Literature DB >> 15468022

Foot contact pattern analysis in hemiplegic stroke patients: an implication for neurologic status determination.

Alice M Wong1, Yu-Cheng Pei, Wei-Hsien Hong, Chia-Yin Chung, Yiu-Chung Lau, Carl P Chen.   

Abstract

OBJECTIVE: To investigate the feasibility of using a foot contact pattern to predict neurologic recovery and the effect of ambulation training in hemiplegic stroke patients.
DESIGN: Case-comparison study.
SETTING: Gait laboratory in a tertiary care center. PARTICIPANTS: Sixty-five functionally ambulant hemiplegic stroke patients, and 30 healthy subjects serving as the control group.
INTERVENTIONS: Gait analyses were performed by using the conventional gait analysis system (6 cameras) and the portable Computer DynoGraphy (CDG) system. Main outcome measures Walking velocity, step length, and cadence were measured from the conventional gait analysis system. Cyclogram, gaitline, and ground reaction force (GRF) patterns were recorded with the CDG system.
RESULTS: Velocity, cadence, and step length increased in higher Brunnstrom stages (P<.01). Negative correlation was noted between the Brunnstrom stages and the foot contact patterns (P<.01). Lower cyclogram, GRF, and gaitline patterns were expected in subjects with higher Brunnstrom stages. There were high prediction probabilities between cyclogram, gaitline, and GRF patterns.
CONCLUSIONS: Foot contact pattern can be a simple and reliable indicator of hemiplegic gait in stroke patients. It is closely related to patient's neurologic status and is correlated with parameters obtained from conventional gait analysis systems. Pathologic presentations are noted in both the affected and unaffected limbs, suggesting that rehabilitation programs should be implemented on both sides.

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Year:  2004        PMID: 15468022     DOI: 10.1016/j.apmr.2003.11.039

Source DB:  PubMed          Journal:  Arch Phys Med Rehabil        ISSN: 0003-9993            Impact factor:   3.966


  9 in total

1.  Lack of maintenance of gait pattern as measured by instrumental methods suggests psychogenic gait.

Authors:  Marcelo Merello; Diego Ballesteros; Malco Rossi; Julieta Arena; Marcos Crespo; Andres Cervio; Carolina Cuello Oderiz; Alberto Rivero; Daniel Cerquetti; Marcelo Risk; Jorge Balej
Journal:  Funct Neurol       Date:  2012 Oct-Dec

2.  Foot Type Biomechanics Part 2: are structure and anthropometrics related to function?

Authors:  Rajshree Mootanah; Jinsup Song; Mark W Lenhoff; Jocelyn F Hafer; Sherry I Backus; David Gagnon; Jonathan T Deland; Howard J Hillstrom
Journal:  Gait Posture       Date:  2012-10-26       Impact factor: 2.840

3.  The effects of ankle-foot orthoses with plantar flexion stop and plantar flexion resistance using rocker-sole shoes on stroke gait: A randomized-controlled trial.

Authors:  Aliyeh Daryabor; Gholamreza Aminian; Mokhtar Arazpour; Mina Baniasad; Sumiko Yamamoto
Journal:  Turk J Phys Med Rehabil       Date:  2021-12-01

4.  Superior gait performance and balance ability in Latin dancers.

Authors:  Yen-Ting Liu; Ang-Chieh Lin; Szu-Fu Chen; Chih-Jen Shih; Tien-Yun Kuo; Fu-Cheng Wang; Pei-Hsin Lee; Adeline Peiling Lee
Journal:  Front Med (Lausanne)       Date:  2022-08-24

5.  Robotic ankle control can provide appropriate assistance throughout the gait cycle in healthy adults.

Authors:  Kei Nakagawa; Keita Higashi; Akari Ikeda; Naoto Kadono; Eiichiro Tanaka; Louis Yuge
Journal:  Front Neurorobot       Date:  2022-09-27       Impact factor: 3.493

6.  Short-Term Effect of Prosthesis Transforming Sensory Modalities on Walking in Stroke Patients with Hemiparesis.

Authors:  Dai Owaki; Yusuke Sekiguchi; Keita Honda; Akio Ishiguro; Shin-Ichi Izumi
Journal:  Neural Plast       Date:  2016-07-31       Impact factor: 3.599

7.  Impact of the difference in the plantar flexor strength of the ankle joint in the affected side among hemiplegic patients on the plantar pressure and walking asymmetry.

Authors:  Young Youl You; Sin Ho Chung; Hyung Jin Lee
Journal:  J Phys Ther Sci       Date:  2016-11-29

8.  Kinetic Gait Changes after Robotic Exoskeleton Training in Adolescents and Young Adults with Acquired Brain Injury.

Authors:  Kiran K Karunakaran; Naphtaly Ehrenberg; JenFu Cheng; Katherine Bentley; Karen J Nolan
Journal:  Appl Bionics Biomech       Date:  2020-10-27       Impact factor: 1.781

9.  Detection and Classification of Stroke Gaits by Deep Neural Networks Employing Inertial Measurement Units.

Authors:  Fu-Cheng Wang; Szu-Fu Chen; Chin-Hsien Lin; Chih-Jen Shih; Ang-Chieh Lin; Wei Yuan; You-Chi Li; Tien-Yun Kuo
Journal:  Sensors (Basel)       Date:  2021-03-07       Impact factor: 3.576

  9 in total

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