Elsevier

Neurocomputing

Volume 84, 1 May 2012, Pages 23-30
Neurocomputing

Is your phone so smart to affect your state? An exploratory study based on psychophysiological measures

https://doi.org/10.1016/j.neucom.2011.12.027Get rights and content

Abstract

Traditional stress management techniques require significant professional training and expertise to administer as well as people, time, and resources, which can be difficult to achieve. Thanks to the recent progress and diffusion of mobile electronic devices, it is possible today to set up and test an effective self-help stress management program outside a clinical setting. Although the efficacy of mobile self-help approaches have been tested through several studies, and promising applications can be developed, as yet no study has tested the feasibility of mobile platforms to actually elicit core affective states. In this study we used an advanced approach to assess the efficacy of these mobile platforms by recording and processing many psychophysiological measures, which extend the capabilities of the standard self-report questionnaires, objectifying the subjective. Our results seem to show the efficacy of inducing positive and negative affective states, using smart phones.

Introduction

According to Cohen and colleagues [1], psychological stress occurs when an individual perceives that environmental demands tax or exceed his or her adaptive capacity to cope with them. This definition integrates the traditional approaches to stress [2], [3], [4], [5], [6], [7] emphasizing that a stressful experience could be conceptualized as a person–environment transaction. Strategies frequently used to cope with stress include relaxation techniques, promotion of a healthy lifestyle, and cognitive-behavioral therapies (e.g., stress inoculation therapy, rational emotive therapy, cognitive restructuring, and behavioral rehearsal). Traditionally, these strategies require significant professional training and expertise to administer as well as people, time, and resources, which can be difficult to achieve.

To overcome these limits, self-help approaches and telehealth-based treatments are being developed to enhance treatment fidelity, effectiveness, and accessibility [6], [7], [8], [9]. Specifically, mobile phones are gaining particular importance in health care services [10], [11]. In fact, the incredible diffusion of mobile electronic devices [12] has introduced the possibility of setting up and testing effective stress management techniques beyond a clinical setting [13], [14]. In a recent work of research, Villani and colleagues [15] verified the efficacy of a stress management protocol supported by the use of mobile phones. According to that study, the advantages of using a mobile approach to reduce stress could be an incremental acquisition of coping skills in an autonomous way [16], a ubiquitous and effective support in facing daily stressful situations, an enhancement of people's compliance [17], and the possibility of living graded exposure experiences while overcoming the difficulties related to the application of coping techniques within a clinical setting. Moreover, thanks to the recent progress in the sophistication and in the usability of biosensors technology wirelessly connected to mobile platform, today it is possible to set up a multimodal assessment of stress levels, including psychological, physiological, behavioral, and contextual data [18].

Although the efficacy of mobile self-help approaches have been tested through several studies and promising applications can be developed, there is as yet no study that has tested the feasibility of mobile platforms to actually elicit core affective states. An advanced approach to assess the efficacy of these mobile platforms is by the means of psychophysiological measures, which extend the capabilities of the standard self-report questionnaires, objectifying the subjective.

Thus a question arises, is it possible to induce positive or negative affective states using a smart phone? To answer this question, we focused on the bidimensional viewpoint from Lang [19] to identify affective states in terms of “activation,“ namely physiological arousal and emotional valence. Fig. 1 offers intuitive identification of affective states based on these two dimensions [20]. Under this perspective, stress and relaxation could be considered as two opposite affective states, characterized by different physiological arousal and emotional valence; we are particularly interested in those states because of their importance in stress management therapies [21], [22].

In psychology, several methods exist to induce a relaxing state built on the exposure of emotion-eliciting materials, such as pictures [23], films [24], [25], or music [26], [27]. In particular, classical music also has been used as a tool for relaxation exercises, producing self-reported behavioral and physiological changes related to reduced stress [28]. For example, listening to classical music has been associated with a reduction in autonomic activity and self-reported tension and improved performance of surgeons [29]. Similarly, listening to classical music in still another study reduced self-reported fatigue, sadness, and tension [30]. Physiological changes associated with listening to classical music and related to decreased stress include a significant decrease in β-endorphin, following one session of combined progressive relaxation, classical music, and guided imagery conditioning [31].

On the other hand, several laboratory procedures have been tested to induce stress using the cognitive tasks that could be easily input into both a PC and a smart phone. According to Dickerson and Kemeny [32], several cognitive tasks have been used to elicit stress responses, including the stroop test, mental arithmetic tasks, vigilance-reaction time tasks, and other analytical tasks (e.g., [33], [34], [35]).

For example, in a recent study, Mauri and colleagues [36] used a Stroop task [37] to elicit stress reactions to investigate psychophysiological signals associated with different affective states.

The two dimensions of “activation” used to assess relaxation and stress, namely, physiological arousal and emotional valence, before described, can be accurately measured through biosensors to obtain signals that can offer considerable information following a signal processing procedure that utilizes multiple mathematical and computational techniques. Briefly, physiological arousal can be measured using an Electroencephalogram (EEG), Galvanic Skin Response (GSR), Electrocardiogram (ECG), and Respiration Signal (RSP). An emotional valence can be measured through EEG, self-reports, facial expression identification, eye-blink startle, and facial EMG corrugator and/or zygomatic. Cardio-respiratory activity is monitored as well to evaluate both the voluntary and autonomic effect of respiration on heart rate, analyzing the R–R interval (from the electrocardiogram) and respiration (from a chest strip sensor) and observing their interaction. Further, standard HRV spectral methods can be used to evaluate the autonomic nervous system response [38], [39], [40], [41], [42].

Spectral analysis can be performed using autoregressive (AR) spectral methods with custom software. The AR spectral decomposition procedure could, for example, be applied to calculate the power of the oscillations embedded in the series.

On the other hand, startle eye-blink reflex, and facial electromyography are related to the valence of the emotional response induced by a stimulus. Due to the dramatic increase in the use of the startle-blink response in research and clinical settings, Gregory Miller, while Editor of Psychophysiology, appointed a committee to consider the guidelines for startle-blink research in humans, and produced the “Committee Report: Guidelines for human startle eyeblink electromyographic studies”. The Committee demonstrated that facial EMG-CS (corrugator) is the best measure of emotion valence [43].

According to these premises, the goal of this study was to test the efficacy of inducing positive and negative affective states using smart phones measured by psycophysiological parameters. To achieve this goal we compared this innovative approach with a traditional one, represented by the induction of positive and negative affective states using a PC.

Section snippets

Participants

Twenty-eight healthy subjects (16 females and 12 males) were included in this study aged from 19 to 55. They were all volunteers from Ospedale San Giuseppe of Piancavallo (VB) – Istituto Auxologico Italiano (ITALY) – and they were recruited among the hospital staff (hospital nurses, physicians, medical assistants, hospital keepers, laboratory technician, etc.). In order to be included in the study, subjects had to meet the following criteria: (1) absence of medical diseases; (2) absence of

Results

A repeated measures ANOVA with a Greenhouse–Geisser correction determined that mean scores for NN50 differed statistically significantly between the four experimental conditions (R, RM, S, SM) [F(1.813, 63)=22.178, p<.001, 2=.514]; mean scores for LF/HF differed statistically significantly between the four experimental conditions [F(1.600, 63)=3.799, p<.042, 2=.153]; mean scores for HR differed statistically significantly between the four experimental conditions [F(1.730, 63)=21.469, p

Discussion

Since this study involves the interpretation of many complex psychophysiological measures we will detail now our results for each index used.

First of all, we used HR, i.e. heart rate, a well-known measure typically expressed as beats per minute (bpm). The typical healthy resting heart rate in adults is 60–80 bpm. In our experiment, we obtained about 70 bpm for Relaxing sessions (both mobile and PC) and an increase reaching about 80 bpm for Stress sessions, as can be seen in Fig. 5. This behavior

Conclusion

Mobile phones have quickly evolved from only voice- and text-based devices, enabling minimal user–device interaction, to the personal digital assistant with digital camera, GPS and navigator, MP3 and video player, interactive agenda, clock and alarms, Instant Messaging, and Internet Browser [12]. Based on to these features, mobile devices are becoming more and more useful also in health care services [10], [11]. In particular, thanks to recent development and diffusion of mobile platforms

Acknowledgments

This study has been made possible partially thanks to funds from European project, “INTERSTRESS—Interreality in the management and treatment of stress-related disorders” (FP7-247685).

Pietro Cipresso is Advanced Researcher at Applied Technology for Neuro-Psychology Lab, IRCCS Istituto Auxologico Italiano, Milan. He graduated from Bocconi University of Milan in economics, major in statistics and operational research. He received his Ph.D. in communication and new technologies, major in psychology, from IULM University of Milan. Cipresso has been a Visiting Research Scholar at Massachusetts Institute of Technology (MIT) and is the author of more than 50 scientific publications

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  • Cited by (0)

    Pietro Cipresso is Advanced Researcher at Applied Technology for Neuro-Psychology Lab, IRCCS Istituto Auxologico Italiano, Milan. He graduated from Bocconi University of Milan in economics, major in statistics and operational research. He received his Ph.D. in communication and new technologies, major in psychology, from IULM University of Milan. Cipresso has been a Visiting Research Scholar at Massachusetts Institute of Technology (MIT) and is the author of more than 50 scientific publications and of the book “Modeling Emotions At the Edge of Chaos. From psychophysiology to networked emotions.”

    Silvia Serino received her B.A. degree in Psychology from Catholic University of Milan and M.Sc. degree in Developmental and Communication Psychology from Catholic University of Milan. She is now a junior researcher at the Applied Technology for Neuro-Psychology Lab—ATN-P Lab, IRCCS Istituto Auxologico Italiano, Milan, Italy and a Ph.D. Candidate in Psychology at Catholic University of Milan. Her main research interest concerns the use of new technologies in the management and treatment of stress-related disorders, the use and the application of Computerized Experience Sampling Method and the mobile psychological self-tracking.

    Daniela Villani received her M.Sc. degree in Psychology from Catholic University of Milan and Ph.D. in Psychology from Catholic University of Milan. She is now a Researcher at Psychology Department of the Catholic University of Milan.

    Claudia Repetto received her M.Sc. degree in Psychology from Catholic University of Milan. Now she is a Ph.D. Candidate in Psychology at Catholic University of Milan.

    Luigi Sellitti is a Medical Doctor (MD) and a resident in Neurology at the Division of Neurology and Neurorehabilitation, San Giuseppe Hospital, IRCCS Istituto Auxologico Italiano, Piancavallo (VB), Italy.

    Giovanni Albani is a Medical Doctor (MD) and Neurologist at the Division of Neurology and Neurorehabilitation, San Giuseppe Hospital, IRCCS Istituto Auxologico Italiano, Piancavallo (VB), Italy.

    Alessandro Mauro is a Medical Doctor (MD) and Neurologist at the Division of Neurology and Neurorehabilitation, San Giuseppe Hospital, IRCCS Istituto Auxologico Italiano, Piancavallo (VB), Italy and a Full Professor of Neurology at University of Torino, Italy.

    Andrea Gaggioli, Ph.D., holds a M.S. degree in Psychology from University of Bologna and a Ph.D. in Psychobiology from the University of Milan. Since January 2001 he is a senior researcher at the Applied Technology for Neuro-Psychology Lab (ATN-P LAB) at the Istituto Auxologico Italiano, a biomedical research institute located in Milan. Dr. Gaggioli's research focuses on psycho-social aspects of emerging technologies, with particular reference to virtual and augmented reality systems. Gaggioli is the coordinator of the European Project “INTERSTRESS. Interreality in the Management and Treatment of Stress-Related Disorders.”

    Giuseppe Riva, Ph.D., is an Associate Professor (tenure position) of General Psychology and Communication Psychology at the Catholic University of Milan, Italy. He is also the Director of the Interactive Communication and Ergonomics of New Technologies – ICE-NET – Lab at the Catholic University of Milan, Italy, and Head Researcher of the Applied Technology for Neuro-Psychology Lab, Istituto Auxologico Italiano, Milano, Italy

    Member of the New York Academy of Science and the American Psychological Association, Riva is the Associate Editor for the journal “Cyberpsychology, Behavior, and Social Networks.” Riva has been the scientific coordinator of several European Project.

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