Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System
This paper presents the development of a wearable accelerometry system for real-time gait cycle parameter recognition. Using a tri-axial accelerometer, the wearable motion detector is a single waist-mounted device to measure trunk accelerations during walking. Several gait cycle parameters, includin...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2011-07-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/11/8/7314/ |
| _version_ | 1798033985235845120 |
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| author | Jun-Ming Lu Che-Chang Yang Kao-Shang Shih Yeh-Liang Hsu |
| author_facet | Jun-Ming Lu Che-Chang Yang Kao-Shang Shih Yeh-Liang Hsu |
| author_sort | Jun-Ming Lu |
| collection | DOAJ |
| description | This paper presents the development of a wearable accelerometry system for real-time gait cycle parameter recognition. Using a tri-axial accelerometer, the wearable motion detector is a single waist-mounted device to measure trunk accelerations during walking. Several gait cycle parameters, including cadence, step regularity, stride regularity and step symmetry can be estimated in real-time by using autocorrelation procedure. For validation purposes, five Parkinson’s disease (PD) patients and five young healthy adults were recruited in an experiment. The gait cycle parameters among the two subject groups of different mobility can be quantified and distinguished by the system. Practical considerations and limitations for implementing the autocorrelation procedure in such a real-time system are also discussed. This study can be extended to the future attempts in real-time detection of disabling gaits, such as festinating or freezing of gait in PD patients. Ambulatory rehabilitation, gait assessment and personal telecare for people with gait disorders are also possible applications. |
| first_indexed | 2024-04-11T20:37:58Z |
| format | Article |
| id | doaj.art-8c081294bc044f9cbc71580a76e5221a |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T20:37:58Z |
| publishDate | 2011-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8c081294bc044f9cbc71580a76e5221a2022-12-22T04:04:18ZengMDPI AGSensors1424-82202011-07-011187314732610.3390/s110807314Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry SystemJun-Ming LuChe-Chang YangKao-Shang ShihYeh-Liang HsuThis paper presents the development of a wearable accelerometry system for real-time gait cycle parameter recognition. Using a tri-axial accelerometer, the wearable motion detector is a single waist-mounted device to measure trunk accelerations during walking. Several gait cycle parameters, including cadence, step regularity, stride regularity and step symmetry can be estimated in real-time by using autocorrelation procedure. For validation purposes, five Parkinson’s disease (PD) patients and five young healthy adults were recruited in an experiment. The gait cycle parameters among the two subject groups of different mobility can be quantified and distinguished by the system. Practical considerations and limitations for implementing the autocorrelation procedure in such a real-time system are also discussed. This study can be extended to the future attempts in real-time detection of disabling gaits, such as festinating or freezing of gait in PD patients. Ambulatory rehabilitation, gait assessment and personal telecare for people with gait disorders are also possible applications.http://www.mdpi.com/1424-8220/11/8/7314/accelerometryaccelerometerParkinson’s diseasegaitmobility |
| spellingShingle | Jun-Ming Lu Che-Chang Yang Kao-Shang Shih Yeh-Liang Hsu Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System Sensors accelerometry accelerometer Parkinson’s disease gait mobility |
| title | Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System |
| title_full | Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System |
| title_fullStr | Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System |
| title_full_unstemmed | Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System |
| title_short | Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System |
| title_sort | real time gait cycle parameter recognition using a wearable accelerometry system |
| topic | accelerometry accelerometer Parkinson’s disease gait mobility |
| url | http://www.mdpi.com/1424-8220/11/8/7314/ |
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