When the parts of the ear that transmit sound to the auditory nerve are damaged—as they often are in the severely deaf—a hearing aid that merely amplifies sound offers little assistance. Today, more than 70,000 deaf people have been connected to the world of sound, some for the first time in their lives, with cochlear implants from Cochlear Limited.
A cochlear implant bypasses the damaged part of the ear, transmitting sound signals directly to the recipient's auditory nerve. It is the only widely available medical device designed to restore a human sense.
Since releasing its first implant system more than 20 years ago, Cochlear has produced five generations of cochlear implants, each incorporating more features in ever smaller devices.
Engineers at Cochlear use MathWorks tools for Model-Based Design to accelerate development and prototype and test new ideas.
Improving the Hearing Experience
One way that engineers assess the effectiveness of new designs is to gather feedback from a Cochlear implant recipient within a specially equipped research laboratory environment—usually over multiple test sessions.
Developing new cochlear implant processing methods typically involves iterating implementations on a custom digital signal processor (DSP) using assembler code. This time-consuming process results in development cycles that can last many years.
To overcome these limitations and test more new ideas, Cochlear decided to develop several rapid prototyping systems. Using MathWorks tools, they modeled and simulated the external speech processor of their Nucleus 24 and Freedom implants, replacing all parts of the system except the implant itself with software. They could then rapidly create many different test cases by simply changing processing steps or parameters in software instead of developing a new product prototype for each test.
Creating a Development and Test Platform
Brett Swanson, senior DSP researcher at Cochlear, used MATLAB to create the Nucleus MATLAB Toolbox (NMT), a development and test platform that replicates the signals typically generated by custom application-specific integrated circuits (ASICs) inside the external speech processor. NMT interfaces to hardware that communicates with a recipient's implant. It includes standard and proprietary signal processing algorithms that enable Cochlear engineers and researchers to quickly try out new designs and algorithm improvements.
Researchers around the world use NMT to create and play back stimuli for implant recipients, who perceive the stimuli as sounds. As researchers adjust the inputs, recipients comment on any improvement or worsening of sound quality. Researchers may also measure the recipients' performance on a variety of objective speech tests to compare processing changes more objectively. They pretest some design changes, such as noise reduction algorithms to improve the signal-to-noise ratio in difficult listening environments by using MATLAB to examine and analyze output signals. This approach helps focus recipient testing by eliminating obvious problems first. Ultimately, however, the implant recipients themselves contribute significantly to the verification of all design changes to improve hearing performance.
While NMT has enabled numerous improvements to implant technology—for example, Cochlear's proprietary SmartSound audio processing strategies—it is limited because it can play only preprocessed recorded sounds. During tests, a recipient hears the signals from NMT but cannot hear the researcher's instructions or other sounds in the room.
Moving to a Real-Time Environment
To address the limitations of NMT, Cochlear sought a more advanced approach. "The next step was to make all the research-friendly features of NMT available in real time," says Michael Goorevich, principal DSP engineer at Cochlear. "That is when we started using Simulink and xPC Target."
Goorevich and his team developed a real-time research platform for developing sound- processing and speech-coding algorithms. Using Simulink, the group designed a custom framework and implemented Simulink blocks of commercially available algorithms from the Nucleus Freedom system. The framework includes standardized signal levels and data format specifications that enable the easy interchange of input, output, and signal processing blocks. The Simulink models are connected to the implant hardware using xPC Target.
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Figure 1. Cochlear's implant interface hardware.
"With Simulink and xPC Target everything is running live, so we can interact with the recipient. We can talk to them, they can hear us, and more importantly, they can hear how their own voice sounds," says Goorevich.
The new platform has many advantages over NMT. Engineers can implement speech-coding algorithms in a similar time frame as they had with NMT, but without having to write the custom DSP assembler code normally required for adequate real-time performance. Preprocessing of sounds is no longer required, enabling researchers to make decisions about input test material on the fly and to vary model parameters to control loudness, compression curves, and electrode levels during tests. The team plans to create a graphical user interface (GUI) in MATLAB that will enable recipients to control parameters themselves, further accelerating the test process.