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Purpose: The goal of this study was to assess the listening behavior and social engagement of cochlear implant (CI) users and normal-hearing (NH) adults in daily life and relate these actions to objective hearing outcomes. Method: Ecological momentary assessments (EMAs) collected using a smartphone app were used to probe patterns of listening behavior in CI users and age-matched NH adults to detect differences in social engagement and listening behavior in daily life. Participants completed very short surveys every 2 hr to provide snapshots of typical, everyday listening and socializing, as well as longer, reflective surveys at the end of the day to assess listening strategies and coping behavior. Speech perception testing, with accompanying ratings of task difficulty, was also performed in a lab setting to uncover possible correlations between objective and subjective listening behavior. Results: Comparisons between speech intelligibility testing and EMA responses showed poorer performing CI users spending more time at home and less time conversing with others than higher performing CI users and their NH peers. Perception of listening difficulty was also very different for CI users and NH listeners, with CI users reporting little difficulty despite poor speech perception performance. However, both CI users and NH listeners spent most of their time in listening environments they considered “not difficult.” CI users also reported using several compensatory listening strategies, such as visual cues, whereas NH listeners did not. Conclusion: Overall, the data indicate systematic differences between how individual CI users and NH adults navigate and manipulate listening and social environments in everyday life. 

Abstract When a visual search target frequently appears in one target-rich region of space, participants learn to search there first, resulting in faster reaction time when the target appears there than when it appears elsewhere. Most research on this location probability learning (LPL) effect uses 2-dimensional (2D) search environments that are distinct from real-world search contexts, and the few studies on LPL in 3-dimensional (3D) contexts include complex visual cues or foraging tasks and therefore may not tap into the same habit-like learning mechanism as 2D LPL. The present study aimed to establish a baseline evaluation of LPL in controlled 3D search environments using virtual reality. The use of a virtual 3D search environment allowed us to compare LPL for information within a participant’s initial field of view to LPL for information behind participants, outside of the initial field of view. Participants searched for a letter T on the ground among letter Ls in a large virtual space that was devoid of complex visual cues or landmarks. The T appeared in one target-rich quadrant of the floor space on half of the trials during the training phase. The target-rich quadrant appeared in front of half of the participants and behind the other half. LPL was considerably greater in the former condition than in the latter. This reveals an important constraint on LPL in real-world environments and indicates that consistent search patterns and consistent egocentric spatial coding are essential for this form of visual statistical learning in 3D environments. 

Previous research has shown that individuals behave differently in certain virtual reality tasks. The effect of VR on human posture and stability is an important factor that can influence the future applications of VR devices. This current study seeks to investigate how a person’s postural stability differs between VR and normal environment while attempting to replicate the influence of target distance on sway. Ten healthy subjects were tested in both environments with targets varying in distance. The results found a significant difference in postural stability for normal anatomical stance tasks between VR and normal environments. 

Proprioception or body awareness is an essential sense that aids in the neural control of movement. Proprioceptive impairments are commonly found in people with neurological conditions such as stroke and Parkinson’s disease. Such impairments are known to impact the patient’s quality of life. Robot-aided proprioceptive training has been proposed and tested to improve sensorimotor performance. However, such robot-aided exercises are implemented similar to many physical rehabilitation exercises, requiring task-specific and repetitive movements from patients. Monotonous nature of such repetitive exercises can result in reduced patient motivation, thereby, impacting treatment adherence and therapy gains. Gamification of exercises can make physical rehabilitation more engaging and rewarding. In this work, we discuss our ongoing efforts to develop a game that can accompany a robot-aided wrist proprioceptive training exercise.