DSP Basics

Arduino AG. 2018a. Arduino—Home. Retrieved August 15, 2018 from https://www.arduino.cc/.

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Emotiv. 2019. Emotiv EPOC+ Neuroheadset. Retrieved April 26, 2019 from https://www.emotiv.com/epoc/.

T. Grosse-Puppendahl, C. Holz, G. Cohn, R. Wimmer, O. Bechtold, S. Hodges, M. S. Reynolds, and J. R. Smith. 2017. Finding common ground: A survey of capacitive sensing in human-computer interaction. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, CHI’17. ACM, New York, NY, 3293–3315. ISBN: 978-1-4503-4655-9.

C. Guger, S. Daban, E. Sellers, C. Holzner, G. Krausz, R. Carabalona, F. Gramatica, and G. Edlinger. 2009. How many people are able to control a P300-based brain–computer interface (BCI)? Neurosci. Lett. 462, 1, 94–98. ISSN: 0304-3940. http://www.sciencedirect.com/science/article/pii/S0304394009008192.

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C. Kiefer, N. Collins, and G. Fitzpatrick. 2008. HCI methodology for evaluating musical controllers: A case study. In NIME Genova, Italy, 87–90.

F. Kinoshita, K. Miyanaga, K. Fujita, and H. Touyama. 2019. Effect of Differences in the Meal Ingestion Amount on the Electrogastrogram Using Non-linear Analysis. Springer, Cham, 468–476. ISBN: 978-3-030-23562-8.

P. Klasnja, S. Consolvo, and W. Pratt. 2011. How to evaluate technologies for health behavior change in HCI research. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI’11. ACM, New York, NY, 3063–3072. ISBN: 978-1-4503-0228-9.

Micro:bit Educational Foundation. 2018. Micro:bit Educational Foundation—Micro:bit. Retrieved August 15, 2018 from http://microbit.org/.

Microchip Technology Inc. 2018. ATmega328/P AVR® Microcontroller with picoPower® Technology. Retrieved August 15, 2018 from https://www.microchip.com/wwwproducts/en/ATmega328P.

M. Nakano, T. Konishi, S. Izumi, H. Kawaguchi, and M. Yoshimoto. 2012. Instantaneous heart rate detection using short-time autocorrelation for wearable healthcare systems. In 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 6703–6706.

Nordic Semiconductor. 2018. nRF51822 Multiprotocol Bluetooth® Low Energy/2.4 GHz RF System on Chip Product Specification v3.3. Retrieved August 15, 2018 from https://www.nordicsemi.com/eng/Products/Bluetooth-low-energy/nRF51822.

K. Pfeuffer, J. Alexander, M. K. Chong, Y. Zhang, and H. Gellersen. 2015. Gaze-shifting: Direct-indirect input with pen and touch modulated by gaze. In Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology, UIST’15. ACM, New York, NY, 373–383. ISBN: 978-1-4503-3779-3.

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J. G. Proakis and D. G. Manolakis. 2007. Digital Signal Processing, Vol. 4. Pearson. ISBN: 01318773741.

M. M. Rahman, M. A. Chowdhury, and S. A. Fattah. 2018. An efficient scheme for mental task classification utilizing reflection coefficients obtained from autocorrelation function of EEG signal. Brain Inform. 5, 1, 1–12.

Raspberry Pi Foundation. 2018. Raspberry Pi—Teach, Learn, and Make with Raspberry Pi. Retrieved August 15, 2018 from https://www.raspberrypi.org/.

T. K. Rawat. 2015. Digital Signal Processing. Oxford University Press. ISBN: 9781680158731.

T. Rodden, K. Cheverst, K. Davies, and A. Dix. 1998. Exploiting context in HCI design for mobile systems. In Workshop on Human Computer Interaction with Mobile Devices, 21–22.

G. Rojas, C. Alvarez, C. Montoya Moya, M. de la Iglesia Vaya, J. Cisternas, and M. Gálvez. 2018. Study of resting-state functional connectivity networks using EEG electrodes position as seed. Front. Neurosci. 12.

A. Schmidt. Dec. 2015. Biosignals in human-computer interaction. Interactions 23, 1, 76–79. ISSN: 1072-5520.

H. P. D. Silva, S. Fairclough, A. Holzinger, R. Jacob, and D. Tan. Jan. 2015. Introduction to the special issue on physiological computing for human-computer interaction. ACM Trans. Comput.-Hum. Interact. 21, 6, 29:1–29:4. ISSN: 1073-0516.

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J. Smith. 2007. Introduction to Digital Filters: With Audio Applications. Music Signal Processing Series. W3K. ISBN: 9780974560717.

J. Suarez and R. R. Murphy. 2012. Hand gesture recognition with depth images: A review. In 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication. IEEE, 411–417.

F. Taher, J. Hardy, A. Karnik, C. Weichel, Y. Jansen, K. Hornbæk, and J. Alexander. 2015. Exploring interactions with physically dynamic bar charts. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems, CHI’15. ACM, New York, NY, 3237–3246. ISBN: 978-1-4503-3145-6.

C. T. Vi, K. Takashima, H. Yokoyama, G. Liu, Y. Itoh, S. Subramanian, Y. Kitamura. 2013. D-FLIP: Dynamic and flexible interactive PhotoShow. In D. Reidsma, H. Katayose, and A. Nijholt (Eds.). Advances in Computer Entertainment, Springer International Publishing, Cham, 415–427. ISBN: 978-3-319-03161-3.

C. T. Vi, J. Alexander, P. Irani, B. Babaee, and S. Subramanian. 2014a. Quantifying EEG measured task engagement for use in gaming applications; Citeseer: University Park, PA, USA.

C. T. Vi, I. Jamil, D. Coyle, and S. Subramanian. 2014b. Error related negativity in observing interactive tasks. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI’14. ACM, New York, NY, 3787–3796. ISBN: 978-1-4503-2473-1.

M. Wairagkar, Y. Hayashi, and S. J. Nasuto. 2018. Exploration of neural correlates of movement intention based on characterisation of temporal dependencies in electroencephalography. PLoS One 13, 3, 1–23.

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