Swathi Jagannath, Neha Kamireddi, Katherine Ann Zellner, Randall S. Burd, Ivan Marsic, and Aleksandra Sarcevic
Designing computerized approaches to support complex teamwork requires an understanding of how activity-related information is relayed among team members. In this paper, we focus on verbal communication and describe a speech-based model that we developed for tracking activity progression during time-critical teamwork. We situated our study in the emergency medical domain of trauma resuscitation and transcribed speech from 104 audio recordings of actual resuscitations. Using the transcripts, we first studied the nature of speech during 34 clinically relevant activities. From this analysis, we identified 11 communicative events across three different stages of activity performance—before, during, and after. For each activity, we created sequential ordering of the communicative events using the concept of narrative schemas. The final speech-based model emerged by extracting and aggregating generalized aspects of the 34 schemas. We evaluated the model performance by using 17 new transcripts and found that the model reliably recognized an activity stage in 98% of activity-related conversation instances. We conclude by discussing these results, their implications for designing computerized approaches that support complex teamwork, and their generalizability to other safety-critical domains.1
Characterizing Speech in Life Saving Interventions to Inform Computerized Clinical Decision Support for Complex Medical Teamwork
We describe an initial analysis of speech during team-based medical scenarios and its potential to indicate process delays in an emergency medical setting. We analyzed the speech of trauma resuscitation teams in cases with delayed intravenous/intraosseous (IV/IO) line placement, a significant contributor to delays during life-saving interventions. The insights gained from this analysis will inform the design of a clinical decision support system (CDSS) that will use multiple sensor modalities to alert medical teams to errors in real time. We contribute to the literature by determining how the intention of each speech line and the sentence can support real-time, automatic detection of delays during time-critical team activities.
IN VIVO IMAGING OF EPITHELIAL WOUND HEALING IN THE CNIDARIAN CLYTIA HEMISPHAERICA DEMONSTRATES EARLY EVOLUTION OF PURSE STRING AND CELL CRAWLING CLOSURE MECHANISMS
Zach Kamran,1 Katie Zellner,1 Harry Kyriazes,2 Christine M. Kraus,3 Jean-Baptiste Reynier,1 and Jocelyn E. Malamy3
We identified cell crawling and purse string-mediated mechanisms of healing in Clytia epithelium that appear highly analogous of those seen in higher animals, suggesting that these mechanisms may have emerged in a common ancestor. Interestingly, we found that epithelial wound healing in Clytia is 75 to >600 times faster than in cultured cells or embryos of other animals previously studied, suggesting that Clytia may provide valuable clues about optimized healing efficiency. Finally, in Clytia, we show that damage to the basement membrane in a wound gap causes a rapid shift between the cell crawling and purse string mechanisms for wound closure. This is consistent with work in other systems showing that cells marginal to a wound choose between a super-cellular actin cable or lamellipodia formation to close wounds, and suggests a mechanism underlying this decision.
"Understanding Speech Patterns During Delays in Life Saving Interventions" Philadelphia, PA 2021
Presented and was one of two winners at the Drexel College for Computing & Informatics Doctoral Student Association Research Symposium.
"WOUND HEALING IN JELLYFISH" CHICAGO, IL, 2016
Presented at the Undergraduate Research Sympsoium for the Midstates Consortium for Math and Science,