Situational Signal Processing with Ecological Momentary Assessment: Leveraging Environmental Context for Cochlear Implant Users

Technological advancements for biomedical interfaces and devices, such as cochlear implants (CIs), depend on the integration of novel signal processing strategies enhanced by situational real-time feedback in naturalistic spontaneous environments. This study proposes the first CI framework for situational signal processing, "Emaging", which incorporates ecological momentary assessment (EMA) on portable and wearable devices. The original "Emaging" application operates simultaneously with the CCi-MOBILE platform, a customized portable signal processing CI platform. EMA is an integrative variant of behavioral medicine research that evaluates physiological and psychological outcomes of individuals in natural contexts and incorporates real-time signaling that prompts the subject to report on their current state in a non-clinical environment. "Emaging" considers two parameters of EMA for the CI subject: sound source localization (SSL) and sound source identification (SSI) for non-spoken sounds. SSL involves neurological coding of interaural time and level differences (ITDs and ILDs), which enable the listener to localize auditory stimuli. SSI, which entails identifying what sound was heard, is especially challenging for CI users due to commercial CI algorithms predominantly optimized for speech perception. With "Emaging", CI users document and "tag" their respective experiences with SSL and SSI in a natural real-time environment on their portable and wearable devices. The "tagging" can run simultaneously with regular CCi-MOBILE processing in online or offline scenarios. CCi-MOBILE’s synchronization with "Emaging" provides a unique opportunity for next generational algorithm design based on situational signal processing algorithms. Such algorithms are conducive to more effective non-linguistic sound coding strategies for next-generation biomedical hearing devices.