Assessment of wearable robotics performance in patients with neurological conditions

While wearable robotics is expanding within clinical settings, particularly for neurological rehabilitation, there is still a lack of consensus on how to effectively assess the performance of these devices. This review focuses on the most common metrics, whose selection and design are crucial for optimizing treatment outcomes and potentially improve the standard care.

The literature reveals that while wearable robots are equipped with various embedded sensors, most studies still rely on traditional, nontechnological methods for assessment. Recent studies have shown that, although quantitative data from embedded sensors are available (e.g., kinematics), these are underutilized in favor of qualitative assessments. A trend toward integrating automatic assessments from the devices themselves is emerging, with a few notable studies pioneering this approach.

Our analysis suggests a critical need for developing standardized metrics that leverage the data from embedded sensors in wearable robots. This shift could enhance the accuracy of patient assessments and the effectiveness of rehabilitation strategies, ultimately leading to better patient outcomes in neurological rehabilitation.