A robotic gait training system integrating split-belt treadmill, footprint sensing and synchronous EEG recording for neuro-motor recovery

Yi Hung Liu, Bo Zhang, Quanquan Liu, Wei Chun Hsu, Yu Tsung Hsiao, Jui Yiao Su, Yo Kobayashi, Masakatsu G. Fujie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper presents a robotic gait training system for neuro-motor rehabilitation of hemiplegic stroke survivors. The system is composed of a treadmill consisting of two separated belts, footprint array sensor attached below each belt for gait data acquisition, and an electroencephalography (EEG) device for monitoring brain activities during gait training. The split belt treadmill allow physical therapists to set different treadmill belt velocities to modify physical workload of the patients during walking, thus being able to better improve the symmetry of gait phases between affected and unaffected (sound) legs in comparison with conventional treadmills where there is only one single belt. In contrast to in-shoe pressure sensors, the under-belt footprint sensor array designed in this study not only reduces the preparation complexity of gait training but also collects more gait data for motion analysis. Recorded EEG is segmented synchronously with gait-related events. The processed EEG data can be used for monitoring brain-activities during gait training, providing a neurological approach for motion assessment. One subject with simulated stroke using an ankle-foot orthosis participated in this study. Preliminary results indicate the feasibility of the proposed system to improve gait function and monitor neuro-motor recovery.

Original languageEnglish
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3573-3577
Number of pages5
Volume2015-November
ISBN (Print)9781424492718
DOIs
Publication statusPublished - 2015 Nov 4
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: 2015 Aug 252015 Aug 29

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
CountryItaly
CityMilan
Period15/8/2515/8/29

Fingerprint

Exercise equipment
Robotics
Electroencephalography
Gait
Recovery
Sensor arrays
Brain
Monitoring
Pressure sensors
Foot Orthoses
Patient rehabilitation
Data acquisition
Shoes
Physical Therapists
Acoustic waves
Workload
Ankle
Walking
Survivors
Leg

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

Liu, Y. H., Zhang, B., Liu, Q., Hsu, W. C., Hsiao, Y. T., Su, J. Y., ... Fujie, M. G. (2015). A robotic gait training system integrating split-belt treadmill, footprint sensing and synchronous EEG recording for neuro-motor recovery. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (Vol. 2015-November, pp. 3573-3577). [7319165] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2015.7319165

A robotic gait training system integrating split-belt treadmill, footprint sensing and synchronous EEG recording for neuro-motor recovery. / Liu, Yi Hung; Zhang, Bo; Liu, Quanquan; Hsu, Wei Chun; Hsiao, Yu Tsung; Su, Jui Yiao; Kobayashi, Yo; Fujie, Masakatsu G.

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015. p. 3573-3577 7319165.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Liu, YH, Zhang, B, Liu, Q, Hsu, WC, Hsiao, YT, Su, JY, Kobayashi, Y & Fujie, MG 2015, A robotic gait training system integrating split-belt treadmill, footprint sensing and synchronous EEG recording for neuro-motor recovery. in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. vol. 2015-November, 7319165, Institute of Electrical and Electronics Engineers Inc., pp. 3573-3577, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015, Milan, Italy, 15/8/25. https://doi.org/10.1109/EMBC.2015.7319165
Liu YH, Zhang B, Liu Q, Hsu WC, Hsiao YT, Su JY et al. A robotic gait training system integrating split-belt treadmill, footprint sensing and synchronous EEG recording for neuro-motor recovery. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Vol. 2015-November. Institute of Electrical and Electronics Engineers Inc. 2015. p. 3573-3577. 7319165 https://doi.org/10.1109/EMBC.2015.7319165
Liu, Yi Hung ; Zhang, Bo ; Liu, Quanquan ; Hsu, Wei Chun ; Hsiao, Yu Tsung ; Su, Jui Yiao ; Kobayashi, Yo ; Fujie, Masakatsu G. / A robotic gait training system integrating split-belt treadmill, footprint sensing and synchronous EEG recording for neuro-motor recovery. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. Vol. 2015-November Institute of Electrical and Electronics Engineers Inc., 2015. pp. 3573-3577
@inproceedings{e611cdc2439f4b57ae14fdea6476df70,
title = "A robotic gait training system integrating split-belt treadmill, footprint sensing and synchronous EEG recording for neuro-motor recovery",
abstract = "This paper presents a robotic gait training system for neuro-motor rehabilitation of hemiplegic stroke survivors. The system is composed of a treadmill consisting of two separated belts, footprint array sensor attached below each belt for gait data acquisition, and an electroencephalography (EEG) device for monitoring brain activities during gait training. The split belt treadmill allow physical therapists to set different treadmill belt velocities to modify physical workload of the patients during walking, thus being able to better improve the symmetry of gait phases between affected and unaffected (sound) legs in comparison with conventional treadmills where there is only one single belt. In contrast to in-shoe pressure sensors, the under-belt footprint sensor array designed in this study not only reduces the preparation complexity of gait training but also collects more gait data for motion analysis. Recorded EEG is segmented synchronously with gait-related events. The processed EEG data can be used for monitoring brain-activities during gait training, providing a neurological approach for motion assessment. One subject with simulated stroke using an ankle-foot orthosis participated in this study. Preliminary results indicate the feasibility of the proposed system to improve gait function and monitor neuro-motor recovery.",
author = "Liu, {Yi Hung} and Bo Zhang and Quanquan Liu and Hsu, {Wei Chun} and Hsiao, {Yu Tsung} and Su, {Jui Yiao} and Yo Kobayashi and Fujie, {Masakatsu G.}",
year = "2015",
month = "11",
day = "4",
doi = "10.1109/EMBC.2015.7319165",
language = "English",
isbn = "9781424492718",
volume = "2015-November",
pages = "3573--3577",
booktitle = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - A robotic gait training system integrating split-belt treadmill, footprint sensing and synchronous EEG recording for neuro-motor recovery

AU - Liu, Yi Hung

AU - Zhang, Bo

AU - Liu, Quanquan

AU - Hsu, Wei Chun

AU - Hsiao, Yu Tsung

AU - Su, Jui Yiao

AU - Kobayashi, Yo

AU - Fujie, Masakatsu G.

PY - 2015/11/4

Y1 - 2015/11/4

N2 - This paper presents a robotic gait training system for neuro-motor rehabilitation of hemiplegic stroke survivors. The system is composed of a treadmill consisting of two separated belts, footprint array sensor attached below each belt for gait data acquisition, and an electroencephalography (EEG) device for monitoring brain activities during gait training. The split belt treadmill allow physical therapists to set different treadmill belt velocities to modify physical workload of the patients during walking, thus being able to better improve the symmetry of gait phases between affected and unaffected (sound) legs in comparison with conventional treadmills where there is only one single belt. In contrast to in-shoe pressure sensors, the under-belt footprint sensor array designed in this study not only reduces the preparation complexity of gait training but also collects more gait data for motion analysis. Recorded EEG is segmented synchronously with gait-related events. The processed EEG data can be used for monitoring brain-activities during gait training, providing a neurological approach for motion assessment. One subject with simulated stroke using an ankle-foot orthosis participated in this study. Preliminary results indicate the feasibility of the proposed system to improve gait function and monitor neuro-motor recovery.

AB - This paper presents a robotic gait training system for neuro-motor rehabilitation of hemiplegic stroke survivors. The system is composed of a treadmill consisting of two separated belts, footprint array sensor attached below each belt for gait data acquisition, and an electroencephalography (EEG) device for monitoring brain activities during gait training. The split belt treadmill allow physical therapists to set different treadmill belt velocities to modify physical workload of the patients during walking, thus being able to better improve the symmetry of gait phases between affected and unaffected (sound) legs in comparison with conventional treadmills where there is only one single belt. In contrast to in-shoe pressure sensors, the under-belt footprint sensor array designed in this study not only reduces the preparation complexity of gait training but also collects more gait data for motion analysis. Recorded EEG is segmented synchronously with gait-related events. The processed EEG data can be used for monitoring brain-activities during gait training, providing a neurological approach for motion assessment. One subject with simulated stroke using an ankle-foot orthosis participated in this study. Preliminary results indicate the feasibility of the proposed system to improve gait function and monitor neuro-motor recovery.

UR - http://www.scopus.com/inward/record.url?scp=84953324481&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84953324481&partnerID=8YFLogxK

U2 - 10.1109/EMBC.2015.7319165

DO - 10.1109/EMBC.2015.7319165

M3 - Conference contribution

C2 - 26737065

AN - SCOPUS:84953324481

SN - 9781424492718

VL - 2015-November

SP - 3573

EP - 3577

BT - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

PB - Institute of Electrical and Electronics Engineers Inc.

ER -