Skin deformation caused by muscle motion is a common source of error for body-mounted sensors. A new method of measuring joint angles using a combination of two-axial accelerometers and reaction force sensors is presented. In this study, the effect of soft tissue deformation was minimized using a new reaction force sensor that is bound onto the body segment. The force sensor was designed using a pressure-sensitive electric conductive rubber. A Fourier transform of the total pressure forces induced by the body-mounted motion sensor modules was implemented to analyze the frequency property of soft tissue deformation on the human body surface. We processed the data of two-axial accelerations measured by the accelerometers using the measurements of soft tissue deformation including the total pressure force and two-directional coordinates of the center of pressure. An experimental study with ten subjects was implemented to verify the new sensor system proposed for estimating the joint angle of the knee. The effectiveness of this system is illustrated by the experimental results using an optical motion analysis system as a reference. If we use the accelerometers alone, the root mean square (RMS) difference and the coefficient of multiple correlation (CMC) over all the subjects walking at each of the three speeds (slow, average, and fast) are 6.3±1.4deg and 0.93±0.05, 6.9±1.7deg and 0.92±0.03, and 8.3±2.0deg and 0.89±0.03, respectively. If we compensate for soft tissue deformation using the surface pressure measurements, the RMS difference and the CMC in each of the three conditions are 4.7±1.1deg and 0.96±0.04, 5.0±1.5deg and 0.96±0.04, and 6.6±1.9deg and 0.93±0.03, respectively. Measurement results of the developed sensor system showed high correlation with results from two alternative methods including an optical motion analysis system and the goniometer system in walking analysis experiments. The results support the effectiveness of the proposed method in the measurement of the flexion and extension angle of the knee. The compensation for soft tissue deformation using the surface pressure measurements improved the accuracy of the body-mounted sensor in the experiments.

1.
Bonato
,
P.
, 2003, “
Wearable Sensors/Systems and Their Impact on Biomedical Engineering
,”
IEEE Eng. Med. Biol. Mag.
0739-5175,
22
, pp.
18
20
.
2.
Giansanti
,
D.
,
Macellari
,
V.
,
Maccioni
,
G.
, and
Cappozzo
,
A.
, 2003, “
Is It Feasible to Reconstruct Body Segment 3-D Position and Orientation Using Accelerometric Data?
IEEE Trans. Biomed. Eng.
0018-9294,
50
, pp.
476
483
.
3.
Tong
,
K.
, and
Granat
,
H. M.
, 1999, “
A Practical Gait Analysis System Using Gyroscopes
,”
Med. Eng. Phys.
1350-4533,
21
, pp.
87
94
.
4.
Pappas
,
I. P. I.
,
Popovic
,
M. R.
,
Keller
,
T.
,
Dietz
,
V.
, and
Morari
,
M.
, 2001, “
A Reliable Gait Phase Detection System
,”
IEEE Trans. Rehabil. Eng.
1063-6528,
9
, pp.
113
125
.
6.
Luinge
,
H. J.
, and
Veltink
,
P. H.
, 2004, “
Inclination Measurement of Human Movement Using a 3-D Accelerometer With Autocalibration
,”
IEEE Trans. Rehabil. Eng.
1063-6528,
12
, pp.
112
121
.
7.
Liu
,
T.
,
Inoue
,
Y.
,
Shibata
,
K.
, and
Morioka
,
H.
, 2006, “
Development of Wearable Sensor Combinations for Human Lower Extremity Motion Analysis
,”
Proceedings of IEEE International Conference on Robotics and Automation
, pp.
1655
1660
.
8.
Parry
,
J.
, 1992,
Gait Analysis Normal and Pathological Function
,
Slack Inc.
,
Thorofare, NJ
, pp.
149
158
.
You do not currently have access to this content.