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Browsing VTechWorks Archives by Author "Abaid, Nicole"

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    Classical and adaptive control of ex vivo skeletal muscle contractions using Functional Electrical Stimulation (FES)
    Cienfuegos, Paola Jaramillo; Shoemaker, Adam; Grange, Robert W.; Abaid, Nicole; Leonessa, Alexander (PLOS, 2017-03-08)
    Functional Electrical Stimulation is a promising approach to treat patients by stimulating the peripheral nerves and their corresponding motor neurons using electrical current. This technique helps maintain muscle mass and promote blood flow in the absence of a functioning nervous system. The goal of this work is to control muscle contractions from FES via three different algorithms and assess the most appropriate controller providing effective stimulation of the muscle. An open-loop system and a closed-loop system with three types of model-free feedback controllers were assessed for tracking control of skeletal muscle contractions: a Proportional-Integral (PI) controller, a Model Reference Adaptive Control algorithm, and an Adaptive Augmented PI system. Furthermore, a mathematical model of a muscle-mass-spring system was implemented in simulation to test the open-loop case and closed-loop controllers. These simulations were carried out and then validated through experiments ex vivo. The experiments included muscle contractions following four distinct trajectories: a step, sine, ramp, and square wave. Overall, the closed-loop controllers followed the stimulation trajectories set for all the simulated and tested muscles. When comparing the experimental outcomes of each controller, we concluded that the Adaptive Augmented PI algorithm provided the best closed-loop performance for speed of convergence and disturbance rejection.
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    Collaborative Multi-Robot Multi-Human Teams in Search and Rescue
    Williams, Ryan K.; Abaid, Nicole; McClure, James; Lau, Nathan; Heintzman, Larkin; Hashimoto, Amanda; Wang, Tianzi; Patnayak, Chinmaya; Kumar, Akshay (2022-04-30)
    Robots such as unmanned aerial vehicles (UAVs) deployed for search and rescue (SAR) can explore areas where human searchers cannot easily go and gather information on scales that can transform SAR strategy. Multi-UAV teams therefore have the potential to transform SAR by augmenting the capabilities of human teams and providing information that would otherwise be inaccessible. Our research aims to develop new theory and technologies for field deploying autonomous UAVs and managing multi-UAV teams working in concert with multi-human teams for SAR. Specifically, in this paper we summarize our work in progress towards these goals, including: (1) a multi-UAV search path planner that adapts to human behavior; (2) an in-field distributed computing prototype that supports multi-UAV computation and communication; (3) behavioral modeling that yields spatially localized predictions of lost person location; and (4) an interface between human searchers and UAVs that facilitates human-UAV interaction over a wide range of autonomy.
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    The Effect of Binaural Beats on Visuospatial Working Memory and Cortical Connectivity
    Beauchene, Christine; Abaid, Nicole; Moran, Rosalyn J.; Diana, Rachel A.; Leonessa, Alexander (PLOS, 2016-11-28)
    Binaural beats utilize a phenomenon that occurs within the cortex when two different frequencies are presented separately to each ear. This procedure produces a third phantom binaural beat, whose frequency is equal to the difference of the two presented tones and which can be manipulated for non-invasive brain stimulation. The effects of binaural beats on working memory, the system in control of temporary retention and online organization of thoughts for successful goal directed behavior, have not been well studied. Furthermore, no studies have evaluated the effects of binaural beats on brain connectivity during working memory tasks. In this study, we determined the effects of different acoustic stimulation conditions on participant response accuracy and cortical network topology, as measured by EEG recordings, during a visuospatial working memory task. Three acoustic stimulation control conditions and three binaural beat stimulation conditions were used: None, Pure Tone, Classical Music, 5Hz binaural beats, 10Hz binaural beats, and 15Hz binaural beats. We found that listening to 15Hz binaural beats during a visuospatial working memory task not only increased the response accuracy, but also modified the strengths of the cortical networks during the task. The three auditory control conditions and the 5Hz and 10Hz binaural beats all decreased accuracy. Based on graphical network analyses, the cortical activity during 15Hz binaural beats produced networks characteristic of high information transfer with consistent connection strengths throughout the visuospatial working memory task.
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    Effects of Environmental Clutter on Synthesized Chiropteran Echolocation Signals in an Anechoic Chamber
    Freeze, Samuel R.; Shirazi, Masoud; Abaid, Nicole; Ford, W. Mark; Silvis, Alexander; Hakkenberg, Dawn (MDPI, 2021-06-11)
    Ultrasonic bat detectors are useful for research and monitoring purposes to assess occupancy and relative activity of bat communities. Environmental “clutter” such as tree boles and foliage can affect the recording quality and identification of bat echolocation calls collected using ultrasonic detectors. It can also affect the transmission of calls and recognition by bats when using acoustic lure devices to attract bats to mist-nets. Bat detectors are often placed in forests, yet automatic identification programs are trained on call libraries using echolocation passes recorded largely from open spaces. Research indicates that using clutter-recorded calls can increase classification accuracy for some bat species and decrease accuracy for others, but a detailed understanding of how clutter impacts the recording and identification of echolocation calls remains elusive. To clarify this, we experimentally investigated how two measures of clutter (i.e., total basal area and number of stems of simulated woody growth, as well as recording angle) affected the recording and classification of a synthesized echolocation signal under controlled conditions in an anechoic chamber. Recording angle (i.e., receiver position relative to emitter) significantly influenced the probability of correct classification and differed significantly for many of the call parameters measured. The probability of recording echo pulses was also a function of clutter but only for the detector angle at 0° from the emitter that could receive deflected pulses. Overall, the two clutter metrics were overshadowed by proximity and angle of the receiver to the sound source but some deviations from the synthesized call in terms of maximum, minimum, and mean frequency parameters were observed. Results from our work may aid efforts to better understand underlying environmental conditions that produce false-positive and -negative identifications for bat species of interest and how this could be used to adjust survey accuracy estimates. Our results also help pave the way for future research into the development of acoustic lure technology by exploring the effects of environmental clutter on ultrasound transmission.
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    Extracting Interactions between Flying Bat Pairs Using Model-Free Methods
    Roy, Subhradeep; Howes, Kayla; Müller, Rolf; Butail, Sachit; Abaid, Nicole (MDPI, 2019-01-09)
    Social animals exhibit collective behavior whereby they negotiate to reach an agreement, such as the coordination of group motion. Bats are unique among most social animals, since they use active sensory echolocation by emitting ultrasonic waves and sensing echoes to navigate. Bats’ use of active sensing may result in acoustic interference from peers, driving different behavior when they fly together rather than alone. The present study explores quantitative methods that can be used to understand whether bats flying in pairs move independently of each other or interact. The study used field data from bats in flight and is based on the assumption that interactions between two bats are evidenced in their flight patterns. To quantify pairwise interaction, we defined the strength of coupling using model-free methods from dynamical systems and information theory. We used a control condition to eliminate similarities in flight path due to environmental geometry. Our research question is whether these data-driven methods identify directed coupling between bats from their flight paths and, if so, whether the results are consistent between methods. Results demonstrate evidence of information exchange between flying bat pairs, and, in particular, we find significant evidence of rear-to-front coupling in bats’ turning behavior when they fly in the absence of obstacles.
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    Transfer Entropy Analysis of Interactions between Bats Using Position and Echolocation Data
    Shaffer, Irena; Abaid, Nicole (MDPI, 2020-10-19)
    Many animal species, including many species of bats, exhibit collective behavior where groups of individuals coordinate their motion. Bats are unique among these animals in that they use the active sensing mechanism of echolocation as their primary means of navigation. Due to their use of echolocation in large groups, bats run the risk of signal interference from sonar jamming. However, several species of bats have developed strategies to prevent interference, which may lead to different behavior when flying with conspecifics than when flying alone. This study seeks to explore the role of this acoustic sensing on the behavior of bat pairs flying together. Field data from a maternity colony of gray bats (Myotis grisescens) were collected using an array of cameras and microphones. These data were analyzed using the information theoretic measure of transfer entropy in order to quantify the interaction between pairs of bats and to determine the effect echolocation calls have on this interaction. This study expands on previous work that only computed information theoretic measures on the 3D position of bats without echolocation calls or that looked at the echolocation calls without using information theoretic analyses. Results show that there is evidence of information transfer between bats flying in pairs when time series for the speed of the bats and their turning behavior are used in the analysis. Unidirectional information transfer was found in some subsets of the data which could be evidence of a leader–follower interaction.