Journal
JOURNAL OF NEUROSCIENCE METHODS
Volume 204, Issue 1, Pages 35-43Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jneumeth.2011.10.017
Keywords
Spinal cord injury; Muscle spasm; Clonus; Wavelet analysis; Surface EMG
Categories
Funding
- National Institutes of Health [NS30226]
- The Miami Project to Cure Paralysis
- Department of Biomedical Engineering, University of Miami
Ask authors/readers for more resources
Clonus can disrupt daily activities after spinal cord injury. Here an algorithm was developed to automatically detect contractions during clonus in 24h electromyographic (EMG) records. Filters were created by non-linearly scaling a Mother (Morlet) wavelet to envelope the EMG using different frequency bands. The envelope for the intermediate band followed the EMG best (74.8-193.9 Hz). Threshold and time constraints were used to reduce the envelope peaks to one per contraction. Energy in the EMG was measured 50 ms either side of each envelope (contraction) peak. Energy values at 5% and 95% maximal defined EMG start and end time, respectively. The algorithm was as good as a person at identifying contractions during clonus (p = 0.946, n = 31 spasms, 7 subjects with cervical spinal cord injury), and marking start and end times to determine clonus frequency (intra class correlation coefficient, alpha: 0.949), contraction intensity using root mean square EMG (alpha: 0.997) and EMG duration (alpha: 0.852). On average the algorithm was 574 times faster than manual analysis performed independently by two people (p <= 0.001). This algorithm is an important tool for characterization of clonus in long-term EMG records. (C) 2011 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available