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Cervicobrachial muscle response to cognitive load in a dual-task scenario ELKE L. C. LEYMAN, GARY A. MIRKA, DAVID B. KABER* and CAROLYN M. SOMMERICH Department of Industrial Engineering, North Carolina State University, 328 Riddick Labs, 2401 Stinson Dr., Raleigh, NC 27695-7906, USA Keywords: Attention; Cognitive task; Multiple-task performance; Electromyography; Mental workload; Physiological measures; Secondary-task performance; Stress; Visual display unit. People working in an office environment often have to deal with significant cognitive workload due to the coordination of multiple, simultaneous tasks. The objective of this research was to examine the impact of cognitive load in officetype tasks on physical-stress response, using a dual-task paradigm involving a primary cognitive task and secondary typing task. The central hypothesis of this research was that altering the demands of the cognitive task would lead to a difference in physical stress-level and performance. Cognitive load was manipulated by presenting participants with three different types of cognitive tasks described in Rasmussen’s (1983) taxonomy, including skill-, rule-, and knowledge-based tasks. Dependent variables examined in the study included: (1) electromyographic activity of the upper trapezius (pars descendens) and cervical erector spinae muscles, (2) performance in a secondary typing task, and (3) subjective measures of stress and cognitive workload. The results of this study revealed that the primary task causing the highest level of perceived workload also produced 61% higher muscle activity in the right trapezius, and 6 and 11% higher activity in the left and right cervical erector spinae, respectively, in comparison to muscle activity associated with the cognitive task causing the lowest perceived workload. With respect to performance, a 23% decrease was observed in typing productivity when the rule-based task was completed simultaneously vs. typing in the absence of any additional cognitive task (the baseline condition). This information may be used to better organize work activities in office environments to increase performance and reduce stress.
1. Introduction Although office work poses low physical workload requirements in comparison to work tasks in many traditional manufacturing industries, many office workers complain of discomfort in the neck and shoulder (cervicobrachial) region. Previous literature has formed a link between these symptoms and psychological/psychosocial stress (e.g. Sauter et al. 1983, Leino 1989, Hales et al. 1994). An underlying cause of this relationship may be static muscle tension during stress and the resulting changes in blood flow in the muscle tissue (Sjøgaard et al. 1988). This logic has been supported by studies examining muscle tension and psychological stress (Sainsbury and Gibson 1954, Westgaard and Bjørklund 1987) and cognitive stress (Jacobson, 1931, Waersted et al. 1991). Since work in most office environments involves *Author for correspondence. e-mail:
[email protected] Ergonomics ISSN 0014-0139 print/ISSN 1366-5847 online # 2004 Taylor & Francis Ltd http://www.tandf.co.uk/journals DOI: 10.1080/00140130310001629766
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psychological or cognitive stress, it can be hypothesized that cognitively/ psychologically mediated muscle tension may play a role in the development of discomfort and musculoskeletal illness in this worker population, and the theoretical underpinnings of this relationship should be examined further. In the contemporary office environment, cognitive (or mental) workload can be defined as the portion of operator information processing capacity, or resources, that is required to meet cognitive task demands (Eggemeier et al. 1991). While performing office work, cognitive task demands may vary both in terms of the amount of information to be processed, as well as the specific demands on cognitive constructs, including decision-making and problem-solving mechanisms. The addition of cognitive performance demands may impact the physiological state of operators because humans are not simply deterministic input – output devices, but are goaloriented and actively search for task-relevant information (Rasmussen 1983). Therefore, additional goals may be associated with increased muscle activation levels. Cognitive load may also be induced by the requirement of different types of behaviour. And, it is possible that different cognitive behaviours are associated with different physical-stress responses. To make a distinction between different levels of human cognitive behaviour, Rasmussen (1983, 1986) identified three categories of human performance (action selection and execution), including skill-, rule-, and knowledge-based performance. Skill-based behaviour is characterized by the use of rote knowledge. It typically involves performance controlled by patterns of behaviour stored in long-term memory. Skill-based task performance usually involves strong signal-response associations and signal processing is relatively automatic (Swezey and Llaneras 1997). Rule-based behaviour is characterized by the use of propositions in long-term memory (Rasmussen 1983). Wickens and Carswell (1997) describe it as a process of mentally mapping environmental characteristics and task goals to actions – ‘if the xxx conditions exist, then do yyyy.’ It also requires human awareness of the state of the task through the use of working memory in order to perform situation classification and select appropriate decision rules. Rule-based performance usually occurs in familiar settings for which definite rules of performance exist (Swezey and Llaneras 1997). Cognitive processing for this type of behaviour is considerably less automatic and more time consuming than for skill-based behaviour. Knowledgebased behaviour also involves the use of long-term memory structures (e.g., mental models representing the structure of complex tasks and systems). Knowledge tasks typically involve other higher-level aspects of cognition, including reasoning/ problem solving, decision-making (goal selection) and projection/planning relying on situation awareness (Sheridan 1997). They involve event-specific actions that are based on operator general knowledge of a system in environments for which known sets of operating rules do not exist (Rasmussen 1983, Wickens and Hollands 2000). These three types of behaviours should not be considered as distinct categories but rather falling on a continuum, with each type flowing over into the next type (Rasmussen 1983, Sanders and McCormick 1993). For example, any plan developed using knowledge-based behaviour will require rule-based procedures and skill-based operation (Swezey and Llaneras 1997). However, cognitive processing as part of knowledge-based performance is generally more elaborate than for skill- or rulebased performance. In general, previous work relating cognitive demands and physical task performance or physiological responses has been limited in the type of tasks used
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to assess such relationships. The majority of existing research has utilized dual-task scenarios that are not representative of contemporary work environments. For example, participants have been asked to perform simple tasks, like memorizing numbers while being presented with a light probe stimulus and providing a motor response to a test stimulus on the numbers, or they have been asked to perform tracking tasks while simultaneously performing tone judgments, or to move a joystick or press a keyboard key in response to a choice-reaction time task while under cognitive stress (memorizing a set of words) (Bauer et al. 1987, Derrick 1988, La Pointe and Engle 1990, Waersted et al. 1991, Bansevicius et al. 1997). An important extension of this work would be to identify real-world work environments and place cognitive demands on these workers and assess their performance and physiological responses. In the office environment this might be simulated by having workers perform a typing task while simultaneously experiencing cognitive demands (skill-, rule- or knowledge-based behaviour), such as remembering important product information, making decisions on office supplies and materials for purchase based on budgets, and planning and updating near- and long-term work schedules, etc. In order, to assess the impact of varied cognitive loads in a dual-task scenario three classes of workload measurement techniques (described by Eggemeier and Wilson (1991)) can be used, including: (1) performance-based assessment; (2) subjective workload assessment; and (3) physiological workload assessment. Eggemeier and Wilson labelled the objective measures of speed and accuracy of operator performance as ‘primary’ task measurements for indicating workload. Subjective workload assessment techniques, on the other hand, involve an operator giving his or her opinion of the workload or effort that is associated with performance of a task or a system function. In many studies, subjective measures have been demonstrated to be sensitive to controlled changes in workload (Wierville and Casali 1983, Derrick 1988, Eggemeier and Wilson 1991, Wierville and Eggemeier 1993). Finally, physiological measures indicate workload by analysing an operator’s physical state in relation to manipulations of task or system demand (Wilson and Eggemeier 1991). Physiological measures demonstrated to be sensitive to global manipulations of workload include heart-rate variability and electro-encephalogram signals (Wickens 1992, Wierville and Eggemeier 1993). In the present research, cognitive load and cervicobrachial muscle response were evaluated and related while research participants performed a typing task in conjunction with one of several cognitive tasks. On the basis of Van Gemmert and Van Galen’s (1997) research, we expected that the coordination of multiple tasks, in particular, would lead to an increase in mental load and possibly a corresponding increase in muscle tension, as compared to baseline tension levels observed during single-task performance. Human ability to maintain performance in dual-task scenarios has been studied extensively (cf., Damos 1991) and research has demonstrated that if primary task demands are significant in terms of required cognitive resources due to task complexity, efficiency and productivity in a secondary task are likely to decline. Depending upon the cognitive load placed on an operator, more resources may become available for allocation to a task, in which case its performance will likely improve (Wickens and Hollands 2000: 441). Therefore, we also expected coordination of the tasks and cognitive load to be reflected through secondary-task performance. The typing task was considered to be a true secondary task (see Wickens (1992) for a definition) because participants were required to simultaneously cognitively process the skill-, rule-, or knowledge-based tasks.
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Manipulating the cognitive task in a dual-task scenario, also involving psychomotor task performance, may cause corresponding changes in perceived physical stress and muscle tension, as well as primary and secondary-task performance. The specific objective of this study was to evaluate the impact of varied cognitive load on perceived stress, tension in the cervicobrachial muscles, and secondary-task performance in the dual-task scenario involving typing. Secondarily, the work was intended to validate muscle tension as an indicator of cognitive load and to determine whether various types of cognitive tasks an office worker is assigned can be differentiated on the basis of physiological responses. 2. Materials and methods 2.1. Participants Thirteen individuals from the university community (mean age 33 years, range 22 – 44) volunteered to participate in this study. Nine were male and four of were female. Twelve of the participants were right-hand dominant. All participants were touch typists. 2.2. Experimental apparatus 2.2.1. Electromyography system: Electromyography was used to study the hypothesized change in muscle activity during typing and cognitive task performance vs. typing alone, as well as differences in levels of activation across the various types of cognitive tasks, including skill-, rule- and knowledge-based tasks. Electromyographic (EMG) activity was recorded using Ag-Ag/Cl bipolar surface electrodes (Model E22x, InVivo Metric). The electrodes were connected to small, lightweight preamplifiers (1000 6 ) and the amplified signal was carried via shielded cables to the EMG processing system (Data Design, Columbus, OH), where the signals were further amplified (*20 6 ) and low pass filtered at 2000 Hz. The resulting processed signals were then A/D converted and collected at a frequency of 1024 Hz. Trapezius muscle activity was sampled using bilateral pairs of electrodes centered about a point 2 cm lateral to the midpoint of a line between C7 and the acromion, in accordance with recommendations by Jensen et al. (1996). Cervical erector spinae muscle activity was sampled using bilateral pairs of electrodes oriented vertically, 2 – 3 cm off of the midline of the spine (variable depending on subject anthropometry), with the superior electrode located at the level of C2 – C3 (Schu¨ldt 1988). Interelectrode distance (centre to centre) was 2.5 cm. 2.2.2. Workstation and typing task software: During each experimental trial, the participants were seated in front of a computer screen that displayed a paragraph, which they typed for 30 s. The height of the table as well as the height and the back inclination of the chair were adjustable and the participant was allowed to adjust the workstation subject to the constraint that the computer screen was positioned so that the top of the viewing area was at eye level. The typing task was performed using the Typing Tutor (Kriya Systems, Que Software), a typing instructor software package for the personal computer designed to increase a person’s typing ability, which captures speed and accuracy data. 2.3. Experimental task 2.3.1. Orientation session: On the first day of the experiment, an orientation session was conducted. First, the experimental procedures were explained to participants,
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who then provided written informed consent. The participants then practiced the typing task using the Typing Tutor software and then practiced three maximum voluntary contraction exertions (MVEs) that they would also be asked to perform on the day of the experiment (described below). Participants were then trained in the primary cognitive tasks, including skill-, rule- and knowledge-based tasks. The details of these training protocols are presented along with the task descriptions in the Experimental Design section. The entire orientation session lasted approximately 1 h. 2.3.2. Test session: On the second day of the experiment, the data collection phase of the study was conducted. Surface electrodes were attached to the skin of subjects and signal quality was verified. Participants were asked to perform three, 5 s MVEs. The first exertion was an isometric neck extension exertion against a stationary, padded surface with the head held in an upright posture. The data collected in this trial were used to normalize data from the cervical erector spinae during the experimental trials. The second two MVEs were bilateral shoulder abduction exertions against experimenter-provided manual resistance with the arms abducted at 908. The data collected in these trials were used to normalize the data from the trapezius during the experimental trials. The normalization technique was employed so that all muscle activity could be expressed in terms of percent of maximum. After the EMG data of the MVEs were collected, participants were asked to type a paragraph using the Typing Tutor 20 times with each trial lasting 45 s. The 20 repetitions were performed in order to ensure that a participant was comfortable with the typing task and the specific words in the paragraph. Since the purpose of the experiment was to examine the effects of the cognitive tasks on secondary (typing) task performance and on physiological stress as indicated by muscle activity, the typing training was also conducted to ensure that secondary-task performance would be a robust and sensitive indicator of cognitive load. Any random variability in performance due to a lack of skill in the typing task had the potential to mask the cognitive task effects. (No EMG or perceived stress data was collected during the typing training trials.) Upon completion of the typing training, ten experimental trials were conducted in random order, including: (1) (2) (3) (4)
two ‘baseline’ trials to measure typing task performance with the practiced paragraph in the absence of any cognitive task requirement; six trials involving typing the practiced paragraph and simultaneous completion of one of six different levels of the skill-based task; one trial involving typing the practiced paragraph and simultaneous performance of the rule-based task; and one trial involving typing the practiced paragraph and simultaneously completing the knowledge-based task.
Before each test trial, participants were informed that the typing task and cognitive task were both important, but that performance of the cognitive task should be emphasized. During the experimental trials, EMG data was collected continuously for a period of 66 s and an electronic trigger was added to demark different trial phases. Based on the design of the experiment, a trial involved five phases including: (1) a rest phase (baseline); (2) a phase in which the cognitive task was presented to the participant; (3) a typing phase; (4) a phase in which the participant responded to
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the cognitive task; and (5) a final phase in which the participant returned to rest. Figure 1 presents an idealized representation of these phases. Participant postures were videotaped during the experiment and the quality and accuracy of performance was captured. Immediately after each trial, participants subjectively rated mental workload experienced during dual-task performance and their current levels of stress. Stress was measured using a visual analogue scale (VAS). Participants rated workload using the Modified Cooper Harper-scale (MCH) based on the level of difficulty they experienced in managing dual-task performance (Wierville and Casali 1983). The MCH was selected as a measure of workload over other multidimensional rating techniques (e.g., NASA Task Load Index) because of the focus of the experiment on cognitive loading in a dual-task scenario and the complexity of completing the workload rating method from a participant’s perspective. The MCH has been demonstrated to be a valid and reliable indicator of cognitive workload (Wierville and Casali 1983). Once these measurements were complete, participants rested for three minutes until the next trial. The entire test session took approximately 2 h.
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2.4. Experimental design 2.4.1. Independent variable: The independent variable in this study was the cognitive task performed as the participants typed. Three different primary, cognitive tasks were designed based on the theory of types of human performance behaviour developed by Rasmussen (1986), including the skill-based task, rule-based task and knowledge-based task. A simple memory task was chosen to represent skillbased behaviour in this experiment. Orientation Session training in the task involved participants reading, rehearsing and recalling lists of two to seven familiar, but
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The EMG signal of an idealized experimental trial divided in the five different phases.
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unrelated, nouns. During the Day 1 training session, each participant completed two repetitions for each list length (2 – 7 words). During the Day 2 experimental trials, each participant received a new list of unrelated words printed on a piece of paper. The number of words in any test list varied between two and seven words. Baddeley et al. (1975), La Pointe and Engle (1990) and Coltheart (1999) found that word length affected recall; specifically more short words can be remembered than long words. In this study, only four-letter nouns were selected from a list compiled by Kucera and Francis (La Pointe and Engle 1990) in order to allow subjects to memorize a broad range of list lengths, including comparatively long lists (7 words). A composite list of the words used in the experiment is presented in Appendix 1. Since these were common terms, participants were able to rely on semantics in longterm memory stores for comprehension; however, limited working memory was also required to temporarily store them. Each word was displayed in turn for a period of 1 s by using a cover page. The list was then shown a second time in order to ensure participants had sufficient time to memorize the words. While viewing the list, participants were asked to read the words out loud to promote verbal encoding in working memory (Baddeley et al. 1975, La Pointe and Engle 1990). After reading the last word for the second time, participants immediately began typing. After a period of 30 s, participants stopped typing and were immediately asked to recall all the words verbally in any order. Rasmussen (1983) said that skill-based behaviour occasionally involves performance based on simple feedback where output is a learned response to signal detection. As an example, Rasmussen (1983) described a musical performance and output of passages (isolated skill routines) based on memory structures. On this basis, our skill-based task involved verbal output of a learned sequence of information upon detection of a stimulus (the end of the typing task). For the rule-based task condition, participants were posed with a geography task that required use of a definite decision rule based on fundamental learning and extensive use of working memory for sequencing perceived information. Rasmussen (1983) described rule-based tasks as being goal-oriented and based on stored rules (in memory). During the Day 1 training session, participants were provided with a list of five US cities and were asked to simply place them in alphabetical order. During the Day 2 experimental trial, participants were also presented with a list of five cities. They were asked to read these cities out loud and then were told that their goal was to order the cities from West to East. As soon as this cognitive task demand was posed, participants were told to begin typing immediately. Participants typed for 30 s and then were required to provide this ordered list of cities (respond to the rulebased task). Participants were not permitted additional time to think about the order of the cities once the typing task was finished. The list of cities that was used is presented in Appendix 2. The knowledge-based task condition required participants to learn a complex schedule of daily work activities and to modify the schedule to include additional activities. During the Day 1 training session, participants were told a story of the daily schedule of an administrative assistant (refer to Appendix 3 for the script that was read to the participants). The story was enhanced with a slide show including pictures of settings in which the activities of the assistant were to take place and of objects involved in the activities. The training of the knowledge-based task was structured in this manner for two reasons. First, the presentation of visual information was intended to promote a rich, complex memory in participants, as
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compared to the simple verbal and visual memories developed for the rule- and skillbased tasks. Rasmussen (1983) offered that the structure of a knowledge-based task is represented by a complex internal model that facilitates adaptable performance. Secondly, multimodal presentation (the story and slides) of the knowledge-based task was expected to address potential participant preferences for modalities and any attentional resource allocation limitations that may have occurred during the training process. Research has demonstrated that each sensory channel may be supported by separate attentional or cognitive resources (Wickens and Hollands 2000) and the multimodal presentation of the knowledge-based task was expected to ensure the transmission of the schedule information to participants. The scheduling task was considered to represent knowledge-based behaviour because the schedule changes presented to participants during the experiment were novel circumstances in comparison to those encoded in participant long-term memory based on the task training. Furthermore, there was no definite or optimal solution for modifying the plan of work activities. Therefore, it may have been necessary for participants to apply rule-based learning developed through personal activity scheduling in order to complete the task. Rasmussen (1983) said that knowledge-based behaviour, like rule-based task, performance is goal-oriented and involves developing alternative plans, testing their effects against goals in memory, and selecting a useful plan. During the Day 2 experimental trial, the schedule and the pictures were reviewed in order to refresh the participant’s memory. Subsequently, the participant was told that there were two meetings that had to be added to the schedule. As soon as this cognitive task was posed, the participant was required to begin typing for 30 s. Immediately after the typing task, the participant was asked how he or she would schedule the two meetings among the daily activities of the assistant. 2.4.2. Dependent variables: Each of the three classes of workload measurement techniques described in the Introduction were exercised in this study in order to quantify the impact of dual-task performance and the types of cognitive behaviour on objective measures and subjective perceptions of workload. This approach also allowed for validation of, for example, the EMG responses based on results on the MCH scale and secondary-task performance (typing). In order to gain insight into the impact of the primary cognitive task on secondary-task performance, the speed and accuracy of typing during each trial was recorded in terms of the number of correct characters typed within the 30 s test phase. To subjectively assess workload in the dual-task scenario (cognitive and typing task performance) as part of this experiment, each participant was asked to select a number on the MCH scale ranging from 1, or ‘Very Easy’, to 10, or ‘Impossible’, immediately after each trial, as recommended by Wierville and Casali (1983). In addition to the MCH scale, a 10-cm VAS was used to subjectively assess participant stress levels in the range of ‘not stressed’ to ‘totally stressed’. At the close of a trial, a participant was asked to mark on the scale to indicate his or her stress levels during (VAS1) and immediately after (VAS2) the trial. The participants were not allowed to see any of their subjective ratings from earlier trials. The normalized, integrated EMG activity (expressed as a percent of maximum activity) of the bilateral upper trapezius (pars descendens) and the bilateral cervical erector spinae were used as a physiological workload assessment measure during the typing phase of the experimental trials. These measures were expected to be
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sensitive local measures of the cognitive workload posed by the office-type tasks under study. 2.5. Data analysis 2.5.1. Data processing: An in-house developed EMG processing software programme was used to filter (notch filtered at 60, 120, 180 and 240 Hz, high pass filtered at 10 Hz, and low pass filtered at 500 Hz), rectify, integrate (100 msec moving average window) and normalize (relative to the EMG value derived from the pertinent MVE) the EMG data from the four muscles. The electrocardiogram (ECG) artifact (represented in the integrated EMG-signal as a single prominent spike) was controlled by identifying and eliminating the spike in the integrated EMG trace. The normalization procedure was followed in order to control inter-individual variation. Due to problems during data collection, the erector spinae data for Participant 8 was not used in the analysis. 2.5.2. Statistics: Analyses of variance (ANOVAs) were conducted in order to test the hypotheses that changes in the primary cognitive task would lead to changes in physical stress-level (indicated by EMG signals), performance of the typing task, and subjective ratings of stress and workload using the VAS and MCH scales, respectively, in the dual-task scenario. Tukey’s Honestly Significant Difference (HSD) test was used to further investigate any significant effect of cognitive task type on the various workload measures and to identify those conditions posing the highest and lowest loads. An alpha-level of 0.05 was used for all tests of statistical significance. 3. Results 3.1. Subjective workload measurements Results of an ANOVA on the MCH scale ratings revealed a significant effect of cognitive task type (p 5 0.0001) (see figure 2 for graph of condition means). The results of Tukey’s HSD revealed that the highest perceived workload was associated with the skill-based task involving a 7-word list (see table 1). The lowest workload was observed during performance of the typing task with no cognitive task requirement. Surprisingly, the rule- and knowledge-based tasks were perceived to be significantly less difficult (p 5 0.05) than the 7-word memory task, but they were not significantly different from each other. The rule-based task was significantly more difficult (p 5 0.05) than skill-based performance involving memorization of four or fewer words, and the knowledge-based task was significantly more difficult (p 5 0.05) than memorization of two words or typing alone. The results on the stress ratings using the VAS scale were divided into two groups, including ‘VAS1’, which represented ratings on stress perceived during the trial, and ‘VAS2’, which represented the ratings on stress after the trial (i.e., subsequent to responding to the cognitive task demand). An ANOVA demonstrated a significant effect of cognitive task type on VAS1 ratings (p 5 0.0001), but not on the VAS2 ratings (p = 0.0936) (also see figure 2 for graph of condition means). These results are consistent with the a prior expectation that perceived stress during the test trials would be impacted by the cognitive task type, but that VAS2 ratings would not (i.e., ratings would return to baseline stress levels). The honestly significant differences among VAS1 ratings are shown in table 2. Perceived stress during test trials was significantly greater for typing with rule-based task performance than for typing and skill-based task performance involving
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VAS1, VAS2 and MCH scale ratings averaged over 13 participants, as a function of psychomotor and cognitive task type.
Table 1.
Tukey’s HSD test results on MCH scale ratings of perceived workload as a function of cognitive task type (1 = ‘Very easy’, 10 = ‘Impossible’). Grouping
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A A
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Typing task with the skill-based task (7 words). Typing task with the skill-based task (6 words) Typing task with the rule-based task. Typing task with the skill-based task (5 words). Typing task with the knowledgebased task. Typing task with the skill-based task (4 words). Typing task with the skill-based task (3 words). Typing task with the skill-based task (2 words). Typing task with no cognitive task.
Mean rating 6.6 5.2 4.5 4.1 3.6 3.1 2.2 1.4 –
Note: Tasks with the same letter are not significantly different. As the MCH scale only measures workload during a dual-task scenario, there are no MCH results for the typing task in the absence of a cognitive demand.
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Tukey’s HSD test results on VAS1 ratings of perceived stress as a function of cognitive task type (0 = ‘Not stressed’, 100 = ‘Totally stressed’). Grouping
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Typing task with the rule-based task. Typing task with the skill-based task (7 words). Typing task with the skill-based task (6 words). Typing task with the skill-based task (5 words). Typing task with the knowledgebased task. Typing task with the skill-based task (4 words). Typing task with the skill-based task (3 words). Typing task with the skill-based task (2 words). Typing task with no cognitive task.
Mean rating 47.2 41.3 38.0 34.3 33.5 29.1 28.2 18.0 15.7
Note: Tasks with the same letter are not significantly different.
memorization of two words or typing without a cognitive task requirement. According to Tukey’s test, stress ratings were comparable across typing, typing and skill-based task performance (with 2, 3, 4, and 5 words), and typing and knowledgebased task performance. 3.2. Secondary-task performance measurements Results of an ANOVA on typing task productivity revealed a significant effect of cognitive task type (p 5 0.0001) (see figure 3 for graph of condition means). It is interesting to note the high levels of concordance of these results with those of the subjective measure of perceived stress. The results of Tukey’s HSD test are shown in table 3 and the order of the tasks from the top to the bottom of the table is almost an exact inversion of the order of the tasks presented in table 2 based on the VAS1 results. Significant differences (p 5 0.05) occurred among typing alone and typing and skill-based task performance involving five or more words, and knowledge- and rule-based task performance. Secondary-task performance decreased 23% from the baseline condition when typing was performed along with the rule-based task. Even memorizing only two to three words while typing allowed for significantly (p 5 0.05) better performance than when subjects typed and memorized seven words or ordered the US cities from West to East. However, Tukey’s test did not indicate significant differences in performance (p 5 0.05) for dual-task conditions involving the knowledge-based task, the rule-based task, and skill-based task performance involving memorizing four or more words. 3.3. Physiological measurements As the general objective of this research was to describe the relationship between cognitive task load and physical stress, only EMG data collected during the third phase of test trials (the phase during which a participant was typing and thinking about the cognitive task) was evaluated (refer to figure 1). Further, the video
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Secondary-task performance averaged over 13 participants for all psychomotor and cognitive task types.
Table 3.
Tukey’s HSD test results on secondary-task performance for all psychomotor and cognitive task scenarios.
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Typing with no cognitive task. Typing task with the skillbased task (2 words). Typing task with the skillbased task (3 words). Typing task with the skillbased task (4 words). Typing task with the skillbased task (5 words). Typing task with the knowl edge-based task. Typing task with the skillbased task (6 words). Typing task with the skillbased task (7 words). Typing task with the rulebased task.
Note: Tasks with the same letter are not significantly different.
Mean number of words typed 171 170 162 158 149 148 141 135 131
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recordings of participant posture revealed no discernible activities or movements involving the trapezius or cervical erector spinae muscles that may have caused activity levels to vary. All participants appeared to sit still without moving their shoulders. 3.3.1. The trapezius: While there was a statistically significant effect of the cognitive task manipulation on the muscle activity of the right trapezius (p = 0.0404) there was no significance for the left trapezius (p = 0.3774) (see figure 4 for graph of condition means). Using the post-hoc test, a significant difference (p 5 0.05) was found between the baseline condition and the skill-based task of memorizing seven words (see table 4). Muscle activation in the right trapezius was 61% greater when the skill-based task involving the longest word list was undertaken at the same time as typing compared to the baseline condition. 3.2.2. The cervical erector spinae: The ANOVA results show that the muscle activity in both the left and the right cervical erector spinae were significantly affected by the cognitive task type (p = 0.0379 and p = 0.0132 for the left and right neck muscles, respectively) (see figure 5 for graph of condition means). When comparing the activation level associated with the rule-based task and the level for the baseline condition or the skill-based task of memorizing two words, a significant increase (p 5 0.05) of 6% was found in the left cervical erector spinae (see Tukey’s test results in table 5). The activation of the right cervical erector spinae muscle was 0.05
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0.04
0.03
0.02
0.01
0
Typing
2 Words
3 Words
4 Words 5 Words 6 Words Pscyhomotor and Cognitve Tasks Left Trapezius
Figure 4.
7 Words
Cities
Schedule
Right Trapezius
Muscle activity of the trapezius bilateral averaged over 13 participants, as a function of psychomotor and cognitive task types.
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Table 4. Tukey’s HSD test results on the mean muscle activity in the right trapezius, as a fraction of maximum activity, across all psychomotor and cognitive task scenarios. Grouping
Task B B B B B B B B
A A A A A A A A
Typing Typing Typing Typing Typing Typing Typing Typing Typing
Mean activity
task with the skill-based task (7 words). task with the skill-based task (4 words). task with the skill-based task (5 words). task with the skill-based task (6 words). task with the rule-based task. task with the skill-based task (2 words). task with the skill-based task (3 words). task with the knowledge-based task. with no cognitive task.
0.020 0.019 0.017 0.017 0.017 0.017 0.015 0.015 0.013
Note: Tasks with the same letter are not significantly different.
0.05
Fraction of Maximum Muscle Activity
0.04
0.03
0.02
0.01
0
Typing
2 Words
3 Words
4 Words
5 Words
6 Words
7 Words
Cities
Schedule
Pscyhomotor and Cognitive Tasks Left Cervical Erector Spinae
Figure 5.
Right Cervical Erector Spinae
Muscle activity of cervical erector spinae bilateral averaged over 13 participants, as a function of psychomotor and cognitive task types.
significantly greater (p 5 0.05) by an average of 11% when participants were required to memorize seven words as compared to two words (see Tukey’s test results in table 6). 3.4. Correlation analysis Simple correlation analyses were conducted on all response measures in order to determine the degree of correspondence among the subjective ratings, ‘primary’ performance measures and physiological measures in capturing cognitive load (i.e.,
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EMG and cognitive load
Table 5. Tukey’s HSD test results on the mean muscle activity in the left cervical erector spinae, as a fraction of maximum activity, across all psychomotor and cognitive task scenarios. Grouping B B B B B B B
A A A A A A A A
Task
Mean activity
Typing task with the rule-based task. Typing task with the skill-based task (7 words). Typing task with the skill-based task (4 words). Typing task with the skill-based task (6 words). Typing task with the skill-based task (5 words). Typing task with the knowledge-based task. Typing task with the skill-based task (3 words). Typing task with no cognitive task. Typing task with the skill-based task (2 words).
0.039 0.038 0.037 0.037 0.037 0.037 0.037 0.037 0.036
Note: Tasks with the same letter are not significantly different.
Table 6. Tukey’s HSD test results on the mean muscle activity in the right cervical erector spinae, as a fraction of maximum activity, across all psychomotor and cognitive task scenarios.. Grouping A A
B
A
B
C
A
B
C
D
A
B
C
D
E
A
B
C
D
E
F
B
C
D
E
F
G
B
C
D
E
F
G
H
D
E
F
G
H
Task
Mean activity
Typing task with the skillbased task (7 words). Typing task with the skillbased task (6 words). Typing task with the rulebased task. Typing task with the skillbased task (4 words). Typing task with the skillbased task (3 words). Typing task with the skillbased task (5 words). Typing task with no cognitive task. Typing task with the knowledge-based task. Typing task with the skillbased task (2 words).
0.042 0.041 0.041 0.040 0.040 0.040 0.039 0.039 0.038
Note: Tasks with the same letter are not significantly different.
to compare the diagnosticity of the measures) and to attempt to validate the EMG measures as local indicators of cognitive load. Pearson Product Moment coefficients were computed for each pairing of the left and right trapezius and erector spinae EMG measures, the secondary-task performance measure, the VAS ratings of perceived stress, and the MCH scale ratings of workload. Significant relationships of interest to this study occurred among the left erector spinae activation level and secondary-task performance (measured in terms of the number of characters typed correctly per time) (r = 7 0.38834, p 5 0.0001), the muscle activation in the right erector spinae and typing performance (r = 7 0.54001,
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p 5 0.0001), perceived stress during the test trials (VAS1) and typing performance (r = 7 0.46290, p 5 0.0001), the VAS1 ratings and perceived ratings of workload obtained using the MCH scale (r = 0.48714, p 5 0.0001), and MCH scale ratings and secondary-task performance (r = 7 0.37975, p 5 0.0001). In general, as muscle activation levels increased, secondary-task performance degraded. That is, with increases in participant physical stress, the level of quality of typing performance was compromised. Similarly, as perceptions of stress in the dual-task scenario increased, secondary-task performance suffered. The same relationship appeared to exist among perceived workload and the quality of typing. Not surprisingly, the perceived stress and perceived workload response measures behaved in a similar manner. 4. Discussion One of the most interesting results of this experiment was the significant difference in muscle activity when different cognitive tasks were posed to participants. On the basis of the results, the cognitive load imposed by a skill-based task in a dual-task scenario can be distinguished from the load caused by rule-based task demand in terms of local muscle activity (tension). Furthermore, it appears that differences in neck muscle activation occur when persons are required to perform skill-based tasks of varying degrees of difficulty. For example, whether someone is asked to memorize two or seven words while typing makes a significant difference in the activation levels of the cervical erector spinae. These observations support one of the hypotheses of this research; specifically manipulating the cognitive task in the experimental test would lead to differences in a participant’s physical stress response. The effect of the cognitive task type on muscle activation showed the right trapezius muscle to be most responsive to increased cognitive demands. These results agree with those of Waersted and Westgaard (1996) in a study of EMG of the trapezius and erector spinae associated with performance of a visual display unit (VDU) -based task demanding continuous attention. They noted that regardless of whether their experimental task required only the right hand or both hands for performance, the right trapezius activity was still significantly higher than the activity of the left. One explanation for this observed lateralization of muscle activity could be based on the fact that nearly all the participants in this study, and in Waersted and Westgaard’s (1996) research, were right-hand dominant. Another explanation can be based on brain hemisphere specialization in terms of cognitive processing and motor control and competition among cognitive processes for attentional resources within a hemisphere. Numerous studies have attempted to identify the underlying factors in the effect of memory task performance on concurrent finger tapping (Kee and Bathurst 1983, Simon and Sussman 1987, Dalen and Hugdahl 1989, Towell et al. 1994, Van Hoof and Van Strien 1997, Waldie and Mosley 2000). Typically tapping consistency and rate are degraded when a person is required to simultaneously recall memorized words. These studies have been motivated by the theory that the motor activity of each hand is programmed primarily by the contralateral hemisphere (Kinsbourne and Hicks 1978). In addition to this motivation, researchers have postulated that each of the two cerebral hemispheres is responsible for processing certain types of information (Waldie and Mosley 2000), for example the left hemisphere is specialized for verbal processing in right-handed individuals (Kinsbourne and Hicks 1978). In a study by Posner et al. (1988), the temporoparietal left-lateralized area was described as a good candidate for phonological processing. They assumed that if word reading required storage in
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short-term memory, the phonological processing center would be activated. Friedman et al. (1988) postulated that hemisphere-specific competition for cognitive processing resources would exist in the use of the left hemisphere for both verbal processing and contralateral motor control. Due to this competition, it is possible that the hemisphere specialization has an influence on muscle activity. As motor control processes executed in the left hemisphere compete with verbal processing as part of a dual-task scenario, like the one used in this research, a stress response may be more apparent in the muscles of the right side of the body than the left for a righthanded person. The significant differences in secondary-task performance observed among the various cognitive-task conditions revealed dual-task scenarios involving complex skill-based task performance and rule- and knowledge-based task performance to degrade typing productivity in comparison to the baseline condition. In general, with increasing cognitive complexity in primary task processing, the number of characters correctly typed decreased. This was also observed in an experiment by Birch et al. (2000). They recorded the EMG activity of shoulder and forearm muscles during a standardized computer design task with different combinations of time pressure, and precision and mental demands in order to study the interaction of these factors and their effect on muscular response. Increased mental load in the computer task caused a decrease in the number of drawings and an increase in the number of drawing errors. The results on secondary-task performance presented here were not surprising, as numerous studies of multiple task performance have demonstrated cognitive resource tradeoffs among primary and secondary tasks (see Damos 1991). However, one important observation that can be made is that the pattern of results on secondary-task performance (an objective measure of workload) nearly mimicked the pattern of results on the perceived stress ratings (VAS1). This observation offers support to the design of the VAS scale used in this study and its effectiveness for capturing cognitive load. Wierville and Casali (1983) conducted three experiments to evaluate the capabilities of the MCH scale. The experiments, although performed in a simulated aircraft environment, emphasized human activity typical in other psychomotor tasks. One of the experiments was designed to test the sensitivity of the MCH scale to cognitive load manipulations. The results of that experiment revealed mean MCH scale ratings to increase monotonically with cognitive load level. Similar results were found in this experiment. In general, as the complexity of the cognitive task increased, the perceived cognitive load increased. Rasmussen (1986) theorized that cognitive complexity would increase from a skillbased task (a task with low complexity) to a knowledge-based task (a task with high complexity). In contrast to this theory, the secondary-task performance measure, the perceived stress rating, and the EMG-levels observed in this study all indicated that the knowledge-based task posed less of a cognitive load than the other two task types. In fact, all of the dependent variables followed a similar trend as a function of increasing cognitive task load, save the VAS2 ratings. These observations suggest that the cognitive complexity of the knowledge-based task was relatively low. One possible explanation for the result is that the knowledge-based task was indeed less complicated or that the skill-based tasks were more resource-intensive from a cognitive perspective. It is possible that the form of the skill-based task may have approached the ‘boundaries’ of Rasmussen’s (1983) original definition of skill-based
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behaviour because participant performance was dependent upon a feedback condition (the end of the secondary psychomotor task) and involved verbal processing instead of automated motor control. Classical examples of skilled-based behaviour include tracking tasks, assembly work, etc., but in terms of the cognitive aspects of performance, the memory task may be classified as skill-based. This classification of the memory test and the form of the knowledge-based task, may have contributed to the finding that cognitive load did not increase consistently across the skill-, rule- and knowledge-based task continuum. Again, it is important to note that even Rasmussen (1983, 1986) observed that the boundaries between skill- and rule-based behaviour, and rule- and knowledge-based performance, are not quite distinct. The classification of tasks depends upon the memory structures of operators and the use of attentional resources. We focused on how semantic, prepositional and schema memories (Wickens 1992) would be used in performance of the cognitive tasks in order to classify the memory test, geography task and activity-scheduling problem. Another potential explanation of the observed relationship of cognitive task complexity to workload response is that knowledge-based training during the orientation session was more effective than rule-based task training. Beyond this, participants may have been more familiar with the task of daily activity scheduling than the geography task, based on personal scheduling, etc. In regard to the VAS2 ratings, the lack of significant differences among cognitive task conditions and graphical analysis demonstrated that the perceived stress-levels of participants returned to near baseline levels after each trial. The majority of the findings based on the correlation analyses were not surprising given that VAS scales, the MCH scale and secondary-task performance measures have all been validated as robust and reliable indicators of primary task workload (see Wickens 1992). However, the analyses did provide important statistical evidence that measures of muscle activation level may also be valid indicators of cognitive load. Pearson coefficients suggested neck tension might be indicative of high cognitive stress (as reflected by secondary-task performance), particularly in dualtask scenarios. The limitations of the current study include the relative simplicity of the cognitive tasks that participants performed. In each of the test trials, participants were exposed to one type of cognitive stress and this stress was only experienced for a short period of time. The absolute magnitude of changes that occurred in muscle activity across the various cognitive tasks was small. It is hypothesized, however, that in real office situations where there may be multiple cognitive demands placed on an individual (and these demands may be made over a period of hours instead of seconds), cervicobrachial muscle activity may increase substantially. Therefore, the results of the present experiment may underestimate actual stress responses in real office environments. Further research is needed to expand on the findings of this study by examining more complex primary cognitive tasks that are of a longer duration in order to obtain results that may be more representative of increases in muscle activation levels in realistic circumstances. Another important direction of future research is analysis of the right/left-handed and hemisphere-lateralization phenomenon hypothesized in this study. It would be interesting to study a sample population consisting of equal numbers of left- and right-handed persons to determine whether results are comparable with those of the present work. In addition to considering handedness, it would be interesting to
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account for gender in a similar experiment. A study by Birch et al. (2000) revealed several significant differences between male and female operators in their approaches to industrial jobs, including: (1) female operators report more occupational injury/ illness symptoms than men; (2) males and females maintain different work postures; and (3) EMG levels vary across genders during computer work. Other research (Dalen and Hugdahl 1989) has also shown that males and females have different patterns of cerebral lateralization. If hemisphere-specialization was a reason for higher stress-levels in the right side of the body in the present study, then different stress-levels might be expected among males and females. 5. Conclusions The aim of this study was to evaluate the impact of cognitive load in office-type tasks on physical stress response, specifically tension in the cervicobrachial muscles during a dual-task scenario involving typing. The results demonstrated significant increases in neck and back muscle tension with increases in cognitive load. These findings were supported by results on validated subjective and performance-based workload measures. In general, manipulation of the type of human performance behaviour required in a dual-task scenario and the complexity of cognitive processing appears to have an impact on the spectrum of workload measurement techniques, including physiological measures, based on muscle activation levels. This is an important observation towards validation of a local EMG measure of cognitive load in office tasks. These results help us to understand the effects of multiple, simultaneous task performance on stress levels and could lead to further work that may provide insight into which combinations of cognitive and physical tasks may pose the greatest load on workers.
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Appendix 1. Skill-based task The words used for the skill-based task included: ‘file’, ‘work’, ‘test’, ‘plan’, ‘code’, ‘post’, ‘list’, ‘talk’, ‘hall’, ‘week’, ‘five’, ‘back’, ‘wire’, ‘cash’, ‘hang’, ‘cell’, ‘heat’, ‘rise’, ‘site’, ‘none’, ‘lack’, ‘boss’, ‘lean’, ‘deep’, ‘draw’, ‘stub’, and ‘lock’. Appendix 2. Rule-based task The cities used for the rule-based task were: Los Angeles, Denver, Chicago, Atlanta, and New York City. These cities were ordered from West to East. Appendix 3. Knowledge-based task The script describing the schedule used for the knowledge-based task was as follows: ‘At 7 o’clock the alarm-clock goes off and you have to get out of bed. At half past seven, you have breakfast so that you can start the car at 8 o’clock and be at work at half past 8. Today, you have to make a schedule for two people in your department, which should be done by 10 o’clock because you have to go to the bookstore on Hillsborough Street to pick up an order. At 12 o’clock, you have lunch with your colleague for 45 min. After lunch, you go quickly to the grocery to buy some items for dinner with visitors at your home tonight. When you return to the office, you find a lot of faxes that have to be arranged. After that, you make coffee for the people in the department. At 2 o’clock there is a class about the latest discoveries concerning the ergonomics of sitting at a computer workstation. At 5 o’clock, the class is finished. There is some time left to clean up your desk after the day’s work. However, at 6 o’clock you have to leave because otherwise you will be late for your visitors.’