Application of Gait Analysis for Hemiplegic Patients using Six-axis Wearable Inertia Sensors

被引:0
|
作者
Fang, Qiang [1 ]
Zhang, Zhe [1 ]
Tu, Yinjun [1 ]
机构
[1] RMIT Univ, Sch Elect Engn, Melbourne, Vic 3000, Australia
来源
IECON 2014 - 40TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY | 2014年
关键词
Gait analysis; Hemiplegic gait; inertia sensors; WALKING;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Gait analysis is considered as an important process which has been wildly adopted in many clinical applications to identify and quantify the lower body functioning impairment of hemiplegic patients. On contrary to the traditional measures which were based on manual observation, numerous researches in recent years have been carried out on utilizing modern assistive devices to analyze gait pattern and produce objective results. In this paper, a novel hemiplegic gait analysis approach based on 6-axis inertial measurement is proposed. The patients' gait data are collected using a set of wearable wireless inertial sensor network and processed to extract gait parameters including step length, hip and knee joint angle. By comparing the sample features between healthy and hemiplegic participants, it is demonstrated that the abnormalities in gait pattern such as irregularity and asymmetry can be found and quantified. This provides clinicians an effective tool to analysis hemiplegic patient's impairment level and recovery progress objectively.
引用
收藏
页码:3993 / 3996
页数:4
相关论文
共 50 条
  • [31] Multimodal Gait Analysis based on Wearable Inertial and Microphone Sensors
    Wang, Cheng
    Wang, Xiangdong
    Long, Zhou
    Yuan, Jing
    Qian, Yueling
    Li, Jintao
    2017 IEEE SMARTWORLD, UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTED, SCALABLE COMPUTING & COMMUNICATIONS, CLOUD & BIG DATA COMPUTING, INTERNET OF PEOPLE AND SMART CITY INNOVATION (SMARTWORLD/SCALCOM/UIC/ATC/CBDCOM/IOP/SCI), 2017,
  • [32] Gait posture estimation using wearable acceleration and gyro sensors
    Takeda, Ryo
    Tadano, Shigeru
    Natorigawa, Akiko
    Todoh, Masahiro
    Yoshinari, Satoshi
    JOURNAL OF BIOMECHANICS, 2009, 42 (15) : 2486 - 2494
  • [33] An Automatic Gait Feature Extraction Method for Identifying Gait Asymmetry Using Wearable Sensors
    Anwary, Arif Reza
    Yu, Hongnian
    Vassallo, Michael
    SENSORS, 2018, 18 (02):
  • [34] Analysis of Gait Characteristics Using Hip-Knee Cyclograms in Patients with Hemiplegic Stroke
    Lee, Ho Seok
    Ryu, Hokyoung
    Lee, Shi-Uk
    Cho, Jae-sung
    You, Sungmin
    Park, Jae Hyeon
    Jang, Seong-Ho
    SENSORS, 2021, 21 (22)
  • [35] Three Dimensional Gait Analysis Using Wearable Acceleration and Gyro Sensors Based on Quaternion Calculations
    Tadano, Shigeru
    Takeda, Ryo
    Miyagawa, Hiroaki
    SENSORS, 2013, 13 (07): : 9321 - 9343
  • [36] Gait analysis as a reliable tool for rehabilitation of chronic hemiplegic patients
    Tenore, N
    Fortugno, F
    Viola, F
    Galli, M
    Giaquinto, S
    CLINICAL AND EXPERIMENTAL HYPERTENSION, 2006, 28 (3-4) : 349 - 355
  • [37] Biometric Database for Human Gait Recognition using Wearable Sensors and a Smartphone
    Al Kork, Samer K.
    Gowthami, Itta
    Savatier, Xavier
    Beyrouthy, Taha
    Korbane, Joe Akl
    Roshdi, Sherif
    2017 2ND INTERNATIONAL CONFERENCE ON BIO-ENGINEERING FOR SMART TECHNOLOGIES (BIOSMART), 2017,
  • [38] Real-time gait event detection using wearable sensors
    Hanlon, Michael
    Anderson, Ross
    GAIT & POSTURE, 2009, 30 (04) : 523 - 527
  • [39] Estimation of Step Length and Gait Asymmetry Using Wearable Inertial Sensors
    Wang, Lei
    Sun, Yun
    Li, Qingguo
    Liu, Tao
    IEEE SENSORS JOURNAL, 2018, 18 (09) : 3844 - 3851
  • [40] Optimal Foot Location for Placing Wearable IMU Sensors and Automatic Feature Extraction for Gait Analysis
    Anwary, Arif Reza
    Yu, Hongnian
    Vassallo, Michael
    IEEE SENSORS JOURNAL, 2018, 18 (06) : 2555 - 2567