University of Massachusetts Amherst

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Miriam Madsen

DS Tea
December 5
Computer Science Building, Room 150/151


Designing a Novel Manual Communication System for Mechanically Ventilated (MV) ICU Patients

In the hospital Intensive Care Unit (ICU), available communication methods for patients using MV - e.g., breathing tubes - are insufficient. While a number of basic communication methods are often tried with these patients (such as writing on whiteboards/clipboards, use of letter boards, and mouthing words), patients and caregivers consistently report dissatisfaction with available methods and limited success in their use.1 Furthermore, patients consider the lack of successful communication strategies to be extremely stressful.2 The ICU setting is more complicated for assistive communication technology use than other settings due to patient population heterogeneity; variation in individuals’ physical/cognitive capabilities over time; robustness and hygiene concerns for communication tools; and a lack of available training time prior to patients’ need for communication assistance.
A novel communication system is under development, with the goal of being easily accessible by MV patients who lack sufficient dexterity to write clearly due to complications of critical illness. Using this system, a patient will manually operate a hand-held component that communicates in real time with a tablet computer, producing audiovisual content specific to ICU patient needs.

Three sets of system requirements have guided the design of this technology: features required by the ICU setting, by the patient, and by the nurses/care team. Features required by the ICU setting include the presence of ICU-specific topics and cost-effective design that is appropriately hygienic. The patient-related system requirements involve a short learning curve; hardware and software that is adaptable to individual patients; and inclusion of non-medical topics of value to patients and their families. Synthesized speech output and some form of tactile feedback are also planned for the final system version to meet patient needs. In considering the requirements of the nurses and care team, the system should be accessible despite physical restraints and should demonstrate a patient’s level of responsiveness, allowing for a clearer assessment of a patient’s cognitive state.

This system has been demonstrated in its prototype form to physicians, nurses, researchers, and engineers; based on their feedback, the system has undergone over two dozen iterations in preparation for deployment with MV ICU patients.  Patient testing in a proof-of-concept pilot trial began in November of 2016, and the system is under active development and revision.


Miriam received her bachelor's and master's degrees at MIT (2009, S.B. in Computer Engineering; 2010, M.Eng. in Autism Technologies). At MIT, she worked with the Speech & Communications Laboratory and the Smart Wheelchair Project in the Department of Electrical Engineering & Computer Science, as well as with Affective Computing, Biomechatronics, and the Voting Technology Project in the MIT Media Lab. She then completed a premedical preparation program at UMass Boston worked as a software engineer in industry.

She is currently in the MD/PhD program at UMass Medical School in Worcester. In her PhD program, she is in the departments of Neurology and Anesthesiology, as well holding a position as a Visiting Research Fellow in Brown University's School of Engineering.