Parivash Ranjbar

Vibrotactile identification of signal-processed sounds from environmental events.

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).

Auditive identification of signal-processed environmental sounds : monitoring the environment

The goal of the present study was to compare six transposing signal-processing algorithms based on different principles (Fourier-based and modulation based), and to choose the algorithm that best enables identification of environmental sounds, i.e. improves the ability to monitor events in the surroundings. Ten children (12–15 years) and 10 adults (21–33 years) with normal hearing listened to 45 representative environmental (events) sounds processed using the six algorithms, and identified them in three different listening experiments involving an increasing degree of experience. The sounds were selected based on their importance for normal hearing and deaf-blind subjects. Results showed that the algorithm based on transposition of 1/3 octaves (fixed frequencies) with large bandwidth was better (p<0.015) than algorithms based on modulation. There was also a significant effect of experience (p<0.001). Adults were significantly (p<0.05) better than children for two algorithms. No clear gender difference was observed. It is concluded that the algorithm based on transposition with large bandwidth and fixed frequencies is the most promising for development of hearing aids to monitor environmental sounds.

Monitor, a Vibrotactile Aid for Environmental Perception: A Field Evaluation by Four People with Severe Hearing and Vision Impairment

Monitor is a portable vibrotactile aid to improve the ability of people with severe hearing impairment or deafblindness to detect, identify, and recognize the direction of sound-producing events. It transforms and adapts sounds to the frequency sensitivity range of the skin. The aid was evaluated in the field. Four females (44–54 years) with Usher Syndrome I (three with tunnel vision and one with only light perception) tested the aid at home and in traffic in three different field studies: without Monitor, with Monitor with an omnidirectional microphone, and with Monitor with a directional microphone. The tests were video-documented, and the two field studies with Monitor were initiated after five weeks of training. The detection scores with omnidirectional and directional microphones were 100% for three participants and above 57% for one, both in their home and traffic environments. In the home environment the identification scores with the omnidirectional microphone were 70%–97% and 58%–95% with the directional microphone. The corresponding values in traffic were 29%–100% and 65%–100%, respectively. Their direction perception was improved to some extent by both microphones. Monitor improved the ability of people with deafblindness to detect, identify, and recognize the direction of events producing sounds.

Signal Processing Methods for Improvement of Environmental Perception of Persons with Deafblindness

Environmental perception is a functional area that is severely limited in persons with deafblindness (DB) who belong a category of people with severe disabilities. Monitor is a vibratory aid developed with the aim to improve environmental perception of persons with DB. The aid consists of a mobile phone with an application connected to a microphone and vibrator. Monitor picks up the sounds produced by events by microphone, processes the sound using an algorithm programmed as an application in the mobile phone and then presents the signal via the vibrator to the persons with DB to be sensed and interpreted. In previous laboratory studies, four algorithms (AM, AMMC, TR, and TRHA) were developed based on modulating, and transposing principles. The algorithms were tested by persons with normal hearing/hearing impairment and selected as good candidates to improve vibratory identification of environmental sounds. In this on-going the algorithms are tested by 13 persons with congenital D and five persons with DB using Monitor in a realistic environment, living room, kitchen or office. Forty five recorded environmental sounds were used as test stimuli. The subjects tested the algorithms two times, Test and Retest each including a test session initiated by a training session. The four algorithms were tested in four days at Test and four days at Retest in total eight test days. Each test day began with a training session where a sound was presented as vibrations to be sensed by the person with the aim to remember its pattern and identity. The 45 sounds were grouped in four groups where an specific algorithm was chosen to process an specific sound group in a specific day. At the test session a sound was presented and the person was given 5 randomly chosen sound alternatives to choose the one as represented sound. The algorithms were different for different sound groups during four different test days so all algorithms were used to process all sounds. The algorithms were tested a second time, Retest, in same way as in Test. The mean value of identification of environmental sounds varied between 74.6% and 84.0% at Test and between 86.9% and 90.4% at Retest. The identification results at Retest were significantly improved (p<0.01) for all algorithms after a relatively short time of training indicating a good learning effect. At Test the algorithm AM was significantly better than the algorithms AMMC and TRHA (p< 0.01) and the algorithm TR was better than TRHA (p<0.01). The algorithms AM, AMMC, and TR were selected as good candidates to be implemented in the Monitor to improve environmental perception.