Reno Filla
Emerging Technologies, Volvo Construction Equipment, Eskilstuna, Sweden
Erik M. G. Olsson
Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
Bo H. C. von Scehéele
Stress Medicine AB, Bergvik, Sweden
Kjell Ohlsson
Department of Management and Engineering, Linköping University, Linköping, Sweden
Ladda ner artikel
http://dx.doi.org/10.3384/ecp1392a29Ingår i: 13th Scandinavian International Conference on Fluid Power; June 3-5; 2013; Linköping; Sweden
Linköping Electronic Conference Proceedings 92:29, s. 293-304
Publicerad: 2013-09-09
ISBN: 978-91-7519-572-8
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
In this study of eighteen wheel loader operators; test-driving a machine in three different traction force settings; we examine if a workload index derived from psychophysiological measurements of heart rate; finger temperature; skin conductance; respiration rate and end-tidal CO2-concentration in exhaled air can be easily used to assess operator workload in sufficient detail to use it as a complement to traditional subjective evaluations in machine testing; either of real machines or in a human-in-the-loop simulator. In a longer perspective; such measurements are expected to play a role in a workload-adaptive operator assistance system.
However; the findings do not give support for this vision. Instead they indicate that other types of measurements than what have been used in our study should be employed if ease of use for practitioners such as test engineers is in focus; but also that other factors than just machine operability must be considered to have a great influence on the operator workload.
Operator; working machines; wheel loaders; operator workload; stress; operability; human-machine interaction
[1] Filla; R. (2011) “Quantifying Operability of Working machines”. Doctoral thesis; Department of Management and Engineering; Linköping University; Sweden. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-70394
[2] Ley; R. (1999) “The modification of breathing behavior. Pavlovian and operant control in emotion and cognition”. Behavior Modification. Vol. 23(3); pp 441-479. http://dx.doi.org/10.1177/0145445599233006
[3] Schleifer; L. M.; Ley; R.; Spalding; T. W. (2002). “A hyperventilation theory of job stress and musculoskeletal disorders”. American Journal of Industrial Medicine. Vol. 41(5); pp 420-432. http://dx.doi.org/10.1002/ajim.10061
[4] Von Schéele; B. H. C. and von Schéele; I. A. M. (1999) “The Measurement of Respiratory and Metabolic Parameters of Patients and Controls Before and After Incremental Exercise on Bicycle: Supporting the Effort Syndrome Hypothesis?”. Applied Psychophysiology and Biofeedback. Vol. 24(3); pp 167-177. http://dx.doi.org/10.1023/A:1023484513455
[5] Filla; R. (2012) “Study of a Method for Assessing Operability of Working Machines in Physical and Virtual Testing”. International Journal of Vehicle Systems Modelling and Testing; vol. 7; no. 3; pp 209-234; 2012. http://dx.doi.org/10.1504/IJVSMT.2012.048939
[6] Begum; S.; Ahmed M. U.; Funk; P.; Xiong; N. and von Schéele; B. (2006) “Using Calibration and Fuzzification of Cases for Improved Diagnosis and Treatment of Stress”. Proceedings of the 8th European Conference on Case-Based Reasoning; pp 113-122. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.97.4004
[7] Begum; S. (2011) “A Personalised Case-Based Stress Diagnosis System Using Physiological Sensor Signals”. Doctoral thesis; Mälardalen University; Västerås; Sweden. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-12257
[8] De Waard; D. (1996) “The Measurement of Driver’s Mental Workload”. Doctoral thesis; University of Groningen; The Netherlands.
http://irs.ub.rug.nl/ppn/297329391
[9] Castor; M.; Hanson; E.; Svensson; E.; Nählinder; S.; Le Blaye; P.; MacLeod; I.; Wright; N.; Alfredson; J.; Ågren; L.; Berggren; P.; Juppet; V.; Hilburn; B.; Ohlsson; K. (2003) “GARTEUR Handbook of Mental Workload Measurement”; Final Report for Flight Mechanics Group of Responsibles (FM GoR) of the Group for Aeronautical Research and Technology in Europe (GARTEUR) by GARTEUR Action Group FM AG13.
[10] Park; B. (2009) “Psychophysiology as a Tool for HCI Research: Promises and Pitfalls”. Proceedings of HCII 2009: New Trends; LNCS 5610; pp 141-148. http://dx.doi.org/10.1007/978-3-642-02574-7_16
[11] Di Stasi; L. L. (2010) “Mental Workload in HMI”. Doctoral thesis; Departamento de Psicología Experimental y Fisiología del Comportamiento; Universidad de Granada; Granada; Spain. http://hdl.handle.net/10481/15439
[12] Begum; S.; Ahmed; M. U.; Funk; P.; Filla; R. (2012) “Driver’s Mental State Monitoring System Using CBR Based on Heart Rate Variability Analysis”. Proceedings from the 7th International Symposium Advances in Artificial Intelligence and Applications (AAIA’12). http://fedcsis.org/proceedings/fedcsis2012/pliks/407.pdf
[13] Von Schéele; B. H. C. (1995) “Respiratory Sinus Arrhythmia as a Diagnostic Tool; a Treatment Goal; a Rule for Treatment Planning; a Cool Biofeedback; and an Out-Come Variable”. Biofeedback and Self Regulation. Vol. 20(3); pp 308-309.
[14] Nählinder; S. (2009) “Flight Simulator Training: Assessing the Potential”. Doctoral thesis; Department of Management and Engineering; Linköping University; Sweden. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-17546
[15] Voskamp; J. and Urban; B. (2009) “Measuring Cognitive Workload in Non-military Scenarios. Criteria for Sensor Technologies”. Proceedings of HCII 2009: Foundations of Augmented Cognition - Neuroergonomics and Operational Neuroscience; LNCS 5638; pp 304-310. http://dx.doi.org/10.1007/978-3-642-02812-0_36
[16] Begum; S.; Barua; S.; Filla; R.; Ahmed; M. U. (2013) “Classification of Physiological Signals for Wheel Loader Operators Using Multi-Scale Entropy Analysis and Case-Based Reasoning”. To be published in Expert Systems with Applications.
