Journal
SENSORS
Volume 14, Issue 10, Pages 18800-18822Publisher
MDPI
DOI: 10.3390/s141018800
Keywords
gait analysis; inertial measurement units; gait event detection; wearable sensors; wireless sensor networks
Funding
- European Commission's 7th Framework Program as part of the CYBERLEGs project [287894]
- Slovenian Research Agency (ARRS) through the Motion Analysis and Synthesis in Man and Machine research program [P20228]
- Swiss National Science Foundation through the National Centre of Competence in Research Robotics
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Previous studies have presented algorithms for detection of turns during gait using wearable sensors, but those algorithms were not built for real-time use. This paper therefore investigates the optimal approach for real-time detection of planned turns during gait using wearable inertial measurement units. Several different sensor positions (head, back and legs) and three different detection criteria (orientation, angular velocity and both) are compared with regard to their ability to correctly detect turn onset. Furthermore, the different sensor positions are compared with regard to their ability to predict the turn direction and amplitude. The evaluation was performed on ten healthy subjects who performed left/right turns at three amplitudes (22, 45 and 90 degrees). Results showed that turn onset can be most accurately detected with sensors on the back and using a combination of orientation and angular velocity. The same setup also gives the best prediction of turn direction and amplitude. Preliminary measurements with a single amputee were also performed and highlighted important differences such as slower turning that need to be taken into account.
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