Journal article
Co-Interpreting Movement With Sensors: Assessing Parkinson's Patients' Deep Brain Stimulation Programming
Human-computer interaction, v 31(3-4), pp 227-260
03 Jul 2016
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Movement sensors have been touted as providing the next generation of health care through objective measurements that will replace "subjective" health assessments and remove the fallible memory of patients from health decision making. However, assessing the level of disability and assessing the efficacy of treatment are iterative and constructive acts reliant on an alignment of shared perceptions between clinician and patient. The challenge then is to utilize movement sensors as a resource for this co-interpretation as opposed to a replacement. The examples presented in this article are from fieldwork of Parkinson's patients' deep brain stimulation programming sessions. We employed a design research study that included observations of the noninstrumented movement assessment in 10 naturally occurring deep brain stimulation clinical programming sessions, design explorations of a sensor for evaluating upper limb movement, and the resulting uptake of the system in the assessment and co-interpretation practices by clinicians and patients through a deployment of this sensor in eight naturally occurring clinical assessments. Our findings highlight how sensors can provide much needed co-interpreted assessment of movement but sensors can also intrude on this process through clinician or sensor authority.
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Details
- Title
- Co-Interpreting Movement With Sensors: Assessing Parkinson's Patients' Deep Brain Stimulation Programming
- Creators
- Helena M. Mentis - University of Maryland, Baltimore CountyRita Shewbridge - University of Maryland, Baltimore CountySharon Powell - University of Maryland, BaltimoreMelissa Armstrong - University of Maryland, BaltimorePaul Fishman - University of Maryland, BaltimoreLisa Shulman - University of Maryland, Baltimore
- Publication Details
- Human-computer interaction, v 31(3-4), pp 227-260
- Publisher
- Taylor & Francis
- Number of pages
- 34
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Web of Science ID
- WOS:000375601300003
- Scopus ID
- 2-s2.0-84946606142
- Other Identifier
- 991021916516204721
UN Sustainable Development Goals (SDGs)
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Cybernetics
- Computer Science, Theory & Methods