Characterizing Touch Using Pressure Data and Auto Regressive Models
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Auteurs : Shlomi Laufer ; Carla M. Pugh ; Barry D. Van VeenSource :
- Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference [ 1557-170X ] ; 2014.
Abstract
Palpation plays a critical role in medical physical exams. Despite the wide range of exams, there are several reproducible and subconscious sets of maneuvers that are common to examination by palpation. Previous studies by our group demonstrated the use of manikins and pressure sensors for measuring and quantifying how physicians palpate during different physical exams. In this study we develop mathematical models that describe some of these common maneuvers. Dynamic pressure data was measured using a simplified testbed and different autoregressive models were used to describe the motion of interest. The frequency, direction and type of motion used were identified from the models. We believe these models can a provide better understanding of how humans explore objects in general and more specifically give insights to understand medical physical exams.
Url:
DOI: 10.1109/EMBC.2014.6943967
PubMed: 25570335
PubMed Central: 4288476
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PMC:4288476Le document en format XML
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<front><div type="abstract" xml:lang="en"><p id="P1">Palpation plays a critical role in medical physical exams. Despite the wide range of exams, there are several reproducible and subconscious sets of maneuvers that are common to examination by palpation. Previous studies by our group demonstrated the use of manikins and pressure sensors for measuring and quantifying how physicians palpate during different physical exams. In this study we develop mathematical models that describe some of these common maneuvers. Dynamic pressure data was measured using a simplified testbed and different autoregressive models were used to describe the motion of interest. The frequency, direction and type of motion used were identified from the models. We believe these models can a provide better understanding of how humans explore objects in general and more specifically give insights to understand medical physical exams.</p>
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