Wearable inertial mouse for children with physical and cognitive impairments

People with multiple physical and cognitive impairments have difficulties for using properly conventional pointing devices, what reduces their possibilities to communicate and improve their cognitive and physical skills through computers. This paper proposes a head control mouse based on a triaxial inertial sensor particularly focused on infants with cerebral palsy (CP). The system consists of a real-time head tracker that translates the head orientation into pointer positions and measures kinematic parameters through the 3D inertial sensor. The algorithm to estimate the angular head orientation is presented and validated with an accuracy about 1°. The experimental results with five healthy users demonstrated that the inertial pointer succeeds what was validated according to the ISO 9241-Part9. The experimental results with two infants with CP (athetoid and dystonic cases) demonstrated that the infants are capable of placing the pointer around the target but they have difficulties for fine motor control. The inertial sensor offers interesting kinematic parameters of the pathological movement. These parameters can be directly obtained by the inertial signals and are very useful to design filtering techniques to extract voluntary intentions. A research technique for filtering some patterns of the involuntary movements is presented. The inertial interface constructed and validated in this paper will allow increasing the knowledge about the pathological motion of the infants with CP.

[1]  N. Vøllestad,et al.  The use and impact of assistive devices and other environmental modifications on everyday activities and care in young children with cerebral palsy , 2005, Disability and rehabilitation.

[2]  M. Mazo,et al.  Experiences in assisted mobility: the SIAMO project , 2002, Proceedings of the International Conference on Control Applications.

[3]  Raymond J. Mooney,et al.  Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing , 2005 .

[4]  H. Stam,et al.  Motor impairments and activity limitations in children with spastic cerebral palsy: a Dutch population-based study. , 2009, Journal of rehabilitation medicine.

[5]  Margrit Betke,et al.  Intelligent Interfaces to Empower People with Disabilities , 2010, Handbook of Ambient Intelligence and Smart Environments.

[6]  Thomas Martinetz,et al.  A facial feature tracker for human-computer interaction based on 3D Time-Of-Flight cameras , 2008, Int. J. Intell. Syst. Technol. Appl..

[7]  Shmuel Shulman,et al.  The Facilitation of Information Processing in Learning Disabled Children Using Computer Games. , 1987 .

[8]  Jeff A. Bilmes,et al.  Longitudinal study of people learning to use continuous voice-based cursor control , 2009, CHI.

[9]  P. Helders,et al.  Effects of a functional therapy program on motor abilities of children with cerebral palsy. , 2001, Physical therapy.

[10]  Josip Musić,et al.  Testing inertial sensor performance as hands-free human-computer interface , 2009 .

[11]  Howell O. Istance,et al.  Why are eye mice unpopular? A detailed comparison of head and eye controlled assistive technology pointing devices , 2003, Universal Access in the Information Society.

[12]  M. Bax.  TERMINOLOGY AND CLASSIFICATION OF CEREBRAL PALSY , 1964, Developmental medicine and child neurology.

[13]  I. Scott MacKenzie,et al.  Fitts' Law as a Research and Design Tool in Human-Computer Interaction , 1992, Hum. Comput. Interact..

[14]  José Luis Pons Rovira,et al.  Virtual reality training and EMG control of the MANUS hand prosthesis , 2005, Robotica.

[15]  Richard Wright,et al.  The Vocal Joystick: A Voice-Based Human-Computer Interface for Individuals with Motor Impairments , 2005, HLT.

[16]  A. Palmer,et al.  Frequency spectrum analysis of wrist motion for activities of daily living , 1989, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.

[17]  T. Benedict,et al.  Synthesis of an optimal set of radar track-while-scan smoothing equations , 1962 .

[18]  Jane Bache,et al.  Access to computer-based leisure for individuals with profound disabilities. , 2008, NeuroRehabilitation.

[19]  Wolfgang Nutt,et al.  Tongue-mouse for quadriplegics , 1998 .

[20]  J Deitz,et al.  Single-switch computer access for infants and toddlers. , 1993, The American journal of occupational therapy : official publication of the American Occupational Therapy Association.

[21]  M. Betke,et al.  The Camera Mouse: visual tracking of body features to provide computer access for people with severe disabilities , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[22]  Toni Granollers,et al.  COMPUTER VISION INTERACTION FOR PEOPLE WITH SEVERE MOVEMENT RESTRICTIONS , 2006 .

[23]  D. Man,et al.  Evaluation of computer-access solutions for students with quadriplegic athetoid cerebral palsy. , 2007, The American journal of occupational therapy : official publication of the American Occupational Therapy Association.

[24]  E. Rocon,et al.  Application of inertial sensors in rehabilitation robotics , 2007, 2007 IEEE 10th International Conference on Rehabilitation Robotics.

[25]  Marco Parvis,et al.  Procedure for effortless in-field calibration of three-axial rate gyro and accelerometers , 1995 .

[26]  C. Manresa-Yee,et al.  Non-verbal communication by means of head tracking , 2006 .

[27]  Takashi Watanabe,et al.  Gyro-Mouse for the Disabled: 'Click' and 'Position' Control of the Mouse Cursor , 2007 .

[28]  P. Veltink,et al.  Compensation of magnetic disturbances improves inertial and magnetic sensing of human body segment orientation , 2005, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[29]  Ronald Poppe,et al.  Vision-based human motion analysis: An overview , 2007, Comput. Vis. Image Underst..

[30]  P Blenkhorn,et al.  Controlling mouse pointer position using an infrared head-operated joystick. , 2000, IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[31]  Ann Johnson.  Prevalence and characteristics of children with cerebral palsy in Europe. , 2002, Developmental medicine and child neurology.

[32]  J. Pons,et al.  A robotic vehicle for disabled children , 2005, IEEE Engineering in Medicine and Biology Magazine.

[33]  L. Cohen,et al.  Drivers of brain plasticity , 2005, Current opinion in neurology.

[34]  Application of novel rotation angular model for 3D mouse system based on MEMS accelerometers , 2009 .

[35]  I. McEwen,et al.  Use of power mobility for a young child with spinal muscular atrophy. , 2003, Physical therapy.

[36]  A. Mihailidis,et al.  Assistive technology for cognitive rehabilitation: State of the art , 2004 .

[37]  Armando Barreto,et al.  Integrated electromyogram and eye-gaze tracking cursor control system for computer users with motor disabilities. , 2008, Journal of rehabilitation research and development.

[38]  Huosheng Hu,et al.  Integration of Vision and Inertial Sensors for Home-based Rehabilitation , 2004 .

[39]  Yu-Luen Chen,et al.  Application of tilt sensors in human-computer mouse interface for people with disabilities. , 2001, IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society.

[40]  Thomas S. Huang,et al.  Face as mouse through visual face tracking , 2007, Comput. Vis. Image Underst..

[41]  A. Gesell,et al.  The first five years of life , 1993 .

[42]  M. Yeargin-Allsopp,et al.  Trends in the prevalence of cerebral palsy in a population-based study. , 2002, Pediatrics.

[43]  P. Hancock,et al.  Do Faces Capture the Attention of Individuals with Williams Syndrome or Autism? Evidence from Tracking Eye Movements , 2009, Journal of autism and developmental disorders.

[44]  Peter H. Veltink,et al.  Measuring orientation of human body segments using miniature gyroscopes and accelerometers , 2005, Medical and Biological Engineering and Computing.