iScreen Aphasia vs Linus Tester

iScreen Aphasia: Streamlined Screening & Reporting for SLPs Ditch the paper forms and elevate your clinical practice. iScreen Aphasia is the ultimate digital screening toolkit designed by and for Speech-Language Pathologists to accurately evaluate, track, and treat patients with aphasia. Built to handle the complexities of neurogenic communication disorders, iScreen Aphasia transforms a time-consuming evaluation process into a smooth, guided digital experience. Evaluate with Precision Conduct thorough expressive, receptive, and oral motor screenings right from your iPad. Expressive: Naming, repetition, automatic speech, reading, and sentence completion. Receptive: Object and body part identification, multi-step directions, and auditory story comprehension. Oral Motor: Document lingual and labial function with intuitive grading scales. Work Smarter, Not Harder Instant Data Analysis: The app automatically calculates accuracy percentages for every subtest, giving you an immediate clinical picture to guide your plan of care. Compliance Made Easy: Generates essential G-code modifiers directly from your screening results to simplify your billing and Medicare reporting. Detailed Patient Histories: Log everything from the date and location of the CVA to TPA administration and prior levels of function. Generate Professional Reports in Seconds Never spend your evening typing up screening notes again. The moment you finish your evaluation, iScreen Aphasia compiles your data, patient history, and clinical observations into a professional, easy-to-read PDF report. Print, save, or email it directly to the patient's care team or your EHR system with a single tap. Built for the Modern Clinician Track patient progress over time with built-in reassessment tools, manage your caseload seamlessly from the Archives dashboard, and establish objective discharge criteria based on real data. Experience a groundbreaking approach to aphasia care. Download iScreen Aphasia today.

The Linus platform allows the coordinated collection of large amounts of information about digital measurements—such as voice, speech, gait, cognition and eye movement—that may have a bearing on brain health and lead to the identification of digital biomarkers. Applying machine learning methods of data analysis to this rich set of measurements, together with information drawn from electronic health records, provides a composite picture with more precise metrics for evaluating the impact of potential interventions and lifestyle changes, and for offering personalized prescriptions to promote brain health.