Abstract
Human-machine interface (HMI) designs offer the possibility of improving quality of life for patient populations as well as augmenting normal user function. Despite pragmatic benefits, utilizing auditory feedback for HMI control remains underutilized, in part due to observed limitations in effectiveness. The goal of this study was to determine the extent to which categorical speech perception could be used to improve an auditory HMI. Using surface electromyography, 24 healthy speakers of American English participated in 4 sessions to learn to control an HMI using auditory feedback (provided via vowel synthesis). Participants trained on 3 targets in sessions 1–3 and were tested on 3 novel targets in session 4. An “established categories with text cues” group of eight participants were trained and tested on auditory targets corresponding to standard American English vowels using auditory and text target cues. An “established categories without text cues” group of eight participants were trained and tested on the same targets using only auditory cuing of target vowel identity. A “new categories” group of eight participants were trained and tested on targets that corresponded to vowel-like sounds not part of American English. Analyses of user performance revealed significant effects of session and group (established categories groups and the new categories group), and a trend for an interaction between session and group. Results suggest that auditory feedback can be effectively used for HMI operation when paired with established categorical (native vowel) targets with an unambiguous cue.
Highlights
Human-machine interfaces (HMIs) are designed to translate volitionally produced physiological signals into commands or control signals to augment or restore normal user function
After training participants to produce specific vowel sounds based on continuous auditory and visual feedback, we found that participants readily transferred ability to control the HMI using auditory feedback alone
We compared HMI control of participants in the three training groups in each of the four behavioral sessions: those with 1) auditory and full visual feedback applied to training targets; 2) auditory and partial visual feedback applied to training targets; 3) auditory feedback only applied to training targets; and 4) auditory feedback only with novel vowel targets
Summary
Human-machine interfaces (HMIs) are designed to translate volitionally produced physiological signals into commands or control signals to augment or restore normal user function. HMI designs typically utilize biosignals such as electro-encephalography (EEG) or surface electromyography (sEMG) (which translate scalp potentials or muscle activities, respectively, into control signals). In many HMI designs, users are required to imagine specific motor movements [1] or fixate on a target in a visual scene to evoke P300 [2] or steady-state visual responses [3]. Effective, these types of HMI designs rely on visual feedback or sustained visual attention for operation, thereby limiting normal user visual function. In an attempt to overcome this, multiple auditory-based HMI designs have exploited the cortical potentials evoked by presented auditory stimuli with increasing success [4,5,6,7]
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