Our goal is to investigate the connection between public health and environmental risk factors and develop technologies to mitigate risk. Our efforts include developing machine learning algorithms for predicting disease, identifying environmental risk factors for rare cancers, and developing sensors to help detect animals in distress.

Characterization of Equine Biomechanics Using Triple-Axis Accelereometer Data

We examined systems of coupled nonlinear oscillators by examining mode interactions in equines. Coupled oscillators are commonly found in nature, primarily in quadrupedal locomotion that is controlled by a central pattern generator capable of producing rhythmic gaits. Equine gait analysis can be modeled using a system composed of four coupled pendulums, where the pendulums can move both in and out of phase. Equines can transition between gaits by changing the network’s driving signal. By using 3D accelerometers and attaching these to common equine tack, we were able to monitor and detect abnormal motion patterns in equines. These data can be further used to diagnose and prevent lameness and future injury.

Close, S.L. et al., “Characterization of Equine Biomechanics Using Triple-Axis Accelerometer Data”, Frontiers in Sensors, in review, 2023.

Investigating the Effects of Birth Month on Rare Diseases

We researched the seasonal dependence of birth month associated with Langerhans cell histiocytosis (LCH), using data from patients collected through online histiocytosis support groups.  We found a correlation between birth month and LCH that was most prominent in the patients showing first symptoms of LCH at an early age (p = 0.003 and p = 0.0004, using two independent methods for establishing the significance of a seasonal dependence).  The seasonal dependence in the youngest patients suggests an environmental factor during pregnancy. In particular, the possibility of a causal correlation with an infection with a seasonal variation may be considered, as well as the role of maternal vitamin D, studied in autoimmune disorders including multiple sclerosis.

Close, I.R. et al., “Seasonallity of Birth Month in Patients Diagnosed with Langerhans Cell Histiocytosis (LCH)”, Pediatric Research, in press, 2021.

Analysis of age threshold. (A) Sample size for the reweighted standard deviation of monthly histograms for Langerhans cell histiocytosis (LCH) cases (age at presentation) filtered using an upper age threshold, and (B) p-value corresponding to the sample using the same upper age threshold. Histogram of the number of LCH cases binned by birth month, (C) using a range of upper age thresholds, and (D) using a range of lower age thresholds.

Developing Sensors to Detect Bees in Distress

Animals, including insects, are an important part of our world but are often threatened by human activities.  Bees often fly into swimming pools and drown.  Our goal was to develop a sensor system that could detect a drowning bee, determine its location, and rescue it.  As a first step, the purpose of this project was to study whether water sensors at the edge of a pool can be used to detect the waves made by a drowning bee.  We used a robotic, rubber bee that could mimic a live bee struggling in the water. We found that a drowning bee created a unique signature in the wave sensor data, compared to wind or a leaf falling into the water. We are currently investigating whether these low-cost sensors can be installed in pools in order to notify owners of animals in distress.

Sample wave data detected by water sensors for a bee dropped from 30 cm above the surface of the water.

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