Abstract
Exoskeleton robots demonstrate promise in their application in assisting or enhancing human physical capacity. Joint muscular torques (JMT) reflect human effort, which can be applied on an exoskeleton robot to realize an active power-assist function. The estimation of human JMT with a wearable exoskeleton is challenging. This paper proposed a novel human lower limb JMT estimation method based on the inverse dynamics of the human body. The method has two main parts: the inverse dynamic approach (IDA) and the sensing system. We solve the inverse dynamics of each human leg separately to shorten the serial chain and reduce computational complexity, and divide the JMT into the mass-induced one and the foot-contact-force (FCF)-induced one to avoid switching the dynamic equation due to different contact states of the feet. An exoskeleton embedded sensing system is designed to obtain the user’s motion data and FCF required by the IDA by mapping motion information from the exoskeleton to the human body. Compared with the popular electromyography (EMG) and wearable sensor based solutions, electrodes, sensors, and complex wiring on the human body are eliminated to improve wearing convenience. A comparison experiment shows that this method produces close output to a motion analysis system with different subjects in different motion.
Highlights
Exoskeleton robots demonstrate promise in their application in assisting or enhancing human physical capacity [1,2,3,4]
The motion information of the human body was acquired by the embedded sensing system.The hip and knee joint muscular torque (JMT) were calculated by the controller of the exoskeleton and sent to a PC in real-time for recording and graphing
This paper proposed a novel human lower limb JMT estimation solution based on an inverse dynamic approach (IDA)
Summary
Exoskeleton robots demonstrate promise in their application in assisting or enhancing human physical capacity [1,2,3,4]. For an intention-based, active, power-assist exoskeleton, such as the Hybrid Assistive Limb (HAL) [10] from Tsukuba University and the Soft Exosuit [4] form Harvard. University, a estimation of human effort is required by the controller to actively generate and exert assistive force/torque onto the human body. The joint muscular torque (JMT) reflects the human effort of each joint [2]. It indicates the direction in which the human tends to move the limbs, and reflects the intensity of the effort. Previous research has confirmed the effectiveness of using JMT for active power-assist control with various kinds of exoskeleton robots [11,12,13].
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