| Autor: |
Yiannos Manoli, Ahmed Al-Jawad, Michailas Romanovas, Anton Barlit, Martin Traechtler |
| Rok vydání: |
2013 |
| Předmět: |
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| Zdroj: |
APCBEE Procedia. 7:93-102 |
| ISSN: |
2212-6708 |
| DOI: |
10.1016/j.apcbee.2013.08.018 |
| Popis: |
The paper presents a quaternion-based extended Kalman filter for postural instability evaluation during stance. It uses low-cost MEMS inertial sensors attached on the lower back of the person at a known height in order to instrumenting the static balancing test. Generally, patients with Parkinson's disease or vestibular-loss are at greater risk for having this problem. The objective of this study was to assess the feasibility of using Kalman filter to characterize the postural steadiness. The Kalman filter is used here as a data fusion algorithm to estimate the orientation of the body based on acceleration and angular rate signals. In order to get the coordinate of the body's centre of mass (CoM), the height of the sensor is projected on the horizontal plane by using the estimated orientation. Many parameters such as the mean velocity of sway, lateral/anterior-posterior range and others are then obtained from the sway path, which help the clinicians to assess the postural instability. The method was tested on 9 healthy individuals (21-31 years). Three different test conditions, namely feet comfortable stance with eyes-open, feet together stance with closed eyes and one-leg stance with eyes-open were evaluated here. The proposed algorithm showed successful estimation of the time-domain parameter for the postural sway analysis. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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