Literature DB >> 14686597

Command control for functional electrical stimulation hand grasp systems using miniature accelerometers and gyroscopes.

K Y Tong1, A F T Mak, W Y Ip.   

Abstract

Recent commercially available miniature sensors have the potential to improve the functions of functional electrical stimulation (FES) systems in terms of control, reliability and robustness. A new control approach using a miniature gyroscope and an accelerometer was studied. These sensors were used to detect the linear acceleration and angular velocity of residual voluntary movements on upper limbs and were small and easy to put on. Five healthy subjects and three cervical spinal cord injured subjects were recruited to evaluate this controller. Sensors were placed on four locations: the shoulder, upper arm, wrist and hand. A quick forward-and-backward movement was employed to produce a distinctive waveform that was different from general movements. A detection algorithm was developed to generate a command signal by identifying this distinctive waveform through the detection of peaks and valleys in the sensor's signals. This command signal was used to control different FES hand grasp patterns. With a specificity of 0.9, the sensors had a success rate of 85-100% on healthy subjects and 82-97% on spinal cord injured subjects. In terms of sensor placement, the gyroscope was better as a control source than the accelerometer for wrist and hand positions, but the reverse was true for the shoulder.

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Year:  2003        PMID: 14686597     DOI: 10.1007/BF02349979

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  18 in total

1.  Sensor systems for lower limb functional electrical stimulation (FES) control.

Authors:  R Williamson; B J Andrews
Journal:  Med Eng Phys       Date:  2000-06       Impact factor: 2.242

2.  Quantitative evaluation of two methods of control of bilateral stimulated hand grasps in persons with tetraplegia.

Authors:  T R Scott; J M Heasman; V A Vare; R Y Flynn; C R Gschwind; J W Middleton; S B Rutkowski
Journal:  IEEE Trans Rehabil Eng       Date:  2000-06

3.  Implanted stimulators for restoration of function in spinal cord injury.

Authors:  N Bhadra; K L Kilgore; P H Peckham
Journal:  Med Eng Phys       Date:  2001-01       Impact factor: 2.242

4.  Functional electrotherapy: stimulation of the peroneal nerve synchronized with the swing phase of the gait of hemiplegic patients.

Authors:  W T LIBERSON; H J HOLMQUEST; D SCOT; M DOW
Journal:  Arch Phys Med Rehabil       Date:  1961-02       Impact factor: 3.966

5.  Evaluation of shoulder movement as a command control source.

Authors:  M W Johnson; P H Peckham
Journal:  IEEE Trans Biomed Eng       Date:  1990-09       Impact factor: 4.538

Review 6.  Challenges to clinical deployment of upper limb neuroprostheses.

Authors:  R Triolo; R Nathan; Y Handa; M Keith; R R Betz; S Carroll; C Kantor
Journal:  J Rehabil Res Dev       Date:  1996-04

Review 7.  Tri-state myoelectric control of bilateral upper extremity neuroprostheses for tetraplegic individuals.

Authors:  T R Scott; P H Peckham; K L Kilgore
Journal:  IEEE Trans Rehabil Eng       Date:  1996-12

8.  The bionic glove: an electrical stimulator garment that provides controlled grasp and hand opening in quadriplegia.

Authors:  A Prochazka; M Gauthier; M Wieler; Z Kenwell
Journal:  Arch Phys Med Rehabil       Date:  1997-06       Impact factor: 3.966

9.  A practical gait analysis system using gyroscopes.

Authors:  K Tong; M H Granat
Journal:  Med Eng Phys       Date:  1999-03       Impact factor: 2.242

10.  Development of computer-based environment for simulating the voluntary upper-limb movements of persons with disability.

Authors:  K Y Tong; A F Mak
Journal:  Med Biol Eng Comput       Date:  2001-07       Impact factor: 3.079

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  2 in total

1.  Computer-based test-bed for clinical assessment of hand/wrist feed-forward neuroprosthetic controllers using artificial neural networks.

Authors:  J L Luján; P E Crago
Journal:  Med Biol Eng Comput       Date:  2004-11       Impact factor: 2.602

2.  Support vector machine for classification of walking conditions using miniature kinematic sensors.

Authors:  Hong-Yin Lau; Kai-Yu Tong; Hailong Zhu
Journal:  Med Biol Eng Comput       Date:  2008-03-18       Impact factor: 2.602

  2 in total

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