Effects of noise suppression and envelope dynamic range compression on the intelligibility of vocoded sentences for a tonal language

Vocoder simulation studies have suggested that the carrier signal type employed affects the intelligibility of vocoded speech. The present work further assessed how carrier signal type interacts with additional signal processing, namely, single-channel noise suppression and envelope dynamic range compression, in determining the intelligibility of vocoder simulations. In Experiment 1, Mandarin sentences that had been corrupted by speech spectrum-shaped noise (SSN) or two-talker babble (2TB) were processed by one of four single-channel noise-suppression algorithms before undergoing tone-vocoded (TV) or noise-vocoded (NV) processing. In Experiment 2, dynamic ranges of multiband envelope waveforms were compressed by scaling of the mean-removed envelope waveforms with a compression factor before undergoing TV or NV processing. TV Mandarin sentences yielded higher intelligibility scores with normal-hearing (NH) listeners than did noise-vocoded sentences. The intelligibility advantage of noise-suppressed vocoded speech depended on the masker type (SSN vs 2TB). NV speech was more negatively influenced by envelope dynamic range compression than was TV speech. These findings suggest that an interactional effect exists between the carrier signal type employed in the vocoding process and envelope distortion caused by signal processing

An asynchronous,low-power architecture for interleaved neural stimulation, using envelope and phase information

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.Includes bibliographical references (p. 122-124).This thesis describes a low-power cochlear-implant processor chip and a charge-balanced stimulation chip that together form a complete processing-and-stimulation cochlear-implant system. The processor chip uses a novel Asynchronous Interleaved Stimulation (AIS) algorithm that preserves phase and amplitude cues in its spectral input while simultaneously minimizing electrode interactions and lowering average stimulation power per electrode. The stimulator chip obviates the need for large D.C. blocking capacitors in neural implants to achieve highly precise charge-balanced stimulation, thus lowering the size and cost of the implant. Thus, this thesis suggests that significant performance, power and cost improvements in the current generation of cochlear implants may be simultaneously possible. The 16-channel ~90 square mm AIS processor chip was built in a 1.5[mu]m VLSI process and consumed 107[mu]W of power over and above that of its analog spectral processing front end, which consumed 250gtW and which has been previously described. The AIS processor was found to faithfully mimic MATLAB implementations of the AIS algorithm. Two perceptual tests of the AIS algorithm with normal-hearing listeners verified that AIS signal reconstructions enabled better melody and speech recognition in noise than traditional envelope-only vocoder simulations of cochlear-implant processing. The average firing rate of the AIS processor was found to be significantly lower than in traditional synchronous stimulators, suggesting that the AIS algorithm and processor can potentially save power and improve hearing performance in cochlear-implant users. The stimulator chip was built in a 0.7glm high-voltage VLSI process and performed dynamic current balancing followed by a shorting phase.(cont.) It achieved <6nA of average DC current error, well below the targeted safety limit of 25nA for cochlear-implant patients. On +6 and -9V rails, the power consumption of a single channel of this chip was 47[mu]W when biasing power is shared by 16 channels. It puts out a charge-balanced stimulation pulse whenever it receives an asynchronous input signal from an AIS processor encoding phase information and 7-bit amplitude information, thus making the AIS processor chip and stimulator chip fully compatible in the cochlear-implant system. The AIS algorithm and charge-balancing circuits described in this work may be useful in other nerve-stimulation prosthetics where good fidelity in input-information encoding, minimization of electrode interactions, low-power strategies for stimulation, and compact charge-balanced stimulation are also important.by Ji-Jon Sit.Ph.D

Pitch perception and signal processing in electric hearing

A study comprised of six hearing experiments was conducted in order to investigate parameters to influence the pitch perception elicited by direct electric stimulation of the auditory nerve. In addition, a new stimulation strategy for the cochlear implant COMBI 40+ (MED-EL, Innsbruck, Austria) was developed and tested. The results derived from a total number of 16 subjects reveal a dominating influence of the place of stimulation in contrast to the rate of stimulation on pitch perception. It was shown that the electrode distance of 2.4 mm for this device is sufficient to allow discriminable electrodes in pitch along the whole array. The influence of stimulation rate on pitch is limited to pulse rates up to about 300 pps. Within this range, the just noticeable change of pitch elicited by pulse rate as well as modulation rate amounts to about 25% of the base rate. In addition it was observed that the sound quality increases with increasing pulse rate up to about 566 pps independent of electrode location. Subjects with residual hearing at the non-implanted ear revealed that the pitch elicited by the most apical electrode depends on the insertion depth of the array and is linearly increasing with electrode location (40 Hz/mm). The results of the hearing experiments were implemented to modify the well known CIS strategy. The new development (termed RateCIS) was designed in order to increase the amount of transmitted spectral information, thus the number of effective channels. Six electrodes were selected to switch adaptively between a high stimulation rate (1515 pps) and a low stimulation rate (252 pps). A test of the RateCIS strategy showed that results for speech recognition are comparable to the CIS strategy. The RateCIS strategy was subjectively preferred by some of the subjects although the majority preferred the CIS strategy for speech recognition and sound quality. Concerning the recognition and appraisal of music however, the RateCIS strategy was preferred by the majority of subjects. Regarding the fact, that the tests were conducted during one day without time for adaptation to the new signal processing, the RateCIS strategy could serve as an interesting option especially for music appraisal

A MODELING PERSPECTIVE ON DEVELOPING NATURALISTIC NEUROPROSTHETICS USING ELECTRICAL STIMULATION

Direct electrical stimulation of neurons has been an important tool for understanding the brain and neurons, since the field of neuroscience began. Electrical stimulation was used to first understand sensation, the mapping of the brain, and more recently function, and, as our understanding of neurological disorders has advanced, it has become an increasingly important tool for interacting with neurons to design and carry out treatments. The hardware for electrical stimulation has greatly improved during the last century, allowing smaller scale, implantable treatments for a variety of disorders, from loss of sensations (hearing, vision, balance) to Parkinson’s disease and depression. Due to the clinical success of these treatments for a variety of impairments today, there are millions of neural implant users around the globe, and interest in medical implants and implants for human-enhancement are only growing. However, present neural implant treatments restore only limited function compared to natural systems. A limiting factor in the advancement of electrical stimulation-based treatments has been the restriction of using charge-balanced and typically short sub-millisecond pulses in order to safely interact with the brain, due to a reliance on durable, metal electrodes. Material science developments have led to more flexible electrodes that are capable of delivering more charge safely, but a focus has been on density of electrodes implanted over changing the waveform of electrical stimulation delivery. Recently, the Fridman lab at Johns Hopkins University developed the Freeform Stimulation (FS)– an implantable device that uses a microfluidic H-bridge architecture to safely deliver current for prolonged periods of time and that is not restricted to charge-balanced waveforms. In this work, we refer to these non-restricted waveforms as galvanic stimulation, which is used as an umbrella term that encompasses direct current, sinusoidal current, or alternative forms of non-charge-balanced current. The invention of the FS has opened the door to usage of galvanic stimulation in neural implants, begging an exploration of the effects of local galvanic stimulation on neural function. Galvanic stimulation has been used in the field of neuroscience, prior to concerns about safe long-term interaction with neurons. Unlike many systems, it had been historically used in the vestibular system internally and in the form of transcutaneous stimulation to this day. Historic and recent studies confirm that galvanic stimulation of the vestibular system has more naturalistic effects on neural spike timing and on induced behavior (eye velocities) than pulsatile stimulation, the standard in neural implants now. Recent vestibular stimulation studies with pulses also show evidence of suboptimal responses of neurons to pulsatile stimulation in which suprathreshold pulses only induce about half as many action potentials as pulses. This combination of results prompted an investigation of differences between galvanic and pulsatile electrical stimulation in the vestibular system. The research in this dissertation uses detailed biophysical modeling of single vestibular neurons to investigate the differences in the biophysical mechanism of galvanic and pulsatile stimulation. In Chapter 2, a more accurate model of a vestibular afferent is constructed from an existing model, and it is used to provide a theory for how galvanic stimulation produces a number of known effects on vestibular afferents. In Chapter 3, the same model is used to explain why pulsatile stimulation produces fewer action potentials than expected, and the results show that pulse amplitude, pulse rate, and the spontaneous activity of neurons at the axon have a number of interactions that lead to several non-monotonic relationships between pulse parameters and induced firing rate. Equations are created to correct for these non-monotonic relationships and produce intended firing rates. Chapter 4 focuses on how to create a neural implant that induces more naturalistic firing using the scientific understanding from Chapters 2 and 3 and machine learning. The work concludes by describing the implications of these findings for interacting with neurons and population and network scales and how this may make electrical stimulation increasingly more suited for treating complex network-level and psychiatric disorders