Engineering Commons^™

Risk Of Injury Analysis In Depth Jump And Squat Jump, Curtis L. Tomasevicz, Jeffrey C. Woldstad, David.Jones@Unl.Edu

Department of Biological Systems Engineering: Papers and Publications

Introduction: The depth jump (DJ) and squat jump (SJ) are accepted ways to assess and train power producing ability but are not without risk of injury. Methods: Sixteen male participants (age = 21.7 ± 1.54 yrs., height = 177.7 ± 11.4 cm, mass = 77.7 ± 13.6 kg) were evaluated for power exertion capabilities while being assessed for risk of injury in the knee and low back through a range of resistances based on a percentage of participants’ heights in the DJ (0% through 50%) and bodyweights for the SJ (0% through 100%). Two variables were used to assess the …

Comparative Analyses Of Variable And Fixed Rate Irrigation And Nitrogen Management For Maize In Different Soil Types: Part I. Impact On Soil-Water Dynamics And Crop Evapotranspiration, Vasudha Sharma, Suat Irmak

Department of Biological Systems Engineering: Papers and Publications

Understanding the soil-water dynamics and maize evapotranspiration (ETc) under variable rate irrigation (VRI) and variable rate fertigation (VRF) management with respect to soil spatial variability constitutes the basis for developing effective variable rate water and nitrogen management strategies. This long-term research was designed to quantify and compare the soil-water dynamics, including available water (AW), and ETc during vegetative and reproductive growth periods of VRI, fixed rate irrigation (FRI) and no-irrigation (NI) under fixed rate fertigation (FRF), VRF and pre-plant (PP) nitrogen management in three different soil types [Crete silt loam (S1); Hastings silty clay loam (S2) and Hastings silt loam …

Engaging Farmers And The Agriculture Industry Through The Testing Agricultural Performance Solutions Program, Charles A. Burr, Daran Rudnick, Matt Stockton, Robert Tigner, Krystle Rhoades

Department of Biological Systems Engineering: Papers and Publications

The University of Nebraska–Lincoln Testing Agricultural Performance Solutions (TAPS) program involves use of farm management competitions to increase engagement across producers, industry, and universities.Participants make several management decisions throughout the growing season in a controlled field trial held at the university research station. Results are analyzed, and awards are presented for most profitable farm, most efficient farm, and farm with the greatest grain yield. The TAPS program involves several techniques for facilitating participatory assistance, including two-way communication and transformational learning. It has resulted in participants' questioning their past management decisions and realizing that they need to improve their marketing skills …

Introduction To Special Issue Of Irrigation Science: Improving Irrigation Management Across The Ogallala Aquifer, Usa, Allan A. Andales, Daran Rudnick, José L. Chávez

Department of Biological Systems Engineering: Papers and Publications

Groundwater stored in aquifers is a major source of irrigation water for many agricultural regions that receive insufficient precipitation for crop production. In the U.S.A., the High Plains aquifer (HPA) that underlies parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming supplies irrigation water for agricultural production. The HPA underlies around 450,658 km² (174,000 mi²) of which the Ogallala aquifer is the principal geologic formation underlying 347,059 km² (134,000 mi²) (Gutentag et al. 1984). The Ogallala aquifer is primarily a water table (unconfined) aquifer with saturated thickness ranging from 0 …

Comparison Of Object Detection And Patch-Based Classification Deep Learning Models On Mid- To Late-Seasonweed Detection In Uav Imagery, Arun Narenthiran Veeranampalayam Sivakumar, Jiating Li, Stephen Scott, Eric T. Psota, Amit J. Jhala, Joe D. Luck, Jiating Li

Department of Biological Systems Engineering: Papers and Publications

Mid- to late-season weeds that escape from the routine early-season weed management threaten agricultural production by creating a large number of seeds for several future growing seasons. Rapid and accurate detection of weed patches in field is the first step of site-specific weed management. In this study, object detection-based convolutional neural network models were trained and evaluated over low-altitude unmanned aerial vehicle (UAV) imagery for mid- to late-season weed detection in soybean fields. The performance of two object detection models, Faster RCNN and the Single Shot Detector (SSD), were evaluated and compared in terms of weed detection performance using mean …

Past, Present And Future Of Irrigation On The U.S. Great Plains, Steve R. Evett, Paul D. Colaizzi, Freddie R. Lamm, Susan A. O'Shaughnessy, Derek M. Heeren, Thomas J. Trout, William L. Kranz, Xiaomao Lin

Department of Biological Systems Engineering: Papers and Publications

Motivated by the need for sustainable water management and technology for next-generation crop production, the future of irrigation on the U.S. Great Plains was examined through the lenses of past changes in water supply, historical changes in irrigated area, and innovations in irrigation technology, management, and agronomy. We analyzed the history of irrigated agriculture through the 1900s to the present day. We focused particularly on the efficiency and water productivity of irrigation systems (application efficiency, crop water productivity, and irrigation water use productivity) as a connection between water resource management and agricultural production. Technology innovations have greatly increased the efficiency …

Classification Of Plant Moisture Conditions Using Canopy And Leaf Temperature Responses To Step Changes Of Incident Radiation, George Meyer, Ellen T. Paparozzi, Erin Stevens

Department of Biological Systems Engineering: Papers and Publications

Environmental and soil conditions affect plant productivity. Determining and understanding how plants respond to moisture stress may be considered in different ways, but often not easily done. This study focused on measuring canopy and individual leaf temperature response times of selected horticultural and agricultural crops, treated to very dry (moisture stress) and well-watered conditions, and subjected to an incident step radiation change at the top of the canopy, in a controlled environment at a constant air temperature. A light-emitting-diode (LED), grow light system, delivering approximately 400 μEinstein s-1 m-2 of photosynthetically-active-radiation (PAR) was turned on and off to produce light …

Retention Of Swine Slurry Constituents In Soil And Crop Residue As Affected By Setback Distance, John E. Gilley, Shannon L. Bartelt-Hunt, Kent M. Eskridge, Xu Li, Amy M. Schmidt, Daniel D. Snow

Department of Biological Systems Engineering: Papers and Publications

Setbacks are prescribed distances from surface waters within which manure application is not allowed. Little information is available concerning the retention of swine slurry constituents in soil and crop residue materials within setback areas. This study was conducted to measure the retention of selected constituents within a setback area following the upslope application of swine slurry and the introduction of simulated rainfall. The no-till cropland site had a slope gradient of 4.9% and a mean winter wheat residue cover of 7.73 Mg ha−1 . Soil and vegetative samples were collected on 3.7 m wide by 23.2 m long plots with …

Economic Comparisons Of Variable Rate Irrigation And Fertigation With Fixed (Uniform) Rate Irrigation And Fertigation And Pre-Plant Fertilizer Management For Maize In Three Soils, Vasudha Sharma, Suat Irmak

Department of Biological Systems Engineering: Papers and Publications

Extensive field research for data collection to conduct economic comparisons of variable rate irrigation (VRI) with fixed (uniform) rate irrigation (FRI) and no irrigation (NI) in combination with three nitrogen application strategies of fixed (uniform) rate fertigation (FRF), variable rate fertigation (VRF) and pre-plant nitrogen (PP) management for maize (Zea mays L.) were conducted. Research was conducted in three soil types [(i) Crete silt loam (S1); (ii) Hastings silty clay loam (S2); and (iii) Hastings silt loam (S3)] for three growing seasons (2015, 2016 and 2017) in Nebraska, USA. For the economic analyses, the average initial investment of the …

Development Of An In Vitro Intervertebral Disc Innervation Model To Screen Neuroinhibitory Biomaterials, Sarah M. Romereim, Caleb A. Johnston, Adan L. Redwine,, Rebecca A. Wachs

Department of Biological Systems Engineering: Papers and Publications

Pain originating from an intervertebral disc (discogenic pain) is a major source of chronic low back pain. Pathological innervation of the disc by pain‐sensing nerve fibers is thought to be a key component of discogenic pain, so treatment with biomaterials that have the ability to inhibit neurite growth will greatly benefit novel disc therapeutics. Currently, disc therapeutic biomaterials are rarely screened for their ability to modulate nerve growth, mainly due to a lack of models to screen neuromodulation. To address this deficit, our lab has engineered a three dimensional in vitro disc innervation model that mimics the interface between primary …

Extracellular Matrix Disparities In An Nkx2-5 Mutant Mouse Model Of Congenital Heart Disease, Deanna Bousalis, Christopher S. Lacko, Nora Hlavac, Fariz Alkassis, Rebecca A. Wachs, Sahba Mobini, Christine E. Schmidt, Hideko Kasahara

Department of Biological Systems Engineering: Papers and Publications

Congenital heart disease (CHD) affects almost one percent of all live births. Despite diagnostic and surgical reparative advances, the causes and mechanisms of CHD are still primarily unknown. The extracellular matrix plays a large role in cell communication, function, and differentiation, and therefore likely plays a role in disease development and pathophysiology. Cell adhesion and gap junction proteins, such as integrins and connexins, are also essential to cellular communication and behavior, and could interact directly (integrins) or indirectly (connexins) with the extracellular matrix. In this work, we explore disparities in the expression and spatial patterning of extracellular matrix, adhesion, and …

Evaluation Of Low-Cost Depth Cameras For Agricultural Applications, Isabella C.F.S. Condotta, Tami M. Brown-Bandl, Santosh Pitla, John P. Stinn, Késia O. Silva-Miranda

Department of Biological Systems Engineering: Papers and Publications

Low-cost depth-cameras have been used in many agricultural applications with reported advantages of low cost, reliability and speed of measurement. However, some problems were also reported and seem to be technology related, so understanding the limitations of each type of depth camera technology could provide a basis for technology selection and the development of research involving its use. The cameras use one or a combination of two of the three available technologies: structured light, time-of-flight (ToF), and stereoscopy. The objectives were to evaluate these different technologies for depth sensing, including measuring accuracy and repeatability of distance data and measurements at …

Biological Systems Engineering, Asmaa Abdella, Fernando Segato, Mark R. Wilkins

Department of Biological Systems Engineering: Papers and Publications

The present work studied the optimization of aeration rate, agitation rate and oxygen transfer and the use of various batch fermentation strategies for xylanase production from a recombinant Aspergillus nidulans strain in a 3 L stirred tank reactor. Maximum xylanase production of 1250 U/mL with productivity of 313 U/mL/day was obtained under an aeration rate of 2 vvm and an agitation rate of 400 rpm using batch fermentation. The optimum volumetric oxygen transfer coefficient (kLa) for efficient xylanase production was found to be 38.6 h1. Fed batch mode and repeated batch fermentation was also performed with kLa was 38.6 h1. …

Sensitivity Analysis Of Data-Driven Groundwater Forecasts To Hydroclimatic Controls In Irrigated Croplands, Alessandro Amaranto, Francesca Pianosi, Dimitri Solomatine, Gerald Corzo-Perez, Francisco Munoz-Arriola

Department of Biological Systems Engineering: Papers and Publications

In the last decades, advancements in computational science have greatly expanded the use of artificial neural networks (ANNs) in hydrogeology, including applications on groundwater forecast, variable selection, extended lead-times, and regime-specific analysis. However, ANN-model performance often omits the sensitivity to ob- servational uncertainties in hydroclimate forcings. The goal of this paper is to implement a data-driven modeling framework for assessing the sensitivity of ANN-based groundwater forecasts to the uncertainties in observational inputs across space, time, and hydrological regimes. The objectives are two-folded. The first objective is to couple an ANN model with the PAWN sensitivity analysis (SA). The second objective …

Capturing Spatial Variability In Maize And Soybean Using Stationary Sensor Nodes, Jasreman Singh, Derek M. Heeren, Yufeng Ge, Geng Bai

Department of Biological Systems Engineering: Papers and Publications

• Irrigation in agriculture maximizes crop yield and improves food security globally • Irrigation scheduling is strongly based on the ability to accurately estimate the appropriate amount and timing of water application • The timing of the irrigation can best be informed through the crop canopy stress, and the amount of irrigation is informed through soil moisture depletion

• Developing upper (non-water stressed) and lower (non-transpiring) baselines for irrigated and non-irrigated maize and soybean • Investigating the relationship between the canopy stress and the soil moisture stress

The canopy temperature stress and soil moisture depletion had stronger correlation for non-irrigated …

Evidence Of Arithmetical Uncertainty In Estimation Of Light And Water Use Efficiency, Meetpal S. Kukal, Suat Irmak Dr.

Department of Biological Systems Engineering: Papers and Publications

It was demonstrated that conventional resource use efficiency (RUE) estimation methodology is largely subject to arithmetic weakness. Extensive field research data on aboveground biomass (AGB), absorbed photosynthetically active radiation (APAR), and crop evapotranspiration (ETc) in maize, soybean, sorghum, and winter wheat confirmed this methodological bias for light use efficiency (LUE) and water use efficiency (WUE) estimation. LUE and WUE were derived using cumulated (data aggregates across samplings) and independent (data increments across samplings) approaches. Use of cumulated data yielded strong-but-false correlation between AGB and APAR or Etc, being a statistical artefact. RUE values from an independent (data increments across samplings) …

Predicting Escherichia Coli Loads In Cascading Dams With Machine Learning: An Integration Of Hydrometeorology, Animal Density And Grazing Pattern, Olufemi P. Abimbola, Aaron R. Mittelstet, Tiffany Messer, Elaine D. Berry, Shannon L. Bartelt-Hunt, Samuel Hansen

Department of Biological Systems Engineering: Papers and Publications

Accurate prediction of Escherichia coli contamination in surface waters is challenging due to considerable uncertainty in the physical, chemical and biological variables that control E. coli occurrence and sources in surface waters. This study proposes a novel approach by integrating hydro-climatic variables as well as animal density and grazing pattern in the feature selection modeling phase to increase E. coli prediction accuracy for two cascading dams at the USMeat Animal Research Center (USMARC), Nebraska. Predictive models were developed using regression techniques and an artificial neural network (ANN). Two adaptive neuro-fuzzy inference system (ANFIS) structures including subtractive clustering and fuzzy c-means …

Banning Carbon Nanotubes Would Be Scientifically Unjustified And Damaging To Innovation, Daniel A. Heller, Prakrit V. Jena, Matteo Pasquali, Kostas Kostarelos, Lucia G. Delogu, Rachel E. Meidl, Slava V. Rotkin, David A. Scheinberg, Robert E. Schwartz, Mauricio Terrones, Yu Huang Wang, Alberto Bianco, Ardemis A. Boghossian, Sofie Cambré, Laurent Cognet, Simon R. Corrie, Philip Demokritou, Silvia Giordani, Tobias Hertel, Tetyana Ignatova, Mohammad F. Islam, Nicole M. Iverson, Anand Jagota, Dawid Janas, Junichiro Kono, Sebastian Kruss, Markita P. Landry, Yan Li, Richard Martel, Shigeo Maruyama, Anton V. Naumov, Maurizio Prato, Susan J. Quinn, Daniel Roxbury, Michael S. Strano, James M. Tour, R. Bruce Weisman, Wim Wenseleers, Masako Yudasaka

Department of Biological Systems Engineering: Papers and Publications

In a recent correspondence, the Swedish non-profit organization ChemSec announced the addition of carbon nanotubes to the SIN (‘Substitute It Now’) list1. Carbon nanotubes were added as an entire material class that “should be restricted or banned in the EU.” We believe that this recommendation confuses researchers and the public as it is based on evidence from a very narrow subset of data. Such a designation will likely hinder innovations that could lead to safe and effective applications of carbon nanotubes. Furthermore, this line of reasoning could damage other fields of science and technology, if applied similarly. We have worked …

Rapeseed Stand Count Estimation At Leaf Development Stages With Uav Imagery And Convolutional Neural Networks, Biquan Zhao, Chenghai Yang, Yeyin Shi, Qingxi Liao, Guangsheng Zhou, Chufeng Wang, Tianjin Xie, Zhao Jiang, Dongyan Zhang, Wanneng Yang, Chenglong Huang, Jing Xie, Jian Zhang

Department of Biological Systems Engineering: Papers and Publications

Rapeseed is an important oil crop in China. Timely estimation of rapeseed stand count at early growth stages provides useful information for precision fertilization, irrigation, and yield prediction. Based on the nature of rapeseed, the number of tillering leaves is strongly related to its growth stages. However, no field study has been reported on estimating rapeseed stand count by the number of leaves recognized with convolutional neural networks (CNNs) in unmanned aerial vehicle (UAV) imagery. The objectives of this study were to provide a case for rapeseed stand counting with reference to the existing knowledge of the number of leaves …

Representing Organic Matter Thermodynamics In Biogeochemical Reations Via Substrate-Explicit Modeling, Hyun-Seob Song, James C. Stegen, Emily B. Graham, Joon-Yong Lee, Vanessa A. Garayburu-Caruso, William C. Nelson, Xingyuan Chen, J. David Moulton, Timothy D. Scheibe

Department of Biological Systems Engineering: Papers and Publications

Predictive biogeochemical modeling requires data-model integration that enables explicit representation of the sophisticated roles of microbial processes that transform substrates. Data from high-resolution organic matter (OM) characterization are increasingly available and can serve as a critical resource for this purpose, but their incorporation into biogeochemical models is often prohibited due to an over-simplified description of reaction networks. To fill this gap, we proposed a new concept of biogeochemical modeling—termed substrate-explicit modeling—that enables parameterizing OM-specific oxidative degradation pathways and reaction rates based on the thermodynamic properties of OM pools. Based on previous developments in the literature, we characterized the resulting kinetic …

Predicting Total Petroleum Hydrocarbons In Field Soils With Vis–Nir Models Developed On Laboratory-Constructed Samples, Nuwan K. Wijewardane, Yufeng Ge, Natasha Sihota, Thomas Hoelen, Toni Miaso, David C. Weindorf

Department of Biological Systems Engineering: Papers and Publications

Accurate quantification of petroleum hydrocarbons (PHCs) is required for optimizing remedial efforts at oil spill sites. While evaluating total petroleum hydrocarbons (TPH) in soils is often conducted using costly and time-consuming laboratory methods, visible and near-infrared reflectance spectroscopy (Vis–NIR) has been proven to be a rapid and cost-effective field-based method for soil TPH quantification. This study investigated whether Vis–NIR models calibrated from laboratory-constructed PHC soil samples could be used to accurately estimate TPH concentration of field samples. To evaluate this, a laboratory sample set was constructed by mixing crude oil with uncontaminated soil samples, and two field sample sets (F1 …

High-Throughput Screening Of Clinically Approved Drugs That Prime Nonviral Gene Delivery To Human Mesenchymal Stem Cells, Tyler Kozisek, Andrew Hamann, Albert Nguyen, Michael Miller, Sarah Plautz, Angela K. Pannier

Department of Biological Systems Engineering: Papers and Publications

Background: Human mesenchymal stem cells (hMSCs) are intensely researched for applications in cell therapeutics due to their unique properties, however, intrinsic therapeutic properties of hMSCs could be enhanced by genetic modification. Viral transduction is efficient, but suffers from safety issues. Conversely, nonviral gene delivery, while safer compared to viral, suffers from inefficiency and cytotoxicity, especially in hMSCs. To address the shortcomings of nonviral gene delivery to hMSCs, our lab has previously demonstrated that pharmacological ‘priming’ of hMSCs with the glucocorticoid dexamethasone can significantly increase transfection in hMSCs by modulating transfection-induced cytotoxicity. This work seeks to establish a library of transfection …

Deep Learning Predicts Microbial Interactions From Self-Organized Spatiotemporal Patterns, Joon-Yong Lee, Natalie C. Sadler, Robert G. Egbert, Christopher R. Anderton, Kirsten S. Hofmockel, Janet K. Jansson, Hyun-Seob Song

Department of Biological Systems Engineering: Papers and Publications

Microbial communities organize into spatial patterns that are largely governed by interspecies interactions. This phenomenon is an important metric for understanding community functional dynamics, yet the use of spatial patterns for predicting microbial interactions is currently lacking. Here we propose supervised deep learning as a new tool for network inference. An agent-based model was used to simulate the spatiotemporal evolution of two interacting organisms under diverse growth and interaction scenarios, the data of which was subsequently used to train deep neural networks. For small-size domains (100 mm x 100 mm) over which interaction coefficients are assumed to be invariant, we …

Predicting Escherichia Coli Loads In Cascading Dams With Machine Learning: An Integration Of Hydrometeorology, Animal Density And Grazing Pattern, Olufemi P. Abimbola, Aaron R. Mittelstet, Tiffany Messer, Elaine D. Berry, Shannon L. Bartelt-Hunt, Samuel Hansen

Department of Biological Systems Engineering: Papers and Publications

Accurate prediction of Escherichia coli contamination in surface waters is challenging due to considerable uncertainty in the physical, chemical and biological variables that control E. coli occurrence and sources in surface waters. This study proposes a novel approach by integrating hydro-climatic variables as well as animal density and grazing pattern in the feature selection modeling phase to increase E. coli prediction accuracy for two cascading dams at the US Meat Animal Research Center (USMARC), Nebraska. Predictive models were developed using regression techniques and an artificial neural network (ANN). Two adaptive neuro-fuzzy inference system (ANFIS) structures including subtractive clustering and fuzzy …

Evaluation Of Low-Cost Depth Cameras For Agricultural Applications, Isabella C.F.S. Condotta, T. M. Brown-Brandl, Santosh Pitla, John P. Stinn, Késia O. Silva-Miranda

Department of Biological Systems Engineering: Papers and Publications

Low-cost depth-cameras have been used in many agricultural applications with reported advantages of low cost, reliability and speed of measurement. However, some problems were also reported and seem to be technology- related, so understanding the limitations of each type of depth camera technology could provide a basis for technology selection and the development of research involving its use. The cameras use one or a combination of two of the three available technologies: structured light, time-of-flight (ToF), and stereoscopy. The objectives were to evaluate these different technologies for depth sensing, including measuring accuracy and repeatability of distance data and measurements at …

Classification Of Tactile And Motor Velocity-Evoked Hemodynamic Response In Primary Somatosensory And Motor Cortices As Measured By Functional Near-Infrared Spectroscopy, Mohsen Hozan, Jacob Greenwood, Michaela Sullivan, Steven M. Barlow

Department of Biological Systems Engineering: Papers and Publications

Functional near-infrared spectroscopy (fNIRS) is an emerging technique in studying cerebral hemodynamics; however, consensus on the analysis methods and the clinical applications has yet to be established. In this study, we demonstrate the results of a pilot fNIRS study of cerebral hemodynamic response (HR) evoked by pneumotactile and sensorimotor stimuli on the dominant hand. Our goal is to find the optimal stimulus parameters to maximally evoke HR in the primary somatosensory and motor cortices. We use a pulsatile pneumatic array of 14 tactile cells that were attached to the glabrous surface of the dominant hand, with a patterned stimulus that …

Glucocorticoid Priming Of Nonviral Gene Delivery To Hmscs Increases Transfection By Reducing Induced Stresses, Andrew Hamann, Tyler Kozisek, Kelly Broad, Angela K. Pannier

Department of Biological Systems Engineering: Papers and Publications

Human mesenchymal stem cells (hMSCs) are under study for cell and gene therapeutics because of their immunomodulatory and regenerative properties. Safe and efficient gene delivery could increase hMSC clinical potential by enabling expression of transgenes for control over factor production, behavior, and differentiation. Viral delivery is efficient but suffers from safety issues, while nonviral methods are safe but highly inefficient, especially in hMSCs. We previously demonstrated that priming cells with glucocorticoids (Gcs) before delivery of DNA complexes significantly increases hMSC transfection, which correlates with a rescue of transfection-induced metabolic and protein synthesis decline, and apoptosis. In this work, we show …

Ultrasmall Mixed Eu−Gd Oxide Nanoparticles For Multimodal Fluorescence And Magnetic Resonance Imaging Of Passive Accumulation And Retention In Tbi, Badrul Alam Bony, Hunter A. Miller, Aria W. Tarudji, Connor C. Gee, Anandakumar Sarella, Michael G. Nichols, Forrest Kievit

Department of Biological Systems Engineering: Papers and Publications

Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. TBI can have a long-term impact on the quality of life for survivors of all ages. However, there remains no approved treatment that improves outcomes following TBI, which is partially due to poor delivery of therapies into the brain. Therefore, there is a significant unmet need to develop more effective delivery strategies that increase the accumulation and retention of potentially efficacious treatments in the injured brain. Recent work has revealed that nanoparticles (NPs) may offer a promising approach for site-specific delivery; however, a detailed understanding of the …

Optimal Depth Jump Height Quantified As Percentage Of Athlete Stature, Curtis L. Tomasevicz, Ryan Hasenkamp, Jack W. Ransone, David Jones

Department of Biological Systems Engineering: Papers and Publications

Purpose: An individual’s optimal depth jump platform height provides a resistive force which allows an athlete to rebound with substantial velocity resulting in maximum power exertion. The objective of this investigation was to show that the optimal platform height in a depth jump can be quantified as a percentage of individual body stature which can serve as measurable quantified value. Although athlete height is not highly correlated to power ability nor does a universal height exist, this value can provide a basis for a rehabilitation or strength and conditioning program. The desired intensity of a program can be prescribed as …

Classification Of Tactile And Motor Velocity-Evoked Hemodynamic Response In Primary Somatosensory And Motor Cortices As Measured By Functional Near-Infrared Spectroscopy

Department of Biological Systems Engineering: Papers and Publications

Functional near-infrared spectroscopy (fNIRS) is an emerging technique in studying cerebral hemodynamics; however, consensus on the analysis methods and the clinical applications has yet to be established. In this study, we demonstrate the results of a pilot fNIRS study of cerebral hemodynamic response (HR) evoked by pneumotactile and sensorimotor stimuli on the dominant hand. Our goal is to find the optimal stimulus parameters to maximally evoke HR in the primary somatosensory and motor cortices. We use a pulsatile pneumatic array of 14 tactile cells that were attached to the glabrous surface of the dominant hand, with a patterned stimulus that …