Vibrotactile identification of signal-processed sounds from environmental events

Abstract

This study compared three different signal-processing principles (eight basic algorithms) - transposing, modulating, and filtering - to find the principle(s)/algorithm(s) that resulted in the best tactile identification of environmental sounds. The subjects were 19 volunteers (9 female/10 male) who were between 18 and 50 years old and profoundly hearing impaired. We processed sounds produced by 45 representative environmental events with the different algorithms and presented them to subjects as tactile stimuli using a wide-band stationary vibrator. We compared eight algorithms based on the three principles (one unprocessed, as reference). The subjects identified the stimuli by choosing among 10 alternatives drawn from the 45 events. We found that algorithm and subject were significant factors affecting the results (repeated measures analysis of variance, p < 0.001). We also found large differences between individuals regarding which algorithm was best. The test-retest variability was small (mean +/- 95% confidence interval = 8 +/-3 percentage units), and no correlation was noted between identification score and individual vibratory thresholds. One transposing algorithm and two modulating algorithms led to significantly better results than did the unprocessed signals (p < 0.05). Thus, the two principles of transposing and modulating were appropriate, whereas filtering was unsuccessful. In future work, the two transposing algorithms and the modulating algorithm will be used in tests with a portable vibrator for people with dual sensory impairment (hearing and vision).