R2Play development: Fostering user-driven technology that supports return-to-play decision-making following pediatric concussion.

Objective: To design a multi-domain return-to-play assessment system (R2Play) for youth athletes with concussion. Methods: The R2Play system was developed using an overarching user-centered approach, the Design Thinking Framework, and research activities included: 1) structured brainstorming within our research team, 2) interviews with clinician and youth sports coaches, 3) building a testable prototype, and 4) interface testing through cognitive walkthroughs with clinician partners. Results: Clinician and coach participants provided feedback on the R2Play concept, which was integrated into the design process and provided future directions for research. Examples of feedback-driven design choices included reducing assessment time, increasing ecological validity by adding in background noise, and developing youth-friendly graphical results screens. Following refinement based on stakeholder feedback, the R2Play system was outlined in detail and a testable prototype was developed. It is made up of two parts: a clinician tablet, and a series of tablet "buttons" that display numbers and letters. Youth athletes run between the buttons to connect a "trail" in ascending alphanumeric order, 1-A-2-B, etc. Their performance across a series of levels of increasing difficulty is logged on the clinician tablet. Initial testing with five clinicians showed the system's interface to have excellent usability with a score of 81% (SD = 8.02) on the System Usability Scale. Conclusion: Through this research, a prototype of the R2Play system was innovated and evaluated by clinician and coach stakeholders. Initial usability was excellent and directions for future iterations were highlighted. Outcomes suggest the potential benefits of using technologies to assist in complex clinical assessment, as well as utilizing a user-centered approach to design.

Customized Access Technology for Children using Head Movement Recognition.

Children with cerebral palsy and complex communication needs face limitations in their access technology (AT) usage. Speech recognition software and conventional ATs (e.g., mechanical switches) can be insufficient for those with speech impairment and limited control of voluntary motion. Automatic recognition of head movements represents a promising pathway. Previous studies have shown the robustness of head pose estimation algorithms on adult participants, but further research is needed to use these methods with children. An algorithm for head movement recognition was implemented and evaluated on videos recorded in a naturalistic environment when children were playing a videogame. A face-tracking algorithm was used to detect the main facial landmarks. Head poses were then estimated using the Pose from Orthography and Scaling with Iterations (POSIT) algorithm and three head movements were classified through Hidden Markov Models (HMMs). Preliminary classification results obtained from the analysis of videos of five typically developing children showed an accuracy of up to 95.6% in predicting head movements.

An MEG-Compatible Electromagnetic-Tracking System for Monitoring Orofacial Kinematics.

We describe a novel motion-tracking system, called MASK (magnetoarticulography for the assessment of speech kinematics) designed to track detailed orofacial movements during magnetoencephalographic (MEG) measures of human brain activity. A three-dimensional electromagnetic-tracking method was employed using lightweight coils energized with high-frequency sinusoidal currents, creating magnetic dipoles that can be continuously localized by the MEG sensors. In addition to being compatible with commercial MEG devices, this system has advantages over optical or video methods in that it can record nonline-of-sight movements (e.g., tongue movements) and advantages over surface electromyographic recordings, which are prone to movement-related artifacts and signal crosstalk. Static and dynamic tracking accuracy was evaluated using calibration devices with fixed intercoil distances. MEG data were collected in two healthy adult volunteers to test feasibility of tracking movements during tongue and facial movement, and during overt speech. The MASK system was shown to have sufficient static and dynamic accuracy to track orofacial movements within the MEG helmet. We successfully acquired spatially precise kinematic information time-locked to brain activity with high temporal resolution. We demonstrated successful tracking of oromotor and speech movements together with brain activity using the MASK system. This novel technology will provide an innovative tool in support of research and clinical applications for individuals with speech and other oromotor disorders.

Evaluation of an ambient noise insensitive hum-based powered wheelchair controller.

PURPOSE: A recently-developed assistive technology nicknamed "the Hummer" was investigated as a potential powered wheelchair controller for individuals with severe and multiple disabilities. System performance in a noisy environment was compared to that obtained with a commercial automatic speech recognition (ASR) system. METHOD: A bi-hum driving protocol was developed to allow the Hummer to serve as a powered wheelchair controller. Participants performed several virtual wheelchair driving tasks of increasing difficulty using the two systems. Custom-written software recorded task execution time, number of commands issued and wall collisions, speed, and trajectory. RESULTS: The bi-hum protocol was shown to be non-intuitive and required user training. Overall, the Hummer achieved lower performance relative to ASR. Once users became accustomed to the protocol, the difference in performance between the two systems became insignificant, particularly for the higher-difficulty task. CONCLUSIONS: The Hummer provides a promising new alternative for powered wheelchair control in everyday environments for individuals with severe and multiple disabilities who are able to hum, particularly for those with severe dysarthria which precludes ASR usage. A more intuitive driving protocol is still needed to reduce user frustration and mitigate user-generated errors; recommendations on how this can be achieved are given herein. [Box: see text].