全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
Sensors  2012 

A Robust Kalman Algorithm to Facilitate Human-Computer Interaction for People with Cerebral Palsy, Using a New Interface Based on Inertial Sensors

DOI: 10.3390/s120303049

Keywords: inertial sensors, human-computer interface, cerebral palsy, Kalman filter

Full-Text   Cite this paper   Add to My Lib

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.

References

[1]  Bax, M. Terminology and classification of cerebral palsy. Dev. Med. Child Neurol 1964, 11, 295–297.
[2]  Winter, S.; Autry, A.; Yeargin-Allsopp, M. Trends in the prevalence of cerebral palsy in a population-based study. Pediatric 2002, 110, 1220–1225, doi:10.1542/peds.110.6.1220.
[3]  Johnson, A. Prevalence and characteristics of children with cerebral palsy in Europe. Dev. Med. Child Neurol 2002, 44, 633–640. 12227618
[4]  Cans, C. Surveillance of cerebral palsy in Europe: A collaboration of cerebral palsy surveys and registers. Dev. Med. Child Neurol 2000, 42, 816–824. 11132255
[5]  Krageloh-Mann, I.; Cans, C. Cerebral palsy update. Brain Dev 2009, 31, 537–544, doi:10.1016/j.braindev.2009.03.009. 19386453
[6]  Palisano, R.; Rosenbaum, P.; Walte, S.; Russell, D.; Word, E.; Galuppi. Gross motor function classification system. Dev. Med. Child Neurol 1997, 39, 214–233. 9183258
[7]  Beckung, E.; Hagberg, G. Correlation between ICIDH handicap code and gross motor function classification system in children with cerebral palsy. Dev. Med. Child Neurol 2000, 42, 669–673, doi:10.1017/S0012162200001237. 11085294
[8]  Eliasson, A.C.; Krumlinde-Sundholm, L.; R?sblad, B.; Beckung, E.; Arner, M.; Ohrvall, A.M.; Rosenbaum, P. The Manual Ability Classification System (MACS) for children with cerebral palsy: Scale development and evidence of validity and reliability. Dev. Med. Child Neurol 2006, 48, 549–554, doi:10.1017/S0012162206001162. 16780622
[9]  Man, D.W.K.; Wong, M.L. Evaluation of computer-access solutions for students with quadriplegic athetoid cerebral palsy. Am. J. Occup. Ther 2007, 61, 355–364, doi:10.5014/ajot.61.3.355. 17569393
[10]  Davies, C.; Mudge, S.; Ameratunga, S.; Stott, S. Enabling self-directed computer use for individuals with cerebral palsy: A systematic review of assistive devices and technologies. Dev. Med. Child Neurol 2010, 52, 510–516, doi:10.1111/j.1469-8749.2009.03564.x. 20059508
[11]  Durfee, J.; Billingsley, F. A comparison of two computer input devices for uppercase letter matching. Am. J. Occup. Ther 1999, 5, 214–220.
[12]  Rao, R.; Seliktar, R.; Rahman, T. Evaluation of an isometric and a position joystick in a target acquisition task for individuals with cerebral palsy. IEEE Trans. Rehabil. Eng 2000, 8, 118–125, doi:10.1109/86.830956. 10779115
[13]  Betke, M.; Gips, J.; Fleming, P. The camera mouse: Visual tracking of body features to provide computer access for people with severe disabilities. IEEE Trans. Neural Syst. Rehabil. Eng 2002, 10, 1–10, doi:10.1109/TNSRE.2002.1021581. 12173734
[14]  Singer, H.; Mink, J.; Gilbert, D.; Jankovic, J. Movement Disorder in Childhood; Saunders Elsevier: Philadelphia, PA, USA, 2010.
[15]  Mauri, C.; Granollers, T.; Lorés, J.; García, M. Computer vision interaction for people with severe movement restrictions. Interdiscip. J. Hum. ICT Environ 2006, 2, 38–54.
[16]  Lin, Y.; Chen, M.; Yeh, C.; Yeh, Y.; Wang, H. Assisting an Adolescent with Cerebral Palsy to Entry Text by Using the Chorded Keyboard. In Computers Helping People with Special Needs, Proceedings of the 11th International Conference (ICCHP ’08), Linz, Austria, 9–11 July 2008; Miesenberger, K., Klaus, J., Zagler, W., Karshmer, A., Eds.; Springer-Verlag: Heidelberg, Germany, 2008; pp. 1177–1183.
[17]  McCormack, D. The effects of keyguard use and pelvic positioning on typing speed and accuracy in a boy with cerebral palsy. Am. J. Occup. Ther 1990, 44, 312–315, doi:10.5014/ajot.44.4.312. 2330961
[18]  Stewart, H.; Wilcock, A. Improving the communication rate for symbol based, scanning voice output device users. Technol. Disabil 2000, 13, 141–150.
[19]  Havstam, C.; Buchholz, M.; Hartelius, L. Speech recognition and dysarthria: A single subject study of two individuals with profound impairment of speech and motor control. Logop. Phoniatr. Vocol 2003, 28, 81–90, doi:10.1080/14015430310015372.
[20]  Parker, M.; Cunningham, S.; Enderby, P.; Hawley, M.; Green, P. Automatic speech recognition and training for severely dysarthric users of assistive technology: The STARDUST project. Clin. Linguist. Phon 2006, 20, 149–156, doi:10.1080/02699200400026884. 16428231
[21]  Hwang, F.; Keates, S.; Langdon, P.; Clarkson, P. Multiple Haptic Targets for Motion-Impaired Computer Users. Proceedings of the CHI ’03, Fort Lauderdale, FL, USA, 5–10 April 2003; pp. 41–48.
[22]  Ahlstr?m, D.; Hitz, M.; Leitner, G. An Evaluation of Sticky and Force Enhanced Targets in Multitarget Situations. Proceedings of the 4th Nordic Conference on Human-Computer Interaction: Changing Roles (NordiCHI ’06), Oslo, Norway, 14–18 October 2006; pp. 58–67.
[23]  Grossman, T.; Balakrishnan, R. The Bubble Cursor: Enhancing Target Acquisition by Dynamic Resizing of the Cursor’s Activation Area. Proceedings of CHI ’05, Portland, OR, USA, 2–7 April 2005; pp. 281–290.
[24]  Wobbrock, J.O.; Gajos, K.Z. A Comparison of Area Pointing and Goal Crossing for People with and without Motor Impairments. Proceedings of 9th International ACM SIGACCESS Conference on Computers and Accessibility, Tempe, AZ, USA, 22–24 October 2007.
[25]  Olds, K.; Sibenaller, S.; Cooper, R.; Ding, D.; Riviere, C. Target Prediction for Icon Clicking by Athetoid Persons. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA ’08), Pasadena, CA, USA, 19–23 May 2008; pp. 2043–2048.
[26]  Raya, R.; Rocon, E.; Ceres, R.; Harlaar, J.; Geytenbeek, J. Characterizing Head Motor Disorders to Create Novel Interfaces for People with Cerebral Palsy. Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR ’11), Zurich, Switzerland, 29 June–1 July 2011.
[27]  Rocon, E.; Ruiz, A.; Pons, J. On the Use of Rate Gyroscopes for Tremor Sensing in the Human Upper Limb. Proceedings of the International Conference Eurosensors XIX, Barcelona, Spain, 1–14 September 2005.
[28]  Roetenberg, D.; Luinge, H.; Baten, C.; Veltink, H. Compensation of magnetic disturbances improves inertial and magnetic sensing of human body segment orientation. IEEE Trans. Neural Syst. Rehabil. Eng 2005, 13, 395–405, doi:10.1109/TNSRE.2005.847353. 16200762
[29]  Raya, R.; Roa, J.O.; Rocon, E.; Ceres, R.; Pons, J.L. Wearable inertial mouse for children with physical and cognitive impairments. Sens. Actuat. A Phys 2010, 162, 248–259, doi:10.1016/j.sna.2010.04.019.
[30]  Fitts, P. The information capacity of the human motor system in controlling the amplitude of movement. J. Exp. Psychol 1954, 47, 381–391, doi:10.1037/h0055392. 13174710
[31]  Zhang, X.; MacKenzie, S. Evaluating Eye Tracking with ISO 9241-Part 9. Proceedings of the HCI International, Beijing, China, 22–27 July 2007; pp. 779–788.
[32]  Douglas, S.A.; Kirkpatrick, A.E.; MacKenzie, I.S. Testing Pointing Device Performance and User Assessment with the ISO9241, Part 9 Standard. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI ’99), Pennsylvania, PA, USA, 15–20 May 1999; pp. 215–222.
[33]  MacKenzie, I.S.; Jusoh, S. An Evaluation of Two Input Devices for Remote Pointing. Proceedings of the 8th IFIP Working Conference on Engineering for Human-Computer Interaction (EHCI ’01), Toronto, ON, Canada, 1–13 May 2001; pp. 235–249.
[34]  Music, J.; Cecic, M.; Bonkovic, M. Testing inertial sensor performance as hands-free human-computer interface. WSEAS Trans. Comput 2009, 8, 715–724.
[35]  Marsden, C.D.; Parkes, J.D. Abnormal movement disorders. Br. J. Hosp. Med 1973, 10, 428–450.
[36]  Gresty, M.A.; Halmagyi, G.M. Abnormal head movements. J. Neurol. Neurosurg. Psychiatry 1979, 42, 705–714, doi:10.1136/jnnp.42.8.705. 490176
[37]  Baldwin, P.; Basu, A.; Zhang, H. Predictive Windows for Delay Compensation in Telepresence Applications. Proceedings of the 1998 IEEE International Conference on Robotics & Automation, Leuven, Belgium, 16–20 May 1998; 1, pp. 2884–2889.
[38]  Brookner, E. Tracking and Kalman Filtering Made Easy; Wiley-Interscience: Malden, MA, USA, 1998.
[39]  Benedict, T.; Bordner, G. Synthesis of an optimal set of radar track-while-scan smoothing equations. IRE Trans. Autom. Control 1962, 7, 27–32, doi:10.1109/TAC.1962.1105477.
[40]  Riviere, C.; Thakor, N. Modeling and canceling tremor in human-machine interfaces. IEEE Eng. Med. Biol 1998, 1, 29–36.
[41]  Pons, J.; Rocon, E.; Ruiz, A.; Moreno, J. Upper-Limb Robotic Rehabilitation Exoskeleton: Tremor Suppression; Intech Education and Publishing: Vienna, Austria, 2007. Chapter 25,; p. 648.
[42]  Gallego, J.; Rocon, E.; Roa, J.; Moreno, J.; Pons, J. Real-time estimation of pathological tremor parameters from gyroscope data. Sensors 2010, 10, 2129–2149, doi:10.3390/s100302129. 22294919
[43]  Bar-Shalom, Y.; Li, X. Estimation and Tracking: Principles, Techniques, and Software; Artech House Publishers: Boston, MA, USA, 1998.
[44]  Kalman, R. A new approach to linear filtering and prediction problems. J. Basic Eng. Trans. ASME 1960, 82, 35–45, doi:10.1115/1.3662552.
[45]  Huber, P. Robust Statistics; Wiley and Sons: Hoboken, NJ, USA, 1981.
[46]  Cipra, T.; Romera, R. Robust Kalman filter and its application in time series analysis. Kybernetika 1991, 27, 481–494.
[47]  McCrea, P.; Eng, J. Consequences of increased neuromotor noise for reaching movements in persons with stroke. Exp. Brain Res 2005, 162, 70–77, doi:10.1007/s00221-004-2106-8. 15536551
[48]  Findlater, L.; Jansen, A.; Shinohara, K.; Dixon, M.; Kamb, P.; Rakita, J.; Wobbrock, J. Enhanced Area Cursors: Reducing Fine-Pointing Demands for People with Motor Impairments. Proceedings of the ACM Symposium on User Interface Software and Technology (UIST ’10), New York, NY, USA, 3–6 October 2010; pp. 153–162.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133