Intelligent upper-limb exoskeleton integrated with soft wearable bioelectronics and deep-learning for human intention-driven strength augmentation based on sensory feedback

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 uses cloud-based deep learning to predict human intention for strength augmentation. The embedded soft wearable sensors provide sensory feedback by collecting real-time muscle signals, which are simultaneously computed to determine the user's intended movement. The cloud-based deep-learning predicts four upper-limb joint motions with an average accuracy of 96.2% at a 500-550 millisecond 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 newton of force while generating displacement of 87 millimeter at maximum. Collectively, the intent-driven exoskeleton can reduce human muscle activities by 3.7 times on average compared to the unassisted exoskeleton. INTRODUCTION Many individuals suffer from neuromotor disorders that primarily arise from stroke-induced and age-associated declines in musculoskeletal strength and control. Statistically, strokes affect one out of four adults over the age of 25 in their lifetime, and 12.2 million of the global population experience stroke each year Such a disorder restricts the functional independence of the inflicted population because the reduced motor control and unwanted tremor of the upper limb usually pose considerable difficulties in performing everyday tasks that require the dexterity of the upper limbs. Moreover, neuromotor disorders generate tremendous social expenditure in healthcare. However, the previously reported exoskeletons cannot provide pragmatic solutions because they lack essential functionalities to augment the upper-extremity movements. Another limitation of the previously reported exoskeletons is their structural design. In addition, sensory haptic feedback in human assistive robotics is crucial because it translates human physiological signals into strength augmentation. In this context, electromyography (EMG) signals can offer direct information about upper-extremity movements as EMG records the electrical signals in the presence of muscle activities.