Title :
Frequency domain surface EMG sensor fusion for estimating finger forces
Author :
Potluri, Chandrasekhar ; Kumar, Parmod ; Anugolu, Madhavi ; Urfer, Alex ; Chiu, Steve ; Naidu, Subbaram D. ; Schoen, Marco P.
Author_Institution :
Meas. & Control Eng. Res. Center (MCERC), Idaho State Univ., Pocatello, ID, USA
fDate :
Aug. 31 2010-Sept. 4 2010
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.
Keywords :
electromyography; genetic algorithms; medical signal detection; medical signal processing; noise; sensor arrays; sensor fusion; transfer functions; frequency domain surface EMG sensor fusion; genetic algorithm; multiinput-single-output transfer function; noise; sensor arrays; sensor fusion scheme; single sensor data; skeletal hand-finger force; spatial modulated signal characteristics; surface electromyographic signal; Electromyography; Force; Force measurement; Muscles; Sensor fusion; Transfer functions; Biomechanics; Databases, Factual; Electromyography; Fingers; Humans; Male; Models, Biological; Reproducibility of Results; Surface Properties;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5627575
