National Science Foundation Grant Will Benefit Severely Hearing-impaired Individuals
A grant from the National Science Foundation (NSF) to Dr. Bonny Banerjee, assistant
professor of electrical and computer engineering and Institute for Intelligent Systems
at the University of Memphis, will not only foster interdisciplinary research bringing
together fields as diverse as computer engineering and audiology, but will eventually
allow severely hearing-impaired people lead the lives of their normal-hearing counterparts.
Hearing loss is the most common birth defect in U.S. affecting 12,000 newborns every
year. Cochlear implants (CIs) are an effective intervention for adults and children
with severe-to-profound sensorineural hearing loss who fail to benefit from acoustic
hearing aids. However, without proper tuning of CIs to each individual’s hearing deficiencies,
optimal access to sound cannot be delivered, even in the case of good candidate selection,
surgery, and rehabilitation support. At present, no universal standards or well-defined
good clinical practices for tuning CIs exist to guide the audiologists. With more
than 200,000 CI users worldwide and an annual increase of over 30,000, lack of proper
tuning is a severe bottleneck to the usage of available life-changing technology.
The $298,203 grant from NSF will fund research that aim to automatically tune CIs
for individuals with severe-to-profound hearing loss. Dr. Lisa Lucks Mendel, associate
professor at the School of Communication Sciences and Disorders, U of M, worked with
Banerjee in obtaining the grant and will handle the clinical aspects of the project.
Before joining U of M, Banerjee spent over three years leading the research in a startup
company, Audigence Inc., for developing automated software solutions for tuning digital
hearing devices (cochlear implants, hearing aids). This research has a number of U.S.
and international patents pending, attracted investor funding over $3 million, and
led to the launch of the company’s first product – a commercial software called ClarujustTM – for the end-user at the Academy of Doctors of Audiology Annual Convention in Tampa,
FL on October 29-31, 2009. ClarujustTM has been covered widely by major news and television channels, such as, Health First,
Fox, ABC News, USA Today, etc. across U.S. In March 2012, Audigence's IP was acquired
by Cochlear Corp., the world’s leading CI manufacturer. Most importantly, in a pilot
study at the University of Florida, 17 of the 20 CI recipients preferred to continue
using the ClarujustTM-tuned setting over traditionally-tuned settings.
Banerjee said, “While ClarujustTM was quite successful in many ways, one thorn in the bud was its test-retest variability.
That is, consecutive tests done on the same patient in exactly the same way sometimes
had very different outcomes. This makes the data from tests unreliable and hence,
the goodness of the tuned device parameters is in doubt.” He attributes two factors
for this behavior – lack of adequate test data and the analysis of an individual’s
stimulus-response errors in terms of hand-coded features. “These hand-coded features
fail to capture the context or norms in the hearing abilities of each individual.”
These observations and insights led Banerjee to seek out Mendel at the other end of
the campus and together submit a proposal to NSF within his six months of joining
U of M. Their working hypothesis is that the deficiencies in hearing for individuals
with significant hearing loss are reflected in their speech. Banerjee and his team
aim to address the shortcomings of ClarujustTM with an entirely different approach – by learning features from day-to-day speech
around the clock in an unsupervised and online manner. Informally, features in this
project will be snippets of sound of very short duration (e.g., one millisecond) that
recur in speech and using which a given speech can be reconstructed. The learning
algorithms will be installed in the implanted CI device. Since the algorithms will
learn online, the speech will not be recorded or stored and privacy will not be compromised.
The learned feature hierarchy from the speech of a severely hearing-impaired individual
will be compared to those learned from the speech of a comparable normal hearing population.
Deficiencies in the patient’s hearing will be ascertained by identifying the missing
or distorted features. This information will guide audiologists to better tune CIs
to enhance the audibility of speech.
Other than Banerjee and Mendel, the project will involve electrical and computer engineering
students, audiology students as well as clinicians, who will work together to design
and deploy the learning algorithms for customized tuning of the CI devices for each
individual with severe-to-profound hearing loss. Besides CI tuning, the algorithms
will be applicable to a variety of monitoring applications within healthcare and beyond.
Continuous monitoring with wearable and implantable body sensors will increase early
detection of emergency conditions and diseases in at-risk patients and also provide
a wide range of healthcare services for people with various degrees of cognitive and
physical disabilities. The project will transform the traditional ways in which the
clinical needs of continuously-monitored patients are met. Its success will open up
avenues for around the clock medical attention focused on the specific needs of individual
patients at minimal cost.
The grant will be distributed over a three-year period. It will support graduate students
and cover the cost of equipments and travel needed for the project.
For more information, contact Dr. Banerjee at 901-678-4498 or firstname.lastname@example.org.