Surface electromyography records the motor unit action potential signals in the vicinity of the electrode to reveal information on muscle activation. Decomposition of sEMG signals for characterization of constituent motor unit action potentials in terms of amplitude and firing times is useful for clinical research as well as diagnosis of neurological disorders. Successful decomposition of sEMG signals would allow for pertinent motor unit action potential information to be acquired without discomfort to the subject or the need for a well-trained operator (compared with intramuscular EMG). To determine amplitudes and firing times for motor unit action potentials in an sEMG recording, Szlavik's perturbation based decomposition may be applied. The decomposition was initially applied to synthetic sEMG signals and then to experimental data collected from the biceps brachii. Szlavik's decomposition estimator yields satisfactory results for synthetic and experimental sEMG signals with reasonable complexity.
","abstract_html":"<p>Surface electromyography records the motor unit action potential signals in the vicinity of the electrode to reveal information on muscle activation. Decomposition of sEMG signals for characterization of constituent motor unit action potentials in terms of amplitude and firing times is useful for clinical research as well as diagnosis of neurological disorders. Successful decomposition of sEMG signals would allow for pertinent motor unit action potential information to be acquired without discomfort to the subject or the need for a well-trained operator (compared with intramuscular EMG). To determine amplitudes and firing times for motor unit action potentials in an sEMG recording, Szlavik's perturbation based decomposition may be applied. The decomposition was initially applied to synthetic sEMG signals and then to experimental data collected from the biceps brachii. Szlavik's decomposition estimator yields satisfactory results for synthetic and experimental sEMG signals with reasonable complexity.</p>","abstract_has_math":false,"creators":["Huettinger, Rachel"],"institution":null,"degree_name":"MS in Biomedical Engineering","degree_level":null,"degree_discipline":"Biomedical and General Engineering","degree_department":null,"school":null,"contributors":["Robert Szlavik"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-03-01T08:00:00Z","date_published":"2019-03-01T08:00:00Z","updated_at":"2026-07-24T01:32:08Z","subjects":["EMG Decomposition","MUAP","sEMG Decomposition","Perturbation Based Decomposition","Perturbative Approximate Series Expansion","Bioelectrical and Neuroengineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["10.15368/theses.2019.6"],"render_values":[{"text":"10.15368/theses.2019.6","href":"https://doi.org/10.15368/theses.2019.6","code":true}]}]},"links":{"outbound_url":"https://digitalcommons.calpoly.edu/theses/1974","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Robert Szlavik"]},{"key":"dc:creator","label":"Author","values":["Huettinger, Rachel"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-03-21T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Biomedical and General Engineering"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS in Biomedical Engineering"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["EMG Decomposition","MUAP","sEMG Decomposition","Perturbation Based Decomposition","Perturbative Approximate Series Expansion","Bioelectrical and Neuroengineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.calpoly.edu/theses/1974","10.15368/theses.2019.6"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Surface electromyography records the motor unit action potential signals in the vicinity of the electrode to reveal information on muscle activation. Decomposition of sEMG signals for characterization of constituent motor unit action potentials in terms of amplitude and firing times is useful for clinical research as well as diagnosis of neurological disorders. Successful decomposition of sEMG signals would allow for pertinent motor unit action potential information to be acquired without discomfort to the subject or the need for a well-trained operator (compared with intramuscular EMG). To determine amplitudes and firing times for motor unit action potentials in an sEMG recording, Szlavik's perturbation based decomposition may be applied. The decomposition was initially applied to synthetic sEMG signals and then to experimental data collected from the biceps brachii. Szlavik's decomposition estimator yields satisfactory results for synthetic and experimental sEMG signals with reasonable complexity.
"]},{"key":"dc:title","label":"Title","values":["Perturbation Based Decomposition of sEMG Signals"]}]}],"canonical_facts":{"dc:contributor":["Robert Szlavik"],"dc:creator":["Huettinger, Rachel"],"dc:date.available":["2019-03-21T07:00:00Z"],"dc:description.abstract":["Surface electromyography records the motor unit action potential signals in the vicinity of the electrode to reveal information on muscle activation. Decomposition of sEMG signals for characterization of constituent motor unit action potentials in terms of amplitude and firing times is useful for clinical research as well as diagnosis of neurological disorders. Successful decomposition of sEMG signals would allow for pertinent motor unit action potential information to be acquired without discomfort to the subject or the need for a well-trained operator (compared with intramuscular EMG). To determine amplitudes and firing times for motor unit action potentials in an sEMG recording, Szlavik's perturbation based decomposition may be applied. The decomposition was initially applied to synthetic sEMG signals and then to experimental data collected from the biceps brachii. Szlavik's decomposition estimator yields satisfactory results for synthetic and experimental sEMG signals with reasonable complexity.
"],"dc:identifier":["https://digitalcommons.calpoly.edu/theses/1974","10.15368/theses.2019.6"],"dc:subject":["EMG Decomposition","MUAP","sEMG Decomposition","Perturbation Based Decomposition","Perturbative Approximate Series Expansion","Bioelectrical and Neuroengineering"],"dc:title":["Perturbation Based Decomposition of sEMG Signals"],"thesis:degree_discipline":["Biomedical and General Engineering"],"thesis:degree_name":["MS in Biomedical Engineering"]},"updated_at":"2026-07-24T01:32:08Z"}