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Gait Cycle Validation and Segmentation Using Inertial Sensors
- Source :
- IEEE Trans Biomed Eng
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- In this paper, we develop an algorithm to automatically validate and segment a gait cycle in real time into three gait events, namely midstance, toe-off, and heel-strike, using inertial sensors. We first use the physical models of sensor data obtained from a foot-mounted inertial system to differentiate stationary and moving segments of the sensor data. Next, we develop an optimization routine called sparsity-assisted wavelet denoising (SAWD), which simultaneously combines linear time invariant filters, orthogonal multiresolution representations such as wavelets, and sparsity-based methods, to generate a sparse template of the moving segments of the gyroscope measurements in the sagittal plane for valid gait cycles. Thereafter, to validate any moving segment as a gait cycle, we compute the root-mean-square error between the generated sparse template and the sparse representation of the moving segment of the gyroscope data in the sagittal plane obtained using SAWD. Finally, we find the local minima for the stationary and moving segments of a valid gait cycle to detect the gait events. We compare our proposed method with existing methods, for a fixed threshold, using real data obtained from three groups, namely controls, participants with Parkinson disease, and geriatric participants. Our proposed method demonstrates an average F1 score of 87.78% across all groups for a fixed sampling rate, and an average F1 score of 92.44% across all Parkinson disease participants for a variable sampling rate.
- Subjects :
- Inertial frame of reference
Computer science
0206 medical engineering
Biomedical Engineering
02 engineering and technology
Accelerometer
Article
law.invention
Computer Science::Robotics
Gait (human)
Inertial measurement unit
law
medicine
Humans
Computer vision
Segmentation
Gait
Aged
Foot
business.industry
Parkinson Disease
Gyroscope
020601 biomedical engineering
Sagittal plane
Biomechanical Phenomena
medicine.anatomical_structure
Artificial intelligence
business
Algorithms
Subjects
Details
- ISSN :
- 15582531 and 00189294
- Volume :
- 67
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Biomedical Engineering
- Accession number :
- edsair.doi.dedup.....6550c651208176c058fc7023dd1cd184