Literature DB >> 17477031

Ground reaction force patterns in stroke patients with various degrees of motor recovery determined by plantar dynamic analysis.

Chung-Yao Chen1, Paul Wei-Hsien Hong, Chia-Ling Chen, Shih Wei Chou, Ching-Yi Wu, Pao-Tsai Cheng, Fuk-Tan Tang, Hsieh-Ching Chen.   

Abstract

BACKGROUND: To study ground reaction force (GRF) patterns in stroke patients with various degrees of motor recovery, using plantar dynamic analysis.
METHODS: Forty-three people with hemiplegic stroke and 20 healthy subjects were enrolled in the study. Motor impairment (motor recovery and muscle tone) and plantar dynamic data (GRF patterns, peak pressure, and walking speeds) were analyzed. GRF patterns were categorized into four patterns based on the force magnitude (spatial features) through time (temporal features) of the vertical GRF. Then stroke patients were classified into good (patterns III and IV) and poor groups (patterns I and II).
RESULTS: Patients with hemiplegic stroke showed characteristic GRF patterns which could be categorized from bimodal (pattern IV) to pathological shapes (I-III). The peak pressures on the paretic side in the metatarsal and toe areas were reduced in stroke patients compared with those in healthy subjects. Walking speeds were higher in the good group than in the poor group (p < 0.05). The peak pressures on both sides in the metatarsal and midfoot areas were lower in the poor group than in the good group (p < 0.05). GRF patterns were highly correlated with walking speeds (r = 0.92, p < 0.01). GRF patterns and walking speeds were positively correlated with motor recovery of knee movement (r > 0.4, p < 0.01), but not with hip and ankle movement or muscle tone in the lower limb.
CONCLUSIONS: GRF patterns, correlated with walking speeds, indicate underlying motor control of hemiplegic or hemiparetic gait. Knee motor control may be the most important factor in determining walking performance. Plantar dynamic analysis could allow clinicians an alternative assessment in detecting gait changes and planning therapeutic strategies in stroke patients.

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Year:  2007        PMID: 17477031

Source DB:  PubMed          Journal:  Chang Gung Med J        ISSN: 2072-0939


  10 in total

1.  Plantar Pressure Distribution During Robotic-Assisted Gait in Post-stroke Hemiplegic Patients.

Authors:  Jin Kyu Yang; Na El Ahn; Dae Hyun Kim; Deog Young Kim
Journal:  Ann Rehabil Med       Date:  2014-04-29

2.  Effect of body mass index on hemiparetic gait.

Authors:  Lynne R Sheffler; Stephanie Nogan Bailey; Douglas Gunzler; John Chae
Journal:  PM R       Date:  2014-04-05       Impact factor: 2.298

3.  Infarct hemisphere and noninfarcted brain volumes affect locomotor performance following stroke.

Authors:  I-Hsuan Chen; Vera Novak; Brad Manor
Journal:  Neurology       Date:  2014-01-31       Impact factor: 9.910

4.  Analysis of Vertical Ground Reaction Force Variables Using Foot Scans in Hemiplegic Patients.

Authors:  Hyun Dong Kim; Jong-Gil Kim; Dong-Min Jeon; Min-Ha Shin; Nami Han; Mi-Ja Eom; Geun-Yeol Jo
Journal:  Ann Rehabil Med       Date:  2015-06-30

Review 5.  Post-Stroke Walking Behaviors Consistent with Altered Ground Reaction Force Direction Control Advise New Approaches to Research and Therapy.

Authors:  Wendy L Boehm; Kreg G Gruben
Journal:  Transl Stroke Res       Date:  2015-12-07       Impact factor: 6.829

6.  The generation of centripetal force when walking in a circle: insight from the distribution of ground reaction forces recorded by plantar insoles.

Authors:  Anna Maria Turcato; Marco Godi; Andrea Giordano; Marco Schieppati; Antonio Nardone
Journal:  J Neuroeng Rehabil       Date:  2015-01-09       Impact factor: 4.262

7.  Effect of handrail use while performing treadmill walking on the gait of stroke patients.

Authors:  Kyung Woo Kang; Na Kyung Lee; Sung Min Son; Jung Won Kwon; Kyoung Kim
Journal:  J Phys Ther Sci       Date:  2015-03-31

8.  A Vibrotactile and Plantar Force Measurement-Based Biofeedback System: Paving the Way towards Wearable Balance-Improving Devices.

Authors:  Christina Zong-Hao Ma; Anson Hong-Ping Wan; Duo Wai-Chi Wong; Yong-Ping Zheng; Winson Chiu-Chun Lee
Journal:  Sensors (Basel)       Date:  2015-12-15       Impact factor: 3.576

9.  Developing a Low-Cost Force Treadmill via Dynamic Modeling.

Authors:  Chih-Yuan Hong; Lan-Yuen Guo; Rong Song; Mark L Nagurka; Jia-Li Sung; Chen-Wen Yen
Journal:  J Healthc Eng       Date:  2017-06-04       Impact factor: 2.682

10.  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

  10 in total

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