Motion pattern tracking for home based stroke rehabilitation exercise using MESA SR4500

Nur Quraisyia Aqilah Mohd Rusli, Mohd Asyraf Zulkifley, Aini Hussain, Mohd. Marzuki Mustafa

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

1 Citation (Scopus)

Abstract

An automated physiotherapy exercise monitoring system requires good postural structure and pose information. Most of human movements for daily activity pivoted on lower limb that requires intensive care, especially for the stroke patient. However, there are a lot of uncertainties in human stance, movement and strength that need to be observed for good rehabilitation training. Hence, home-based rehabilitation monitoring system for lower limb therapy is crucial to encourage and facilitate the patient to perform the exercise effectively. This paper presents a novel real time rehabilitation system by tracking the lower limb information based on 3D information by using MESA SR4500, which produces Red, Green, Blue and Depth (RGBD) information. In this paper, only Depth and grayscale image have been utilized to track and evaluate the patient movement. A marker that located at the centroid of the moving body region has been estimated by using Kalman Filter, which acts as the main component. The pattern for a correctly performed exercise is different compared to the wrongly done exercise. The motion pattern has been evaluated to test the effectiveness of the exercise from the obtained graph. In conclusion, the results show that depth information is more important compared to grayscale information as it affects the tracking performance the most.

Original languageEnglish
Title of host publication2015 IEEE 2nd International Conference on InformationScience and Security, ICISS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781467386111
DOIs
Publication statusPublished - 4 Jan 2016
Event2nd IEEE International Conference on Information Science and Security, ICISS 2015 - Seoul, Korea, Republic of
Duration: 14 Dec 201516 Dec 2015

Other

Other2nd IEEE International Conference on Information Science and Security, ICISS 2015
CountryKorea, Republic of
CitySeoul
Period14/12/1516/12/15

Fingerprint

Patient rehabilitation
Physical therapy
Monitoring
Kalman filters
Uncertainty

Keywords

  • Kalman Filter
  • Lower Limb Exercise
  • MESA SR4500
  • Stroke Rehabilitation.

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications
  • Information Systems

Cite this

Rusli, N. Q. A. M., Zulkifley, M. A., Hussain, A., & Mustafa, M. M. (2016). Motion pattern tracking for home based stroke rehabilitation exercise using MESA SR4500. In 2015 IEEE 2nd International Conference on InformationScience and Security, ICISS 2015 [7371021] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICISSEC.2015.7371021

Motion pattern tracking for home based stroke rehabilitation exercise using MESA SR4500. / Rusli, Nur Quraisyia Aqilah Mohd; Zulkifley, Mohd Asyraf; Hussain, Aini; Mustafa, Mohd. Marzuki.

2015 IEEE 2nd International Conference on InformationScience and Security, ICISS 2015. Institute of Electrical and Electronics Engineers Inc., 2016. 7371021.

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

Rusli, NQAM, Zulkifley, MA, Hussain, A & Mustafa, MM 2016, Motion pattern tracking for home based stroke rehabilitation exercise using MESA SR4500. in 2015 IEEE 2nd International Conference on InformationScience and Security, ICISS 2015., 7371021, Institute of Electrical and Electronics Engineers Inc., 2nd IEEE International Conference on Information Science and Security, ICISS 2015, Seoul, Korea, Republic of, 14/12/15. https://doi.org/10.1109/ICISSEC.2015.7371021
Rusli NQAM, Zulkifley MA, Hussain A, Mustafa MM. Motion pattern tracking for home based stroke rehabilitation exercise using MESA SR4500. In 2015 IEEE 2nd International Conference on InformationScience and Security, ICISS 2015. Institute of Electrical and Electronics Engineers Inc. 2016. 7371021 https://doi.org/10.1109/ICISSEC.2015.7371021
Rusli, Nur Quraisyia Aqilah Mohd ; Zulkifley, Mohd Asyraf ; Hussain, Aini ; Mustafa, Mohd. Marzuki. / Motion pattern tracking for home based stroke rehabilitation exercise using MESA SR4500. 2015 IEEE 2nd International Conference on InformationScience and Security, ICISS 2015. Institute of Electrical and Electronics Engineers Inc., 2016.
@inproceedings{f69f140c196b4c148cd05c370ea43f27,
title = "Motion pattern tracking for home based stroke rehabilitation exercise using MESA SR4500",
abstract = "An automated physiotherapy exercise monitoring system requires good postural structure and pose information. Most of human movements for daily activity pivoted on lower limb that requires intensive care, especially for the stroke patient. However, there are a lot of uncertainties in human stance, movement and strength that need to be observed for good rehabilitation training. Hence, home-based rehabilitation monitoring system for lower limb therapy is crucial to encourage and facilitate the patient to perform the exercise effectively. This paper presents a novel real time rehabilitation system by tracking the lower limb information based on 3D information by using MESA SR4500, which produces Red, Green, Blue and Depth (RGBD) information. In this paper, only Depth and grayscale image have been utilized to track and evaluate the patient movement. A marker that located at the centroid of the moving body region has been estimated by using Kalman Filter, which acts as the main component. The pattern for a correctly performed exercise is different compared to the wrongly done exercise. The motion pattern has been evaluated to test the effectiveness of the exercise from the obtained graph. In conclusion, the results show that depth information is more important compared to grayscale information as it affects the tracking performance the most.",
keywords = "Kalman Filter, Lower Limb Exercise, MESA SR4500, Stroke Rehabilitation.",
author = "Rusli, {Nur Quraisyia Aqilah Mohd} and Zulkifley, {Mohd Asyraf} and Aini Hussain and Mustafa, {Mohd. Marzuki}",
year = "2016",
month = "1",
day = "4",
doi = "10.1109/ICISSEC.2015.7371021",
language = "English",
isbn = "9781467386111",
booktitle = "2015 IEEE 2nd International Conference on InformationScience and Security, ICISS 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Motion pattern tracking for home based stroke rehabilitation exercise using MESA SR4500

AU - Rusli, Nur Quraisyia Aqilah Mohd

AU - Zulkifley, Mohd Asyraf

AU - Hussain, Aini

AU - Mustafa, Mohd. Marzuki

PY - 2016/1/4

Y1 - 2016/1/4

N2 - An automated physiotherapy exercise monitoring system requires good postural structure and pose information. Most of human movements for daily activity pivoted on lower limb that requires intensive care, especially for the stroke patient. However, there are a lot of uncertainties in human stance, movement and strength that need to be observed for good rehabilitation training. Hence, home-based rehabilitation monitoring system for lower limb therapy is crucial to encourage and facilitate the patient to perform the exercise effectively. This paper presents a novel real time rehabilitation system by tracking the lower limb information based on 3D information by using MESA SR4500, which produces Red, Green, Blue and Depth (RGBD) information. In this paper, only Depth and grayscale image have been utilized to track and evaluate the patient movement. A marker that located at the centroid of the moving body region has been estimated by using Kalman Filter, which acts as the main component. The pattern for a correctly performed exercise is different compared to the wrongly done exercise. The motion pattern has been evaluated to test the effectiveness of the exercise from the obtained graph. In conclusion, the results show that depth information is more important compared to grayscale information as it affects the tracking performance the most.

AB - An automated physiotherapy exercise monitoring system requires good postural structure and pose information. Most of human movements for daily activity pivoted on lower limb that requires intensive care, especially for the stroke patient. However, there are a lot of uncertainties in human stance, movement and strength that need to be observed for good rehabilitation training. Hence, home-based rehabilitation monitoring system for lower limb therapy is crucial to encourage and facilitate the patient to perform the exercise effectively. This paper presents a novel real time rehabilitation system by tracking the lower limb information based on 3D information by using MESA SR4500, which produces Red, Green, Blue and Depth (RGBD) information. In this paper, only Depth and grayscale image have been utilized to track and evaluate the patient movement. A marker that located at the centroid of the moving body region has been estimated by using Kalman Filter, which acts as the main component. The pattern for a correctly performed exercise is different compared to the wrongly done exercise. The motion pattern has been evaluated to test the effectiveness of the exercise from the obtained graph. In conclusion, the results show that depth information is more important compared to grayscale information as it affects the tracking performance the most.

KW - Kalman Filter

KW - Lower Limb Exercise

KW - MESA SR4500

KW - Stroke Rehabilitation.

UR - http://www.scopus.com/inward/record.url?scp=84964687615&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84964687615&partnerID=8YFLogxK

U2 - 10.1109/ICISSEC.2015.7371021

DO - 10.1109/ICISSEC.2015.7371021

M3 - Conference contribution

SN - 9781467386111

BT - 2015 IEEE 2nd International Conference on InformationScience and Security, ICISS 2015

PB - Institute of Electrical and Electronics Engineers Inc.

ER -