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Abstract The age and stroke-associated decline in musculoskeletal strength degrades the ability to perform daily human tasks using the upper extremities. Here, we introduce an intelligent upper-limb exoskeleton system that utilizes deep learning to predict human intention for strength augmentation. The embedded soft wearable sensors provide sensory feedback by collecting real-time muscle activities, which are simultaneously computed to determine the user’s intended movement. Cloud-based deep learning predicts four upper-limb joint motions with an average accuracy of 96.2% at a 500–550 ms response rate, suggesting that the exoskeleton operates just by human intention. In addition, an array of soft pneumatics assists the intended movements by providing 897 newtons of force while generating a displacement of 87 mm at maximum. The intent-driven exoskeleton can reduce human muscle activities by 3.7 times on average compared to the unassisted exoskeleton.

Abstract Activities and physical effort have been commonly estimated using a metabolic rate through indirect calorimetry to capture breath information. The physical effort represents the work hardness used to optimize wearable robotic systems. Thus, personalization and rapid optimization of the effort are critical. Although respirometry is the gold standard for estimating metabolic costs, this method requires a heavy, bulky, and rigid system, limiting the system’s field deployability. Here, this paper reports a soft, flexible bioelectronic system that integrates a wearable ankle-foot exoskeleton, used to estimate metabolic costs and physical effort, demonstrating the potential for real-time wearable robot adjustments based on biofeedback. Data from a set of activities, including walking, running, and squatting with the biopatch and exoskeleton, determines the relationship between metabolic costs and heart rate variability root mean square of successive differences (HRV-RMSSD) (R = −0.758). Collectively, the exoskeleton-integrated wearable system shows potential to develop a field-deployable exoskeleton platform that can measure wireless real-time physiological signals.