# Towards Online Estimation of Human Joint Muscular Torque with a Lower Limb Exoskeleton Robot
## 1 Introduction  
Exoskeleton robots demonstrate promise in their application in assisting or enhancing human physical capacity [1; 2; 3; 4]. Estimating the intention of the user is fundamental for collaborative control of such wearable robots [5; 6; 7; 8; 9]. 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. In fact, the joint muscular torque (JMT) reflects the human effort of each joint [2]. It not only indicates the direction in which the human tends to move the limbs, but also 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]. However, estimating JMT is challenging. More recent research has focused on improving the portability, stability, and convenience of solutions for JMT estimation. Some pure mechanical walking assist exoskeletons have been developed for simplicity and practicability. Elastic elements and cams have been adopted in mechanicalstructures to mimic human joint torque in some motion patterns, such as walking and running. Through the use of this torque, the exoskeleton is able to help the human body to perform some specific motion. [PERSON] et al. designed a mechanical system to help users with a walking disability [14]. [PERSON] et al. proposed an unpowered ankle exoskeleton to help with the reduction of the user's metabolic rate during walking [3]. An orthotic knee-extension made use of the gravity balancing technique to compensate for the user's body weight [15]. These simplified solutions are good for reducing the weight and cost, and increasing the reliability, but they are always not adaptable to complex and changeable motion patterns, because the JMT of the human body changes during different motions, and the mismatch of the torque curve can lead to motion interference. A general solution is required to support the voluntary motion of a human body. There are two general methods for JMT estimation: (1) the electromyography (sEMG) based biological method, and (2) the inverse dynamics approach (IDA) based physics solution. sEMG is an intuitive biological signal for detecting muscle activity. [PERSON] et al. estimated joint moments and muscle forces using sEMG signals and verified them with inverse dynamics [16]. HAL is a typical active power-assist exoskeleton that uses sEMG [2]. Electrodes are pasted on the human body to determine the sEMG of each muscle group, and muscle activities are estimated to derive JMT based on the HAL generated assistive torques. Many other exoskeletons also use sEMG [11; 12; 13; 17]. However, some limitations of sEMG are still under research. For example, in [18], it was concluded that sEMG is susceptible to the variation of electrode-skin conductivity, positioning, muscle fatigue and interactions between nearby muscles, so calibration is always required which increases the inconvenience of this method's use. Complex wiring on the human body also influences its wearing convenience. IDA has been successfully applied in clinical gait analysis. In Ref. [19], IDA was adopted to calculate human JMT during sit-to-stand movement. In Ref. [20], a motion capture system and several force plates were used to sense motion information and foot contact force (FCF). The entire clinical gait analysis system is universal but lacks portability. Hence, many wearable solutions have been proposed in recent years. Goniometers, inertial measurement units (IMUs), and air bladder based ground reaction force (GRF) measurement insoles are commonly used for human kinematic and kinetic measurements [21; 22]. The problem is that it is difficult to precisely locate the wearable sensors and maintain stability on the soft tissue of the human body.