Ergonomics in the 21st Century: New Solutions for The UC Ergonomics - - PDF document

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Ergonomics in the 21st Century: New Solutions for The UC Ergonomics - - PDF document

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3/8/18 I have no personal conflicts of interest to disclose. Ergonomics in the 21st Century: New Solutions for The UC Ergonomics Research & Graduate Training Program is supported by: Old Problems Google Pentax Carisa Harris Adamson,

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Ergonomics in the 21st Century: New Solutions for Old Problems

Carisa Harris Adamson, PhD, CPE, PT

  • Asst. Professor, UCSF Department of Medicine

Director, UC Ergonomics Research & Graduate Training Program

I have no personal conflicts of interest to disclose. The UC Ergonomics Research & Graduate Training Program is supported by: Google Pentax Logitech Facebook/Occulus

Learning Objectives

  • Identify age old ergonomic issues that may be improved

using new wearable technology.

  • Identify 3 types of wearable technology being applied to

ergonomics.

  • Discuss applications of existing & evolving technology in

ergonomics

  • Identify how health/medical practitioners may use

wearable technology to prevent and treat musculoskeletal disorders.

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ERGONOMIC ISSUES THROUGH THE AGES

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ERGONOMIC ISSUES THROUGH THE AGES

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ERGONOMIC ISSUES THROUGH THE AGES

MSDs by Body Region

Type Incidence per 10,000 FTEs(b) Median Lost Workdays(c) Median Cost(d)

All 90.0 56 $11,183 Back 40.8 35 $6,032 Shoulder 14.8 129 $28,228 Elbow/forearm 5.3 116 $18,083 Hand/wrist 15.3 79 $14,166 Knee 10.1 56 $14,245

Work-Related Musculoskeletal Disorders (WMSDs) of the Neck, Back, and Upper Extremity, Washington State Workers’ Compensation Compensable(a) Claims, State Fund and self-insured, 2002–2010

MSDs By Occupation

Occupation Number of Incident Cases Incidence Rate per 10,000 Workers Laborers and freight handlers 21,990 111.0 Nursing aides and orderlies 19,360 180.5 Janitors and cleaners 15,810 102.6 Heavy and tractor-trailer truck drivers 15,320 95.6 Emergency medical technicians/paramedics 3,980 187.4 Firefighters 5,630 168.5 Telecommunication line installers/repairers 2,190 224.6

Incidence of Work-Related Musculoskeletal Disorders in Private Industry, United, States, 2015 https://www.cdc.gov/niosh/docs/97-141/pdfs/97-141.pdf

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Quantifying Physical Exposures.

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Laboratory Approach

Er Ergon

  • nom
  • mic Evaluation
  • n of
  • f Bed Making

Am Among Hotel Room Cl Clean aners

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Mi Missing Ma Markers….

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Wh What about the other tasks?

Pushing Supply Cart Making Bed Dusting Vacuuming Cleaning Bathroom

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Drawings taken from: https://ergonomics.osu.edu/ergonomics-resources-housekeeping

12 to 20 Rooms/Day

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https://www.realwire.com/realResource.asp?ReleaseID=37982&d=w&nam e=BRL-Wearable-Technology-Applications-Chart- 2014%2Ejpg&title=Wearable%20tech%20application%20chart

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The BIONIC (WO)MAN

Emerging Wearable Technologies in Ergonomics

  • Inertial Measuring Units
  • Electromyography
  • Exoskeletons

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Sensor Fusion

gyro accel UWB RF GNSS mag baro

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Inertial Measuring Units (IMUs)

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  • 3D angular velocity (rad/s)
  • 3D acceleration (m/s2)
  • 3D earth magnetic field

(mGauss)

  • Drift free 3D absolute
  • rientation (calculated)
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Activity Classification Algorithm

Stand Accelerometer Data

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Sit Accelerometer Data Walk Accelerometer Data

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Ac Activity Classification Al Algorithm

Th dis

Behavior Cueing Framework

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Data Based Push Notifications

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SpineTrack

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Summary Dashboard

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Ph Physical al Dem eman ands Asses essmen ent

LIFTRATE (LIFTS/HR) MOMENT (Nm) SAG POS (DEG) TWIST VEL (DEG/s) LATERAL VEL (DEG/s) 41

PROBABILITY OF HIGH RISK GROUP MEMBERSHIP (%)

Probability of Lumbar Spine Disorder (RISK MODEL)

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Sp SpineTrack Performance

Worker 1 Worker 2 Worker 3 Worker 4

Percent Probability of Belonging to High Risk Group

24% 21% 32% 40%

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25 March 8, 2018

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Inertial Motion Capture

17 Synchronized Inertial Measuring Units (IMUs) report position, acceleration, velocity of segments and joints

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Jo Job Analy lysis is

March 8, 2018

Jo Job (R (Re)D )Desig ign through Sim imula latio ion

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https://www.pehub.com/canada/2016/10/top-q3-canadian-vc-deals/

Wearable EMG

https://www.youtube.com/watch?v=oWu9TFJjHaM

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The picture can't be displayed. https://www.roadtovr.com/thalmic-labs-120-million-series-b-wristband-gesture-tracking-virtual-reality/

Wearable EMG Wearable EMG

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Purpose

  • Develop a model to predict grip/pinch hand

posture & force magnitude using IMU & wEMG

  • Quantify individual UE exposure to compare

to thresholds (1kg Pinch Grip;4kg Power Grip)

  • Percent time in heavy hand exertion
  • Forceful repetition rate
  • % time spent in wrist deviation while in forceful

exertion

  • Use gold standard technique to compare

with predictive model

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Harris-Adamson C, et al., Biomechanical risk factors for carpal tunnel syndrome: a pooled study of 2474 workers. Occup Environ Med 2014;0:1–9

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Average R- squared values for grip force prediction across 11 subjects. Average R- squared values for pinch force prediction across 11 subjects.

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14

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Multimedia Video Task Analysis

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Hand Posture Prediction

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HandTrack Hand Posture & Force Estimation

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Disability Prevention

Exposure N=340 (n=178) HR* Pace Change Hal Scale>4 & ≤6 1.87 [1.19-2.94] Hal Scale>6 1.69 [0.97-2.93] % time in All Exertions>58% & ≤76% 0.81 [0.50-1.31] % time in All Exertions>76% 1.96 [1.20-3.20] Lost Time Total Repetition Rate>14 & ≤24 2.33 [1.02-5.34] Total Repetition Rate>24 2.16 [0.97-4.79] Forceful Repetition Rate>3 & ≤8 2.23 [1.01-4.95] Forceful Repetition Rate>8 1.83 [0.88-3.77]

*All models adjusted for gender, age, BMI, study site & non-overlapping exposures

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Passive Exoskeletons

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Passive Exoskeletons

Arm Support Exoskeleton

  • Weighs 12.4 lbs
  • Provides 5-15lbs (70-200lb-in) of support

Allows for most of shoulder ROM

  • Adjustable to fit 5%-95% population

Trunk Support Exoskeleton

  • Weighs 5-8 lbs
  • Provides up to 30 lbs (min. of 120 lb-

in)of support

  • No gait impedance
  • Adjustable to fit 5%-95% population

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Study Tasks

Prolonged static posture Dynamic overhead drilling

Welding, Mechanical work, Electrical work, Grinding, Inspection Automotive under-body, Construction, Aviation Assembly

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Arm Exo Study Design

Static posture

2lb tool

No device Support = load* Self selected support

10 lb tool

No device Support = load* Self selected support

R1: Task R2: Support Within subjects 2x2x3 design: 12-16 participants from local construction industry * Support = load determined by measured arm weight + tool weight

Dynamic posture

2lb tool

No device Support = load* Self selected support

10 lb tool

No device Support = load* Self selected support

Assessment

  • EMG (agonist & antagonist)
  • Rate of Perceived Exertion

Muscle Fatigue

  • Productivity
  • Usability

Performance

  • MSD Discomfort
  • Overheating
  • Device Comfort

Worker perception

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Outcome Measures

Muscle Activity

  • Shoulder Flexors
  • (anterior deltoid, pectoralis

major, biceps long head)

  • Shoulder Extensors
  • (lattisimus dorsi, posterior

deltoid)

  • Spinal Extensors
  • (erector spinae)
  • Grip (FDS, ED)

Rate of Perceived Exertion

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Outcome Measures

Performance

  • Static: accuracy & amount of line traced
  • Dynamic: number of screws inserted

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Outcome Measures

Discomfort (NPS 0-10)

No pain Moderate Worst

  • a. Neck/Traps: 0 1 2 3 4 5 6 7 8 9 10
  • b. Shoulders: 0 1 2 3 4 5 6 7 8 9 10
  • c. Forearms: 0 1 2 3 4 5 6 7 8 9 10
  • d. Wrist/Hand: 0 1 2 3 4 5 6 7 8 9 10
  • e. Elbow: 0 1 2 3 4 5 6 7 8 9 10
  • f. Hips: 0 1 2 3 4 5 6 7 8 9 10
  • g. Back: 0 1 2 3 4 5 6 7 8 9 10

* Questions repeated for R&L

  • 2. On a scale of 1-5 please identify

comfort of primary device contact points

  • 3. Please identify any locations of

discomfort from the device and if possible indicate its cause

  • abrasion, pinching, pressure, heat

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“Do No Harm” Evaluation

Assess Benefits & Challenges

  • Extra weight
  • Increased temperature
  • Contact pressure points
  • Implication on antagonist muscle groups
  • Usability
  • donning/doffing
  • wearing over time
  • Task based preferences
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Muscle activity during static work and use of heavy tool.

Static task-Heavy tool

  • ff

low medium high p Median upper trap 21.4(9.08)a,b 18.44(7.83)c 16.48(9.20)a 13.33(6.72)b,c 0.00 Peak upper trap 28.62(12.75)a,b 25.16(11.03)c 22.77(13.67)a 18.49(9.12)b,c 0.00 Median anterior deltoid 18.06(6.27)a,b,c 13.73(4.39)a,d,e 9.87(2.98)b,d 7.21(2.83)c,e 0.00 Peak anterior deltoid 25.5(9.55)a,b,c 20.08(7.40)a,d,e 15.50(6.05)b,d 11.66(3.91)c,e 0.00 Median infraspinatus 16.63(8.39)a,b 14.73(6.28) 13.19(6.73)a 12.24(5.06)b 0.01 Peak infraspinatus 22.37(12.34)a 20.82(10.17) 18.45(10.74) 17.26(6.98)a 0.05

Muscle activity during dynamic work and use of heavy tool.

Dynamic task- Heavy tool

  • ff

low medium high p Median upper trap

20.73(9.82)a,b,c 16.51 (6.66)a 16.11 (6.60)b 13.68(7.16)c 0.00

Peak upper trap

30.63(13.67)a,b,c 23.92(9.67)a 22.63(9.03)b 19.68(9.01)c 0.00

Median anterior deltoid

17.92(5.85)a,b,c 12.79(3.16)a,d 9.97(3.56)b 6.73(3.26)c,d 0.00

Peak anterior deltoid

29.95(11.52)a,b 23.22(6.23)c 17.14(4.64)a 12.90(5.54)b,c 0.00

Median infraspinatus

15.47(7.13)a,b 13.19(5.49) 12.12(4.17)a 11.78(4.61)b 0.02

Peak infraspinatus

23.18(11.03)a,b 19.93(8.77) 17.65(6.92)a 17.39(6.95)b 0.02

Passive Exoskeletons

Job Requirements Environmental Limitations Individual Needs

Worker Capacity Work Demand

Goals & Priorities

  • Assist high risk workers

(based on cumulative/ typical/peak exposure)

  • Supplement aging/female

workers

  • Accommodate injured

workers during RTW

Wearable Technology

Inertial Measuring Units

  • Magnitude, velocity &

acceleration of movement

  • Static postures
  • % time spent in different

postures/ above thresholds

  • Repetitive exertions
  • Physical demands summary
  • Posture/ Activity Detection

Wearable EMG

  • Muscle activity & activation

patterns

  • % time spent in different

exertions

  • Force prediction
  • Hand posture prediction

Passive Exoskeletons

  • Increase Worker Capacity
  • Supplement aging/ female

workers

  • Accommodate injured

workers

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JOB ANALYSIS PROGRAM MANAGEMENT SURVEILLANCE MSD MANAGEMENT JOB DESIGN

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A different approach to MSD prevention

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Emerging Solutions

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Question #1

The following is NOT a wearable technology that is being applied to solving ergonomic challenges: a) Inertial measuring units (IMUs) b) Electromyography c) Exoskeletons d) Video Monitoring

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Question #2

Wearable technology in ergonomics can be used for: a) Surveillance b) Job analysis c) Job (re)design d) Musculoskeletal disorder management e) All of the above

Question #3

Wearable technology may soon be used by medical/ health care practitioners to: a) Understand the physical demands of a job b) Support a quantitative approach to return to work c) Allow for accommodation by increasing worker capacity for earlier return to work or stay at work purposes d) Assist in directing injury prevention programs e) All of the above

Questions & Comments http://ergo.berkeley.edu

Carisa.Harris-Adamson@ucsf.edu