Consumer-grade wearable activity devices such as Fitbits are increasingly being used in research settings to promote physical activity (PA) due to their low-cost and widespread popularity. However, Fitbit-derived measures of activity intensity are consistently reported to be less accurate than intensity estimates obtained from research-grade accelerometers (i.e., ActiGraph). As such, the potential for using a Fitbit to measure PA intensity within research contexts remains limited. This study aims to model ActiGraph-based intensity estimates from the validated Freedson vector magnitude (VM3) algorithm using measures of steps, metabolic equivalents, and intensity levels obtained from Fitbit. Minute-level data collected from 19 subjects, who concurrently wore the ActiGraph GT3X and Fitbit Flex devices for an average of 1.8 weeks, were used to generate the model. After testing several modeling methods, a naïve Bayes classifier was chosen based on the lowest achieved error rate. Overall, the model reduced Fitbit to ActiGraph errors from 19.97% to 16.32%. Moreover, the model reduced misclassification of Fitbit-based estimates of moderate-to-vigorous physical activity (MVPA) by 40%, eliminating a statistically significant difference between MVPA estimates derived from ActiGraph and Fitbit. Study findings support the general utility of the model for measuring MVPA with the Fitbit Flex in place of the more costly ActiGraph GT3X accelerometer for young healthy adults.

As our robotics community advances its understanding toward the optimal design of robotic exoskeletons for human gait training, the question we ask in this paper is how the anterior lunge degree of freedom in the robotic exoskeleton affects human gait training. Answering this question requires both novel robotic design and novel protocols for human gait training to characterize this effect. To the best of the authors' knowledge, this is the first study to characterize the effect of an exoskeleton's degrees of freedom on human gait adaptation. We explored this question using the Active Leg EXoskeleton (ALEX) II. The study presented was performed using ALEX II under the following two configurations: 1) locking the anterior/posterior translation in the exoskeleton, while allowing other degrees-of-freedom (labeled as locked mode) and 2) keeping the anterior/posterior degree of freedom unlocked (labeled as unlocked mode). Healthy subjects walked at self-selected speeds on a treadmill and were trained to walk with a new gait template, scaled down from their normal template. While both groups showed adaptation and retention over a 26-min period following training, the unlocked group showed better performance in terms of adaptation and retention compared with the locked group.

This paper addresses an important question in the field of rehabilitation robotics that can help engineers to develop and optimize future gait training robotic exoskeletons. This question can be posed as follows: Do the exoskeleton's degrees-of-freedom at the pelvis affect human adaptation to new gait templates? More specifically, would additional degrees-of-freedom in the exoskeleton that allow the human trunk to translate and rotate, and the hips to abduct/adduct increase human gait adaptation with an exoskeleton?

This paper outlines how a control moment gyroscope can be used to generate haptic torque feedback while minimizing the effects of a constrained gimbal workspace. We present the design of the iTorqU 2.1 and discuss how it compares to previously developed systems. We then detail the control algorithms we have developed for both transparency and torque output modes. The prescribed transparency controller is typical in design, but the torque output algorithm is novel to this type of haptic device. It makes use of a series of position-p-at-time-t commands, which we call packets. Five packet designs were considered in this research, but we have included only the most important three in this paper. While this research deals with torque feedback, it ultimately presents a method for working with devices that are limited by the need for continuous reset to a home position before subsequent outputs.