Characterization of the mechanosensitivity of tactile receptors using multivariate logistical regression

Sam Bradshaw, Fred J. Looft, Sean S. Kohles, Peter Grigg

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations


Our initial objective was to establish a framework for modeling afferent mechanoreceptor behavior under dynamic compressive loads using multivariate regression techniques. A multivariate logistical model of the system was chosen because the system contains continuous input variables and a singular binary output variable corresponding to an "all-or-nothing" nerve action potential. Subsequently, this method was used to quantitatively assess the sensitivity of rapidly adapting afferents in rat hairy skin to the stimulus metrics stress, strain, and their time derivatives. In-vitro experiments involving compressive stimulation of isolated afferents using pseudorandom and non-repeating noise sequences were completed and an analysis of the data was performed using multivariate logistical regression.

Original languageEnglish (US)
Pages (from-to)65-66
Number of pages2
JournalProceedings of the IEEE Annual Northeast Bioengineering Conference, NEBEC
StatePublished - 2001
Externally publishedYes
Event27th IEEE Annual Northeast Bioengineering Conference - Storrs, CT, United States
Duration: Mar 31 2001Apr 1 2001

ASJC Scopus subject areas

  • Chemical Engineering(all)


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