using technology to assess upper extremity function ... · han jj, kurillo g, abresch rt, de bie e,...
TRANSCRIPT
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Using Technology to Assess Upper Extremity Function (Reachable Workspace) in Neuromuscular Disorders
Jay J. Han, MD
Professor
Dept. of Physical Medicine & Rehabilitation
UC Irvine
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Advances in Neuromuscular field
• Recent advances in therapeutic developments
– Neuromuscular field has been active
– Drug therapies & pharmacologic interventions
– Gene and cell therapies
– But also assistive devices and robotics
• Highlight the need for effective outcome measures
– Improve monitoring of disease severity and progression
– Better characterization for natural history studies
– Identify clinical outcome measures for planned efficacy trials
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Traditional tools
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III (I)
IV (II) II (IV)
I (III)
R
x
z
x
z
L
Traditional Motion Capture Lab
van Andel et al. Gait & Posture (2008) 27:120-127
•Large cost•Space & equipment requirements•Not very portable•Marker-based (active or passive)
Example output
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• Development of algorithm and methods to reconstruct an individual’s
reachability (Reachable workspace).
• Graphical visualization of reachable workspace (3D)
-1000-500
0 -1000-50005001000
-1000
-500
0
500
1000
y(mm)
Movement Trajectory
x(mm)
z(m
m)
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Steps to determining the Reachable Workspace
1. Area obtained
2. Normalized by
the area of the
hemisphere
(2r2)
3. Allows
comparison
between
individuals
Relative Surface
Area (RSA)
Kurillo G, Chen A, Bajcsy R, Han JJ. Evaluation of upper extremity reachable workspace using Kinect camera. Technol Health Care. 2013;21(6):641-56
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Kurillo, Han et al. Development and Application of Stereo Camera-Based Upper Extremity Workspace Evaluation in Patients with Neuromuscular Diseases. PLoS One 2012
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Kurillo G, Chen A, Bajcsy R, Han JJ. Evaluation of upper extremity reachable workspace using Kinect camera. Technol Health Care. 2013;21(6):641-56
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Han JJ, Kurillo G, Abresch RT, de Bie E, Nicorici Lewis A, Bajcsy R. Upper extremity 3D reachable workspace analysis in dystrophinopathyusing Kinect. Muscle Nerve. 2015 Sep;52(3):344-55
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Set up(sensor + display + computer)
• Simple• Quick• Low-cost• Unobtrusive (no markers)• Intuitive (visualization of reachable workspace)
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Kinect Reachable Workspace
RSA - Reliability testing
Kinect vs.
Test and retest
R=0.891R=0.891
R=0.858
R=0.930
Motioncapture
Kurillo G, Chen A, Bajcsy R, Han JJ. Evaluation of upper extremity reachable workspace using Kinect camera. Technol Health Care. 2013;21(6):641-56
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Also, Test re-test reliability in DMD
ICC=0.935
Han JJ, Kurillo G et al. Muscle Nerve. 2015 Sep;52(3):344-55
Han JJ et al. Muscle Nerve. 2016 Apr;53(4):545-54
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Reachable Workspace Differences between:
DMD, BMD, FSHD, and ALS
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RSAvs.Brooke
(DMD)
Han JJ, Kurillo G et al. Muscle Nerve.
2015 Sep;52(3):344-55
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ElbowFlexion
ShoulderAbduction
Combined
Elbow Flexion % - predicted MVIC
0 20 40 60 80 100 120 140 160
Cohort
%
0
5
10
15
20
25
30
FSHD
CTRL
Shoulder Abduction % - predicted MVIC
0 20 40 60 80 100 120 140 160
Co
ho
rt %
0
5
10
15
20
25
30
FSHD
CTRL
Combined (Elbow Flexion + Shoulder Abduction) % - predicted MVIC
0 20 40 60 80 100 120 140 160
Cohort
%
0
5
10
15
20
25
30
FSHD
CTRL
RSA vs. Strength(FSHD)
Han JJ, de Bie E, Nicorici A, Abresch RT,
Bajcsy R, Kurillo G. Muscle Nerve. 2015
Dec;52(6):948-55.
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No Weight (no loading)
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500 Gram wrist weight (~1 lb loading)
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Han JJ, Kurillo G, Abresch RT, de Bie E, Nicorici Lewis A, Bajcsy R. Upper extremity 3D reachable workspace analysis in dystrophinopathyusing Kinect. Muscle Nerve. 2015 Sep;52(3):344-55
Using simple wrist-weight to detect subtle differences in Reachability
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FSHD:
Reachable workspace
by
QMT
• Shoulder Abduction
• Elbow Flexion
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Han JJ, de Bie E, Nicorici A, Abresch RT, Anthonisen C, Bajcsy R, Kurillo G, Mcdonald CM. Reachable workspace and performance of upper limb (PUL) in Duchenne muscular dystrophy. Muscle Nerve. 2016 Apr;53(4):545-54
R= 0.945, P<0.001
RSA correlates well with PUL
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Mapping ADL functions (PRO – NeuroQOL)to Reachable workspace Quadrants
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Han JJ, Kurillo G, Abresch RT, de Bie E, Nicorici Lewis A, Bajcsy R. Upper extremity 3D reachable workspace analysis in dystrophinopathy using Kinect. Muscle Nerve. 2015 Sep;52(3):344-55
Reachable workspace correlation with
ADLs
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FSHD: Longitudinal study (18 subjects: 8mo-5yrs, ave 2.5yrs)
Hatch et al. Longitudinal Study of Upper Extremity Reachable Workspace in FSHD. Neuromuscular Disorders (2019). doi: https://doi.org/10.1016/j.nmd.2019.05.006
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FSHD: Longitudinal (8mo-5 years follow up)
Hatch et al. Longitudinal Study of Upper Extremity Reachable Workspace in FSHD. Neuromuscular Disorders (2019). doi: https://doi.org/10.1016/j.nmd.2019.05.006
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Hatch et al. Longitudinal Study of Upper Extremity Reachable Workspace in FSHD. Neuromuscular Disorders (2019). doi: https://doi.org/10.1016/j.nmd.2019.05.006
FSHD Longi: 500g weight
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Hatch et al. Longitudinal Study of Upper Extremity Reachable Workspace in FSHD. Neuromuscular Disorders (2019). doi: https://doi.org/10.1016/j.nmd.2019.05.006
FSHD Longitudinal: 18 subjects followed 8mo-5yrs (ave. 2.5 years)
∆-1.63%/yr
∆-1.82%/yr
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Hatch et al. Longitudinal Study of Upper Extremity Reachable Workspace in FSHD. Neuromuscular Disorders (2019). doi: https://doi.org/10.1016/j.nmd.2019.05.006
Entire cohort
w/o High-function
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ALS longitudinal data
de Bie E, Oskarsson B, Joyce NC, Nicorici A, Kurillo G, Han JJ. Longitudinal evaluation of upper extremity reachable workspace in ALS by Kinect sensor. Amyotroph Lateral Scler Frontotemporal Degener. 2017 Feb;18(1-2):17-23
Oskarsson B, Joyce NC, De Bie E, Nicorici A, Bajcsy R, Kurillo G, Han JJ. Upper extremity 3-dimensional reachable workspace assessment in amyotrophic lateral sclerosis by Kinect sensor. Muscle Nerve. 2016 Feb;53(2):234-41.
∆ -19.3%/year
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Pompe patients: pre- & post-ERT
Pre
3 months post
6 months post
Subject 105 Subject 107
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Clinical Trial & in-clinic RWS system
• >20 systems deployed around the world (NA, South America, Asia, Europe)
– Neuromuscular conditions
– Neurological
– Orthopedic & musculoskeletal
– Post breast cancer rehab
– Drug trial
• Portable system can be taken to patient’s home (laptop, tripod+Kinect)
• Cloud-based system– Internet sign-on
– Automatic data upload to cloud server
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Acknowledgement
• These studies were supported by grants from:
– NIH, NIAMS U01-AR065113-01
– NSF, #1111965
– NIDRR, #H133B090001
– CITRIS seed grant
– PPMD exploratory grant
• UC Berkeley/ Tele-immersion Lab
Gregorij Kurillo
Ruzena Bajcsy
Posu Yan
Robert Matthew
• UC Davis NIDRR RRTC in NMD
Craig McDonald
Ted Abresch
Colleen Anthonisen
Michelle Cregan
Evan deBie
Erica Goude
Erik Henricson
Linda Johnson
Alina Nicorici
Sean Sumner
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Thank you !
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