Muscle Activity Estimation at Drop Vertical Jump Landing Using Passive Muscle Mechanical Model.
Annu Int Conf IEEE Eng Med Biol Soc
; 2021: 4722-4727, 2021 11.
Article
en En
| MEDLINE
| ID: mdl-34892266
ABSTRACT
Among the various elements that facilitate the movement of the lower limbs, the anterior cruciate ligament (ACL) is prone to injury. An adequate joint control of the lower limb can prevent ACL injury. Balancing activities between the agonist and the antagonist muscles is vital for joint control. However, prior studies on muscle activities were limited since they could not determine passive muscle activities. In this study, we develop a muscle model considering the passive properties to analyze the movement mechanism of the ACL under heavy loads, such as those produced during jump landing. We estimated the muscle activities occurring during a drop vertical jump (DVJ) by applying to the proposed method the physiological constraint that muscle activities are constant during a short time around landing. In addition, the knee joint torque and muscle forces were calculated from the estimated muscle activities, which were thereafter compared with those obtained using the conventional method. The results revealed that this passive muscle model appropriately represented the knee joint torque at DVJ landing by decreasing the passive muscle strain and increasing the isometric maximum muscle force. Moreover, the estimated muscle activities were larger than those obtained using the conventional method, which may be caused by the co-contraction between agonist and antagonist muscles that cannot be represented by the conventional method. This muscle co-contraction estimation algorithm would estimate the muscle load under heavy loads, and applying this knowledge to training would help to prevent ACL injuries.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Ligamento Cruzado Anterior
/
Lesiones del Ligamento Cruzado Anterior
Límite:
Humans
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Año:
2021
Tipo del documento:
Article