Journal article
An Analysis of Speech as a Modality for Activity Recognition during Complex Medical Teamwork
International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare, v 2018, pp 88-97
May 2018
PMID: 30323960
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We analyzed the nature of verbal communication among team members in a dynamic medical setting of trauma resuscitation to inform the design of a speech-based automatic activity recognition system. Using speech transcripts from 20 resuscitations, we identified common keywords and speech patterns for different resuscitation activities. Based on these patterns, we developed narrative schemas (speech “workflow” models) for five most frequently performed activities and applied linguistic models to represent relationships between sentences. We evaluated the narrative schemas with 17 new cases, finding that all five schemas adequately represented speech during activities and could serve as a basis for speech-based activity recognition. We also identified similarities between narrative schemas of different activities. We conclude with design implications and challenges associated with speech-based activity recognition in complex medical processes.
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Details
- Title
- An Analysis of Speech as a Modality for Activity Recognition during Complex Medical Teamwork
- Creators
- Swathi Jagannath - Drexel University Philadelphia, PA, United StatesAleksandra Sarcevic - Drexel University Philadelphia, PA, United StatesIvan Marsic - Rutgers University Piscataway, NJ, United States
- Publication Details
- International Conference on Pervasive Computing Technologies for Healthcare : [proceedings]. International Conference on Pervasive Computing Technologies for Healthcare, v 2018, pp 88-97
- Publisher
- Association for Computing Machinery
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000614057600011
- Scopus ID
- 2-s2.0-85116311572
- Other Identifier
- 991014976809604721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Health Care Sciences & Services
- Medical Informatics