title: Broad-band Gaussian noise is most effective in improving motor performance and is most pleasant.
abstract: Modern attempts to improve human performance focus on stochastic resonance (SR). SR is a phenomenon in non-linear systems characterized by a response increase of the system induced by a particular level of input noise. Recently, we reported that an optimum level of 0-15 Hz Gaussian noise applied to the human index finger improved static isometric force compensation. A possible explanation was a better sensorimotor integration caused by increase in sensitivity of peripheral receptors and/or of internal SR. The present study in 10 subjects compares SR effects in the performance of the same motor task and on pleasantness, by applying three Gaussian noises chosen on the sensitivity of the fingertip receptors (0-15 Hz mostly for Merkel receptors, 250-300 Hz for Pacini corpuscles and 0-300 Hz for all). We document that only the 0-300 Hz noise induced SR effect during the transitory phase of the task. In contrast, the motor performance was improved during the stationary phase for all three noise frequency bandwidths. This improvement was stronger for 0-300 Hz and 250-300 Hz than for 0-15 Hz noise. Further, we found higher degree of pleasantness for 0-300 Hz and 250-300 Hz noise bandwidths than for 0-15 Hz. Thus, we show that the most appropriate Gaussian noise that could be used in haptic gloves is the 0-300 Hz, as it improved motor performance during both stationary and transitory phases. In addition, this noise had the highest degree of pleasantness and thus reveals that the glabrous skin can also forward pleasant sensations.
authors.affiliation: Department of Neurology and Neurophysiology, Albert-Ludwigs-University Freiburg, Germany.
authors.forename: Carlos
authors.initials: C
authors.lastname: Trenado
authors.affiliation: Department of Neurology and Neurophysiology, Albert-Ludwigs-University Freiburg, Germany.
authors.forename: Areh
authors.initials: A
authors.lastname: Mikulić
authors.affiliation: Instituto de Fisiología, Benemérita Universidad Autonoma de Puebla Puebla, Mexico.
authors.forename: Elias
authors.initials: E
authors.lastname: Manjarrez
authors.affiliation: Facultad de Psicología, Benemérita Universidad Autonoma de Puebla Puebla, Mexico.
authors.forename: Ignacio
authors.initials: I
authors.lastname: Mendez-Balbuena
authors.affiliation: Institute for Medical Biometry and Medical Informatics, University of Freiburg Freiburg, Germany.
authors.forename: Jürgen
authors.initials: J
authors.lastname: Schulte-Mönting
authors.affiliation: Department of Neurology and Neurophysiology, Albert-Ludwigs-University Freiburg, Germany.
authors.forename: Frank
authors.initials: F
authors.lastname: Huethe
authors.affiliation: Institute of Neuroinformatics, University of Zürich and ETH Zürich Zurich, Switzerland.
authors.forename: Marie-Claude
authors.initials: MC
authors.lastname: Hepp-Reymond
authors.affiliation: Department of Neurology and Neurophysiology, Albert-Ludwigs-University Freiburg, Germany.
authors.forename: Rumyana
authors.initials: R
authors.lastname: Kristeva
keywords: finger; force; frequency; humans; motor; noise; stochastic resonance