[Abstract] Individualization of exosuit assistance based on measured muscle dynamics during versatile walking

Abstract

Variability in human walking depends on individual physiology, environment, and walking task. Consequently, in the field of wearable robotics, there is a clear need for customizing assistance to the user and task. Here, we developed a muscle-based assistance (MBA) strategy wherein exosuit assistance was derived from direct measurements of individuals’ muscle dynamics during specific tasks. We recorded individuals’ soleus muscle dynamics using ultrasonographic imaging during multiple walking speeds and inclines. From these prerecorded images, we estimated the force produced by the soleus through inefficient concentric contraction and designed the exosuit assistance profile to be proportional to that estimated force. We evaluated this approach with a bilateral ankle exosuit at each measured walking task. Compared with not wearing a device, the MBA ankle exosuit significantly reduced metabolic demand by an average of 15.9, 9.7, and 8.9% for level walking at 1.25, 1.5, and 1.75 meters second⁻¹, respectively, and 7.8% at 1.25 meters second⁻¹ at 5.71° incline while applying lower assistance levels than in existing literature. In an additional study (n = 2), we showed for multiple walking tasks that the MBA profile outperforms other bioinspired strategies and the average profile from a previous optimization study. Last, we show the feasibility of online assistance generation in a mobile version for overground outdoor walking. This muscle-based approach enables relatively rapid (~10 seconds) generation of individualized low-force assistance profiles that provide metabolic benefit. This approach may help support the adoption of wearable robotics in real-world, dynamic locomotor tasks by enabling comfortable, tailored, and adaptive assistance.

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[Abstract] Wearable Movement Sensors for Rehabilitation: A Focused Review of Technological and Clinical Advances – PM&R

Abstract

Recent technologic advancements have enabled the creation of portable, low-cost, and unobtrusive sensors with tremendous potential to alter the clinical practice of rehabilitation. The application of wearable sensors to track movement has emerged as a promising paradigm to enhance the care provided to patients with neurologic or musculoskeletal conditions. These sensors enable quantification of motor behavior across disparate patient populations and emerging research shows their potential for identifying motor biomarkers, differentiating between restitution and compensation motor recovery mechanisms, remote monitoring, telerehabilitation, and robotics. Moreover, the big data recorded across these applications serve as a pathway to personalized and precision medicine. This article presents state-of-the-art and next-generation wearable movement sensors, ranging from inertial measurement units to soft sensors. An overview of clinical applications is presented across a wide spectrum of conditions that have potential to benefit from wearable sensors, including stroke, movement disorders, knee osteoarthritis, and running injuries. Complementary applications enabled by next-generation sensors that will enable point-of-care monitoring of neural activity and muscle dynamics during movement also are discussed.

 

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