 Endurance Charts Linear relationship: endurance limit vs. time domain (Yeung & Evans, 1998) Non-Linear relationship Exponential relationship: endurance limit vs. MVC% (Rohmert, 1973) Quadratic relationship: endurance limit vs. MVC% (Al Meanazel, 2013) Important findings Some researchers obtained similar results (Bjorksten & Jonsson, 1977) Others found it misjudging (overestimating) at Low MVC Percentages (Nag, 1991; Rose et al., 1992, Sjogaard et al., 1986; Garg et al., 2002) Conclusion : Verify New results & Compare with the new model and Rohmert, 1973

42 Endurance Limit ModelsAuthors Model End. limit (Second) Rohmert (1960) 𝑻 𝑬 =−𝟏.𝟓+ 𝟐.𝟏 𝒇 − 𝟎.𝟔 𝒇 𝟐 + 𝟎.𝟏 𝒇 𝟑 152.20 Huijgens (1981) 𝑻 𝑬 =𝟎.𝟖𝟔𝟓× ( 𝟏−𝒇 𝒇−𝟎.𝟏𝟓 ) 𝟎.𝟕𝟏𝟒 156.00 Stao et al (1984) 𝑻 𝑬 =𝟎.𝟑𝟖𝟎𝟐× (𝒇−𝟎.𝟎𝟒) −𝟏.𝟒𝟒 158.70 Manenica (1986 a) 𝑻 𝑬 =𝟏𝟒.𝟖𝟖× 𝒆 −𝟒.𝟒𝟖𝒇 232.90 Manenica (1986 b) 𝑻 𝑬 =𝟏𝟔.𝟔𝟏× 𝒆 −𝟒.𝟓𝒇 258.40 Sjogaard (1986) 𝑻 𝑬 =𝟎.𝟐𝟗𝟗𝟕× 𝒇 −𝟐.𝟏𝟒 236.50 Rose et al (1992) 𝑻 𝑬 =𝟕.𝟗𝟔× 𝒆 −𝟒.𝟏𝟔𝒇 137.10 Van Dieen and Oude Vrielink (1994) 𝑻 𝑬 =𝟏𝟗.𝟖𝟐𝟔× 𝒆 −𝟒.𝟕𝟎𝟐𝒇 290.00 Bishu et al. (1995) 𝑻 𝑬 =𝟒𝟑𝟓.𝟐𝟓𝟕× 𝒆 −𝟑.𝟎𝟕𝟗𝟐𝒇 172.80 El ahrache et al (2006 a) N/A 182.40 El ahrache et al (2006 b) 180.60 Eksioglu (2011) 𝑻 𝑬 =𝟑.𝟏𝟖+𝟐.𝟕𝟐 𝑺 −𝟎.𝟕𝟏𝟔 𝑺 𝟐 −𝟑.𝟑𝟕 𝑩𝑴𝑰𝒑+𝟎.𝟐𝟗𝟑 𝑽 𝑭𝑯 191.00 Al Meanazel (2013 a) NL 𝑻 𝑬 = −𝟑𝟑𝟓𝟐𝟔.𝟕𝟎 + 𝟏𝟕𝟑𝟕𝟏.𝟓𝟏 𝑯𝑫 +𝟑𝟑𝟑𝟎.𝟐𝟒 𝑺𝑴 −𝟏𝟏.𝟗𝟕 𝑭 − 𝟎.𝟔𝟖 𝑮𝑪 −𝟓𝟕𝟗𝟐.𝟐𝟐 𝑯𝑫 𝟐 −𝟏𝟎𝟗𝟖.𝟐𝟎 𝑺𝑴 𝟐 +𝟎.𝟎𝟏 𝑮𝑪 𝟐 +𝟎.𝟏𝟓 𝑭 𝟐 141.55

43 Posture Effect On MVC ConclusionAviation industry subjects exerted almost same MVC in both postures Highest MVC value was in (30-35) y age period then A0: (25-<30), age period Lowest MVC value in older ages (above 50) y age period Literature Subjects exerted more grip strength in standing position than sitting position by 3% (Ibarra et al., 2012) For pinch grip, no statistical difference between standing and sitting positions but key pinch strength marginally higher for standing and sitting positions (Ibarra et al., )

44 Age Effect MVC Isom, End, limit Isotonic, End, limitDifferent MVC for different age periods Highest: In (30-35)y age period then A0: (25-<30)y age period Lowest in older ages (above 50) y Highest: A0: (25-<30)y then (30-35) years ago period then start decreasing by older ages Highest mean (85 sec) then start decreasing by older ages. High endurance on low percentages higher than high MVC percentages. Highest: Older ages above 50 exerted highest isotonic endurance limit then ages between 45 to 50 years old Youngest ages have the lowest isotonic endurance limit. Highest isotonic endurance limit exerted in envelop Isoto, End 20-60%, LS, RH.

45 Age Effect (cont’d) Charts Range Max Strength Independent of AgeIndustry Charts (10-99) Years old Young Ages (18-25) years (Chatterjee & Chodhuri, 1991; Minnal, 2014; Al Meanazel, 2013) Middle Ages (18-40) years (Koley et al., ) Old Ages, (75-79), (80-84), (85-89) & (90-99) years (Bohannon et al., 2006) Max Strength Ages around age 20 years as a peak amount then started to decline with older ages (Asmussen & Heeboll-Nielsen 1955, 1956, 1962) Ages (18-22 ), years old group (Chatterjee & Chodhuri, 1991) Ages (25-29), years old group (Industry Charts) Ages (35 to 44), year-old group for both sexes (Anakwe et al, 1995) Independent of Age No effect of aging noticed on isometric muscle strength (Petrofsky & Linda, 1975) At fraction MVC at 40% MVC level independent of gender and age (Chatterjee & Chowdhuri, 1991) Interactive effects of age, gender, and effort level have significant influence on fatigue (Yassierli et al., 2003) Grip strength inversely proportional with aging (Bohannon et al. 2006)

46 A0: (25-<30)//A1:(30- <35)//A2:(35-<40)//A3:(40-<45)Age Effect (Examples) MVC A0, MVC (Kg) =  0.723 Age (Y) + 24.43 Height (M) - 0.329 BMI - 0.040 HGC (CM) + 1.742 FAC (CM) A1, A2, A3, A4, A5, MVC (Kg) =  0.723 Age (Y) + 24.43 Height (M) - 0.329 BMI - 0.040 HGC (CM) + 1.742 FAC (CM) Isom, End, limit A0 Isometric AVG =  0.593 Age (Y) - 44.9 Height(M) - 1.448 BMI - 2.21 HGC(CM)+ 4.598 FAC(CM) A1 A2 A3 A4 A5 Isometric AVG =  0.593 Age (Y) - 44.9 Height(M) - 1.448 BMI - 2.21 HGC(CM) 4.598 FAC(CM) Isotonic, End, limit A0 Isoto, End, 20%-60% =  0.302 Age (Y) - 59.9 Height (M) - 0.669 BMI+ 3.800 HGC (CM) + 1.358 FAC (CM) A4 A5 Isoto, End, 20%-60% =  0.302 Age (Y) - 59.9 Height (M) - 0.669 BMI+ 3.800 HGC (CM) + 1.358 FAC (CM) A0: (25-<30)//A1:(30- <35)//A2:(35-<40)//A3:(40-<45) A4:(45-<50)//A5: Above 50

47 Height Effect MVC Isometric End. Limit Isotonic End. LimitHeight has major effect on MVC Taller people exerted more MVC result with extra 9.1% and 12.21% respectfully Limited effect of height on isometric endurance limit. Medium to tall height exerted higher endurance limits Medium height exerted higher endurance limits Literature A positive association was documented between height and dominant hand grip strength, while the respective comparison for weight and dominant hand strength documented a statistically significant positive association only in the male group (Alex et al., 2013)

48 Height Effect (cont’d)MVC S, MVC (Kg) =  0.4342 Age (Y) + 31.57 Height (M) - 0.381 BMI + 0.148 HGC (CM) + 1.873 FAC (CM) M, MVC (Kg) =  0.4342 Age (Y) + 31.57 Height (M) - 0.381 BMI + 0.148 HGC (CM) + 1.873 FAC (CM) T, MVC (Kg) =  0.4342 Age (Y) + 31.57 Height (M) - 0.381 BMI + 0.148 HGC (CM) + 1.873 FAC (CM) Isom, End, limit M, Isometric AVG =  0.248 Age (Y) - 128.8 Height(M) - 1.625 BMI - 2.70 HGC(CM)+ 5.106 FAC(CM) S, Isometric AVG =  0.248 Age (Y) - 128.8 Height(M) - 1.625 BMI - 2.70 HGC(CM)+ 5.106 FAC(CM) T, Isometric AVG =  0.248 Age (Y) - 128.8 Height(M) - 1.625 BMI - 2.70 HGC(CM)+ 5.106 FAC(CM) Isotonic, End, limit S, Isoto, End, 20%-60% l =  0.1917 Age (Y) - 55.1 Height (M) - 0.670 BMI+ 3.470 HGC (CM) + 1.272 FAC (CM) M, Isoto, End, 20%-60% l =  0.1917 Age (Y) - 55.1 Height (M) - 0.670 BMI  3.470 HGC (CM) + 1.272 FAC (CM) T, Isoto, End, 20%-60% l =  0.1917 Age (Y) - 55.1 Height (M) - 0.670 BMI+ 3.470 HGC (CM) + 1.272 FAC (CM) Range Short: S (<= 1.70) Medium: M (> ) Tall: (above 1.81)

49 BMI Effect MVC Isom, End, limit Isotonic, End, limitLimited effect of BMI on MVC Medium BMI subjects exerted higher MVC by 1.2% more than Large BMI and 4.43 than small BMI Highest MVC exerted in MVC (Kg, Stand, D) envelope **BSA (Body Surface Area) Limited effect of BMI on isometric endurance limit Medium to small BMI exerted higher endurance limits by 8.83% than Large BMI Large BMI values have lowest isometric endurance limit Highest isometric endurance limit exerted in (20%) envelope Limited effect of BMI on isometric endurance limit. Larger BMI exerted higher isotonic endurance limit Highest isometric end, limit exerted in isotonic endurance 20-60% (HS, LH) envelope

50 Physical Factors: BMI & BSAPositive correlation (Sheriff et al., 2012, Montes, 2001; Minnal, 2014; Al Meanazel, 2013; Fraser et al., ; Crosby, 1994) Depends on muscles strength and brain related factors (Stulen & De Luca, 1981) No relationship endurance values limit (Chatterjee & Chowdhuri, 1991, Caldwell, 1963, Start & Graham, 1964, Funderburk et al., 1974, Start & Garham, 1964) Experimental conditions (Miller et al., 1993) Different when both weaker and stronger persons subjected to (medium to high) MVC levels Weaker persons maintained better the endurance activities specially at high MVC%

51 BMI Effect MVC L, MVC (Kg) =  0.4386 Age (Y) + 21.31 Height (M) - 0.432 BMI + 0.264 HGC (CM) + 1.803 FAC (CM) M, MVC (Kg) =  0.4386 Age (Y) + 21.31 Height (M) - 0.432 BMI + 0.264 HGC (CM) + 1.803 FAC (CM) S, MVC (Kg) =  0.4386 Age (Y) + 21.31 Height (M) - 0.432 BMI + 0.264 HGC (CM) + 1.803 FAC (CM) Isom, End, limit L, Isometric AVG =  0.315 Age (Y) - 51.8 Height(M) + 1.185 BMI - 2.74 HGC(CM) + 5.063 FAC(CM) M, Isometric AVG =  0.315 Age (Y) - 51.8 Height(M) + 1.185 BMI - 2.74 HGC(CM) + 5.063 FAC(CM) S, Isometric AVG =  0.315 Age (Y) - 51.8 Height(M) + 1.185 BMI - 2.74 HGC(CM) + 5.063 FAC(CM) Isotonic, End, limit L, Isoto, End, 20%-60% l =  0.1636 Age (Y) - 53.9 Height (M) - 0.256 BMI+ 3.341 HGC (CM) + 1.191 FAC (CM) M, Isoto, End, 20%-60% l =  0.1636 Age (Y) - 53.9 Height (M) - 0.256 BMI 3.341 HGC (CM) + 1.191 FAC (CM) S, Isoto, End, 20%-60% l =  0.1636 Age (Y) - 53.9 Height (M) - 0.256 BMI + 3.341 HGC (CM) + 1.191 FAC (CM) Range: Small: S (19 = <25) Medium: M (25 =<30) Large: L (Above =<30)

52 Hand Grip Circumference (HGC) EffectMVC Isom, End, limit Isotonic, End, limit HGC has major effect on MVC (more MVC when they have larger FGC Highest MVC exerted in MVC (Kg, Stand, D) envelop Limited effect of BMI on isometric endurance limit Medium HGC exerted higher endurance limits average by 4.84% than large and 9.12 than small BMI Larger HGC subjects exerted more Isotonic Endurance Limit Highest Isotonic end, limit exerted in Isoto, End, 20-60% (HS, LH) Literature Higher Grip Circumference more MVC (Minnal, 2014; Al Meanazel, 2013)

53 HGC Effect (cont’d) Range:MVC L, MVC (Kg) =  0.4379 Age (Y) + 24.16 Height (M) - 0.349 BMI - 1.343 HGC (CM) + 1.727 FAC (CM) M, MVC (Kg) =  0.4379 Age (Y) + 24.16 Height (M) - 0.349 BMI - 1.343 HGC (CM) + 1.727 FAC (CM) S, MVC (Kg) = 8.6 - 0.4379 Age (Y) + 24.16 Height (M) - 0.349 BMI - 1.343 HGC (CM) + 1.727 FAC (CM) Isom, End, limit L Isometric AVG =  0.326 Age (Y) - 56.1 Height(M) - 1.560 BMI - 5.38 HGC(CM) + 4.977 FAC(CM) M Isometric AVG =  0.326 Age (Y) - 56.1 Height(M) - 1.560 BMI - 5.38 HGC(CM) + 4.977 FAC(CM) S Isometric AVG =  0.326 Age (Y) - 56.1 Height(M) - 1.560 BMI - 5.38 HGC(CM) + 4.977 FAC(CM) Isotonic, End, limit L Isoto,End, 20%-60%=  0.1641 Age (Y) - 55.6 Height(M) - 0.589 BMI + 3.79 HGC(CM) + 1.140 FAC(CM) M Isoto,End, 20%-60%=  0.1641 Age (Y) - 55.6 Height(M) - 0.589 BMI + 3.79 HGC(CM) + 1.140 FAC(CM) S Isoto,End, 20%-60%=  0.1641 Age (Y) - 55.6 Height(M) - 0.589 BMI + 3.79 HGC(CM) + 1.140 FAC(CM) Range: Small: S (=< 21.5) Medium: M (> ) Large: (Above 23.5)

54 Forearm Grip Circumference (FAC) EffectMVC Isom, End, limit Isotonic, End, limit FAC has major effect on MVC Subjects exerted more MVC when they have larger FGC Highest MVC exerted in MVC (Kg, Stand, D) envelop FAC has major effect exerted more isometric endurance limit in all percentages then medium then smaller FAC FAC has major effect exerted more Isotonic Endurance Limit then other BMI Highest Isotonic end, limit exerted in Isoto, End, 20-60% (HS, LH)

55 Forearm CircumferenceForearm circumference generally decreased with age for both men and women, although this decline was less marked for women (Anakwe et al., 2007) British subjects have slightly greater values for dominant forearm circumference measurements in both men and women (29.1 cm vs cm for men and 25.6 cm vs cm for women (Fraser et al., 1999) Found that forearm circumference delivered the best practical method for assessing the MVC grip strength and muscle mass for both genders (Kallman et al., 1990)

56 FAC Effect MVC L, MVC (Kg) =  0.4366 Age (Y) + 22.05 Height (M) - 0.354 BMI + 0.135 HGC (CM) + 2.036 FAC (CM) M, MVC (Kg) =  0.4366 Age (Y) + 22.05 Height (M) - 0.354 BMI + 0.135 HGC (CM) + 2.036 FAC (CM) S, MVC (Kg) =  0.4366 Age (Y) + 22.05 Height (M) - 0.354 BMI + 0.135 HGC (CM) + 2.036 FAC (CM) Isom, End, limit L, Isometric AVG =  0.301 Age (Y) - 57.8 Height(M) - 1.581 BMI - 2.59 HGC(CM) + 6.71 FAC(CM) M, Isometric AVG =  0.301 Age (Y) - 57.8 Height(M) - 1.581 BMI - 2.59 HGC(CM)+ 6.71 FAC(CM) S , Isometric AVG =  0.301 Age (Y) - 57.8 Height(M) - 1.581 BMI - 2.59 HGC(CM)+ 6.71 FAC(CM) Isotonic, End, limit L, Isoto,End, 20%-60% =  0.1657 Age (Y) - 55.3 Height(M) - 0.497 BMI + 3.437 HGC(CM) + 2.094 FAC(CM) M, Isoto,End, 20%-60% =  0.1657 Age (Y) - 55.3 Height(M) - 0.497 BMI+ 3.437 HGC(CM) + 2.094 FAC(CM) S, Isoto,End, 20%-60% = 6.5 + 0.1657 Age (Y) - 55.3 Height(M) - 0.497 BMI+ 3.437 HGC(CM) + 2.094 FAC(CM) Range Small: S (=< 27.5) Medium: M (=> ) Large: (above 31)

57 Trade Effect MVC Isom, End, limit Isotonic, End, limitMinor effect on MVC (All trades mostly exerted same MVC) Highest exerted by engine and E& I trades Engine and E&I have the mean ages 42 is 37 respectively Major effect on Isometric Endurance limit Highest exerted by APG and Engine trades then E&I Lowest Isometric Endurance limit exerted in COMNAV Highest exerted by Engine then then Electrical& Instrument trade

58 Trade Effect (cont’d) MVCAPG, MVC (Kg) =  0.4309 Age (Y) + 20.40 Height (M) - 0.437 BMI + 0.465 HGC (CM) + 1.892 FAC (CM) COMNAV, MVC (Kg) =  0.4309 Age (Y) + 20.40 Height (M) - 0.437 BMI + 0.465 HGC (CM) + 1.892 FAC (CM) E&I, MVC (Kg) =  0.4309 Age (Y) + 20.40 Height (M) - 0.437 BMI + 0.465 HGC (CM) + 1.892 FAC (CM) ENG, MVC (Kg) =  0.4309 Age (Y) + 20.40 Height (M) - 0.437 BMI + 0.465 HGC (CM) + 1.892 FAC (CM) GSE, MVC (Kg) =  0.4309 Age (Y) + 20.40 Height (M) - 0.437 BMI + 0.465 HGC (CM) + 1.892 FAC (CM) Isom, End, limit APG, Isom, AVG =  0.360 Age (Y) - 49.9 Height(M) - 1.262 BMI - 2.58 HGC(CM) + 4.526 FAC(CM) COMNAV Isom, AVG =  0.360 Age (Y) - 49.9 Height(M) - 1.262 BMI -  2.58 HGC(CM)+ 4.526 FAC(CM) E&I, Isometric AVG =  0.360 Age (Y) - 49.9 Height(M) - 1.262 BMI - 2.58 HGC(CM) + 4.526 FAC(CM) ENG, Isometric AVG =  0.360 Age (Y) - 49.9 Height(M) - 1.262 BMI - 2.58 HGC(CM) + 4.526 FAC(CM) GSE, Isometric AVG =  0.360 Age (Y) - 49.9 Height(M) - 1.262 BMI - 2.58 HGC(CM) + 4.526 FAC(CM) Isotonic, End, limit APG, Isoto, End, 20%-60%=  0.1584 Age (Y) - 53.3 Height (M) - 0.496 BMI+ 2.906 HGC (CM) + 1.059 FAC (CM) COMNAV Isoto, End, 20%-60%=  0.1584 Age (Y) - 53.3 Height (M) - 0.496 BMI+ 2.906 HGC (CM) + 1.059 FAC E&I, Isoto, End, 20%-60%=  0.1584 Age (Y) - 53.3 Height (M) - 0.496 BMI+ 2.906 HGC (CM) + 1.059 FAC (CM) ENG, Isoto, End, 20%-60%=  0.1584 Age (Y) - 53.3 Height (M) - 0.496 BMI+ 2.906 HGC (CM) + 1.059 FAC (CM)

59 Race Effect ComparisonPopulation MVC (Kg) (Males) MVC(Kg) (Females) Researcher(s) Singaporean 24.1 N/A Incel et al., 2002 Indian 22.75 Vaz et al., 2002, Koley et al., 2009 Jordan (Pilot Study) 33.619 Al-Momani, 2015 Spanish 39.95 25.72 Heredia et al., 2005 Scotland 35.12 23.02 40.0–48.8 27.5–34.4 Brenner et al., 1989 Jordan 46.58 Al-momani, 2015 USA 62.0 37.0 Crosby & Wehbe, 1994 44.8 35.0 Al Menaezel, 2013

60 Jordan Race Isometric & Isotonic ResultsVariable Mean StDev Minimum Maximum Isometric End, Limit (20%) 167.45 61.94 60.00 343.00 Isometric End, Limit (40%) 73.12 35.61 21.00 203.00 Isometric End, Limit (60%) 38.37 21.90 9.00 116.00 Isometric End, Limit (80%) 21.75 13.66 5.00 93.00 Variable Mean StDev Minimum Maximum Isoto, End % (LS, RH) 38.32 15.72 6.00 110.00 Isoto, End, % (HS, RH) 33.73 15.18 9.00 80.00 Isoto, End, % (HS, LH) 42.45 22.33 109.00 Isoto, End % (LS, LH) 30.67 13.99 7.00 85.00

61 Smoking Effect MVC Isom, End, limit Isotonic, End, limitSmokers exerted more MVC than non-smokers by 2% Highest MVC exerted in MVC (Kg, Stand, D) Reason: Nature of experiment (low to medium effort beside 56% smokers and younger ages. Smokers exerted more than non-smokers by 1.98% Highest exerted in isometric end, limit (20%) Reason: Nature of experiment (low to medium effort beside 56% smokers and younger ages.  Smokers exerted more than non-smokers by 1.85%. Highest exerted in Isoto, end, 20-60% (HS, LH) Literature: Most researchers found that non-smokers can exert more force (Asano & Branemark, 1970; Isaac & Rand, 1969; Diehl, 1969; Al Meanazel, 2013)

62 Smoking Effect (cont’d)MVC NS, MVC (Kg) =  0.4369 Age (Y) + 21.66 Height (M) - 0.379 BMI + 0.142 HGC (CM) + 1.875 FAC (CM) S, MVC (Kg) =  0.4369 Age (Y) + 21.66 Height (M) - 0.379 BMI + 0.142 HGC (CM) + 1.875 FAC (CM) Isom, End, limit NS, Isometric AVG =  0.262 Age (Y) - 52.7 Height(M) - 1.454 BMI - 2.54 HGC(CM) + 4.778 FAC(CM) S, Isometric AVG =  0.262 Age (Y) - 52.7 Height(M) - 1.454 BMI - 2.54 HGC(CM) + 4.778 FAC(CM) Isotonic, End, limit NS, Isoto,End, 20%-60%=  0.1589 Age (Y) - 55.7 Height(M) - 0.584 BMI + 3.558 HGC(CM) + 1.138 FAC(CM) S, Isoto,End, 20%-60%=  0.1589 Age (Y) - 55.7 Height(M) - 0.584 BMI + 3.558 HGC(CM) + 1.138 FAC(CM)

63 Hand Dominancy Effect MVC Isom, End, limit Isotonic, End, limitDominant exerted more MVC by 7.41% Sitting :Dominant exerted more MVC by 1.41% Highest MVC exerted for dominant hand for ages (30-45) years then (25-30) years then decreased above 45 years old Dominant exerted more isometric end, limit by 3.57% The highest isometric end, limit exerted for dominant hand for ages A4: (45-<50) (then A2: (35-<40) Lowest isometric end, limit exerted in A5 (above 50) and A0 and A0: (25-<30) There is almost no effect for hand dominancy on isotonic endurance limit. Highest exerted in Isoto, end, 20-60% (HS, LH)

64 Hand Dominancy vs. Right & Left HandDominant hand is significantly stronger: By (0.1–3%) in right-handed people and no worthy difference found for dominancy issues in left-handed people (Armstrong & Oldham, 1999) By (3.9%) for dominant or non-dominant positions and for pinch grip found no statistical difference for dominant or non-dominant positions (Ibarra et al., 2012) By (10.93% and 33.33%) for right and left handed subject respectively (Incel et al., 2002; Bohannon et al., 2006) Dominant right hand is stronger than left hand (Bohannon et al., 2006; Koley et al., 2009; Sorensen et al., 2009; Al Meanazel, 2013) Endurance of dominant hand 15 Seconds more than the non-dominant hand (Chatterjee & Chowdhuri, 1991) 16 Seconds more than the non-dominant hand (Chatterjee & Chowdhuri, 1991) No Difference: No difference in grip strength between left and right handed persons (Incel et al., )

65 Hand Dominancy Effect MVCD, MVC (Kg) =  0.4302 Age (Y) + 22.60 Height (M) - 0.352 BMI + 0.174 HGC (CM) + 1.813 FAC (CM) ND, MVC (Kg) =  0.4302 Age (Y) + 22.60 Height (M) - 0.352 BMI + 0.174 HGC (CM) + 1.813 FAC (CM) Isom, End, limit D, Isometric AVG =  0.289 Age (Y) - 57.9 Height(M) - 1.654 BMI - 2.56 HGC(CM) + 5.160 FAC(CM)  ND, Isometric AVG =  0.289 Age (Y) - 57.9 Height(M) - 1.654 BMI - 2.56 HGC(CM) + 5.160 FAC(CM) Isotonic, End, limit D, Isoto, End, 20%-60% l =  0.1571 Age (Y) - 55.8 Height (M) - 0.584 BMI + 3.542 HGC (CM) + 1.145 FAC (CM) ND, Isoto, End, 20%-60% l =  0.1571 Age (Y) - 55.8 Height (M) - 0.584 BMI+ 3.542 HGC (CM) + 1.145 FAC (CM)

66 Neural Network AnalysisOutputs MVC(Kg,Sit,D) MVC(Kg,Sit,ND) MVC(Kg,Stand,D) MVC(Kg,Stand,ND)   Isometric End, Limit (20%) Isometric End, Limit (40%) Isometric End, Limit (60%) Isometric End, Limit (80%) Isoto,End 20-60% low, S, Right Isoto,End,20-60% High, SP, Right Isoto, End, 20-60% High,SP,Left Isoto,End, 20-60% low,SP,Left Inputs Age (Y) Height (M) BMI HGC (CM) FAC (CM)

67 Neural Network AssumptionsTraining 70% (92 samples) presented where the Neural network adjusted according to its error) Validation 15% (20 samples) to measure neural network generalization approach, and to stop training when generalization get highest accuracy (stops improving) Testing 15% (20 samples) as a kind of independent measure of neural network through the overall process. Number of hidden neurons: 10 Training algorithm used is Levenberg- Marquard Back-Propagation. It is generally used when there is a large amount of input/output and the relationship between those inputs and outputs is complex or unknown. Also it takes less time with more memory and stops when generalization got its most as indicated by increase in mean square error according to (Beale et al., 1998). Levenberg-Marquardt algorithm selected due to its fast adjustment mechanisms Unless there is not enough memory, in which case scaled conjugate gradient backpropagation will be used. Validation Checks: 6

68 Neural Network Analysis ResultsMVC Isometric Endurance Limit Isotonic Endurance Limit MSE R-Sq 7.09 e -8 9.9 e-1 3.35 e-7 1.2 e-3 1.56 e-7 3.4 e-7 6.5 e-4 7.51 e-8 2.54 e-7 2.4 e-3 **Mean Squared Error is the average squared difference between outputs and targets. Lower values are better. Zero means no error.

69 Neural Network Performance Plot

70 Neural Network Error Histogram (Error Size Distribution)

71 Neural Network Function Fit Plot ,Targets)

72 Neural Network Regression

73 Adaptive Network-Based Fuzzy Inference System (ANFIS)ANFIS is considered the most efficient and optimal way (one can use the best parameters obtained by genetic algorithm) Number of nodes: 1016 Number of linear parameters: 2916 Number of nonlinear parameters: 54 Total number of parameters: 2970 Number of training data pairs: 100 Number of checking data pairs: 0 Number of fuzzy rules: 486 Epoch Completed at: 49, 50

74 ANFIS Output Test Results Error MVC (Kg,Sit,D) 3.84522e-05MVC (Kg,Sit,ND) e-05 MVC (Kg,Stand,D) 3.6203e-05 MVC (Kg,Stand,ND) e-05  Test Results Error Isometric End, Limit (20%) Isometric End, Limit (40%) e-05 Isometric End, Limit (60%) e-05 Isometric End, Limit (80%) e-05  Test Results Error Isoto, End 20-60% low, SP, RH e-05 Isoto, End, % High, SP, RH e-05 Isoto, End, % High, SP, LH 4.6505e-05 Isoto, End, % low, SP, LH e-05

75 ANFIS Diagram

76 Research Limitations Male subjects onlySubjective judgment could limit accuracy Subjects show less interest at late stages of experiment Experiment done one time (more than one time increase accuracy) Unequal sample sizes for Trades, Hand Dominancy, and Smoking Conditions

77 Summary & Conclusions Variables MVC Isometric Isotonic Age (years)Above 50 Trade Minor Effect Major effect APG & Engine Engine &(E&I) Smoking Smokers Body Mass Index (BMI)  Major Effect (H,M,L) Hand Grip Circumference (CM) Major Effect (B,M,S) Limited Effect (B,M,S) Hand Dominancy Major Effect No effect Forearm Circumference (CM) Posture Height (M) Major Effect (T,M,L) Limited Effect

78 Future Work Extend research to include more racesPerform new research considering high number of subjects undergoing different treatments Risk of stroke in people over age 65 (Kilgour et al., 2009) Cancer rates survival Chronic Kidney Disease Patients Dementia & Walking Speed Find relations for MVC & endurance effect on nutritional status, bone mineral content Design and build new palm (grip strength reader), to measure MVC in a different way (dynamometer use mainly 4 fingers) Use advanced apparatus like Biometrics’ computerized tools for strength evaluation Starting studies to evaluate the palm reflexology hand therapy Start finger strength and pinch strength studies and find out correlations with diseases and max MVC Include new trades: surgery doctors, nurses in hospitals and welding technicians (argon welding)

79 Key References Management of Health and Safety at Work Regulations 1999. Approved Code of Practice and guidance L21 (Second edition) HSE Books 2000 ISBN 0 7176 2488 9. NIOSH. (1997, March). Elements of Ergonomics Programs: A Primer Based on Workplace Evaluations of Musculoskeletal Disorders. Public Health Servic, Ceneter of Disease Control and Prevention, National Institute for Occupational Safety and Health. Cincinnati, OH. Fernandez & Marley, 2011) Fernandez, J. E., & Marley, R. J. (2011). Applied Occupational Ergonomics (3rd ed.). Cincinnati: International Journal of Industrial Engineering Press. Jeong (2005) Jeong WC. (2005). Symptom prevalence and Primary intervention of work-related musculoskeletal disorders and their related factors among manufacturing workers. Korean J Occupational/Environmental Medicine, Volume17 (2), Rohmert, W. (1960b). Statische Haltearbeit des Menschen, Benth Vertrid, Berlin-Koln-Frank-furt. AND Rohmert, W. (1966). Determination of relaxation allowances in industrial operations. Production Engineer, 45(11), Edwards, R.H.T. (1981). Human muscle function and fatigue. Dept. of Human Metabolism, University College London School of Medicine, U.K., Published by Pitman Medical Ltd., London. Snook, S.H., Irvine, C.H. (1969). Psychophysical Studies of Physiological Fatigue Criteria. Human Factors: The Journal of the Human Factors and Ergonomics Society, Volume 11 (3), Snook, S. H. (1978). The Design of Manual Material Handling Tasks: Ergonomics. London: Taylor and Francis . Vollestad, N. (1997). Measurement of human muscle fatigue. Journal of Neuroscience Methods, 74(2), Chaffin, D. B., Andersson, G. B., & Martin, B. J. (1999). Occupational Biomechanics (3rd ed.). Wiley-Interscience and Chaffin, D. B., Herrin, Gary, D., Keyserling, W., & Monroe, M. S. (1978). An Up dated Position. Joirnal of Occupational and Enviromental Medicine, 20(6), 403

80 Thank You!