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- Creators: Barrett, The Honors College
- Creators: Santello, Marco
- Resource Type: Text
Description
In recent years, machine learning and data mining technologies have received growing attention in several areas such as recommendation systems, natural language processing, speech and handwriting recognition, image processing and biomedical domain. Many of these applications which deal with physiological and biomedical data require person specific or person adaptive systems. The greatest challenge in developing such systems is the subject-dependent data variations or subject-based variability in physiological and biomedical data, which leads to difference in data distributions making the task of modeling these data, using traditional machine learning algorithms, complex and challenging. As a result, despite the wide application of machine learning, efficient deployment of its principles to model real-world data is still a challenge. This dissertation addresses the problem of subject based variability in physiological and biomedical data and proposes person adaptive prediction models based on novel transfer and active learning algorithms, an emerging field in machine learning. One of the significant contributions of this dissertation is a person adaptive method, for early detection of muscle fatigue using Surface Electromyogram signals, based on a new multi-source transfer learning algorithm. This dissertation also proposes a subject-independent algorithm for grading the progression of muscle fatigue from 0 to 1 level in a test subject, during isometric or dynamic contractions, at real-time. Besides subject based variability, biomedical image data also varies due to variations in their imaging techniques, leading to distribution differences between the image databases. Hence a classifier learned on one database may perform poorly on the other database. Another significant contribution of this dissertation has been the design and development of an efficient biomedical image data annotation framework, based on a novel combination of transfer learning and a new batch-mode active learning method, capable of addressing the distribution differences across databases. The methodologies developed in this dissertation are relevant and applicable to a large set of computing problems where there is a high variation of data between subjects or sources, such as face detection, pose detection and speech recognition. From a broader perspective, these frameworks can be viewed as a first step towards design of automated adaptive systems for real world data.
ContributorsChattopadhyay, Rita (Author) / Panchanathan, Sethuraman (Thesis advisor) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2013
Description
Myoelectric control is lled with potential to signicantly change human-robot interaction.
Humans desire compliant robots to safely interact in dynamic environments
associated with daily activities. As surface electromyography non-invasively measures
limb motion intent and correlates with joint stiness during co-contractions,
it has been identied as a candidate for naturally controlling such robots. However,
state-of-the-art myoelectric interfaces have struggled to achieve both enhanced
functionality and long-term reliability. As demands in myoelectric interfaces trend
toward simultaneous and proportional control of compliant robots, robust processing
of multi-muscle coordinations, or synergies, plays a larger role in the success of the
control scheme. This dissertation presents a framework enhancing the utility of myoelectric
interfaces by exploiting motor skill learning and
exible muscle synergies for
reliable long-term simultaneous and proportional control of multifunctional compliant
robots. The interface is learned as a new motor skill specic to the controller,
providing long-term performance enhancements without requiring any retraining or
recalibration of the system. Moreover, the framework oers control of both motion
and stiness simultaneously for intuitive and compliant human-robot interaction. The
framework is validated through a series of experiments characterizing motor learning
properties and demonstrating control capabilities not seen previously in the literature.
The results validate the approach as a viable option to remove the trade-o
between functionality and reliability that have hindered state-of-the-art myoelectric
interfaces. Thus, this research contributes to the expansion and enhancement of myoelectric
controlled applications beyond commonly perceived anthropomorphic and
\intuitive control" constraints and into more advanced robotic systems designed for
everyday tasks.
Humans desire compliant robots to safely interact in dynamic environments
associated with daily activities. As surface electromyography non-invasively measures
limb motion intent and correlates with joint stiness during co-contractions,
it has been identied as a candidate for naturally controlling such robots. However,
state-of-the-art myoelectric interfaces have struggled to achieve both enhanced
functionality and long-term reliability. As demands in myoelectric interfaces trend
toward simultaneous and proportional control of compliant robots, robust processing
of multi-muscle coordinations, or synergies, plays a larger role in the success of the
control scheme. This dissertation presents a framework enhancing the utility of myoelectric
interfaces by exploiting motor skill learning and
exible muscle synergies for
reliable long-term simultaneous and proportional control of multifunctional compliant
robots. The interface is learned as a new motor skill specic to the controller,
providing long-term performance enhancements without requiring any retraining or
recalibration of the system. Moreover, the framework oers control of both motion
and stiness simultaneously for intuitive and compliant human-robot interaction. The
framework is validated through a series of experiments characterizing motor learning
properties and demonstrating control capabilities not seen previously in the literature.
The results validate the approach as a viable option to remove the trade-o
between functionality and reliability that have hindered state-of-the-art myoelectric
interfaces. Thus, this research contributes to the expansion and enhancement of myoelectric
controlled applications beyond commonly perceived anthropomorphic and
\intuitive control" constraints and into more advanced robotic systems designed for
everyday tasks.
ContributorsIson, Mark (Author) / Artemiadis, Panagiotis (Thesis advisor) / Santello, Marco (Committee member) / Greger, Bradley (Committee member) / Berman, Spring (Committee member) / Sugar, Thomas (Committee member) / Fainekos, Georgios (Committee member) / Arizona State University (Publisher)
Created2015
Description
Bioscience High School, a small magnet high school located in Downtown Phoenix and a STEAM (Science, Technology, Engineering, Arts, Math) focused school, has been pushing to establish a computer science curriculum for all of their students from freshman to senior year. The school's Mision (Mission and Vision) is to: "..provide a rigorous, collaborative, and relevant academic program emphasizing an innovative, problem-based curriculum that develops literacy in the sciences, mathematics, and the arts, thus cultivating critical thinkers, creative problem-solvers, and compassionate citizens, who are able to thrive in our increasingly complex and technological communities." Computational thinking is an important part in developing a future problem solver Bioscience High School is looking to produce. Bioscience High School is unique in the fact that every student has a computer available for him or her to use. Therefore, it makes complete sense for the school to add computer science to their curriculum because one of the school's goals is to be able to utilize their resources to their full potential. However, the school's attempt at computer science integration falls short due to the lack of expertise amongst the math and science teachers. The lack of training and support has postponed the development of the program and they are desperately in need of someone with expertise in the field to help reboot the program. As a result, I've decided to create a course that is focused on teaching students the concepts of computational thinking and its application through Scratch and Arduino programming.
ContributorsLiu, Deming (Author) / Meuth, Ryan (Thesis director) / Nakamura, Mutsumi (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The goal of this project was to explore biomimetics by creating a jellyfish flying device that uses propulsion of air to levitate while utilizing electromyography signals and infrared signals as mechanisms to control the device. Completing this project would require knowledge of biological signals, electrical circuits, computer programming, and physics to accomplish. An EMG sensor was used to obtain processed electrical signals produced from the muscles in the forearm and was then utilized to control the actuation speed of the tentacles. An Arduino microprocessor was used to translate the EMG signals to infrared blinking sequences which would propagate commands through a constructed circuit shield to the infrared receiver on jellyfish. The receiver will then translate the received IR sequence into actions. Then the flying device must produce enough thrust to propel the body upwards. The application of biomimetics would best test my skills as an engineer as well as provide a method of applying what I have learned over the duration of my undergraduate career.
ContributorsTsui, Jessica W (Author) / Muthuswamy, Jitteran (Thesis director) / Blain Christen, Jennifer (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
This research study examined the bilateral asymmetry found in muscle pairs including the right and left sides of the upper rectus abdominis, lower rectus abdominis, external oblique, and internal oblique in college-aged, apparently fit men and women. Bilateral symmetry was found using surface electromyography (EMG) during three core exercises: 1) ab-slides using paper plates (paper), 2) planks, and 3) ab-slides using a commercial AbSlide® roller device by comparing maximal voluntary contractions (MVCs) of the four muscles previously listed. This research analyzed the percentage of muscle activation during these exercises to each person’s MVC using Noraxon® software. Analysis found that asymmetry for each muscle group was present although there is no measure of clinical significance for symmetry scores of the core muscles yet.
Asymmetry scores were calculated for all three exercises. The exercise that produced the greatest absolute, average asymmetry score was the ab-slide using the roller device. The muscle that the greatest absolute asymmetry was found was the internal oblique. This means that during the three exercises and MVC, the greatest difference between right and left side pair muscles was observed in the internal obliques. The standard deviation of symmetry scores for all exercises and muscles was great as there was much variation in the skill levels in the participants of this study. Bilateral asymmetry was found by visually comparing the asymmetry scores. In conclusion, bilateral asymmetry was found in the core muscles of college-aged individuals during bilateral abdominal exercises.
Asymmetry scores were calculated for all three exercises. The exercise that produced the greatest absolute, average asymmetry score was the ab-slide using the roller device. The muscle that the greatest absolute asymmetry was found was the internal oblique. This means that during the three exercises and MVC, the greatest difference between right and left side pair muscles was observed in the internal obliques. The standard deviation of symmetry scores for all exercises and muscles was great as there was much variation in the skill levels in the participants of this study. Bilateral asymmetry was found by visually comparing the asymmetry scores. In conclusion, bilateral asymmetry was found in the core muscles of college-aged individuals during bilateral abdominal exercises.
ContributorsFavaro, Miguel Angel (Author) / Berger, Christopher (Thesis director) / Lorenz, Kent (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2015-05
Description
The global population over the age of 60 is estimated to rise to 23% by 2050 only increase the prevalence of functional neurological disorders and stroke. Increase in cases of functional neurological disorders and strokes will place a greater burden on the healthcare industry, specifically physical therapy. Physical therapy is vital for a patient’s recovery of motor function which is time demanding and taxing on the physical therapist. Wearable robotics have been proven to improve functional outcomes in gait rehabilitation by providing controlled high dosage and high-intensity training. Accurate control strategies for assistive robotic exoskeletons are vital for repetitive high precisions assistance for cerebral plasticity to occur.
This thesis presents a preliminary determination and design of a control algorithm for an assistive ankle device developed by the ASU RISE Laboratory. The assistive ankle device functions by compressing a spring upon heel strike during gait, remaining compressed during mid-stance and then releasing upon initiation of heel-off. The relationship between surface electromyography and ground reactions forces were used for identification of user-initiated heel-off. The muscle activation of the tibialis anterior combined with the ground reaction forces of the heel pressure sensor generated potential features that will be utilized in the revised control algorithm for the assistive ankle device. Work on this project must proceed in order to test and validate the revised control algorithm to determine its accuracy and precision.
This thesis presents a preliminary determination and design of a control algorithm for an assistive ankle device developed by the ASU RISE Laboratory. The assistive ankle device functions by compressing a spring upon heel strike during gait, remaining compressed during mid-stance and then releasing upon initiation of heel-off. The relationship between surface electromyography and ground reactions forces were used for identification of user-initiated heel-off. The muscle activation of the tibialis anterior combined with the ground reaction forces of the heel pressure sensor generated potential features that will be utilized in the revised control algorithm for the assistive ankle device. Work on this project must proceed in order to test and validate the revised control algorithm to determine its accuracy and precision.
ContributorsGaytan-Jenkins, Daniel Rinaldo (Author) / Zhang, Wenlong (Thesis director) / Tyler, Jamie (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Electromyography (EMG) and Electroencephalography (EEG) are techniques used to detect electrical activity produced by the human body. EMG detects electrical activity in the skeletal muscles, while EEG detects electrical activity from the scalp. The purpose of this study is to capture different types of EMG and EEG signals and to determine if the signals can be distinguished between each other and processed into output signals to trigger events in prosthetics. Results from the study suggest that the PSD estimates can be used to compare signals that have significant differences such as the wrist, scalp, and fingers, but it cannot fully distinguish between signals that are closely related, such as two different fingers. The signals that were identified were able to be translated into the physical output simulated on the Arduino circuit.
ContributorsJanis, William Edward (Author) / LaBelle, Jeffrey (Thesis director) / Santello, Marco (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-12
Description
Training the bench press exercise on a traditional flat bench does not induce a level of instability as seen in sport movements and activities of daily living. Because of this, many new types of equipment have been created in an attempt to induce instability, such as the COR Bench. 15 males and 7 females between the ages of 18 and 30 were recruited for the present study, which tested two forms of instability: using one dumbbell rather than two, and lifting on the COR bench compared to a flat bench. Thusly, EMG was used to measure muscle activity in four separate conditions of unilateral bench press movements: on a flat bench with one dumbbell, on a flat bench with two dumbbells, on the COR Bench with one dumbbell, and on the COR Bench with two dumbbells. Results indicated that lifting with one dumbbell compared to two dumbbells on the flat bench significantly increased muscle activity across all four muscles being analyzed (pectoralis major, p = .005; middle trapezius, p = .008; external obliques, p = .004; and internal obliques, p = .003), but lifting with one dumbbell compared to two dumbbells on the COR Bench only significantly increased muscle activity in the middle trapezius (p = .001), external obliques(p = . 032), and internal obliques (p = .001). The only muscle to exhibit a significant increase in muscle activity when going from one dumbbell on the flat bench to one dumbbell on the COR Bench was the middle trapezius (p = .010). These results imply that the COR Bench itself does not increase muscle activity as much as switching from two dumbbells to one dumbbell, regardless of the bench being used.
ContributorsPatterson, Jeffrey (Author) / Harper, Erin (Thesis director) / Broman, Tannah (Committee member) / Cataldo, Donna (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2013-12
Description
Electromyography (EMG) is an extremely useful tool in extracting control signals from the human body. Needle electromyography is the current standard for obtaining superior quality muscle signals and obtaining signals corresponding to individual muscles. However, needle EMG faces many problems when converting from the laboratory to marketable devices, specifically in home devices. Many patients have issues with needles and the extra care required of needle EMG is prohibitive. Therefore, a surface EMG device that can obtain clear signals from individual muscles would be valuable to many markets in the development of next generation in home devices. Here, signals from surface EMG were analyzed using a low noise EMG evaluation system (RHD 2000; Intan Technologies). The signal to noise ratio (SNR) was calculated using MatLab. The average SNR is 4.447 for the Extensor Carpi Ulnaris, and 7.369 for the Extensor Digitorum Communis. Spectral analysis was performed using the Welch approach in MatLab. The power spectrum indicated that low frequency signals dominate the EMG of small hand muscles. Also, harmonic bands of 60Hz noise were present as part of the signal which should be accounted for with filters in future iterations of the testing method. Provided is evidence that strong, independent signals were acquired and could be used in further application of surface EMG corresponding to lifting of the fingers.
ContributorsSnyder, Joshua Scott (Author) / Muthuswamy, Jit (Thesis director) / Buneo, Christopher (Committee member) / Harrington Bioengineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Abstract
This work details the process of designing and implementing an embedded system
utilized to take measurements from a water cooler and post that data onto a publicly accessible web server. It embraces the Web 4.0, Internet of Things, mindset of making everyday appliances web accessible. The project was designed to satisfy the needs of a local faculty member who wished to know the water levels available in his office water cooler, potentially saving him the disappointment of discovering an empty container.
This project utilizes an Arduino microprocessor, an ESP 8266 Wi-Fi module, and a variety of sensors to detect water levels in filtered water unit located on the fourth floor of the the Brickyard Building, BYENG, at Arizona State University. This implementation will not interfere with the system already set in place to store and transfer water. The level of accuracy in water levels is expected to give the ability to discern +/- 1.5 liters of water. This system will send will send information to a created web service from which anyone with internet capabilities can gain access. The interface will display current water levels and attempt to predict at what time the water levels will be depleted. In the short term, this information will be useful for individuals on the floor to discern when they are able to extract water from the system. Overtime, the information this system gathers will map the drinking trends of the floor and can allow for a scheduling of water delivery that is more consistent with the demand of those working on the floor.
This work details the process of designing and implementing an embedded system
utilized to take measurements from a water cooler and post that data onto a publicly accessible web server. It embraces the Web 4.0, Internet of Things, mindset of making everyday appliances web accessible. The project was designed to satisfy the needs of a local faculty member who wished to know the water levels available in his office water cooler, potentially saving him the disappointment of discovering an empty container.
This project utilizes an Arduino microprocessor, an ESP 8266 Wi-Fi module, and a variety of sensors to detect water levels in filtered water unit located on the fourth floor of the the Brickyard Building, BYENG, at Arizona State University. This implementation will not interfere with the system already set in place to store and transfer water. The level of accuracy in water levels is expected to give the ability to discern +/- 1.5 liters of water. This system will send will send information to a created web service from which anyone with internet capabilities can gain access. The interface will display current water levels and attempt to predict at what time the water levels will be depleted. In the short term, this information will be useful for individuals on the floor to discern when they are able to extract water from the system. Overtime, the information this system gathers will map the drinking trends of the floor and can allow for a scheduling of water delivery that is more consistent with the demand of those working on the floor.
ContributorsEnriquez, Alexander (Author) / Meuth, Ryan (Thesis director) / Burger, Kevin (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05