The influence of the spatial separation of control elements on the workload for mobile information systems

Mobile information systems (MIS) are finding their way into private and business every-day activities. There are also increased attempts to establish MIS for on-site activities in industrial facilities. Industrial environments, however, place significantly higher demands on mobile user interfaces than office or home environments. Common interaction styles are often unsuitable for this domain. MIS comprising specialized configurations like wearable systems might overcome current limitations. Wearable systems make it possible to arrange system components in the immediate environment of the user's body in order to create an ergonomic and intuitive user interface. However, the use of distributed, body-worn user interfaces, and in particular separation of input and output devices, might increase the workload for the user. This study examines the extent to which the separation of input and output devices affects the workload for wearable MIS. Three interaction styles in two different configurations are investigated with four different measures to determine the workload covering both objective and subjective indicators. This investigation shows that there is no significant increase of workload in general. However, the measurement of the heart rate variability revealed subtle but significant differences between the two configurations, particularly for one interaction style. These findings indicate that physiological measures can provide more detailed and subtle information about additional workload and its source than other measures.

[1]  O. J. Dunn.  Multiple Comparisons among Means , 1961 .

[2]  Lutz Krauss.  Entwicklung und Evaluation einer Methodik zur Untersuchung von Interaktionsgeräten für Maschinen- und Prozessbediensysteme mit grafischen Benutzungsoberflächen , 2003 .

[3]  Wayne D. Gray,et al.  Milliseconds Matter: an Introduction to Microstrategies and to Their Use in Describing and Predicting Interactive Behavior Milliseconds Matter: an Introduction to Microstrategies and to Their Use in Describing and Predicting Interactive Behavior , 2022 .

[4]  James H. Garrett,et al.  An interaction constraints model for mobile and wearable computer-aided engineering systems in industrial applications , 2002 .

[5]  G. R. J. Hockey.  Compensatory control in the regulation of human performance under stress and high workload: A cognitive-energetical framework , 1997, Biological Psychology.

[6]  D. Levy,et al.  Impact of reduced heart rate variability on risk for cardiac events. The Framingham Heart Study. , 1996, Circulation.

[7]  F. Thomas Eggemeier,et al.  Some Measurement and Methodological Considerations in the Application of Subjective Workload Measurement Techniques , 1995 .

[8]  Katharina Seifert,et al.  Evaluation multimodaler Computer-Systeme in frühen Entwicklungsphasen , 2002 .

[9]  Dietrich Manzey,et al.  Impact of automated decision aids on performance, operator behaviour and workload in a simulated supervisory control task , 2009, Ergonomics.

[10]  Andrew L. Kun,et al.  Estimating cognitive load using remote eye tracking in a driving simulator , 2010, ETRA.

[11]  Dick de Waard,et al.  The measurement of drivers' mental workload , 1996 .

[12]  A. H. Roscoe,et al.  Heart rate as a psychophysiological measure for in-flight workload assessment. , 1993, Ergonomics.

[13]  C. Wittenberg.  Is multimedia always the solution for human-machine interfaces? - a case study in the service & maintenance domain , 2008, 2008 15th International Conference on Systems, Signals and Image Processing.

[14]  Leon Urbas,et al.  A mobile system for industrial maintenance support based on embodied interaction , 2011, Tangible and Embedded Interaction.

[15]  Barbara Pernici.  Mobile Information Systems: Infrastructure and Design for Adaptivity and Flexibility , 2006 .

[16]  S Cerutti,et al.  Sympathovagal interaction during mental stress. A study using spectral analysis of heart rate variability in healthy control subjects and patients with a prior myocardial infarction. , 1991, Circulation.

[17]  Hagen Malberg,et al.  Nonlinear Methods of Cardiovascular Physics and their Clinical Applicability , 2007, Int. J. Bifurc. Chaos.

[18]  Yili Liu,et al.  Introduction to Human Factors Engineering (2nd Edition) , 2003 .

[19]  A. Malliani,et al.  Heart rate variability. Standards of measurement, physiological interpretation, and clinical use , 1996 .

[20]  Bruce Thomas,et al.  User Interface Design for Electronic Appliances , 2001 .

[21]  J. Miller,et al.  Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. , 1987, The American journal of cardiology.

[22]  Maximilian Schwalm.  Pupillometrie als Methode zur Erfassung mentaler Beanspruchungen im automotiven Kontext , 2009 .

[23]  Christoph Pohl,et al.  SNOW - A Multimodal Approach for Mobile Maintenance Applications , 2006, 15th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE'06).

[24]  Markus Aleksy,et al.  Challenges in the Development of Mobile Applications in Industrial Field Service , 2009, 2009 International Conference on Network-Based Information Systems.

[25]  S. Huffel,et al.  Instantaneous changes in heart rate regulation due to mental load in simulated office work , 2011, European Journal of Applied Physiology.

[26]  Leon Urbas,et al.  Realization of Tangible Mobile Human Machine Interfaces Using Wireless Personal Area Networks , 2009 .

[27]  Luca Chittaro,et al.  Visualizing information on mobile devices , 2006, Computer.

[28]  Otthein Herzog,et al.  Changing the working environment of mobile workers by wearable computing , 2007, 2007 IEEE International Technology Management Conference (ICE).

[29]  Maury A. Nussbaum,et al.  Effects of wearing chemical protective clothing on text entry when using wearable input devices , 2007 .

[30]  H. Malberg,et al.  Comparison of three methods for beat-to-beat-interval extraction from continuous blood pressure and electrocardiogram with respect to heart rate variability analysis / Vergleich von drei Methoden der Schlag-zu-Schlag-Intervall-Extraktion aus kontinuierlichen Blutdruckverläufen und Elektrokardiogramm , 2006 .

[31]  Chris Baber,et al.  Ergonomics of wearable computers , 1999, Mob. Networks Appl..

[32]  Stephen A. Brewster,et al.  A paradigm shift: alternative interaction techniques for use with mobile & wearable devices , 2003, CASCON.