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Clinical Trial
Journal Article
Using the discrete wavelet transform in assessing the effectiveness of rehabilitation in patients after ACL reconstruction.
PURPOSE: The purpose of the current study was to assess the effectiveness of rehabilitation in patients after anterior cruciate ligament reconstruction (ACLR) using a wavelet analysis of the torque-time curve patterns of the extensors of the affected knee. The analysis aimed at the quantitative evaluation of irregularities in these torque-time patterns.
METHODS: The study involved a group of 22 men who had had ACL reconstruction. The torque-time characteristics were recorded 3, 6 and 12 months after the surgery by an isokinetic dynamometer. They were then examined using the orthogonal Daubechies 4 (Db 4) and biorthogonal Bior 3.1 wavelets.
RESULTS: A statistical analysis of the results revealed significant differences in values of the high-frequency energy stored in the details of the signal from the dynamometer between the first and last measurements, both for the Db 4 ( p ≤ 0.023) and Bior 3.1 ( p ≤ 0.01) wavelets. These differences were found in 73% of patients whose curve patterns were analysed using the Db 4 wavelet and in 82% of patients in the case of the Bior 3.1 wavelet.
CONCLUSIONS: The wavelet transform proved to be an effective research tool in the qualitative evaluation of irregularities occurring in the curve patterns of the torque generated by the extensors of the ACL reconstructed knee. The findings of the study suggest that time-frequency analyses of these characteristics can be of practical importance, as they help assess the state of the patient's knee joint and his progress in rehabilitation after ACLR.
METHODS: The study involved a group of 22 men who had had ACL reconstruction. The torque-time characteristics were recorded 3, 6 and 12 months after the surgery by an isokinetic dynamometer. They were then examined using the orthogonal Daubechies 4 (Db 4) and biorthogonal Bior 3.1 wavelets.
RESULTS: A statistical analysis of the results revealed significant differences in values of the high-frequency energy stored in the details of the signal from the dynamometer between the first and last measurements, both for the Db 4 ( p ≤ 0.023) and Bior 3.1 ( p ≤ 0.01) wavelets. These differences were found in 73% of patients whose curve patterns were analysed using the Db 4 wavelet and in 82% of patients in the case of the Bior 3.1 wavelet.
CONCLUSIONS: The wavelet transform proved to be an effective research tool in the qualitative evaluation of irregularities occurring in the curve patterns of the torque generated by the extensors of the ACL reconstructed knee. The findings of the study suggest that time-frequency analyses of these characteristics can be of practical importance, as they help assess the state of the patient's knee joint and his progress in rehabilitation after ACLR.
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