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Donetsk National Technical University. 58 Artyom Street, 83000 Donetsk, Ukraine .... Medical & biological engineering & computing, vol. 46, no. 2, pp. 169–178 ...

Sensor Network Architecture to Measure Characteristics of a Handshake Between Humans Artem Melnyk 1, 3 ETIS UMR 8051, UCP-ENSEA-CNRS Cergy-Pontoise University F-95000 Cergy Pontoise, France [email protected]

Viacheslav Khomenko3 Donetsk National Technical University 58 Artyom Street, 83000 Donetsk, Ukraine [email protected] Volodymyr Borysenko 3 Donetsk National Technical University 58 Artyom Street, 83000 Donetsk, Ukraine [email protected]


Patrick Henaff LORIA UMR 7503, University of Lorraine-INRIA-CNRS F-54506 Nancy [email protected]

Abstract—Handshaking is an important component of social interaction between people in many cultures. Thus, for further applications in human/humanoid-robot interaction it is important to understand and measure the characteristics of a handshake during interaction between humans. In this paper, a new wearable sensor network to measure a handshake is described. It consists of a set of several sensors (accelerometers, gyroscopes and force sensors) attached to the glove, and of a microcontroller for signal acquisition and conditioning. The paper focuses on the applicability and qualitative analysis of the proposed architecture of sensors through several experiments of handshaking between two human subjects. The results show that the proposed system allows reproducible experiments to quantify handshake characteristics such as duration and strength of the grip, vigor and rhythmicity of a handshake. Keywords— handshaking; physical interaction; inertial sensor; force sensor; data glove; synchrony

I. II.



A. Principle of measurement B. Calibration of Sensors Network III.



ACKNOWLEDGMENT Authors would like to thank the head of Neurocybernetics team of ETIS laboratory, Philippe Gaussier for his advice. Special thanks to associated professor Pavlo Rozkariaka for his help in gyroscope calibration. This work is supported in part by the French Embassy in Ukraine and by the INTERACT French project referenced ANR-09-CORD-014.

REFERENCES D. Schiffrin, “Handwork as Ceremony: The Case of the Handshake,” Semiotica. 12(3): 185-280. doi:10.1515/semi.1974.12.3.189 [2] F. J. Bernieri and K. N. Petty, “The influence of handshakes on first impression accuracy,” Social Influence, vol. 6, no. 2, pp. 78–87, Apr. 2011. [3] P. M. Hall and D. A. S. Hall, “The handshake as interaction,” Semiotica. 45(3-4): 191-379. doi:10.1515/semi.1983.45.3-4.249 [4] J. Aström and L. H. Thorell, “Greeting behaviour and psychogenic need: interviews on experiences of therapists, clergymen, and car salesmen.” Perceptual and motor skills, vol. 83, no. 3 Pt 1, pp. 939–956, Dec. 1996. [5] J. Astrom, “Introductory greeting behaviour: a laboratory investigation of approaching and closing salutation phases, Perceptual and Motor Skills, Vol 79(2), Oct 1994, 863-897. doi: 10.2466/pms.1994.79.2.863 [6] W. F. Chaplin, J. B. Phillips, J. D. Brown, N. R. Clanton, and J. L. Stein, “Handshaking, gender, personality, and first impressions.” Journal of personality and social psychology, vol. 79, no. 1, pp. 110–117, Jul. 2000. [7] M. L. Walters, K. Dautenhahn, S. N. Woods, K. L. Koay, R. Te Boekhorst, and D. Lee, “Exploratory studies on social spaces between humans and a mechanical-looking robot,” Connection Science, vol. 18, no. 4, pp. 429–439, Dec. 2006. [8] K. Dautenhahn, S. Woods, C. Kaouri, M. L. Walters, K. L. Koay, and I. Werry, “What is a robot companion - friend, assistant or butler?” in Intelligent Robots and Systems, (IROS 2005). 2005 IEEE/RSJ Int. Conf. on. IEEE, pp. 1192–1197. [9] R. Alami, A. Albu-Schaeffer, A. Bicchi, R. Bischoff, R. Chatila, A. D. Luca, A. D. Santis, G. Giralt, J. Guiochet, G. Hirzinger, F. Ingrand, V. Lippiello, R. Mattone, D. Powell, S. Sen, B. Siciliano, G. Tonietti, and L. Villani, "Safe and dependable physical Human-Robot interaction in anthropic domains: State of the art and challenges," in Procceedings IROS Workshop on pHRI - Physical Human-Robot Interaction in Anthropic Domains, A. Bicchi and A. D. Luca, Eds., Beijing, China, Oct. 2006. [10] M. Jindai and T. Watanabe, “Development of a handshake robot system based on a handshake approaching motion model,” in Advanced intelligent mechatronics, 2007 IEEE/ASME international conference on. IEEE, 2007, pp. 1–6. [11] Y. Yamato, M. Jindai, and T. Watanabe, “Development of a shakemotion leading model for human-robot handshaking,” in SICE Annual Conference, 2008. IEEE, Aug. 2008, pp. 502–507 [1]







S. Kwon and J. Kim, “Real-Time upper limb motion estimation from surface electromyography and joint angular velocities using an artificial neural network for Human–Machine cooperation,” Information Technology in Biomedicine, IEEE Transactions on, vol. 15, no. 4, pp. 522–530, Jul. 2011. Available: 10.1109/titb.2011.2151869 A. Karniel, I. Nisky, G. Avraham, and B.-c. Peles, “A turing-like handshake test for motor intelligence.” E. Giannopoulos, Z. Wang, A. Peer, M. Buss, and M. Slater, “Comparison of people’s responses to real and virtual handshakes within a virtual environment.” Brain research bulletin, vol. 85, no. 5, pp. 276– 282, Jun. 2011. W. Bainbridge, S. Nozawa, R. Ueda, K. Okada, and M. Inaba, “Robot sensor data as a means to measure human reactions to an interaction,” in Humanoid Robots (Humanoids), 2011 11th IEEE-RAS International Conference on. IEEE, Oct. 2011, pp. 452–457. J. R. Morris, “Accelerometry–a technique for the measurement of human body movements.” Journal of biomechanics, vol. 6, no. 6, pp. 729–736, Nov. 1973. A. Godfrey, R. Conway, D. Meagher, and G. OLaighin, “Direct measurement of human movement by accelerometry.” Medical engineering & physics, vol. 30, no. 10, pp. 1364–1386, Dec. 2008. K. Aminian and B. Najafi, “Capturing human motion using body-fixed sensors: Outdoor measurement and clinical applications: Research articles,” Comput. Animat. Virtual Worlds, vol. 15, no. 2, pp. 79–94, May 2004. [Online]. Available:

[18] K. Saber-Sheikh, E. C. Bryant, C. Glazzard, A. Hamel, and R. Y. W. Lee, “Feasibility of using inertial sensors to assess human movement,” Manual Therapy, vol. 15, no. 1, pp. 122–125, Feb. 2010. [19] A. G. G. Cutti, A. Giovanardi, L. Rocchi, A. Davalli, and R. Sacchetti, “Ambulatory measurement of shoulder and elbow kinematics through inertial and magnetic sensors.” Medical & biological engineering & computing, vol. 46, no. 2, pp. 169–178, Feb. 2008. Available: [20] D. Roetenberg, H. Luinge, and P. Slycke, "Xsens MVN: Full 6DOF human motion tracking using miniature inertial sensors," xsens, Tech. Rep., 2009. [21] K. N. Tarchanidis and J. N. Lygouras, “Data glove with a force sensor,” Instrumentation and Measurement, IEEE Transactions on, vol. 52, no. 3, pp. 984–989, Jun. 2003. [22] S. S. Fels and G. E. Hinton, “Glove-Talk: a neural network interface between a data-glove and a speech synthesizer.” IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council, vol. 4, no. 1, pp. 2–8, 1993. [23] A. Karime, H. Al-Osman, W. Gueaieb, and A. El Saddik, “E-Glove: An electronic glove with vibro-tactile feedback for wrist rehabilitation of post-stroke patients,” in Multimedia and Expo (ICME), 2011 IEEE International Conference on. IEEE, Jul. 2011, pp. 1–6. [24] M. Bianchi, P. Salaris, and A. Bicchi, “Synergy-based hand pose sensing: Reconstruction enhancement,” CoRR, vol. abs/1206.0555, 2012.