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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

Block diagram of the robust Kalman filter.
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f5-sensors-12-03049: Block diagram of the robust Kalman filter.

Mentions: Figure 5 depicts the block diagram of the robust Kalman filter. The result is a very easy implementation and simple derivation of the classic Kalman algorithm that includes the detection and elimination of undesirable data by an iterative downweighting of the outlying observations within the least squares method. The selection of the threshold b is a trade-off between outlier rejection and control delay. Using this trade-off, b was empirically selected (b = 5).


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)

Block diagram of the robust Kalman filter.
© Copyright Policy
Related In: Results  -  Collection

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

f5-sensors-12-03049: Block diagram of the robust Kalman filter.
Mentions: Figure 5 depicts the block diagram of the robust Kalman filter. The result is a very easy implementation and simple derivation of the classic Kalman algorithm that includes the detection and elimination of undesirable data by an iterative downweighting of the outlying observations within the least squares method. The selection of the threshold b is a trade-off between outlier rejection and control delay. Using this trade-off, b was empirically selected (b = 5).

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