Exoskeletons often initiate assistance at unexpected moments, disrupting natural movement and reducing user acceptance. The timing of mechanical assistance is critical for enabling users to perform fast and accurate movements without conscious effort. This study examined how assistance onset timing affects movement accuracy, muscle activation, and subjective evaluation during simple tasks. Twenty healthy young participants performed visually guided elbow flexions (30°–120°) within 1.15 s, lifting a dumbbell equal to 25% of their maximum voluntary contraction with 40% mechanical assistance under seven onset conditions (±300 ms, ±200 ms, ±100 ms, and 0 ms relative to the start cue). The findings indicate that both early and delayed assistance provide unique advantages but are subject to a fundamental trade-off: early assistance improves movement accuracy, whereas delayed assistance better preserves the sense of agency. The most effective cooperation occurred within a ±100 ms window, balancing accuracy and agency—factors essential for improving device acceptance. © 2025 The Authors.

Background: Although several signals have been proposed to control the activation timing of wearable robots, there is no consensus on the suitability of these signals in terms of their ability to promote effective cooperation and smooth device activation. Objective: This study investigated the effects of biomechanical (grip forces and voice commands), bioelectrical (electromyography [EMG]), and external sound (EX) signals on elbow flexion to trigger a wearable robot arm. Methods: Constant torque control was applied to a single-degree-of-freedom (DOF) wearable robot arm, which operated within a range of 30°–130° of elbow flexion. Activation of the wearable robot arm was initiated using a grip force applied to a handle from either hand, the verbal command "go," EMG signals, and an EX cue, while lifting a load equivalent to 15% of maximum voluntary contraction (MVC). Results: Prior to initiating the wearable robot arm, the grip force used to activate the movement using the hand on the side of the assisted arm significantly induced activities of the biceps brachii (BB) (%MVCBB) by approximately 6%–10%MVCBB compared to bioelectrical and biomechanical signals. Nonetheless, after assistive forces were generated, the %MVCBB elicited during the initial phase of elbow flexion was similar to other activation signals. In contrast, EMG-induced activation increased the triceps brachii (TB) activity (%MVCTB) by approximately 7.2%MVCTB during elbow flexion, resulting in the highest joint angular acceleration during the initial phase among all signals. Conclusion: These findings suggest that the grip force applied from the assistive hand was the most effective at triggering the wearable robot arm and may enhance muscle preparation and cooperation with the device more effectively. Copyright © 2025 Teerapapa Luecha et al. Journal of Robotics published by John Wiley & Sons Ltd.

One way to provide assistance in a dynamic lifting task is to pre-emptively move the exoskeleton based on a predicted reference trajectory. However, the level of aggressiveness in the prediction (i.e., how far ahead in time) and the exoskeleton's degree of adherence to the reference trajectory (stiffness) are not yet fully understood. This study investigated the effects of stiffness and pre-emptive offset parameters in an impedance-controlled robotic arm on muscle activation and perceived exertion of the user. Thirteen participants were instructed to lift a load equivalent to 15% of their maximal voluntary contracted force in collaboration with a robotic arm with 40°–135° of elbow flexion in 1.12 s. Three levels of stiffness (lower: 0.1 N m deg−1, medium: 0.2 N m deg−1, and higher: 0.31 N m deg−1) and two levels of pre-emptive offsets (shorter: 0.1 s and longer: 0.4 s) were investigated. We found that (1) during 0–0.5 s (acceleration stage) of elbow flexion, a higher stiffness level and a longer pre-emptive offset decreased muscle activity; (2) during 0.5–1 s (deceleration stage) of elbow flexion, medium and higher stiffness with a shorter pre-emptive offset decreased muscle activity; (3) the perceived exertion and assistance of participants were improved with a higher stiffness and a longer pre-emptive offset, whereas cooperation was rated higher at a shorter pre-emptive offset under higher stiffness. This study reveals that the optimal parameters for stiffness and pre-emptive offsets for predictive impedance controls are different for different stages of elbow flexion. © 2024 The Authors

As technology develops and robots gradually become a part of everyday life, devices that provide physical assistance to humans will become increasingly common. Such robots must often physically interact with the user for extended periods of time and must provide auxiliary forces that complement the user's strength to accomplish certain goals. This requires close cooperation and close coordination between the human user and the assistive robot. The purpose of this study is to understand how two humans cooperate and coordinate in order to gain insight into how to improve human-robot coordination. In this study, a tracking task involving a pair of humans was conducted. The task used 'predictable' and 'unpredictable' sine waves. In the experiment, the roles of the two humans were divided into a 'user' focusing on the experimental task and an 'assistant' focusing on support, and the amount of information given to the 'assistant' was divided into three levels ('Full knowledge', 'Short-term knowledge', and 'No knowledge') to try to understand the coordination and cooperation tendencies of the two humans. The experimental results showed that in some conditions, the rate of increase in error and load decreased as the amount of task knowledge given to the 'assistant' increased, compared to when the task was performed 'solo'. © 2024 The Society of Instrument and Control Engineers - SICE.