title: Resolution of superpositions in EMG signals using belief propagation: results for the known constituent problem.
abstract: The problem of resolving superpositions in electromyographic (EMG) signals is considered. The shapes of the motor unit action potentials that make up each superposition are assumed to be known a-priori (known constituent problem). Two different and novel belief propagation algorithms have been developed to solve this problem. These algorithms and simulation results are presented in this paper.
authors.affiliation: Signal and Information Processing Laboratory, ETH Zurich, Zurich, Switzerland. koch@isi.ee.ethz.ch
authors.forename: Volker M
authors.initials: VM
authors.lastname: Koch
authors.forename: Kevin C
authors.initials: KC
authors.lastname: McGill
authors.forename: Hans-Andrea
authors.initials: HA
authors.lastname: Loeliger
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D004576:Electromyography / Q000379:methods*; D006801:Humans; D009046:Motor Neurons / Q000502:physiology*; D009119:Muscle Contraction / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D010363:Pattern Recognition, Automated / Q000379:methods*