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- All Subjects: robotics
Description
This study consisted of several related projects on dynamic spatial hearing by both human and robot listeners. The first experiment investigated the maximum number of sound sources that human listeners could localize at the same time. Speech stimuli were presented simultaneously from different loudspeakers at multiple time intervals. The maximum of perceived sound sources was close to four. The second experiment asked whether the amplitude modulation of multiple static sound sources could lead to the perception of auditory motion. On the horizontal and vertical planes, four independent noise sound sources with 60° spacing were amplitude modulated with consecutively larger phase delay. At lower modulation rates, motion could be perceived by human listeners in both cases. The third experiment asked whether several sources at static positions could serve as "acoustic landmarks" to improve the localization of other sources. Four continuous speech sound sources were placed on the horizontal plane with 90° spacing and served as the landmarks. The task was to localize a noise that was played for only three seconds when the listener was passively rotated in a chair in the middle of the loudspeaker array. The human listeners were better able to localize the sound sources with landmarks than without. The other experiments were with the aid of an acoustic manikin in an attempt to fuse binaural recording and motion data to localize sounds sources. A dummy head with recording devices was mounted on top of a rotating chair and motion data was collected. The fourth experiment showed that an Extended Kalman Filter could be used to localize sound sources in a recursive manner. The fifth experiment demonstrated the use of a fitting method for separating multiple sounds sources.
ContributorsZhong, Xuan (Author) / Yost, William (Thesis advisor) / Zhou, Yi (Committee member) / Dorman, Michael (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2015
Description
Robotic rehabilitation for upper limb post-stroke recovery is a developing technology. However, there are major issues in the implementation of this type of rehabilitation, issues which decrease efficacy. Two of the major solutions currently being explored to the upper limb post-stroke rehabilitation problem are the use of socially assistive rehabilitative robots, robots which directly interact with patients, and the use of exoskeleton-based systems of rehabilitation. While there is great promise in both of these techniques, they currently lack sufficient efficacy to objectively justify their costs. The overall efficacy to both of these techniques is about the same as conventional therapy, yet each has higher overhead costs that conventional therapy does. However there are associated long-term cost savings in each case, meaning that the actual current viability of either of these techniques is somewhat nebulous. In both cases, the problems which decrease technique viability are largely related to joint action, the interaction between robot and human in completing specific tasks, and issues in robot adaptability that make joint action difficult. As such, the largest part of current research into rehabilitative robotics aims to make robots behave in more "human-like" manners or to bypass the joint action problem entirely.
ContributorsRamakrishna, Vijay Kambhampati (Author) / Helms Tillery, Stephen (Thesis director) / Buneo, Christopher (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / W. P. Carey School of Business (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Electroencephalogram (EEG) used simultaneously with video monitoring can record detailed patient physiology during a seizure to aid diagnosis. However, current patient monitoring systems typically require a patient to stay in view of a fixed camera limiting their freedom of movement. The goal of this project is to design an automatic patient monitoring system with software to track patient movement in order to increase a patient's mobility. This report discusses the impact of an automatic patient monitoring system and the design steps used to create and test a functional prototype.
ContributorsBui, Robert Truong (Author) / Frakes, David (Thesis director) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Electrical Engineering Program (Contributor)
Created2014-05
Description
The goal of this project was to use the sense of touch to investigate tactile cues during multidigit rotational manipulations of objects. A robotic arm and hand equipped with three multimodal tactile sensors were used to gather data about skin deformation during rotation of a haptic knob. Three different rotation speeds and two levels of rotation resistance were used to investigate tactile cues during knob rotation. In the future, this multidigit task can be generalized to similar rotational tasks, such as opening a bottle or turning a doorknob.
ContributorsChalla, Santhi Priya (Author) / Santos, Veronica (Thesis director) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / School of Earth and Space Exploration (Contributor)
Created2014-05
Description
Humans have an inherent capability of performing highly dexterous and skillful tasks with their arms, involving maintaining posture, movement and interacting with the environment. The latter requires for them to control the dynamic characteristics of the upper limb musculoskeletal system. Inertia, damping and stiffness, a measure of mechanical impedance, gives a strong representation of these characteristics. Many previous studies have shown that the arm posture is a dominant factor for determining the end point impedance in a horizontal plane (transverse plane). The objective of this thesis is to characterize end point impedance of the human arm in the three dimensional (3D) space. Moreover, it investigates and models the control of the arm impedance due to increasing levels of muscle co-contraction. The characterization is done through experimental trials where human subjects maintained arm posture, while perturbed by a robot arm. Moreover, the subjects were asked to control the level of their arm muscles' co-contraction, using visual feedback of their muscles' activation, in order to investigate the effect of the muscle co-contraction on the arm impedance. The results of this study showed a very interesting, anisotropic increase of the arm stiffness due to muscle co-contraction. This can lead to very useful conclusions about the arm biomechanics as well as many implications for human motor control and more specifically the control of arm impedance through muscle co-contraction. The study finds implications for the EMG-based control of robots that physically interact with humans.
ContributorsPatel, Harshil Naresh (Author) / Artemiadis, Panagiotis (Thesis advisor) / Berman, Spring (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Neurological disorders are the leading cause of physical and cognitive declineglobally and affect nearly 15% of the current worldwide population. These disorders
include, but are not limited to, epilepsy, Alzheimer’s disease, Parkinson’s disease,
and multiple sclerosis. With the aging population, an increase in the prevalence of
neurodegenerative disorders is expected. Electrophysiological monitoring of neural
signals has been the gold standard for clinicians in diagnosing and treating neurological
disorders. However, advances in detection and stimulation techniques have paved the
way for relevant information not seen by standard procedures to be captured and
used in patient treatment. Amongst these advances have been improved analysis of
higher frequency activity and the increased concentration of alternative biomarkers,
specifically pH change, during states of increased neural activity. The design and
fabrication of devices with the ability to reliably interface with the brain on multiple
scales and modalities has been a significant challenge.
This dissertation introduces a novel, concentric, multi-scale micro-ECoG array
for neural applications specifically designed for seizure detection in epileptic patients.
This work investigates simultaneous detection and recording of adjacent neural tissue
using electrodes of different sizes during neural events. Signal fidelity from electrodes
of different sizes during in vivo experimentation are explored and analyzed to highlight
the advantages and disadvantages of using varying electrode sizes. Furthermore, the
novel multi-scale array was modified to perform multi-analyte detection experiments
of pH change and electrophysiological activity on the cortical surface during epileptic
events. This device highlights the ability to accurately monitor relevant information
from multiple electrode sizes and concurrently monitor multiple biomarkers during
clinical periods in one procedure that typically requires multiple surgeries.
ContributorsAkamine, Ian (Author) / Blain Christen, Jennifer (Thesis advisor) / Abbas, Jimmy (Committee member) / Muthuswamy, Jitendran (Committee member) / Goryll, Michael (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2024