Muscles Cooperation Analysis Using Akaike Information Criteria for Anterior Cruciate Ligament Injury Prevention
| Autor: | Yuri Mizutani, Hinako Suzuki, Emiko Uchiyama, Kohei Kawaguchi, Shuji Taketomi, Yosuke Ikegami, Yoshihiko Nakamura, Tokuhide Doi |
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| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Computer science Anterior cruciate ligament Anterior Cruciate Ligament Injuries medicine.disease ACL injury Vertical jump Physical medicine and rehabilitation medicine.anatomical_structure Similarity (network science) Risk Factors Injury prevention medicine Humans Akaike information criterion Data patterns Muscle Skeletal Muscle force |
| Zdroj: | EMBC |
| ISSN: | 2694-0604 |
| Popis: | In this paper, we propose the analysis method for finding out the similarity of the muscle force patterns to mine the risk factor of the anterior cruciate ligament (ACL) injury. Akaike information criteria (AIC) under the assumption of the auto-regression model is adapted to analyze the similarities of muscle force patterns in time-series. The difference of AIC values between 2 muscles is considered to be the distance between 2 muscle force patterns and the dexterity of the maneuver is expected to be discussed. We measured drop vertical jump (DVJ) and use the data around the contact timing of whom hadn’t had ACL injury experiments. The results showed that we could successfully calculate AIC distance according to the similarity of the time-series data pattern and it can be useful to discuss one’s dexterity of controlling body maneuvers soon after contact timing of DVJ motion. |
| Databáze: | OpenAIRE |
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