Matching Items (3)
- All Subjects: Arduinos
- All Subjects: Electromyography
- Creators: Berger, Christopher
- Resource Type: Text
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.
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.
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.