{"id":"07415","slug":"quantitative-performance--07415","source":{"id":"07415","dataset":"techtransfer","title":"Quantitative Performance Assessment Tool for Alternative Communication (AAC) Access","description_":"<p>This innovation is a specialized software application designed to help clinicians evaluate and select the most effective access methods for individuals using augmentative and alternative communication (AAC) devices. By providing objective data during initial evaluations, the tool empowers healthcare providers to make evidence-based recommendations tailored to a user&#39;s specific physical capabilities.</p><p><h2>Description</h2>The Selection Rate application functions as a data-driven clinical decision support tool that measures how efficiently a user can interact with different AAC control interfaces. Unlike traditional assessment methods that often rely on qualitative \"target practice\" activities, this software generates a precise quantitative score to represent a user's performance. This allows for a direct, side-by-side comparison of various access methods—such as switch scanning or eye tracking—to identify which one yields the highest selection rate for the individual. \r\n\r\nThe software includes integrated features for clinicians to view real-time user data and track performance metrics across multiple measurement trials and different AAC devices. By capturing longitudinal data, the application helps identify trends in user proficiency, ensuring that the selected interface is not only functional but optimized for the user's long-term communication needs.</p><p><h2>Applications</h2>- Clinical AAC Evaluations: Primary use in speech-language pathology clinics and rehabilitation centers for initial alternative access assessments. \r<br>- Assistive Technology Research: A tool for researchers to gather objective data on the usability and effectiveness of new AAC interface designs. \r<br>- Educational Settings: Use in special education programs to help determine the best communication tools for students with complex communication needs.</p><p><h2>Advantages</h2>- Objective Quantifiable Metrics: Replaces subjective clinical observation with a standardized quantitative score for comparing user performance. \r<br>- Enhanced Clinical Decision-Making: Enables clinicians to select the most appropriate access method based on empirical evidence rather than trial and error.  \r<br>- Longitudinal Performance Tracking: Provides the ability to monitor a user’s progress and selection accuracy across multiple trials and devices over time.</p><p><h2>Invention Readiness</h2>The technology is currently at the prototype stage, with functional software code already developed. Initial groundwork and general material related to the performance of these interfaces have been explored through academic research, establishing a strong theoretical and preliminary practical foundation. Future development will focus on full technical validation of the application and potential expansion of the software to include more diverse AAC interface types and more robust data analytics for clinical reporting.</p><p><h2>IP Status</h2>Copyright</p><p></p>","tags":["Software"],"file_number":"07415","collections":[],"meta_description":"A data-driven AAC access evaluator quantifies user performance across interfaces, enabling objective, longitudinal, evidence-based decisions.","image_url":"","apriori_judge_output":"{\"scores\":{\"novelty\":3.0,\"potential_impact\":3.0,\"readiness\":3.0,\"scalability\":2.0,\"timeliness\":3.0},\"weighted_score\":2.95,\"risks\":[\"Prototype stage may limit near-term adoption\",\"IP status copyright only; patent protection unclear\",\"Clinical workflow integration challenges\",\"Regulatory considerations for medical software not addressed\"],\"one_sentence_take\":\"Moderate novelty with practical clinical utility; current prototype readiness and copyright IP limit near-term impact and scalability.\"}","lead_inventor_name":"Michael O'Leary","lead_inventor_dept":"SHRS-Physicians Assistant Program","technology_type":"Digital Health","technology_subtype":"Clinical Decision Support","therapeutic_areas":["Neuroscience"],"therapeutic_indications":[],"custom_tags":[],"all_tech_innovators":["Michael O'Leary"],"date_submitted":"2025-12-04","technology_readiness_level":"3. Prototype development"},"highlight":{},"matched_queries":null,"score":0.0}