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A robust Kalman algorithm to facilitate human-computer interaction for people with cerebral palsy, using a new interface based on inertial sensors.

Raya R, Rocon E, Gallego JA, Ceres R, Pons JL - Sensors (Basel) (2012)

Bottom Line: This characterization is used to design a filtering technique that reduces the effect of involuntary motion on person-computer interaction.The filter increases mouse pointer directivity and the target acquisition time is reduced by a factor of ten.The interface ENLAZA and the RKF enabled them to use the computer.

View Article: PubMed Central - PubMed

Affiliation: Bioengineering Group, CSIC, Arganda del Rey, Madrid 28500, Spain. rafael.raya@csic.es

ABSTRACT
This work aims to create an advanced human-computer interface called ENLAZA for people with cerebral palsy (CP). Although there are computer-access solutions for disabled people in general, there are few evidences from motor disabled community (e.g., CP) using these alternative interfaces. The proposed interface is based on inertial sensors in order to characterize involuntary motion in terms of time, frequency and range of motion. This characterization is used to design a filtering technique that reduces the effect of involuntary motion on person-computer interaction. This paper presents a robust Kalman filter (RKF) design to facilitate fine motor control based on the previous characterization. The filter increases mouse pointer directivity and the target acquisition time is reduced by a factor of ten. The interface is validated with CP users who were unable to control the computer using other interfaces. The interface ENLAZA and the RKF enabled them to use the computer.

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Related in: MedlinePlus

Remaining distance versus time for 4 consecutive reaching tasks performed by CP1, (a) without filtering, (b) with BBF, (c) with KF, (d) with RKF.
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f8-sensors-12-03049: Remaining distance versus time for 4 consecutive reaching tasks performed by CP1, (a) without filtering, (b) with BBF, (c) with KF, (d) with RKF.

Mentions: The effect of the filtering techniques can be shown graphically. Figure 7 depicts the target-reaching trajectory without the adaptive filter and with BBF, KF and RKF. Figure 8 shows the remaining distance versus time without and with adaptive filters for four consecutive targets. Table 5 shows that the RKF had the best performance followed by the KF and BBF. Although the BBF is able to filter high-frequency movements, it had lower performance than RKF. The reason is that BBF responds faster to changes in movement (involuntary movements) that is undesired. The detection and elimination of outliers (sub-movements following the initial movement), included by the RKF, are more adequate for this application. The gain filter is modulated in real-time and is lower during straight paths in which the prediction error is smaller. By means of outliers suppression and the dynamic gain filter, the initial movement that rapidly covers distance is smoothly filtered, whereas the movements around the target are filtered more strongly. As a consequence, the filtering technique facilitates fine control.


A robust Kalman algorithm to facilitate human-computer interaction for people with cerebral palsy, using a new interface based on inertial sensors.

Raya R, Rocon E, Gallego JA, Ceres R, Pons JL - Sensors (Basel) (2012)

Remaining distance versus time for 4 consecutive reaching tasks performed by CP1, (a) without filtering, (b) with BBF, (c) with KF, (d) with RKF.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376565&req=5

f8-sensors-12-03049: Remaining distance versus time for 4 consecutive reaching tasks performed by CP1, (a) without filtering, (b) with BBF, (c) with KF, (d) with RKF.
Mentions: The effect of the filtering techniques can be shown graphically. Figure 7 depicts the target-reaching trajectory without the adaptive filter and with BBF, KF and RKF. Figure 8 shows the remaining distance versus time without and with adaptive filters for four consecutive targets. Table 5 shows that the RKF had the best performance followed by the KF and BBF. Although the BBF is able to filter high-frequency movements, it had lower performance than RKF. The reason is that BBF responds faster to changes in movement (involuntary movements) that is undesired. The detection and elimination of outliers (sub-movements following the initial movement), included by the RKF, are more adequate for this application. The gain filter is modulated in real-time and is lower during straight paths in which the prediction error is smaller. By means of outliers suppression and the dynamic gain filter, the initial movement that rapidly covers distance is smoothly filtered, whereas the movements around the target are filtered more strongly. As a consequence, the filtering technique facilitates fine control.

Bottom Line: This characterization is used to design a filtering technique that reduces the effect of involuntary motion on person-computer interaction.The filter increases mouse pointer directivity and the target acquisition time is reduced by a factor of ten.The interface ENLAZA and the RKF enabled them to use the computer.

View Article: PubMed Central - PubMed

Affiliation: Bioengineering Group, CSIC, Arganda del Rey, Madrid 28500, Spain. rafael.raya@csic.es

ABSTRACT
This work aims to create an advanced human-computer interface called ENLAZA for people with cerebral palsy (CP). Although there are computer-access solutions for disabled people in general, there are few evidences from motor disabled community (e.g., CP) using these alternative interfaces. The proposed interface is based on inertial sensors in order to characterize involuntary motion in terms of time, frequency and range of motion. This characterization is used to design a filtering technique that reduces the effect of involuntary motion on person-computer interaction. This paper presents a robust Kalman filter (RKF) design to facilitate fine motor control based on the previous characterization. The filter increases mouse pointer directivity and the target acquisition time is reduced by a factor of ten. The interface is validated with CP users who were unable to control the computer using other interfaces. The interface ENLAZA and the RKF enabled them to use the computer.

Show MeSH
Related in: MedlinePlus