Literature DB >> 12173736

Evaluation of force-sensing resistors for gait event detection to trigger electrical stimulation to improve walking in the child with cerebral palsy.

Brian T Smith1, Daniel J Coiro, Richard Finson, Randal R Betz, James McCarthy.   

Abstract

Force-sensing resistors (FSRs) were used to detect the transitions between five main phases of gait for the control of electrical stimulation (ES) while walking with seven children with spastic diplegia, cerebral palsy. The FSR positions within each child's insoles were customized based on plantar pressure profiles determined using a pressure-sensitive membrane array (Tekscan Inc., Boston, MA). The FSRs were placed in the insoles so that pressure transitions coincided with an ipsilateral or contralateral gait event. The transitions between the following gait phases were determined: loading response, mid- and terminal stance, and pre- and initial swing. Following several months of walking on a regular basis with FSR-triggered intramuscular ES to the hip and knee extensors, hip abductors, and ankle dorsi and plantar flexors, the accuracy and reliability of the FSRs to detect gait phase transitions were evaluated. Accuracy was evaluated with four of the subjects by synchronizing the output of the FSR detection scheme with a VICON (Oxford Metrics, U.K.) motion analysis system, which was used as the gait event reference. While mean differences between each FSR-detected gait event and that of the standard (VICON) ranged from +35 ms (indicating that the FSR detection scheme recognized the event before it actually happened) to -55 ms (indicating that the FSR scheme recognized the event after it occurred), the difference data was widely distributed, which appeared to be due in part to both intrasubject (step-to-step) and intersubject variability. Terminal stance exhibited the largest mean difference and standard deviation, while initial swing exhibited the smallest deviation and preswing the smallest mean difference. To determine step-to-step reliability, all seven children walked on a level walkway for at least 50 steps. Of 642 steps, there were no detection errors in 94.5% of the steps. Of the steps that contained a detection error, 80% were due to the failure of the FSR signal to reach the programmed threshold level during the transition to loading response. Recovery from an error always occurred one to three steps later.

Entities:  

Mesh:

Year:  2002        PMID: 12173736     DOI: 10.1109/TNSRE.2002.1021583

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  12 in total

1.  Gait Cycle Validation and Segmentation Using Inertial Sensors.

Authors:  G V Prateek; Pietro Mazzoni; Gammon M Earhart; Arye Nehorai
Journal:  IEEE Trans Biomed Eng       Date:  2019-11-25       Impact factor: 4.538

2.  Bipedal gait model for precise gait recognition and optimal triggering in foot drop stimulator: a proof of concept.

Authors:  Muhammad Faraz Shaikh; Zoran Salcic; Kevin I-Kai Wang; Aiguo Patrick Hu
Journal:  Med Biol Eng Comput       Date:  2018-03-10       Impact factor: 2.602

3.  Gait event detection on level ground and incline walking using a rate gyroscope.

Authors:  Paola Catalfamo; Salim Ghoussayni; David Ewins
Journal:  Sensors (Basel)       Date:  2010-06-04       Impact factor: 3.576

4.  Gait detection in children with and without hemiplegia using single-axis wearable gyroscopes.

Authors:  Nicole Abaid; Paolo Cappa; Eduardo Palermo; Maurizio Petrarca; Maurizio Porfiri
Journal:  PLoS One       Date:  2013-09-04       Impact factor: 3.240

Review 5.  Gait Partitioning Methods: A Systematic Review.

Authors:  Juri Taborri; Eduardo Palermo; Stefano Rossi; Paolo Cappa
Journal:  Sensors (Basel)       Date:  2016-01-06       Impact factor: 3.576

6.  Adjustable Method for Real-Time Gait Pattern Detection Based on Ground Reaction Forces Using Force Sensitive Resistors and Statistical Analysis of Constant False Alarm Rate.

Authors:  Fangli Yu; Jianbin Zheng; Lie Yu; Rui Zhang; Hailin He; Zhenbo Zhu; Yuanpeng Zhang
Journal:  Sensors (Basel)       Date:  2018-11-03       Impact factor: 3.576

7.  Wearable step counting using a force myography-based ankle strap.

Authors:  Kelvin Ht Chu; Xianta Jiang; Carlo Menon
Journal:  J Rehabil Assist Technol Eng       Date:  2017-12-06

8.  MoRe-T2 (mobility research trajectory tracker): validation and application.

Authors:  Chinemelu Ezeh; Catherine Holloway; Tom Carlson
Journal:  J Rehabil Assist Technol Eng       Date:  2016-11-22

9.  An Evaluation of Three Kinematic Methods for Gait Event Detection Compared to the Kinetic-Based 'Gold Standard'.

Authors:  Nicole Zahradka; Khushboo Verma; Ahad Behboodi; Barry Bodt; Henry Wright; Samuel C K Lee
Journal:  Sensors (Basel)       Date:  2020-09-15       Impact factor: 3.576

10.  Self-Tuning Threshold Method for Real-Time Gait Phase Detection Based on Ground Contact Forces Using FSRs.

Authors:  Jing Tang; Jianbin Zheng; Yang Wang; Lie Yu; Enqi Zhan; Qiuzhi Song
Journal:  Sensors (Basel)       Date:  2018-02-06       Impact factor: 3.576

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