Multi-body sensor data fusion to evaluate the hippotherapy for motor ability improvement in children with cerebral palsy
Hippotherapy is a new rehabilitation therapy for children with cerebral palsy (CP). Although it has been proved to be effective in clinical research, a quantitative evaluation of such results is still lacking in previous studies. In this research, one method for evaluating the effectiveness of hippo...
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| Published in | Information fusion Vol. 70; pp. 115 - 128 |
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| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
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Elsevier B.V
01.06.2021
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| Online Access | Get full text |
| ISSN | 1566-2535 1872-6305 |
| DOI | 10.1016/j.inffus.2021.01.002 |
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| Abstract | Hippotherapy is a new rehabilitation therapy for children with cerebral palsy (CP). Although it has been proved to be effective in clinical research, a quantitative evaluation of such results is still lacking in previous studies. In this research, one method for evaluating the effectiveness of hippotherapy based on body sensor network (BSN) is proposed. The method adopts distributed magnetic, angular rate, and gravity (MARG) sensors to evaluate the gross motor function of CP children by multi-sensor data fusion algorithm, the comparison results with the golden standard optical capture system demonstrate the robustness of sensor fusion algorithm. Moreover, via tracking one-year’s hippotherapy projects, a pilot study was conducted for measuring and evaluating the motor coordination function and gait parameters of CP children. Finally, the rehabilitation of gross motor function for the chosen subjects under different treatment periods was evaluated through kinematic analysis. The results of our method show that some children’s symptoms, such as limb stiffness, poor joint range of motion, scissors gait, knee flexion gait, have been relieved. Thus, it provides an empirical basis for hippotherapy in the rehabilitation of motor function corresponding to CP children.
•Sensor fusion to utilize the gross motor function of CP children.•An evaluation method for hippotherapy based on BSN.•A method of human motion capture by traversing the kinematic chains.•Lower limb gait analysis to evaluate the rehabilitation of CP children.•Evaluation of upper limb balance ability based on trunk posture. |
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| AbstractList | Hippotherapy is a new rehabilitation therapy for children with cerebral palsy (CP). Although it has been proved to be effective in clinical research, a quantitative evaluation of such results is still lacking in previous studies. In this research, one method for evaluating the effectiveness of hippotherapy based on body sensor network (BSN) is proposed. The method adopts distributed magnetic, angular rate, and gravity (MARG) sensors to evaluate the gross motor function of CP children by multi-sensor data fusion algorithm, the comparison results with the golden standard optical capture system demonstrate the robustness of sensor fusion algorithm. Moreover, via tracking one-year’s hippotherapy projects, a pilot study was conducted for measuring and evaluating the motor coordination function and gait parameters of CP children. Finally, the rehabilitation of gross motor function for the chosen subjects under different treatment periods was evaluated through kinematic analysis. The results of our method show that some children’s symptoms, such as limb stiffness, poor joint range of motion, scissors gait, knee flexion gait, have been relieved. Thus, it provides an empirical basis for hippotherapy in the rehabilitation of motor function corresponding to CP children.
•Sensor fusion to utilize the gross motor function of CP children.•An evaluation method for hippotherapy based on BSN.•A method of human motion capture by traversing the kinematic chains.•Lower limb gait analysis to evaluate the rehabilitation of CP children.•Evaluation of upper limb balance ability based on trunk posture. |
| Author | Li, Jie Wang, Zhelong Wang, Jiaxin Shi, Xin Zhao, Hongyu Fortino, Giancarlo Qiu, Sen Liang, Bing |
| Author_xml | – sequence: 1 givenname: Jie orcidid: 0000-0002-2977-8559 surname: Li fullname: Li, Jie email: jerry1165530693@163.com organization: The Laboratory of Intelligent System, Dalian University of Technology, Dalian, 116024, China – sequence: 2 givenname: Zhelong orcidid: 0000-0003-4959-3372 surname: Wang fullname: Wang, Zhelong email: wangzl@dlut.edu.cn organization: The Laboratory of Intelligent System, Dalian University of Technology, Dalian, 116024, China – sequence: 3 givenname: Sen surname: Qiu fullname: Qiu, Sen organization: The Laboratory of Intelligent System, Dalian University of Technology, Dalian, 116024, China – sequence: 4 givenname: Hongyu surname: Zhao fullname: Zhao, Hongyu organization: The Laboratory of Intelligent System, Dalian University of Technology, Dalian, 116024, China – sequence: 5 givenname: Jiaxin surname: Wang fullname: Wang, Jiaxin organization: The Laboratory of Intelligent System, Dalian University of Technology, Dalian, 116024, China – sequence: 6 givenname: Xin surname: Shi fullname: Shi, Xin organization: The Laboratory of Intelligent System, Dalian University of Technology, Dalian, 116024, China – sequence: 7 givenname: Bing surname: Liang fullname: Liang, Bing organization: Suzhou Industrial Park Boai School & Clinic, Suzhou, 215000, China – sequence: 8 givenname: Giancarlo surname: Fortino fullname: Fortino, Giancarlo organization: University of Calabria, Rende, 87036, Italy |
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| Cites_doi | 10.1109/TNSRE.2017.2786269 10.1109/TIM.2018.2826198 10.12733/jics20101833 10.1109/TMECH.2018.2811730 10.1109/TIM.2012.2196397 10.1109/JSEN.2016.2569160 10.1109/TIE.2017.2701783 10.1016/j.inffus.2017.04.006 10.1080/09593980902776662 10.1007/978-3-030-34833-5_25 10.1109/TSMCC.2012.2215852 10.1109/TAC.2008.923738 10.1089/107555303771952163 10.1111/j.1469-8749.2008.03089.x 10.1016/S0021-9290(01)00222-6 10.1038/sj.sc.3101492 10.1109/TSMCA.2012.2189876 10.1111/j.1469-8749.2008.02045.x 10.1016/j.inffus.2014.03.005 10.1016/j.inffus.2016.09.005 10.1017/S0012162201002675 10.1016/j.inffus.2019.06.001 10.1109/TSMC.2016.2521823 10.1589/jpts.27.273 10.3349/ymj.2014.55.6.1736 10.1109/ICORR.2011.5975346 10.1109/TNSRE.2012.2206055 10.1109/TII.2018.2843169 10.3390/s140406891 |
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| Keywords | Sensor fusion Cerebral palsy Rehabilitation medicine Body sensor network Hippotherapy |
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| Snippet | Hippotherapy is a new rehabilitation therapy for children with cerebral palsy (CP). Although it has been proved to be effective in clinical research, a... |
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| SubjectTerms | Body sensor network Cerebral palsy Hippotherapy Rehabilitation medicine Sensor fusion |
| Title | Multi-body sensor data fusion to evaluate the hippotherapy for motor ability improvement in children with cerebral palsy |
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