A novel approach to reducing number of sensing units for wearable gait analysis systems.
Gait analysis methods to estimate spatiotemporal measures, based on two, three or four gyroscopes attached on lower limbs have been discussed in the literature. The most common approach to reduce the number of sensing units is to simplify the underlying biomechanical gait model. In this study, we propose a novel method based on prediction of movements of thighs from movements of shanks. Datasets from three previous studies were used. Data from the first study (ten healthy subjects and ten with Parkinson's disease) were used to develop and calibrate a system with only two gyroscopes attached on shanks. Data from two other studies (36 subjects with hip replacement, seven subjects with coxarthrosis, and eight control subjects) were used for comparison with the other methods and for assessment of error compared to a motion capture system. Results show that the error of estimation of stride length compared to motion capture with the system with four gyroscopes and our new method based on two gyroscopes was close (  -0.8 ±6.6 versus   3.8 ±6.6 cm). An alternative with three sensing units did not show better results (error:  -0.2 ±8.4 cm). Finally, a fourth that also used two units but with a simpler gait model had the highest bias compared to the reference (error:  -25.6 ±7.6 cm). We concluded that it is feasible to estimate movements of thighs from movements of shanks to reduce number of needed sensing units from 4 to 2 in context of ambulatory gait analysis.
Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Fédéral de Lausanne, Lausanne CH-1015, Switzerland. arash.salarian@ieee.org
Arash
A
Salarian
Pierre R
PR
Burkhard
François J G
FJ
Vingerhoets
Brigitte M
BM
Jolles
Kamiar
K
Aminian
D000368:Aged; D019644:Arthroplasty, Replacement, Hip; D016022:Case-Control Studies; D003020:Clothing; D005260:Female; D005684:Gait / Q000502:physiology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D018670:Monitoring, Ambulatory / Q000295:instrumentation* / Q000379:methods; D010300:Parkinson Disease / Q000503:physiopathology; D012815:Signal Processing, Computer-Assisted