title: Frequency domain surface EMG sensor fusion for estimating finger forces.
abstract: Extracting or estimating skeletal hand/finger forces using surface electro myographic (sEMG) signals poses many challenges due to cross-talk, noise, and a temporal and spatially modulated signal characteristics. Normal sEMG measurements are based on single sensor data. In this paper, array sensors are used along with a proposed sensor fusion scheme that result in a simple Multi-Input-Single-Output (MISO) transfer function. Experimental data is used along with system identification to find this MISO system. A Genetic Algorithm (GA) approach is employed to optimize the characteristics of the MISO system. The proposed fusion-based approach is tested experimentally and indicates improvement in finger/hand force estimation.
authors.affiliation: Measurement and Control Engineering Research Center (MCERC), Idaho State University, Pocatello, Idaho 83201, USA. potlchan@isu.edu
authors.forename: Chandrasekhar
authors.initials: C
authors.lastname: Potluri
authors.forename: Parmod
authors.initials: P
authors.lastname: Kumar
authors.forename: Madhavi
authors.initials: M
authors.lastname: Anugolu
authors.forename: Alex
authors.initials: A
authors.lastname: Urfer
authors.forename: Steve
authors.initials: S
authors.lastname: Chiu
authors.forename: D
authors.initials: D
authors.lastname: Naidu
authors.forename: Marco P
authors.initials: MP
authors.lastname: Schoen
mesh_terms: D001696:Biomechanical Phenomena / Q000502:physiology; D016208:Databases, Factual; D004576:Electromyography / Q000295:instrumentation*; D005385:Fingers / Q000502:physiology*; D006801:Humans; D008297:Male; D008954:Models, Biological; D015203:Reproducibility of Results; D013499:Surface Properties