Setup for the Quantitative Assessment of Motion and Muscle Activity During a Virtual Modified Box and Block Test.

The ability to move allows us to interact with the world. When this ability is impaired, it can significantly reduce one's quality of life and independence and may lead to complications. The importance of remote patient evaluation and rehabilitation has recently grown due to limited access to in-person services. For example, the COVID-19 pandemic unexpectedly resulted in strict regulations, reducing access to non-emergent healthcare services. Additionally, remote care offers an opportunity to address healthcare disparities in rural, underserved, and low-income areas where access to services remains limited. Improving accessibility through remote care options would limit the number of hospital or specialist visits and render routine care more affordable. Finally, the use of readily available commercial consumer electronics for at-home care can enhance patient outcomes due to improved quantitative observation of symptoms, treatment efficacy, and therapy dosage. While remote care is a promising means to address these issues, there is a crucial need to quantitatively characterize motor impairment for such applications. The following protocol seeks to address this knowledge gap to enable clinicians and researchers to obtain high-resolution data on complex movement and underlying muscle activity. The ultimate goal is to develop a protocol for remote administration of functional clinical tests. Here, participants were instructed to perform a medically-inspired Box and Block task (BBT), which is frequently used to assess hand function. This task requires subjects to transport standardized cubes between two compartments separated by a barrier. We implemented a modified BBT in virtual reality to demonstrate the potential of developing remote assessment protocols. Muscle activation was captured for each subject using surface electromyography. This protocol allowed for the acquisition of high-quality data to better characterize movement impairment in a detailed and quantitative manner. Ultimately, these data have the potential to be used to develop protocols for virtual rehabilitation and remote patient monitoring.

Surface Electromyography Provides Neuromuscular Insights for Skill Acquisition in Microgravity.

The human motor system has evolved to perform efficient motor control in Earth's gravity. Altered gravity environments, such as microgravity and hypergravity, pose unique challenges for performing fine motor tasks with object manipulation. Altered gravity has been shown to reduce the speed and accuracy of complex manual tasks. This study aims to leverage electromyography (EMG) and virtual reality (VR) technologies to provide insights into the neuromuscular mechanism of object weight compensation. Seven healthy subjects were recruited to perform arm and hand movements, including a customized Box and Block Test with three different block weights, 0 (VR), 0.02, and 0.1 kg. EMG was recorded from 15 muscles of arm and hand while manipulating objects instrumented with force sensors to collect contact forces. Muscle co-contraction extracted from EMGs of antagonistic muscles was used as a measure of joint stiffness for each task. Results show that the co-contraction levels increased in the task with the heavy object and decreased in the VR task. This relationship suggests that the internal expectations of the object weight and the proprioceptive and haptic feedback from the contact with the object are driving the co-contraction of antagonistic muscles.