# Kinematic Analysis of Dynamic Coactivation During Arm Swing at the Shoulder and Elbow Joints
## 1 Introduction  
Recent advancements in exoskeletal technology have focused on amplifying human physical capabilities, including strength, endurance, and mobility [1]. These wearable systems have been increasingly adopted in fields such as physical rehabilitation, elderly support, and industrial operations that require activities like walking, running, repetitive motions, and material handling [2]. Exoskeletons, as integrated mechatronic devices, are specifically designed to mirror human anatomy--either in parallel or in series--with the goal of assisting in load bearing and transmitting force to the ground or other parts of the body [3]. This body-machine interface plays a crucial role in minimizing physical strain by lowering joint resistance, reducing muscular workload, and improving energy efficiency during tasks [4]. The exoskeletal devices continue to face several design and engineering challenges [5]. Effective locomotion requires natural interlimb coordination, which can be disrupted by mechanical constraints introduced by the device [6; 7]. Misalignment between the exoskeleton's joints and the user's anatomical joints may induce resistance during movement, resulting in discomfort and reduced mobility [1]. Furthermore, the added mass of the device can elevate metabolic demands and restrict range of motion, potentially contributing to premature fatigue during ambulation [8]. Traditionally, wearable robotic systems have focused primarily on sensor-based prediction of user intent to guide robotic actuation, often overlooking the neuromechanical synergy required for coordinated limb movement during arm swing [9; 10; 11]. Consequently, there remains a gap in the literature regarding the integration of human motor control principles, neural feedback mechanisms, and ergonomic design in exoskeleton development. To overcome the current limitations in the development of human-machine interfaces, particularly in assistive and wearable robotics, it is imperative to gain a comprehensive understanding of the biomechanical characteristics and neuromuscular control of natural arm swing during gait. From an ergonomics and human factors engineering perspective, effective mechanical integration requires that joint impedance and force controllability be precisely tuned to accommodate the dynamic properties of the upper limbs. [PERSON] et al. [12] provided critical evidence indicating that arm swing is not merely a passive byproduct of locomotion, but serves an active functional role in maintaining postural stability and restoring dynamic balance following perturbations. This suggests that any ergonomic device interfacing with the upper extremities must support such intrinsic stabilizing functions. Moreover, [PERSON] and [PERSON] [13], along with [PERSON] et al. [14], demonstrated through musculoskeletal modeling that arm swing encompasses both passive mechanical oscillations and active neuromuscular control, with the contribution of active components increasing significantly at higher walking speeds. This finding underscores the need for adaptive control strategies in robotic systems or exoskeletal devices to accommodate varying task demands and user states. Further insights have been gleaned from clinical gait analyses focusing on upper-limb kinematics, particularly with respect to spatiotemporal parameters and coordination patterns across different walking speeds [15; 16; 17; 18; 19]. However, the study by [PERSON] and [PERSON] [18], while informative in quantifying joint range of motion in upper-body segments such as the shoulders, trunk, and pelvis, did not capture essential dynamic variables such as angular velocity and angular acceleration. These parameters are critical from an ergonomic standpoint, as they influence momentary joint loading, energy expenditure, and the timing requirements for motor assistance or resistance in wearable technologies.