Wearable EEG headband using printed electrodes and powered by energy harvesting for emotion monitoring in ambient assisted living

Globally, human life expectancy is steadily increasing causing an increase in the elderly population and consequently increased costs of supporting them. Ambient assisted living is an active research area aimed at supporting elderly people to live independently in their preferred living environment. This paper presents the design and testing of a self-powered wearable headband for electroencephalogram (EEG) based detection of emotions allowing the evaluation of the quality of life of assisted people. Printed active electrode fabrication and testing is discussed followed by the design of an energy harvester for powering the headband. The results show that the fabricated electrodes have similar performance to commercial electrodes and that the electronics embedded into the headband, as well as the wireless sensor node used for processing the EEG, can be powered by energy harvested from solar panels integrated on the headband. An average real time emotion classification accuracy of 90 (±9) % was obtained from 12 subjects. The results show that the self-powered wearable headband presented in this paper can be used to measure the wellbeing of assisted people with good accuracy.

[1]  Steve Beeby,et al.  Novel active electrodes for ECG monitoring on woven textiles fabricated by screen and stencil printing , 2015 .

[2]  K. Scherer,et al.  The Geneva affective picture database (GAPED): a new 730-picture database focusing on valence and normative significance , 2011, Behavior research methods.

[3]  L. Trainor,et al.  Frontal brain electrical activity (EEG) distinguishes valence and intensity of musical emotions , 2001 .

[4]  Ned H Kalin,et al.  Affective style and in vivo immune response: Neurobehavioral mechanisms , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[5]  S. Rauch,et al.  Neurobiology of emotion perception I: the neural basis of normal emotion perception , 2003, Biological Psychiatry.

[6]  Jyh-Yeong Chang,et al.  Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors , 2012, Journal of NeuroEngineering and Rehabilitation.

[7]  Maurizio Codispoti,et al.  Unmasking emotion: exposure duration and emotional engagement. , 2009, Psychophysiology.

[8]  Bethany E. Kok,et al.  How Positive Emotions Build Physical Health , 2013, Psychological science.

[9]  H. Aurlien,et al.  EEG background activity described by a large computerized database , 2004, Clinical Neurophysiology.

[10]  John Tudor,et al.  Fuzzy logic based emotion classification , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[11]  Randal P. Ching,et al.  Relationship Between Head Mass and Circumference in Human Adults , 2007 .

[12]  B. Fredrickson,et al.  Positive Emotions Trigger Upward Spirals Toward Emotional Well-Being , 2002, Psychological science.

[13]  Klas Ihme,et al.  A Dry EEG-System for Scientific Research and Brain–Computer Interfaces , 2010, Front. Neurosci..

[14]  Fatimah Ibrahim,et al.  Smartphone-Based Solutions for Fall Detection and Prevention: Challenges and Open Issues , 2014, Sensors.

[15]  Özlem Durmaz Incel,et al.  Multimodal Wireless Sensor Network-Based Ambient Assisted Living in Real Homes with Multiple Residents , 2014, Sensors.

[16]  Vladimir Leonov,et al.  Wearable electronics self-powered by using human body heat: The state of the art and the perspective , 2009 .

[17]  Pasin Israsena,et al.  Emotion classification using minimal EEG channels and frequency bands , 2013, The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE).

[18]  Tzyy-Ping Jung,et al.  A brain-machine interface using dry-contact, low-noise EEG sensors , 2008, 2008 IEEE International Symposium on Circuits and Systems.

[19]  William J Doyle,et al.  Emotional Style and Susceptibility to the Common Cold , 2003, Psychosomatic medicine.

[20]  Laurel J. Trainor,et al.  Processing Emotions Induced by Music , 2003 .

[21]  Jae Yun Lee,et al.  Emotion recognition based on the asymmetric left and right activation , 2011 .

[22]  J. R. Smith,et al.  A wearable UHF RFID-based EEG system , 2013, 2013 IEEE International Conference on RFID (RFID).

[23]  Refet Firat Yazicioglu,et al.  A $160~\mu {\rm W}$ 8-Channel Active Electrode System for EEG Monitoring , 2011, IEEE Transactions on Biomedical Circuits and Systems.

[24]  R. A. Mcfarland Relationship of skin temperature changes to the emotions accompanying music , 1985, Biofeedback and self-regulation.

[25]  Richard E. Lucas,et al.  Personality, culture, and subjective well-being: emotional and cognitive evaluations of life. , 2003, Annual review of psychology.

[26]  Refet Firat Yazicioglu,et al.  A low-power, wireless, 8-channel EEG monitoring headset , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[27]  John Tudor,et al.  Real time emotion detection within a wireless sensor network and its impact on power consumption , 2014, IET Wirel. Sens. Syst..

[28]  Fabien Lotte,et al.  Brain-Computer Interfaces: Beyond Medical Applications , 2012, Computer.

[29]  R. Matthews,et al.  Real time workload classification from an ambulatory wireless EEG system using hybrid EEG electrodes , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.