Literature DB >> 26923356

Best facilitated cortical activation during different stepping, treadmill, and robot-assisted walking training paradigms and speeds: A functional near-infrared spectroscopy neuroimaging study.

Ha Yeon Kim1,2, Sung Phil Yang3, Gyu Lee Park1, Eun Joo Kim3, Joshua Sung Hyun You2.   

Abstract

BACKGROUND: Robot-assisted and treadmill-gait training are promising neurorehabilitation techniques, with advantages over conventional gait training, but the neural substrates underpinning locomotor control remain unknown particularly during different gait training modes and speeds.
OBJECTIVE: The present optical imaging study compared cortical activities during conventional stepping walking (SW), treadmill walking (TW), and robot-assisted walking (RW) at different speeds.
METHODS: Fourteen healthy subjects (6 women, mean age 30.06, years ± 4.53) completed three walking training modes (SW, TW, and RW) at various speeds (self-selected, 1.5, 2.0, 2.5, and 3.0  km/h). A functional near-infrared spectroscopy (fNIRS) system determined cerebral hemodynamic changes associated with cortical locomotor network areas in the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), prefrontal cortex (PFC), and sensory association cortex (SAC).
RESULTS: There was increased cortical activation in the SMC, PMC, and SMA during different walking training modes. More global locomotor network activation was observed during RW than TW or SW. As walking speed increased, multiple locomotor network activations were observed, and increased activation power spectrum.
CONCLUSIONS: This is the first empirical evidence highlighting the neural substrates mediating dynamic locomotion for different gait training modes and speeds. Fast, robot-assisted gait training best facilitated cortical activation associated with locomotor control.

Entities:  

Keywords:  Cortical activation; functional near-infrared spectroscopy; gait training modes and speeds; neurorehabilitation

Mesh:

Year:  2016        PMID: 26923356     DOI: 10.3233/NRE-161307

Source DB:  PubMed          Journal:  NeuroRehabilitation        ISSN: 1053-8135            Impact factor:   2.138


  12 in total

1.  Detecting self-paced walking intention based on fNIRS technology for the development of BCI.

Authors:  Chunguang Li; Jiacheng Xu; Yufei Zhu; Shaolong Kuang; Wei Qu; Lining Sun
Journal:  Med Biol Eng Comput       Date:  2020-02-21       Impact factor: 2.602

Review 2.  Neuroimaging of Human Balance Control: A Systematic Review.

Authors:  Ellen Wittenberg; Jessica Thompson; Chang S Nam; Jason R Franz
Journal:  Front Hum Neurosci       Date:  2017-04-10       Impact factor: 3.169

3.  Neuroplastic effects of end-effector robotic gait training for hemiparetic stroke: a randomised controlled trial.

Authors:  Hayeon Kim; Gyulee Park; Joon-Ho Shin; Joshua H You
Journal:  Sci Rep       Date:  2020-07-27       Impact factor: 4.379

4.  Pilot Study on Gait Classification Using fNIRS Signals.

Authors:  Hedian Jin; Chunguang Li; Jiacheng Xu
Journal:  Comput Intell Neurosci       Date:  2018-10-17

5.  Validating attentive locomotion training using interactive treadmill: an fNIRS study.

Authors:  Seunghue Oh; Minsu Song; Jonghyun Kim
Journal:  J Neuroeng Rehabil       Date:  2018-12-20       Impact factor: 4.262

6.  Five-day rehabilitation of patients undergoing total knee arthroplasty using an end-effector gait robot as a neuromodulation blending tool for deafferentation, weight offloading and stereotyped movement: Interim analysis.

Authors:  Kyo-In Koo; Chang Ho Hwang
Journal:  PLoS One       Date:  2020-12-16       Impact factor: 3.240

Review 7.  The Relationship between Neurocircuitry Dysfunctions and Attention Deficit Hyperactivity Disorder: A Review.

Authors:  Yuncheng Zhu; Daoliang Yang; Weidong Ji; Tianming Huang; Lianxue Xue; Xixi Jiang; Liangliang Chen; Fang Wang
Journal:  Biomed Res Int       Date:  2016-09-01       Impact factor: 3.411

Review 8.  Functional near-infrared spectroscopy in movement science: a systematic review on cortical activity in postural and walking tasks.

Authors:  Fabian Herold; Patrick Wiegel; Felix Scholkmann; Angelina Thiers; Dennis Hamacher; Lutz Schega
Journal:  Neurophotonics       Date:  2017-08-01       Impact factor: 3.593

9.  Immediate muscle strengthening by an end-effector type gait robot with reduced real-time use of leg muscles: A case series and review of literature.

Authors:  Chang Ho Hwang
Journal:  World J Clin Cases       Date:  2019-10-06       Impact factor: 1.337

10.  Increased gait variability during robot-assisted walking is accompanied by increased sensorimotor brain activity in healthy people.

Authors:  Alisa Berger; Fabian Horst; Fabian Steinberg; Fabian Thomas; Claudia Müller-Eising; Wolfgang I Schöllhorn; Michael Doppelmayr
Journal:  J Neuroeng Rehabil       Date:  2019-12-27       Impact factor: 4.262

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