an-chih tsai tsung-han hsieh2 meng-tien wu1,3 ta-te lin2 pei...
Post on 31-Aug-2020
1 Views
Preview:
TRANSCRIPT
Results
Methods
1. Two healthy young, six healthy middle-aged and older
adults, and three stroke patients participated in the study
(Table 1).
2. Examples of tracking performance curves (Fig. 6).
3. The subjects reduced tracking errors over time whether as
individuals or as groups (Table 2.)(Fig. 7).
• The Motor Sequence Learning Paradigm:
• The design: a baseline test, five-day training period, and a
retention test
• Set-up: The IMU was fastened to the dorsal-anterior aspect of
the non-dominant foot of the subject (Fig. 4); the subject was
sitting in front of the monitor equipped with the interface and
analysis software (Fig. 5)
• Procedures: each subject performed ankle dorsiflexion
/plantarflexion movements to track the upward/downward
trajectories of the target. On each day of training, 12 blocks of
ten 12-sec repeated/random sequence trials were practiced.
• Dependent measure: RMSEbaseline, RMSEretention, and
normalized change (∆) of RMSE after training
•Normalized ∆ of RMSE
= (RMSEbaseline - RMSEretention)/RMSEbaseline x 100%
• The ankle tracking device: The system consisted of a wireless
inertial measurement unit (IMU) (InvenSense® )(Fig. 1), a
computer monitor, interface software, and analysis software.
• The IMU: Equipped with a 3-DoF accelerometer, a 3-DoF
gyro sensor, a 3-DoF magnetometer, and a microprocessor;
can precisely and reliably measure roll, yaw, and pitch
angles with less than 0.8° of errors as validated by a
standard potentiometer encoder.
• The interface: developed by using C++ Builder (Borland® ),
used for producing and displaying target tracking trajectories
(Fig. 2), which were derived from polynomial equations, and
for displaying subject’s ankle position (Fig. 2)
• The analysis software: to record tracking performance and
calculate the root mean square errors (RMSE) between
target position and subject’s ankle position, normalized to
subject’s maximal ankle range of motion (Fig. 3).
Ko Chiao1 An-Chih Tsai2 Tsung-Han Hsieh2 Meng-Tien Wu1,3 Ta-Te Lin2 Pei-Fang Tang1*
1 School and Graduate Institute of Physical Therapy, National Taiwan University, Taipei, Taiwan, ROC2 Department of Bio-Industrial Mechatronics Engineering, National Taiwan University, Taipei, Taiwan, ROC3 Rehabilitation Center, Cardinal Tien Hospital Yunghe Branch, Taipei, Taiwan, ROC
Conclusions
Fig. 2 Target and ankle
position displayed on the
monitor
Fig. 1 IMU
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.10
1 2 3 4 5 6 7
RM
SE
Repeated Sequence
Young aver. Older aver. Stroke_aver.
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.10
1 2 3 4 5 6 7
RM
SE
Random Sequence
Young aver. Older aver. Stroke_aver.
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
1 2 3 4 5 6 7
RM
SE
Day
Y01
Repeated Random
0.02
0.03
0.04
0.05
1 2 3 4 5 6 7
RM
SE
Day
H06
Repeated Random
0.06
0.07
0.08
0.09
0.10
0.11
0.12
0.13
1 2 3 4 5 6 7
RM
SE
Day
S02
Repeated Random
Young Subjects Baseline test Retention test Normalized ∆
Y01 0.0800 0.0500 37.50%
Y02 0.0600 0.0500 16.67%
Mean 0.0700 0.0500 27.08%
Older Subjects Baseline test Retention test Normalized ∆
H02 0.0486 0.0338 30.42%
H03 0.0788 0.0493 37.41%
H04 0.0688 0.0257 62.69%
H05 0.0401 0.0276 31.20%
H06 0.0443 0.0274 38.10%
H07 0.0658 0.0418 36.51%
Mean 0.0577 0.0343 39.39%
Stroke Subjects Baseline test Retention test Normalized ∆
S01 0.0707 0.0546 22.75%
S02 0.1193 0.0671 43.78%
S03 0.0649 0.0474 26.93%
Mean 0.0850 0.0564 31.15%
Young Subjects Baseline test Retention test Normalized ∆
Y01 0.0500 0.0300 40.00%
Y02 0.0500 0.0200 60.00%
Mean 0.0500 0.0250 50.00%
Older Subjects Baseline test Retention test Normalized ∆
H02 0.0490 0.0338 31.03%
H03 0.0791 0.0477 39.75%
H04 0.0642 0.0294 54.20%
H05 0.0412 0.0270 34.35%
H06 0.0428 0.0270 36.86%
H07 0.0570 0.0391 31.44%
Mean 0.0556 0.0340 37.94%
Stroke Subjects Baseline test Retention test Normalized ∆
St01 0.0634 0.0601 5.32%
St02 0.1130 0.0733 35.08%
St03 0.1048 0.0491 53.17%
Mean 0.0937 0.0608 31.19%
Table 2. The RMSE and normalized ∆ of RMSE of the ankle tracking
performance of young, older and stroke groups (Left: Repeated
sequence; Right: Random sequence)
Repeated sequence Random sequence
Background and Purpose
Fig. 6 Performance curves of 3 subjects.
Fig. 3 Examples of repeated and random sequences of ankle
tracking trajectories with subject’s tracking performance (green)
being superimposed on the target trajectories (red).
Fig. 4 Placement of IMU
• Ankle motor control is crucial for balance and walking. Few
portable devices are available for the assessment and training
of ankle motor control.
• We invented a new portable wireless device and tested its
feasibility to be used for the assessment and training of ankle
tracking performance in healthy and clinical populations using
a motor sequence learning paradigm.
Subject
Target
Max. dorsiflexion
Max. plantarflexion
• Preliminary results support that the devise is applicable to the
assessment and training of ankle plantarflexion/dorsiflexion
tracking movements. Further studies will be needed using
larger samples of different populations.
Acknowledgments
NSC 101–2314–B–002–009 awarded to Dr. Tang;
Advanced Biomedical MRI Lab at NTUH
Subject Age GenderFooted-
ness
Hemiplegic
sideMMSE
Muscle
strength
(kg)
Fugl-
Meyer
score
Fugl-Meyer
score of
ankle motion
Y01 24.4 F R -- 30 23.60 -- --
Y02 22.2 F R -- 30 17.43 -- --
H02 67.9 M R -- 28 23.60 -- --
H03 64.3 F R -- 30 13.20 -- --
H04 49.0 F R -- 30 21.90 -- --
H05 52.2 F R -- 30 20.57 -- --
H06 58.0 F R -- 30 17.40 -- --
H07 61.2 F R -- 28 16.87 -- --
S01 76.1 F R L 29 13.07 30/34 8/8
S02 66.8 M R L 30 -- 30/34 8/8
S03 27.2 F R R 28 -- 27/34 5/8
Table 1. Demographics of all subjects
Fig. 7 Mean performance curves of 3 subject groups for repeated and
random sequence learning.
Fig. 5 Experimental setting
top related