An algorithm to reduce human-robot interface compliance errors in posture estimation in wearable robots

Guided Exploration Leads to Faster Familiarization with a Wearable Robot: First Results of an Innovative Protocol

Wearable robots show promise in addressing physical and functional deficits in individuals with mobility impairments. However, the process of learning to use these devices can take a long time. In this study, we propose a novel protocol to support the familiarization process with a wearable robot (the Myosuit) and achieve faster walking speeds. The protocol involves applying an anterior pulling force while participants perform a series of 10-meter Walking Tests (10mWT) with or without the Myosuit under various experimental conditions. We hypothesized that guiding the exploration of novel walking patterns can help the users learn to exploit the Myosuit's assistance faster by leading to larger step lengths and ultimately higher walking speeds. In this paper, we present the preliminary results of the protocol with seven participants with lower-limb mobility impairments. Participants who were assisted by the Myosuit showed a continuous increase in walking speed over the course of the pulling part of the experiment with a maximum increase of 41.3% (10.4%) when compared to the baseline 10mWT. Following the removal of the pulling force, these participants continued to show an increased walking speed while being supported by the Myosuit. This higher walking speed was primarily due to a significant increase in step length of 24% (16.6%) and cadence of 11% (8.9%). The results of this study may help the development of familiarization techniques for wearable robots.

Use of Lower Limb Exoskeletons as an Assessment Tool for Human Motor Performance: A Systematic Review

Exoskeletons are a promising tool to support individuals with a decreased level of motor performance. Due to their built-in sensors, exoskeletons offer the possibility of continuously recording and assessing user data, for example, related to motor performance. The aim of this article is to provide an overview of studies that rely on using exoskeletons to measure motor performance. Therefore, we conducted a systematic literature review, following the PRISMA Statement guidelines. A total of 49 studies using lower limb exoskeletons for the assessment of human motor performance were included. Of these, 19 studies were validity studies, and six were reliability studies. We found 33 different exoskeletons; seven can be considered stationary, and 26 were mobile exoskeletons. The majority of the studies measured parameters such as range of motion, muscle strength, gait parameters, spasticity, and proprioception. We conclude that exoskeletons can be used to measure a wide range of motor performance parameters through built-in sensors, and seem to be more objective and specific than manual test procedures. However, since these parameters are usually estimated from built-in sensor data, the quality and specificity of an exoskeleton to assess certain motor performance parameters must be examined before an exoskeleton can be used, for example, in a research or clinical setting.