Jon Erickson | Washington and Lee University | Department of Physics and Engineering

Bioelectricity Lab

My lab pursues projects at the boundary of engineering, physics and biology. We develop electronics hardware and automated signal processing algorithms.  Our current primary research interests is developing techniques for non-invasive monitoring of electrical activity patterns in the gastrointestinal system. These are the electrical waves that correlate to and/or correspond to the mixing and propulsion of food contents. Typically, this activity goes largely unnoticed in a normal, healthy state. Not so for the approximately 10-15 percent of people who suffer from a GI disorder (e.g. irritable bowel syndrome). The long term goal of the lab is to enable diagnostics that lead to better clinical care.

My lab has previously worked on developing optimal neural-electric stimuli for cockroach biobots.

In the more distant past, we have also investigated synaptic plasticity of primary rat neural cultures subjected to chronic stimuli.

Selected publications are listed at the bottom of this page.

Gastrointestinal Electrical Activity Patterns

We develop automated signal processing techniques analyze the big data sets resulting from high-resolution electrical recordings.  Our fully automated algorithms can: remove motion and other contaminating artifacts; identify slow waves and group them into individual propagating wavefronts; and identify spike bursts. We are also developing low-cost, open-source wireless hardware for gastrointestinal mapping studies. This work has been done in collaboration with the Auckland Bioengineering Institute GI Systems group. These algorithms are available in the user friendly data viewing and analysis GEMS software package.

 

Comparison of electrical images of gastric slow wave activity determined by an array of non-invasive body surface (top) and invasive serosal (bottom) electrode arrays. The slow move activity imaged with HR-EGG is highly correlated to the ground truth serosal activity, and is seen to move from right to left (antegrade direction) in both measurement modes. Automated signal processing techniques allow for accurate, rapid, and unbiased visualization and analysis. .

 

Intsy open-source, portable, multichannel bioamplier system. The system can record 32 or 64 channels. Data can be transmitted wirelessly (Bluetooth) or over USB for higher throughput. The system was designed especially for GI electrical recordings. Source files can be freely downloaded here

Hybrid Insect Robots

We design strategies and build neural-electric interfaces to control locomotion in various insects.  We have studied and defined optimal stimulus parameters (amplitude, frequency, duration, waveform type) for piloting Madagascar hissing cockroaches along a desired path. We published a journal article describing our findings. Our current work focuses on wireless tracking of biobot cockroaches as they move through a 3-D maze. We have also previously made grasshoppers hop on command

 

 

Top: Madagascar hissing cockroach (G. portentosa) implanted with thin micro electrodes atop 3-D treadmill trackball. A pair of optical mice record the motion in response to neural-electric stimulus.   Bottom: Trajectories following stimuli for stimuli applied to both cerci and right or left antenna.

Selected Publications

(* denotes undergraduate student co-author)

    GI electronics and algorithms:
  1. Erickson J, Hayes J*, Bustamanate M*, Joshi R*, Rwagaju A*, Paskaranandavadivel N, Angeli TR. (2018); Intsy: a low-cost, open-source, wirelessly multi-channel bioamplifier system, Ii>Physiollogical Measurement; 39: 035008. doi: 10.1088/1361-6579/aaad51. [www]
  2. Erickson J, Putney J*, Hilbert D*, O'Grady G, Cheng LK, and Angeli TR. (2016); Iterative Covariance-based Removal of Time-Synchronous Artifacts: Application to Gastrointestinal Electrical Recordings, IEEE Trans. Biomed. Eng. 63(11): 2262-2272. doi: 10.1109/TBME.2016.2521764. [www]
  3. Erickson J., Velasco-Castedo R*., Obioha C. Cheng L.K., Angeli, T.R. and O'Grady G. (2013); Automated Algorithm for GI Spike Burst Detection and Demonstration of Efficacy in Ischemic Small Intestine. Annals of Biomedical Engineering. doi: 10.1007/s10439-013-0812-8. [www]


  4. Biobots:
  5. Erickson J., Herrera M.*, Bustamante M.*, Shingiro A.*, and Bowen T.*(2015); Effective Stimulus Parameters for Directed Locomotion in Madagascar Hissing Cockroach Biobot. PLoS ONE 10(8):e0134348. doi: 10.1371/journal.pone.0134348 [www]
  6. Giampalmo S.*, Absher B.*, Bourne W.T.*, Steves L.*, Vodenski V.*, O'Donnell P.*, and Erickson J. (2011) Generation of Complex Motor Patterns in American Grasshopper Via Current Controlled Thoracic Electrical Interfacing. Conf. Proc. IEEE-EMBS 2011, 1275 - 1278, doi: IEMBS.2011.6090300. [pdf]

 

 

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