Some Biomechanical Perspectives on Musculoskeletal Disorders: Causation and Prevention

Transcription

1 Some Biomechanical Perspectives on Musculoskeletal Disorders: Causation and Prevention Don B. Chaffin, PhD The G. Lawton and Louise G. Johnson Professor The University of Michigan

2 Materials Handling in shipping and baggage handling. Issues: Back Stress Wrist Stress Shoulder Stress Balance

3 Materials Handling In Manufacturing Operations. Issues: Balance Shoulder Stress Back Stress Wrist Stress

4 Repetitive exertions when Scanning products at a checkout counter. Issues: Wrist Stress Back Stress

5 Transferring fully dependent patients Issues: Back Stress Shoulder Stress Balance

6 Themes of talk: From Spinal Biomechanics to other joi nts. From Acute LoadingtoCumulative Loading. From Static to Dynamic Biomechanics. From Reactive to Proactive Risk Reduction. From protecting all to protecting some.

7 Occupational Biomechanics Research Status Work Tasks INTPUT HUMAN ANTHROPOMETRY EXTERNAL FORCES & MOMENTS POSTURES & MOTION DATA Human HUMAN KINETIC Kinetic Models MODELS EMG ANATOMIC DATA ON MUSCLE, LIGAMENT, TENDON, & BONE GEOMETRIES JOINT MOMENTS & FORCES SOFT TISSUE & BONE STRESS MODEL MUSCLE ACTIVATION RULES MUSCLE FORCES PASSIVE TISSUE STIFFNESS PROPERTIES TISSUE INJURY PREDICTION MODEL TISSUE STRAIN TOLERANCE LIMITS OUTPUT Effective Prevention Tactics VALID ETIOLOGY OF MUSCULOSKELETAL TRAUMA IN WORKPLACE

8 Joint Load Moments can be estimated for 3D exertions. Existing 3D Biomechanical Model for predicting joint moment loads, given: Hand forces Postures Anthropometry Computations can best be done with software. Chaffin, 1985

9 BIOMECHANICAL EXAMPLE: BATTERY LIFTING IN 3D POSTURE BATTERY WEIGHS EITHER 25 OR 50 Lbs.

10 Existing Strength Model can predict the Percentage of Population Capable of Single Static Exertion by assuring: [Each Joint Load Moment] < [Population Strength Moments] (Predicted from model) (Statistically defined norms) Above is basis for: UM: 3D Static Strength Prediction Program which is based on static strength measurements of over 2000 people in various workplaces.

11 3DSSPP Software analysis of asymmetric Battery Lifting with two weights. ASYMMETRIC SIDE LIFT FROM FLOOR 25Lb. Battery: MALE FEMALE Back Comp. (lbs) L4/L5 A/P Spinal Shear (lbs.) % Pop. Strength 85% 59% Limiting Muscles R. Hip Ext. R. Hip Ext. 50Lb. Battery: Back Comp. (lbs) L4/L5 A/P Spinal Shear (lbs.) % Pop. Strength 66% 18% Limiting Muscles R. Hip Ext. R. Hip Ext.

12 What about internal tissue Stress prediction? That Requires: Tissue geometry data. Muscle force estimations or predictions.

13 CAT SCAN OF TORSO AT L4/L5 LEVEL DISCLOSES MULTIPLE MUSCLES MUST BE REPRESENTED.

14 Torso at L4/L5 Force Diagram There are more unknown muscle and spinal forces than there are state equations.

15 Optimization Model Predictions of muscle forces Champions: Schultz, Brand, Hughes, 1980 s and 1990 s Objective: Minimize Fi (individual muscle forces) Subject to : Fi < maximum strength of each muscle Fi > 0 muscles only in tension Possibly also minimize F SPINAL COMP (Fi)(mi ) = External Joint Moments

16 EMG SURFACE ELECTRODES USED TO VALIDATE LOW BACK MUSCLE EXERTION MODEL PREDICTIONS IN LABORATORY STUDIES AT UM. Also can be used to construct EMG driven predictions of Muscle Forces.

17 EMG Driven Models for estimating muscle activation levels Champions:Marras and McGill, late 1980 s 1. Measure EMG s of multiple muscles during controlled torso loads -> Estimate muscle forces 2. Use estimates from #1 to predict muscle forces in complex exertions.

18 Neural Net Prediction Method (championed by Nussbaum and Karwowski) W. Lee, et al, Ergonomics, 46(1), 2003

19 Does a biomechanical model that includes muscle force predictions provide explanation of tissue injury causation? It helps to identify specific job conditions where-in risk of acute muscle strain may exist, but we need more knowledge to predict the probability of specific tissue failure. Which tissue seems to fail during exertions?

20 For preventing disabling Low Back Pain: Understanding cause of disc prolapse is a major goal. Sciatica

21 RECOVERY FROM SCIATICA CAUSED BY LUMBAR DISC PROLAPSE IS MUCH SLOWER THAN RECOVERY FROM ACUTE LOW BACK PAIN 100 Percent (%) Early Differential Diagnosis is very important. SCIATICA 20 Months Acute LBP Frymoyer, 1988

22 Primary Prevention Requires Determination of Vertebral Motion Segment Compression Tolerance FORCE APPLICATION F PLASTIC COVER BONE CEMENT SPINAL MOTION SEGMENT D AIR; 36.5 C 100% HUM. BONE CEMENT METAL CUP

23 Typical Spinal Motion Segment Response to Compression Loading F ULTIMATE STRENGTH) FRACTURE FAILURE PHASE FORCE (KN) 3 2 ELASTIC RESPONSE PHASE D - DEFORMATION (mm)

24 Cartilage Endplate Fractures from Compression Ovederloads Brinckmann & Johannleweling (1986)

25 COMPRESSION SPINE STRENGTH DEPENDS ON AGE & GENDER (Disc Size & Vertebra Density) Male compression strength in KN 10 5 strength/kn = a+b age/dec a=10.53 b= c 2 = N: Max. Perm. Lim. 3400N: Action Limit 0 n = Female compression Strength in KN n = a=7.03 b= c 2 = N 3400N Combined Compression Strengths n = a=8.60 b= 0728 c 2 = age in years Current NIOSH Limit 3400N

26 Age Affect reconfirmed by Jager et al, Dortmund Recommendations - Age-and-gender related recommended limits for lumbar-spine compressive forces during occupational activities, in particular, manual materials handling (derived from measurements provided in the literature on ultimate compressive strength of lumbar disc-or-vertebra autopsy material) from Jäger et al DHMC. Age Female Male 20 years 4.4 kn 6.0 kn 30 years 3.8 kn 5.0 kn 40 years 3.2 kn 4.1 kn 50 years 2.5 kn 3.2 kn 60 years 1.8 kn 2.3 kn NIOSH 3400 N Limit Recall: NIOSH recommended limit is 3.4 kn for all ages and both genders.

27 Can we detect who is most susceptible to lumbar disc failure? Correlation of Spinal Motion Segment Strengths with Size and Density of Vertebral Bodies 10 ULTIMATE COMPRESSION STRENGTH (KN) NIOSH 6.4kN limit NIOSH 3.4kN limit BONE DENSITY X ENDPLATE AREA Is a problem with osteoporosis in the vertebral bodies with age Varies more than bone density in normal, healthy population. Brinckmann & Johannleweling, 1986

28 One Conclusion: Spinal Motion Segment Compression Failure is now well known as a risk factor for disc related LBP, but individual susceptibility (Age and Gender) remains to be studied more. But what about Shear and Torsional Loading? Callaghan &McGill have shown relatively high motion segment shear tolerances, but raise questions about combined shear, compression and torsion loading tolerances of segments. Callaghan & McGill, Clin. Biomech. 2001

29 Is one method of lifting better? CURVED BACK SEMI-CURVED BACK STRAIGHT BACK CRITERIA ST OP LIFT- 2 H3 PARALLEL STANCE DE EP SQUAT LIFT - STRADDLE STANCE PEAK L5/S N 7002 N 4527 N COMP. FORCE MAX. LUMBO- 9.3% 3.7% -0- (WITH FLATTENED DORSAL FASCIA BACK STRAIN %MEN CAPABLE 20% 73% 31% STRENGTH (HIP LIMIT) (HIP LIMIT) (KNEE LIMIT) The typical stoop lift posture on the left is compared with two different types of squat lifting of a 400-N box (as adapted from Anderson and Chaffin, 1986)

30 GEOMETRIC REPRESENTATIONS OF THE LOW-BACK LIGAMENT ELEMENTS LUMBAR L5 VERTEBRA LIGAMENTS (EACH SIDE) NORMAL VERTEBRA ORIENTATION LIGAMENTUM FLAVUM SACRUM EXAGGERATED DISTANCES (NO DISC) ARTICULAR CAPSULAR LI GAMENTS (EACH SIDE) INTERSPINOUS SUPRASPINOUS LIGAMENT) LUMBODORSAL FASCIA (HIGHLY STRAINED IN BACK LIFTS) Kumar commented on very high ligament strains in the lumbosacral fascia when lifting/transferring patients. Kumar et al, Ergonomics, 2003

31 STRESS STRAIN CURVE FOR LIGAMENTS Failure Strain Limit 3 4 LOAD ELONGATION (PERCENT STRAIN ) -7% Stress-strain curve for a human anterior cruciate ligament tested in tension to failure. This ligament has about 90% collagen fibers. (Adapted from Noyes, 1977.) 1. The wavy collage fibers straighten out. 2. Deformation occurs. 3. Progressive failure of collagen bundles (elongation 6-8%). 4. Complete failure. Ligaments have a little longer toe region than tendons due to matrix orientation. Noyes, 1977

32 Status in Biomechanical Models: We are just beginning to understand the complex response and failure mechanics of the ligaments under common job exertion scenarios, especially during highly dynamic exertions.

33 What about Movement as a risk factor? What does physiology say? Muscle strength declines with velocity of shortening. Muscle coordination becomes very complex & instability increases. Muscle strain injury risk increases with stretch velocity.

34 Epidemiology supports concern over Speed of Motions: Low Back Pain Risk Factors Factors Odds Ratio Workplace Factors Ave. weight handled 2.76 Max. weight handled 3.17 Ave. moment (L5/S1) 4.08 Max. moment (L5/S1) 5.17 Trunk Motion Factors Sagittal Plane (flex/ext) Ave. angular velocity 3.33 Max. angular velocity 1.73 Lateral Plane (lat. Flexion) Ave. angular velocity 1.73 Max. angular velocity 1.55 Horizontal Plane (twist) Ave. angular velocity 1.66 Overloading Hurts! Speed Hurts! Marras et al. 1993

35 Many different motion measurement systems now exist. TAPE SECURING WIRE TO SKIN FLEXIBLE WIRE LINEAR DISPLACEMENT TRANSDUCER TAPED TO SKIN (Armstrong et al., 1988).

36 The LMM Lumbar Motion Monitoring System Developed in the Biodynamics Laboratory at Ohio State University (courtesy of W. Marras).

37 Example of some of the 67,000 motions captured in UM: Human Motion Simulation Laboratory.

38 FAST LIFTING OF LIGHT LOADS CAN INDUCE PEAK LOW BACK COMPRESSION FORCES THAT ARE 30% TO 50% LARGER OR SMALLER THAN PREDICTED BY THE STATIC MODELS.

39 Conclusion: Certain types of motions increase the peak joint moment loads and require complex muscle co-contractions to stabilize a joint, which increases tissue stresses Injury Risk. Implication: Dynamic biomechanical models coupled with motion measurement and prediction systems must be developed and used to prevent motion related injuries.

40 What about Acute Tissue Overload v. Cumulative Trauma? POPULATION BASED TOLERANCE LIMIT TRAUMATIC ACUTE FAILURE MARGIN OF SAFETY Tissue Load During Work Day OCCASIONAL SPINAL LOADING ON JOB POPULATION BASED TOLERANCE LIMIT MARGIN OF SAFETY FATIGUE FAILURE OF MOTION SEGMENT Working Time CUMULATIVE TRAUMA FAILURE FREQUENT SPINAL LOADING ON JOB Depiction of spinal motion segment failure due to either a single overexertion event (top) or frequent exertion and fatigue failure (bottom), as adapted from McGill (1997).

41 Strain (Deformation) Response of Spinal Motion Segment to Repetitive Loadings COMPRESSIVE STRAIN OR DISC DEFORMATION FRACTURE INITIATION From repetitive Loading TIME (REPEATED LOADINGS) Can low back pain be considered a CTD? Do repetitive spinal loads increase risk?

42 Repetitive Loading Effect in Spinal Motion Segment Compression Strengths 100% SPINAL ENDPLATE FRACTURES AS PERCENT OF ULTIMATE STRENGTH 80% 60% 40% 20% Upper Range Mean Lower range ,000 LOG, NUMBER OF LOADING CYCLES Adapted from:brinckmann & Johannleweling, 1986

43 Does cartilage and ligament tissue tolerance decrease at a faster rate than muscle fatigue in repetitive actions? RECOMMENDED WEIGHT LIFTING POPULATION LIMIT PSYCHO PHYSICAL PHYSIOLOGICAL BIOMECHANICAL COMPRESSION LIMIT TO LIFTING Conceptualized model of how the recommended weight of lift depends on the frequency of lifting (from Ayoub, 1992, and Kumar, 2001).

44 What about Upper Extremity CTD biomechanics? Does the Force, Posture, Repetition risk factor paradigm apply to the upper extremity?

45 Many common tasks require high finger forces 203 STAR Symposium

46 Finger Flexor Tendons are subject to high forces when gripping or pressing. SMALL OBJECT GRASP: F t ~ 2.8 F L SMALL HAND 3.1 F L LARGE HAND F L F t PRESSING DOWN OR LARGE OBJECT GRASP: F t = ~ 3.7 F L SMALL HAND 4.3 F L LARGE HAND RATIOS OF FINGER FLEXOR TENDON FORCES TO FINGER LOADS VARY WITH GRIP POSTURE AND HAND SIZE (ARMSTRONG, 1976)

47 REPEATED HIGH TENDON FORCES CAUSE COLLAGEN SPLITTING INFLAMATION PAIN MEDIAN NERVE ENTRAPMENT SYNDROME TENSILE FORCES (STRESS) IDEALIZED REPEATED EXERTIONS s per day S TENDON ELONGATION (STRAIN) S % RESIDUAL STRAIN = RESTING LENGTH X 100 Goldstein et al, 1986

48 Wrist in flexion showing median nerve entrapment in tunnel.

49 F L 4x F' T FS FN R 0 INTRAWRIST COMPRESSION FORCES ACTING AT WRIST DUE TO FINGER FLEXOR TENDONS BEING DEVIATED FROM NEUTRAL POSITION (FROM ARMSTRONG AND CHAFFIN, 1978) F T FR Compression Force on synovium leads to high frictional forces and tearing of Synovium (Sweizer, et al 2002

50 A growing problem in industry: Shoulder Rotator Tendon Entrapment Syndrome A common problem with high moment loads and arm abduction. A DELTOID NORMAL SHOULDER STRUCTURE ROTATOR CUFF TENDON ON ABDUCTION B SUBACROMIAL IMPINGEMENT C RESULTING INFLAMMATION AND DEGENERATION BURSA b = DELTOID BURSA, c = ROTATOR CUFF, d = DELTOID MUSCLE, t = TENDONS Adapted from Cailliet, 1981

51 Shoulder musculoskeletal stress modeling to predict extreme reach and exertion capabilities. Clark Dickerson UM:PhD Thesis

52 Conclusion: Developing better shoulder biomechanical models is greatly needed for guiding job improvement: Prevalent area of CTD in industry. Shoulder is inherently unstable, requires muscle co-contraction. Many women have low shoulder strength capabilities that limit reaching on jobs.

53 In Summary: So how does Biomechanics help in preventing musculoskeletal disorders in the Workplace? Explains the mechanism of some types of common occupational injuries. Helps differentiate acute trauma from serious cumulative trauma. Provides a scientific basis for OH&S guidelines. Provides a scientific basis for injury risk prediction for primary prevention in job design.

54 In the future Proactive Ergonomics will allow job designers And engineers to use Digital Human Models that include realistic Dynamic Human Motion and Biomechanical Analysis Tools Motion Capture Motion Visualizing and Modeling CAD Motion Prediction Job Simulation provided by the University of Michigan s Human Motion Simulation HUMOSIM Laboratory

55 My strategic Goals for future Occupational Biomechanics research: 1. Dynamic Biomechanical Models that accurately predict tissue stresses (including cartilage, ligaments, and tendons) for a variety of work conditions. 2. Improved population data on tissue failure limits, and for different population strata. ( Remember, there is a 10:1 variation in people s strengths.) 3. Human Motion prediction models that mimic real human motions to allow dynamic biomechanical modeling during simulations of job conditions, thus promoting much more proactive ergonomics.

56 Thank you!