[PAST] Robot mediated diagnosis of neurological disorders and musculoskeletal diseases/injuries
[PAST] Robot mediated diagnosis of neurological disorders and musculoskeletal diseases/injuries [17]
2014 / 03 / 26 / PM 5:00
Location: 301 - 117
Speaker: Sang Hoon Kang
2012- Present
Instructor, Dept. of Biomedical Engineering, McCormick School of Engineering,
Northwestern University, Evanston, IL

May 2010- Present
Postdoctoral Fellow, Dept. of Physical Medicine and Rehabilitation, Feinberg School of
Medicine, Northwestern University, Chicago, IL

Jan. 2010- Present
Research Associate, Sensory Motor Performance Program, Rehabilitation Institute of
Chicago, Chicago, IL

Apr. 2009-Jan. 2010
Researcher, National Research Foundation of Korea (NRF), Daejeon, South Korea
* KOSEF is changed to NRF due to the Korean government policy (June 26 2009).

Mar. 2000-Jan. 2009
Graduate Research Assistant, Robot Control Lab., Dept. of Mechanical Engineering,

Teaching Assistant, Dept. of Mechanical Engineering, KAIST

Dec. 1999-Jan. 2000
Intern Research Assistant, Korea Institute of Nuclear Safety (KINS), Daejeon, South


In this seminar, robot mediated diagnosis of neurological disorders and musculoskeletal
diseases/injuries will be presented.
- Upper limb post stroke (and other neurological disorders) may display impairment(s) across multiple
joints/DOFs: namely, increased stiffness within and across multiple joints/DOF, loss of individuation, and
stereotypical patterns of deformity (e.g., adducted/internally rotated shoulder, flexed elbow and wrist,
and clenched fist). Clinically, it is, however, difficult to diagnose impairment(s) involving multiple joints
with the manual examination(s) using ordinal clinical scales such as Fugl-Meyer scale and Modified
Ashworth Scale (MAS). To address the issue, a multi-DOF exoskeleton robot, IntelliArm, was developed
and showed promising results in helping diagnosis of the multiple joint/DOF impairment(s) and
providing (impairment-specific) therapy accordingly.
- Knee osteoarthritis (OA) is a chronic degenerative disease with disabling pain and is prevalent with
increase of human life-span. The external knee adduction moment (EKAM) is closely associated with the
presence, progression, and severity of knee OA. However, there is a lack of convenient and practical
real-time methods to estimate and track the EKAM of patients with knee OA for clinical evaluation and
gait training, especially outside of gait laboratories. A practical real-time EKAM estimation method on
an elliptical trainer was developed and its high reliability of the method was verified. Moreover,
substantial changes in the EKAM and other knee moments during stepping in the patient with knee OA
were observed. This is the first study to develop and test feasibility of the real-time EKAM tracking
method on patients with knee OA, which provides us an accurate and practical real-time method to
evaluate the critical EKAM for diagnosis of patients with knee OA and real-time EKAM feedback
rehabilitation training., 02-880-7149