Literature DB >> 11204044

Patient-driven control of FES-supported standing up and sitting down: experimental results.

R Riener1, M Ferrarin, E E Pavan, C A Frigo.   

Abstract

A patient-driven control strategy for standing-up and sitting-down was experimentally tested on two paraplegic patients by applying functional electrical stimulation (FES) to the quadriceps muscle. The strategy--also known as "patient-driven motion reinforcement" (PDMR)--was developed by computer simulations reported in a former study. It is based on an inverse dynamic model (IDM) that predicts the stimulation pattern required to maintain the movement as it is initiated by the patient's voluntary effort. For reasons of safety and weight relief, the movement was supported by a seesaw construction. After some practice the patients were able to influence the stimulator output and to control the movement by their voluntary effort. Consequently, no pre-programmed reference trajectory was required. As a positive side effect, upper body effort could be minimized compared to trials without FES. To achieve a satisfactory performance of the PDMR controller a careful parameter identification of the inverse dynamic model was fundamental.

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Year:  2000        PMID: 11204044     DOI: 10.1109/86.895956

Source DB:  PubMed          Journal:  IEEE Trans Rehabil Eng        ISSN: 1063-6528


  9 in total

1.  A method for paraplegic upper-body posture estimation during standing: a pilot study for rehabilitation purposes.

Authors:  Gaël Pages; Nacim Ramdani; Philippe Fraisse; David Guiraud
Journal:  Med Biol Eng Comput       Date:  2009-03-10       Impact factor: 2.602

2.  Using Person-Specific Muscle Fatigue Characteristics to Optimally Allocate Control in a Hybrid Exoskeleton - Preliminary Results.

Authors:  Xuefeng Bao; Vahidreza Molazadeh; Albert Dodson; Brad E Dicianno; Nitin Sharma
Journal:  IEEE Trans Med Robot Bionics       Date:  2020-03-02

3.  Robust Control of the Human Trunk Posture Using Functional Neuromuscular Stimulation: A Simulation Study.

Authors:  Xuefeng Bao; Musa L Audu; Aidan R Friederich; Ronald J Triolo
Journal:  J Biomech Eng       Date:  2022-09-01       Impact factor: 1.899

4.  Experimental parameter identification of a multi-scale musculoskeletal model controlled by electrical stimulation: application to patients with spinal cord injury.

Authors:  Mourad Benoussaad; Philippe Poignet; Mitsuhiro Hayashibe; Christine Azevedo-Coste; Charles Fattal; David Guiraud
Journal:  Med Biol Eng Comput       Date:  2013-02-05       Impact factor: 2.602

5.  Standing-up exerciser based on functional electrical stimulation and body weight relief.

Authors:  M Ferrarin; E E Pavan; R Spadone; R Cardini; C Frigo
Journal:  Med Biol Eng Comput       Date:  2002-05       Impact factor: 2.602

6.  Real-time motion onset recognition for robot-assisted gait rehabilitation.

Authors:  Roushanak Haji Hassani; Mathias Bannwart; Marc Bolliger; Thomas Seel; Reinald Brunner; Georg Rauter
Journal:  J Neuroeng Rehabil       Date:  2022-01-28       Impact factor: 4.262

7.  Volitional EMG Estimation Method during Functional Electrical Stimulation by Dual-Channel Surface EMGs.

Authors:  Joonyoung Jung; Dong-Woo Lee; Yong Ki Son; Bae Sun Kim; Hyung Cheol Shin
Journal:  Sensors (Basel)       Date:  2021-11-30       Impact factor: 3.576

8.  Improving stand-to-sit maneuver for individuals with spinal cord injury.

Authors:  Sarah R Chang; Mark J Nandor; Rudi Kobetic; Kevin M Foglyano; Roger D Quinn; Ronald J Triolo
Journal:  J Neuroeng Rehabil       Date:  2016-03-15       Impact factor: 4.262

9.  Nondestructive Estimation of Muscle Contributions to STS Training with Different Loadings Based on Wearable Sensor System.

Authors:  Kun Liu; Yong Liu; Jianchao Yan; Zhenyuan Sun
Journal:  Sensors (Basel)       Date:  2018-03-25       Impact factor: 3.576

  9 in total

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