Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-24T17:15:46.825Z Has data issue: false hasContentIssue false
  • English
  • Français

Psychophysiological Training of Operators in Adaptive Biofeedback Cardiorhythm Control

Published online by Cambridge University Press:  10 April 2014

Nikolay Suvorov
Nikolay Suvorov*
Affiliation:
Institute for Experimental Medicine, Russian Academy of Medical Science, St. Petersburg
*
Correspondence concerning this article should be addressed to Nicolay Suvorov, Institute for Experimental Medicine, Russian Academy of Medical Science, St. Petersburg, Russia. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

A new individual computerized technique for psychophysiological training of operators before performing psychomotor activity on a computer model (psychomotor concentration and spatial orientation test) was developed. Qualitative criteria for the prediction of safe operator activity were formulated. Preliminary testing of operators' activity quality showed great dispersion of individual results: The amount of errors ranged from 0 to 56 and the rate of information processing varied from 1.01 up 3.56 bit/s. Subjects with initially identified respiratory sinus arrhythmia or synchronization caused by respiratory movements committed minimal recognition errors in initial stages at a high rate of information processing. The number of errors remained unchanged after the biofeedback cardio-training cycle, with the rate of information processing increasing noticeably. Subjects without inherent harmonics developed harmonics after sessions of cardiorhythm biofeedback control, and their operator activity quality improved significantly, making fewer mistakes and increasing the rate of information processing. Biofeedback control led not only to the restoration of respiratory sinus arrhythmia, a favorable diagnostic sign, as revealed by cardiorhythmograms, but also resulted in improvement of the quality of operator activity.

Se desarrolló una nueva técnica informática para el entrenamiento psicofísiológico de operadores antes de llevar a cabo una actividad psicomotora en un modelo informático (test de concentración psicomotora y orientación espacial). Se formularon los criterios cualitativos para la predicción de la actividad segura de los operadores. Las pruebas preliminares de la calidad de la actividad de los operadores reveló una gran dispersión de los resultados individuales: la cantidad de errores oscilaba entre 0 y 56 y el porcentaje de información procesado variaba entre 1.01 y 3.56 bits/s. Los sujetos inicialmente identificados con una arritmia respiratoria sinusal o sincronización causada por los movimientos respiratorios cometían mínimos errores de reconocimiento en las fases iniciales, con una alta velocidad de procesamiento de la información. El número de errores no cambió después del ciclo de entrenamiento biofeedback cardíaco y la velocidad de procesamiento de la información aumentó considerablemente. Los sujetos sin armónicos inherentes desarrollaron armónicos después de las sesiones de control biofeedback del ritmo cardíaco, y su calidad de actividad mejoró significativamente, cometiendo menos errores y aumentando su velocidad de procesamiento de la información. El control biofeedback no sólo llevó a la restauración de la arritmia respiratoria sinusal, una señal diagnóstica favorable, como se observa en los cardiorritmogramas, sino que también mejoró la calidad de la actividad de los operadores.

Keywords

adaptive cardio-biofeedbackharmonic target functionpsychomotor testoperator psychophysiological trainingcardio-respiratory synchronizationretroalimentación cardiaca adaptativafunción armónicatest psicomotorentrenamiento psicofisológico de operadoressincronización cardiaca-respiratoria
Type
Articles
Information
The Spanish Journal of Psychology , Volume 9 , Issue 2 , November 2006 , pp. 193 - 200
Copyright
Copyright © Cambridge University Press 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bulleten' Sibirskogo otdeleniya Rossiyskoy Akademii meditsinskikh nauk, 3, 2004.Google Scholar
Eckberg, D.L. (1995). Respiratory sinus arrhythmia and other human cardiovascular neural periodicities. In Dempsey, J.A. & Pack, A. (Eds.), Regulation of breathing (2nd ed., pp. 669–740). New York: Dekker.Google Scholar
Eckberg, D.L., Kifle, Y.T., & Roberts, V.L. (1980). Phase relationship between normal human respiration and baroreflex responsiveness. The Journal of Physiology, 304, 489–502.CrossRefGoogle ScholarPubMed
Hatch, P.J., Borchering, S., & German, C. (1992). Cardiac sympathetic and parasympathetic activity during self-regulation of heart period. Biofeedback and Self-Regulation, 17, 89–106.CrossRefGoogle ScholarPubMed
Lehrer, R.M., Hochron, S.M., Mayne, T., Isenberg, S., Carlson, V., Gilchrist, J., & Porges, S. (1997). Relationship between changes in EMG and respiratory sinus arrhythmia in a study of relaxation therapy for asthma. Applied Psychophysiology and Biofeedback, 22, 183–191.CrossRefGoogle Scholar
Lehrer, R.M., Vaschillo, E., & Vaschillo, B. (2002). Resonant frequency biofeedback training to increase cardiac variability: Rationale and manual for training [in English]. In Shtark, M.B. & Schwartz, M.S. (Eds.), Bioupravlenie, 4. Teoriya i praktika (pp. 157–164). Novosibirsk: Tseris.Google Scholar
Schäfer, C., Rosenblum, M.G., Kurths, J., & Abel, H.H. (1998). Heartbeat synchronized with ventilation. Nature, 392, 239–240.CrossRefGoogle ScholarPubMed
Schiek, M., Drepper, F.R., Engbert, R., Abel, H.H., & Suder, K. (1998) Cardiorespiratory synchronization. In Kantz, H. & Kurths, J. (Eds.), Nonlinear analysis of physiological data (pp. 191–209). Berlin: Springer.CrossRefGoogle Scholar
Shtark, M.B., & Call, R. (Eds.). (1998). Bioupravlenie, 3. Teoriya i praktika. Novosibirsk: Tseris.Google Scholar
Shtark, M.B., & Schwartz, M.S. (2002a). Nekotorye aspekti bioupravleniya v interpretatsii redaktorov (vmesto predisloviya) [Our thoughts about a few selected aspects of the biofeedback field (instead of a preface)]. In Shtark, M.B. & Schwartz, M.S. (Eds.), Bioupravlenie, 4. Teoriya i praktika (pp. 3–7). Novosibirsk: Tseris.Google Scholar
Shtark, M.B., & Schwartz, M.S. (Eds.). (2002b). Bioupravlenie, 4. Teoriya i praktika. Novosibirsk: Tseris.Google Scholar
Suvorov, N.B. (1998). Adaptivnye sistemi znakoperemennogo bioupravleniya [Adaptive systems of oscillatory biofeedback]. In Yusupov, R.M. & Polonnikov, R.I. (Eds.), Telemeditsina. Novye informatsionnye tekhnologii na poroge XXI veka (pp. 253–272). Saint Petersburg: Anatoliya.Google Scholar
Suvorov, N.B. (2002). Biofeedback control and functional state correction. In Klonowski, W. (Ed.), Attractors, signals and synergetics (pp. 547–552). Lengerich, Berlin: Pabst Science.Google Scholar
Suvorov, N.B. (2004). Ustroistvo dlia osushchestvleniya funktsionalnoy psikhofiziologicheskoy korrektsii sostoyaniya cheloveka [The device for functional psychophysiological modification of the human condition]. Patent of the Russian Federation Nr. 43143, 26.05.2004.Google Scholar
Suvorov, N.B., Frolova, N.L., & Chikhirzhin, G.M. (2004). Sposob funktsionalnoy psikho-fiziologicheskoy korrektsii sostoyaniya cheloveka i diagnostiki v protsesse korrektsii [The method of functional psychophysiological modification of the human condition and diagnostics during modification]. Patent of the Russian Federation Nr. 2221477, 20.01.2004.Google Scholar
Suvorov, N.B., Menitskiy, D.N., & Frolova, N.L. (1998). Znakoperemenniy kardiotrening: praktika primeneniya [Oscillatory cardio-training: Application practice]. In Shtark, M.B. & Call, R. (Eds.), Bioupravlenie, 3. Teoriya i praktika (pp. 69–79). Novosibirsk: Tseris.Google Scholar
Vassilevsky, N.N., Suvorov, N.B., & Bekshaev, S.S. (1988). Statistical structure in space and time patterning of EEG. In International Federation for Information Processing-International Medical Informatics Association, Progress in computer-assisted function analysis (pp. 83–90). North-Holland: Elsevier Science.Google Scholar
Vassilevsky, N.N., Suvorov, N.B., Sidorov, Yu.A., & Bovtushko, V.G. (1996). Faktory riska i nekotorye osobennosti patologii v zavisimosti ot tipa organizatsii neirodinamiki golovnogo mozga [Risk factors and some features of a pathology depending on type organization of neurodynamics of the brain]. Vestnik RAMN, 9, 14–18.Google Scholar
Zwiener, U., Schelenz, C., Bramer, S., & Hoyer, D. (2001). Short-term dynamics of relative coordination between respiratory movements, heart rate and arterial pressure fluctuations within the respiratory frequency range. Physiology Research, 50, 59–69.Google ScholarPubMed