1.1. Introduction

“It is only with the heart that one can see rightly; what is essential is invisible to the eye” [DES 43]. This quote is the perfect introduction to this chapter, which contains an approach to evaluating the impact of the synchronization of demands with heart beats in terms of the occurrence of attentional dissonances.

An accident or an incident is often due to a combination of human, technical, environmental or organizational factors. Two levels of gaps are generally envisaged [VAN 03]: a behavioral gap, for example when the actual behavior of a human operator is not as expected, and a situational gap, for example when the true consequences of behavior are not as expected. To simplify these risk analyses, acceptability thresholds are defined in order to determine whether such and such a gap must be processed. Yet, this approach neglects gaps of low amplitude or frequency that could sometimes provide an explanation of the occurrence of some undesirable events. These margins can, in the long term, be associated with dangerous situations.

The concept of dissonance, generated voluntarily or involuntarily, with or without the knowledge of its real or possible consequences, responds to this problem. It allows consideration of imperceptible signals that can generate risks such as these.

The occurrence of a dissonance can be associated with physiological measurements of pain, stress, boredom or fasting, for example [JOU 87]. It is then evaluated from the electrodermal activity, electroencephalographic activity, acids contained in the blood and related to inanition, or blood pressure. Even if the dissonances in terms of personal conviction do not appear to affect the activity of the heart [JOU 87], the impact of heartbeats on certain emotional factors such as stress, joy or surprise has often been a subject of research. On the other hand, only rarely has research related these heart rhythms to attentional factors such as being awake or perception. It is about treating an imperceptible signal that could have an impact on human performance.

This chapter is based on the following assumption: genesis of attentional dissonances can be due to the synchronization of stimuli with heart rate. The first two sections establish a link between different concepts, in other words between human error and dissonance, then between cognitive conflict, attention and attentional dissonance. Following a description of the causes and the evaluations of dissonances, the last two sections describe an exploratory assessment and its results on attentional dissonances, based on the analysis of the heart rate synchronized with the activation of visual and auditory stimuli. The results are promising and make it possible to envisage design of automated systems that are capable of detecting synchronization of this kind and to control any related attentional dissonances.

1.2. From human error to dissonance

Human reliability is defined as the capability of a human operator to correctly carry out their prescribed tasks and additional tasks in compliance with predefined conditions, over a time interval or at a given moment in time, for various evaluation criteria such as safety, production or quality of activity, workload or satisfaction [VAN 17a]. Human error is the complementary factor of this: this is the human capability to incorrectly carry out planned or additional tasks under the same conditions.

More than 70% of accidents are due to human error and 100% of them are directly or indirectly related to human factors [AMA 13]. Retrospective analysis of accidents leads to the identification of the cause of their occurrence. It allows a list to be drawn up of all the factors that have resulted in the accident occurring and can be added to using prospective assessments in order to anticipate all the possible accident scenarios. The factors that can affect human performance or the safety of a system are called PSFs (performance shaping factors) in the field of human reliability analysis. PSFs allow the characteristics of the human operator to be taken into account, as well as the context and environment that affect their performance in a positive or negative way. In comparison to research work into occurrence mechanisms of human errors, PSFs that are most often processed are attention, vigilance and workload [VAN 09, RAC 14, RAN 17]. These prospective or retrospective analyses allow new safety barriers to be set up or adaptation of those already in place.

However, designing a system to support the control of safety in order to reduce a risk is not sufficient; it is also necessary to assess the possible evolutions of its use and the associated risks. For example, the use of an automatic speed control device can generate behavioral deviations such as the creation of new functions of the technical system, the reduction of the distance between vehicles, or the increase in response time or hypovigilance [DUF 14, VAN 14]. Naive reasoning could lead to the development of automated vigilance control systems to reduce these risks of use of other automated systems.

The accident of August 30, 2004 in Rouen [BEA 05] is an example of the limitations of this approach. It was caused by the state of hypovigilance of a driver who went through a red signal and hit the back of a train carriage that was stopped in front of him. In the accident report, it is written: “The automatic driver surveillance system (i.e. the VACMA) of the impacting carriage, although in an operational state and apparently still activated by the driver, was not effective in preventing the accident”. Thus, the driver would be capable of activating these automated systems as a habit, without being vigilant or attentive. It is important to note that the surveillance system can only detect a major incapacity (loss of consciousness) and not a slight incapacity such as a reduction in vigilance [CAB 93, CAB 95].

Many studies have identified situations that are likely to cause human errors or have defined methods to evaluate them quantitatively or qualitatively [VAN 04, VAN 10, HIC 13, SED 13, PAN 16, QIU 17, RAN 17]. However, most of these approaches limit themselves to the assessment of planned or prescribed tasks, and do not take into account additional tasks due to the dynamic evolution of human knowledge over time and the creativity of human operators who can modify the initial functions of a system or invent new ones. In addition, something that is considered to be erroneous by some may become acceptable by the same actors, or be assessed as normal by others: different analysis reference frames exist and must be taken into consideration in the analysis of human errors. Lastly, human error can be seen as a consequence of a malfunctioning system rather than as a cause of an undesirable event, which calls into question the interest of classic accident analyses [REA 00].

The concept of dissonance allows a response to be given to these constraints that discredit the results of analysis of human errors [VAN 17a]. Based on Festinger’s work on cognitive dissonance [FES 57] and Kervern’s work on collective or organizational dissonance [KER 94], a dissonance is a conflict between cognitions, in other words between knowledge or elements of knowledge on an individual, collective or organizational level [VAN 14, VAN 16]. It is an immediate or future disagreement or incoherence in data or information, in perception, processing or interpretation of them, and in the solutions applied to process them, concerning technical, human or sociotechnical systems. A dissonance can be evaluated in terms of instantaneous or long-lasting gaps between what is prescribed, felt, perceived, expected and real. The reference basis used to identify a dissonance may be inexistent, erroneous, unique or multiple. Several conflicting criteria can be processed: for example, conflicts of use, independence, intention, interest, perception, emotion, allocation or attention (see Table 1.1 [VAN 17b, VAN 18]).

A dissonance can be intuitive or can appear with or without prior explanation or justification. It cannot be detected or its detection can be correct or erroneous. Processing of this dissonance can then generate different effects: generation of a new dissonance, increase in workload, increase in the level of discomfort or awkwardness, increase in risk-taking tendencies, increase in personal satisfaction, etc. This is why the acceptability of a dissonance is inversely proportional to the difficulty of processing it. Indeed, if, for example, significant learning effort is required for the latter, the dissonance cannot be acceptable and impact reduction strategies relating to the reinforcement of knowledge can be implemented: rejection of dissonance, promotion of current knowledge, denial of disturbing knowledge or change of point of view. These knowledge reinforcement methods can be implemented in learning models [VAN 14, ENJ 17].

1.3. Cognitive conflict, attention and attentional dissonance

A cognitive conflict is a temporary incoherence during which at least one limited resource is subject to multiple solicitations or at least two pieces of information contradict each other [DEH 12]. Multiple solicitation can generate an action dissonance, and data incoherences can cause informational dissonance due to changes in organization, for example. During simultaneous execution of tasks, attention resources can be saturated due to their limited capacity because they are managed by short-term memory [KAH 73]. A human operator can then choose to concentrate on one of the tasks, leaving the secondary task to one side: this is the paradigm of selective attention [CHE 53].

Attention is the focus of mental activity on a subset of the perceptive field with selectivity about the information taken in. Its role is therefore to control and orient the activity. It necessarily implies a certain degree of vigilance, bearing witness to the state of wakefulness of the human operator, where vigilance is highly sensitive to ultradian and circadian fluctuations. Two situations can be distinguished: the evaluation of this state at a given time and its evolution over time [MAC 61]. There are two types of attention: the selective type and the sustained type [BAL 96, OKE 06]. Selective attention allows cognitive resources to be focused on priority tasks, whereas sustained attention consists of maintaining it continuously while taking into account modifications that may arise in the tasks to be carried out. These distinctions sometimes lead to very common confusions in the definition of the concepts where attention is then assimilated to an instantaneous state of wakefulness and vigilance to a sustained state of attention. As for workload, this can have an impact on the state of vigilance and consequently on attention. It is defined as the difficulty felt by human operators to carry out tasks as a function of their cognitive, physical and physiological state.

Automatic cognitive processes, implemented during usual situations, are differentiated from controlled cognitive processes, activated in the event of more complex situations [SCH 77, SHI 85]. The first are not very costly in terms of attention resources and can be executed concomitantly with a controlled activity. The second are very costly and cannot be implemented simultaneously with another activity that calls on the same process due to limited attention capacities.

Blindness to change with analysis of complex visual scenes illustrates the incapacity of a subject to detect the changes from one visual scene to another, even when these changes are significant [REN 97]. Attention is required to detect them correctly, in particular when visual signals disturb the subject’s attention [SIM 05] or during an interruption, even rapid, of visual contact [SIM 98]. Similarly, a subject can be incapable of perceiving an unexpected object while their attention is focused on another object [MAC 98]. This phenomenon of inattentional blindness has been made famous by the experiment using a video in which basketball players exchange passes and an incongruous character slips in among the players during the game [SIM 99]. If the subjects are asked to count the number of passes made, their attention is focused on that, and 46% of them do not perceive the presence of the unexpected person. According to those authors, the probability of perceiving an unexpected object can be related to its similarity with objects on which attention is focused and also on the complexity of control of the task to be carried out.

The tunnel effect can be compared to this inattentional blindness. It can occur when the cognitive capacities of the operators are altered, for example during a situation requiring a certain mental effort [WIC 09]. At that time, important information such as visual and/or auditory alarms can be neglected by the operator [DEH 10]. This behavior can lead an operator to focus excessively on an irrelevant set of information to the detriment of critical information such as alarms [DEH 16]. However, the tunnel effect is eliminated by alarms that are coherent to the context, whereas this is not the case when alarms are out of context. The tunnel effect or attentional tunnelization therefore appears to depend on emotions and on the mental workload of the operator. It can also occur during particularly stressful situations, and can induce unsuitable responses for the various situations, depending on the level of stress felt by operators [PIN 11].

An attentional dissonance is a cognitive conflict of attention. It involves the dissonances shown in Table 1.1, of which the causes or consequences are related to an attention failure. These dissonances can be explained by differences between attention that is felt and effective attention, or between the certainty that one will do a good job and the reproach of inattention. The tunnel effect is an example of attentional dissonance because it may be due to an attention failure and generate an overload if the problem associated with it is detected and processed in time, or awkwardness if it is too late. An organizational change is another example of attentional dissonance. Indeed, structural or operational modification to communication media can disturb the search for pertinent information by dispersing attention. The gaps between the attention levels that are required, desired, perceived and real, from a reference frame or various reference frames, lead to the identification of dissonances of this kind. They must help qualify the type of attention conflict:

• – attention overload: since the demands of the task are very significant, attention resources are not sufficient to process them;
• – attention focusing: attention resources are monopolized on one given task or group of tasks, with no provision made for possible new disturbances;
• – attentional blindness: everything appears to be normal but no human reaction occurs when alarms are activated;
• – attention diversion: human operators are concentrated on their work but a sudden event that is assimilated to an alert diverts their attention;
• – attentional disturbance: attention is disturbed by regular events that are not essential. For example, irrelevant information can disturb perception of important messages [LEW 70, POS 98];
• – attention dispersion: attention is distributed across several tasks simultaneously, which increases the risk of an error in the perception of important information.

1.4. Causes and evaluation of attentional dissonance

Attentional dissonances can be evaluated by applying different methods of evaluation of attention, vigilance, workload, human error or emotion. These approaches allow qualitative, quantitative or subjective indicators about the actual cognitive state. For example, indicators associated with excessive or low solicitation of cognitive resources or associated with the execution frequency of identical actions can affect the vigilance or attention of a human operator, and increase the number of occurrences of human errors [VAN 99, DON 15, MIN 17]. There are various objective indicators for studying mental load, in particular physiological indicators (heart and respiratory rates, endocrine system) and performance indicators (double task paradigm), as well as subjective indicators, such as the National Aeronautics and Space Administration Task Load Index which is more commonly known as the NASA-TLX. The NASA-TLX [HAR 88] leads to evaluation of the subjective workload by carrying out a multidimensional analysis. It is based on six parameters: mental demand, physical demand, time pressure, performance, effort and frustration. When it is difficult to quantify factors, the subjective method visual analog scale (VAS) can be used [CRI 01, TOR 01]. It proposes subjective scales that contain antagonistic terms at their extremities. The estimates carried out from methods such as NASA-TLX or VAS allow an overall load level to be calculated or the parameters associated with this load to be studied separately. Since there appears to be a link between workload, emotion and tunnel effect, emotion self-evaluation methods can be used, including questionnaires for understanding the attitudes of each operator [MAN 07]. The standardized scale Self-Assessment Manikin (SAM) is an example of this [BRA 94]. It demonstrates three dimensions: valence, emotional arousal and dominance, represented by three series of lines of nine manikins. The first series corresponds to the valence dimension. If the subject is in an extreme positive state, they must mark a cross on the manikin that is the furthest to the right, otherwise they must select the one that is the furthest to the left. However, the subject can choose to select intermediary manikins. They must apply the same principles for the dimensions of emotional arousal (very awake/excited for the right-hand manikin; very calm for the left-hand manikin) and dominance of the situation in progress (highly submissive for the left-hand manikin; highly dominant for the right-hand manikin). This scale has been used in a large number of studies and constitutes a simple, rapid and valid means of recording feeling.

Research work in neuropsychology that aims to estimate cognitive processes generally requires heavy and sensitive apparatus, physically connected to the body of an individual. As for research in engineering, it has for too long been restricted to research with classic indicators such as the percentage of eyelid closure or the diameter of pupils, without looking into the validation of unusual hypotheses based on other physical or physiological data obtained from evaluations of attention, vigilance or workload. For example, for a long time, the increase in the diameter of pupils has been correlated with the increase in the level of demand for the tasks to be carried out. Thus, the higher the cognitive load, the more the pupils tend to dilate [BEA 82]. Similarly, the difficulty of a problem to be treated causes an increase in the diameter of pupils [LEM 14]. Yet, it has recently been demonstrated that though this hypothesis is verified for cognitive demands, an increase in physical demands reduces this diameter [FLE 17]. In addition, this hypothesis is faced with various problems such as the variation in ambient light, whether medicines or drugs have been taken or the occurrence of strong emotions.

Heart activity is often correlated with a level of stress or workload [CAB 03, PIZ 12, BUC 16]. Yet, following stress, these palpitations are felt strongly by a subject, whereas in a normal situation, the latter does not hear them. A recent study looked closely at the fact that the human brain does not perceive the body’s heartbeats [SAL 16]. Thus, it has demonstrated that when an image flashes in a way that is synchronized with the heart rhythm, the activity in the insular cortex is greatly reduced, to the point of causing difficulty or an incapacity of the subjects to perceive flashing shapes. Thus, it is possible that there is a link between attention and these physiological reactions.

Estimation of the attention state of human operators and detection of the tunnel effect can be carried out by combining the position of the operators’ gaze and their heart rate as an indicator of stress and workload [PIZ 11]. The use of an eye-tracking device has led to it being shown that if the operator focuses on a target for a long period of time, the probability that they perceive other information diminishes. The attention focus of the operator is then associated with a low rate of ocular saccades and a high rate of ocular fixations.

With respect to external solicitations at work, noise can often disturb or reduce human attention and increase the level of stress. However, listening to music [CHT 15] or increasing the speed of the ticking of a clock [YAM 13] can increase individual physical capacities. Other studies do not find significant differences between the impact of noise or music on these capacities [DAL 07]. Lastly, the silence generated by relaxation techniques can increase the level of attention, in particular, for convalescence situations [PRI 17]. The effects of digestion can also affect vigilance and consequently human attention. Thus, certain studies have demonstrated an improvement of these factors during diets or fasts [FON 13].

Verbal presentation of a problem or a situation can attract the attention of certain people or not produce any effect for others. These are stimuli associated with culture, experience or personal learning. For example, when calling a person by their name, the person turns around but they do not turn around if it is someone else’s name. Being sensitive or indifferent to a given formulation or expression can be exploited to manage attentional dissonances. Methods of analysis of verbalizations can help to identify behaviors and create a link between the perceived state of human operators and the associated PSFs [CAI 16].

1.5. Exploratory study of attentional dissonances

Taking inspiration from the work of Salomon et al. [SAL 16], the aim of this exploratory study was to try to identify whether attentional dissonance can occur for subjects whose mental workload is high, and when the simultaneous appearance of visual and auditory alarms to be detected is synchronous with the heart rhythm.

Each alarm was defined by simultaneous appearance, always at the same location on the display screen. It consisted of two flashing squares each with a surface area of 3 cm × 3 cm, amber and red in color. The alarms were systematically accompanied by a specific sound, identical to that used in aeronautics to indicate an abnormality. They were presented in a random manner and distributed over four levels of difficulty, described in the following paragraphs, and the subjects were warned that they could occur.

In order to analyze and understand this tunnel effect phenomenon, objective data were collected, such as the heart rate (Hr), using a specific device attached to the subjects’ wrist (the Mio^TM watch). This device was also synchronized with the experimental material in such a way as to be able to create similar conditions to those mentioned by Salomon et al. [SAL 16], where the alarms are synchronized to the subject’s heart rhythm.

Errors and omissions of tasks to be carried out were also counted for each level. An error was counted as a false alarm when the subject indicated an alarm, but there had been no alarm. As for the subjective data, their goal was to give information about the mental load, and the performances and emotions felt by the participant. They were obtained by means of the NASA-TLX, SAM and VAS methods. The simplified and standardized French version of the NASA-TLX method was used [CEG 09].

Twenty-seven subjects, mostly recruited from within ESTIA (M = 28 years; SD = 8), participated in this experiment. They were randomly divided into two groups depending on whether the appearance of 30 visual and auditory alarms (couples of flashing squares) that they had to detect were configured as synchronous (n = 15) or asynchronous (n = 12) to their heart rhythm.

After filling in a questionnaire with the objective of collecting information about their various characteristics (age, visual problems, attention capacities, tiredness, etc.) and having the experiment explained to them, the participants were equipped with the Mio™ watch. The watch read their heart rhythm, with which the appearance of alarms may – or may not – have been synchronized. The watch also allowed the heart rate of subjects at rest to be known in advance.

Three short video tests were then presented to them, inspired by the model from Simons and Chabris [SIM 99], in order to carry out an initial verification in relation to the concept of inattentional blindness. The subject was then placed in front of a touchscreen for the experiment, which took place over four levels of increasing difficulty. The first level, with a duration of three minutes, was considered to be an adaptation stage, during which only six alarms were presented. Over the course of the three following levels, with a duration of six minutes each, eight alarms were presented each time.

The subject’s main task was to carry out an attention test that consisted of surveying digital events (cursor movements, control of indicator lights). The test used was inspired by the MultiAttribute Task Battery (MATB) [COM 92], frequently used in research into aeronautics to measure the mental load of operators.

For level 1, the subject had to survey four cursors and two indicator lights, and then for the three following levels, eight cursors and four indicators. The cursors moved vertically. When one of the cursors came to the end of its track, either upper or lower, the subject had to press the corresponding function button of the touchscreen (F1, F2, F3, F4) to bring the process back to a stable state. One of the indicators was initially lit and the other was turned off. When one of the buttons changed state (in other words, the unlit indicator turned on or the lit indicator tuned off), the subject had to press the corresponding function button (F5 or F6) to bring the process back to its initial state. If the subject required more than five seconds to react when the cursor reached the end of its track, the process returned to a normal state and they were warned of this by an auditory alarm.

The order of appearance of the events was programmed, and was reproduced

11 times over the three-minute period for level 1 and 34 times for each six-minute period for the three following levels, according to a predefined procedure.

In addition, for the last two levels, the load increased even more with the appearance of a secondary task: the resolution of a tangram (Chinese puzzle with seven pieces) which broke down more and more quickly between levels 3 and 4 (Figure 1.1). The subject had reconstitute it little by little by occasionally pressing the touchscreen whilst continuing to survey the cursors and display buttons, and also anticipating the appearance of alarms. If the participant did not click on the pieces of the tangram when they began to separate, or if they did not detect that the pieces had become totally separated, the experiment was stopped.

As soon as the subject saw the flashing shape accompanied by an auditory signal, they were instructed to press a pushbutton located within reach. As soon as the button was pressed, the auditory signal stopped and the squares disappeared. If it was not pressed within 10 seconds, the subject was considered to have omitted the alarm.

Taking into account the fact that between each level, the subject was distracted by requests for evaluation of their actions, it was considered that they could not memorize the various events that had taken place during the test. A possible learning effect was therefore neutralized, which was verified during the experiments.

After performing each of the four levels of the experiment, the subject had to evaluate their mental workload using NASA-TLX, and their level of performance, level of confidence in the preceding evaluation, the difficulty of the task and the effort made using the VAS method. These evaluations, graded on a scale from 0 to 100, were presented by means of a touchscreen. The three scales in the SAM method (represented by various pictograms to tick) relating to valence, arousal and dominance were also presented to the subject but only at the start or the end of the experiment (end of the first level and the last level).

1.6. Results of the exploratory study

For the two factors in the experiment, meaning the condition (synchronous or asynchronous) and the level (progressive increase in difficulty or the four-point mental workload), the following dependent variables (DV) have been analyzed:

• – percentage of omissions and errors;
• – heart rate (Hr);
• – NASA-TLX scale;
• – analogical scales for subjective evaluations (performance, confidence, difficulty, effort, SAM valence, SAM arousal, SAM dominance).

Where the data allow it (homogeneity of variances, compliance with normality conditions), ANOVA inferential analysis has been carried out using the various selected parameters [COR 03].

Thus, an ANOVA F-test has allowed the overall effect of each of the two factors to be analyzed. For two-by-two comparisons of the experimental content (concerning the levels), a post hoc test was used (Scheffé test) when the overall effect was significant. Lastly, when the overall effect of each factor was significant, the effect of interaction was tested.

With the exception of the heart rate, the parameters selected to characterize the behavior of the subject, as much from the point of view of the performance as that of their feeling, are sensitive to synchronization of the alarms with the heart rhythm of the subject and to the effect of the complexity of the task. The same goes for the subjective evaluations given by the NASA-TLX, VAS and SAM scales. Figures 1.2–1.8 that are commented on hereafter give average values of the results with a confidence interval of 95%

The descriptive statistics of these data indicate that the subjects in the asynchronous condition make an average of 13.30% omissions/errors (SD = 8.53), whereas the subjects in the synchronous condition make an average of 23.11% (SD = 9.14), and the overall effect is significant: F (1,25) = 8.15; p = .008 (Figure 1.2). The same is true for the levels, where the overall effect is significant: F (3,75) = 7.23; p = .0002 (Figure 1.3).

Levels N3 and N4 of the experiment, which induce the greatest mental load, encourage subjects to commit the greatest number of errors or omissions. But even though it is true that this number of errors/omissions increases progressively as a function of the level of complexity of the task, the effect is only significant between level 1 and the other levels (Scheffé post hoc tests), and the subjects adopt behavior that is quite homogeneous (equivalent dispersions for N2, N3 and N4).

For all levels of mental demand, the subjects of the synchronous condition make more mistakes than the subjects of the asynchronous condition, and the difference is more significant for levels N2 and N3. For the most difficult level N4, the subjects for the synchronous condition increase their rate of errors enormously, whereas those in the asynchronous condition reduce them (Figure 1.4).

The heart rate (Hr) is expressed in beats per minute (bpm). Although for the synchronous condition (M = 84.77, SD = 18.83), the Hr is slightly higher than for the asynchronous condition (M = 82.93, SD = 10.46), the difference is not significant. A larger dispersion occurs for the synchronous condition. Nevertheless, the effect of the difficulty of the task is significant, and a progressive variation exists related to the level of demand, no matter what type of condition the subject is attributed to (F (3,75) = 7.47; p = .0002). This indicates that the experiment has been validated from the point of view of the increase in mental workload (Figure 1.5).

The NASA-TLX is made up of six parameters to be evaluated, each graded on a scale from 0 to 100: mental demand, physical demand, time demand, evaluation of effort, performance, frustration. For the results presented hereafter, the Raw Task Load Index (RTLX) [BYE 89] was calculated by taking the average of the results obtained for the six dimensions. There is a difference of 2.50 evaluation points for the overall mental load between the group of subjects of the asynchronous condition (M = 51.10, SD = 3.60) and the group of the synchronous condition (M = 48.56, SD = 3.19). On the other hand, for all the subjects, the evaluation between the various levels is significant (Figure 1.6), which tends towards the same conclusion as the results given by the analysis of the Hr (F (3,78) = 54.5791; p = 0.0000).

The VAS used is over four dimensions, each given a mark out of 100: evaluation of performance (VASperf), evaluation of the confidence (VASconf) attributed to the assessment given for performance, evaluation of the difficulty (VASdiff) and the effort made to carry out the task (VASeff). The inferential statistics indicate that the effect of the condition is not significant for VASdiff, VASeff and VASconf.

On the other hand, it is significant for the VASperf for levels 2, 3 and 4, where the synchronous subjects believe their performances to be less important than those evaluated by the asynchronous subjects (Figure 1.7a and 1.7b).

The variation in performance evaluation between the synchronous condition and the asynchronous condition is very different. Indeed, concerning the synchronous condition, there is a high evaluation of performances for level 1; this diminishes for level 2, also for level 3, whereas for level 4, performance evaluation increases. Concerning the asynchronous condition, the evaluation remains relatively homogeneous from one level to the next.

Thus, the subjects do not appear to be aware of the real evolution of their performance in terms of the occurrence of omission errors.

The SAM scale includes three evaluations, each given a mark from 1 to 9, regarding the “pleasure” that the subject has or has not felt when doing the task (SAM Valence), their state of wakefulness (SAM Arousal) or their dominance or lack of this with respect to the requested task (SAM Domin). There is no significant effect between the two conditions, no matter what kind of evaluation is to be provided. However, from a descriptive point of view, the evaluation of valence at the end of the experience is slightly lower for synchronous subjects (6.50 points vs. 6.20 points), whereas the opposite is true for asynchronous subjects (6.50 points vs. 7.00 points). Concerning the effect of the level of demand, there is no significant effect on valence, but there is an increase in the evaluation of arousal and of dominance between the beginning and the end of the experiment, no matter what the condition is, and the effects are significant: F (1,26) = 12.55; p = .002 and F (1,26) = 9.50; p = .005 (Figures 1.8a and 1.8b).

1.7. Conclusion

This chapter has proposed a new approach to analyze dissonances that is based on an attention factor: heart rate. An exploratory study has demonstrated the interest of taking into account the synchronization of visual and auditory alarms with heartbeats to justify errors of perception.

Four levels of increasing difficulty were proposed to 27 subjects. This increase in difficulty level is confirmed by the results of evaluation of the overall workload perceived with the NASA-TLX method. For these four levels, there were no significant differences in the heart rhythm of the participants; there were no atypical subjects for any group (synchronous or asynchronous condition).

Over the course of the experiments, 15 subjects carried out the four levels for which activation of the alarms was synchronized with their heart rhythm, and 12 subjects carried them out without synchronization. The quantitative omission errors are significantly higher for the first group than for the second. This difference is again seen with the subjective evaluation of performance using the SAM method and of arousal and dominance with the VAS method. The same level of confidence is attributed to the subjective mark for performance and the difficulty felt for the task to be carried out. The effort made to execute it or the “pleasure” felt during the experiments is similar in both groups. The debriefing carried out after the experiment also allowed future experimental routes to be identified, in that the majority of the subjects for whom the occurrence of alarms was synchronized with their heart rate did not mention these alarms or indicated that they did not have the feeling of having omitted many, on the contrary to those who were asynchronous. These verbalizations are expected to be studied in further detail soon using semantic discourse analysis methods [WOL 05, CAI 16]. The eye-tracking data could also have corroborated these feelings and could also have been related to the data for omissions/errors. Construction of the next experimental devices will need to take these eye-tracking constraints into account.

This first exploratory study opens up interesting possibilities in terms of the design of sociotechnical systems and assessment of the risks associated with attentional dissonances. Figure 1.9 gives an example of genesis of this type of conflict due to synchronization of physiological signals (heartbeats) with information about the process that is being controlled (alarms).

Attentional dissonances of this kind can affect perception of alarms, interpretation of them, associated actions or the perception of performances. Future research must lead to a more in-depth look at this hypothesis and at design optimization of visual and auditory alarms to avoid activating them in a way that is synchronized with the rhythms of physiological activity.