Analysis of Stress and Strain in Head Based Control of Cooperative Robots through Tetraplegics
Industrial robots as part of highly automated manufacturing are recently developed to cooperative (light-weight) robots. This offers the opportunity of using them as assistance robots and to improve the participation in professional life of disabled or handicapped people such as tetraplegics. Robots under development are located within a cooperation area together with the working person at the same workplace. This cooperation area is an area where the robot and the working person can perform tasks at the same time. Thus, working people and robots are operating in the immediate proximity. Considering the physical restrictions and the limited mobility of tetraplegics, a hands-free robot control could be an appropriate approach for a cooperative assistance robot. To meet these requirements, the research project MeRoSy (human-robot synergy) develops methods for cooperative assistance robots based on the measurement of head movements of the working person. One research objective is to improve the participation in professional life of people with disabilities and, in particular, mobility impaired persons (e.g. wheelchair users or tetraplegics), whose participation in a self-determined working life is denied. This raises the research question, how a human-robot cooperation workplace can be designed for hands-free robot control. Here, the example of a library scenario is demonstrated. In this paper, an empirical study that focuses on the impact of head movement related stress is presented. 12 test subjects with tetraplegia participated in the study. Tetraplegia also known as quadriplegia is the worst type of spinal cord injury. In the experiment, three various basic head movements were examined. Data of the head posture were collected by a motion capture system; muscle activity was measured via surface electromyography and the subjective mental stress was assessed via a mental effort questionnaire. The muscle activity was measured for the sternocleidomastoid (SCM), the upper trapezius (UT) or trapezius pars descendens, and the splenius capitis (SPL) muscle. For this purpose, six non-invasive surface electromyography sensors were mounted on the head and neck area. An analysis of variance shows differentiated muscular strains depending on the type of head movement. Systematically investigating the influence of different basic head movements on the resulting strain is an important issue to relate the research results to other scenarios. At the end of this paper, a conclusion will be drawn and an outlook of future work will be presented.
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 Wings for Life. Rückenmarksverletzung. (accessed 18.10.2016) Available at.: http://www.wingsforlife.com/de/querschnittslaehmung/.
 World Health Organization. Spinal cord injury. Fact sheet N°384. November 2013. (accessed 18.10.2016) Available at: http://www.who.int/mediacentre/factsheets/fs384/en/.
 International Classification of Diseases, 10th Revision. G82.5 – Quadriplegia. Last Updated: Oct 01, 2016. (accessed 18.10.2016) Available at: http://icd10coded.com/cm/ch6/G80-G83/G82/
 J. Bickenbach et al., International perspectives on spinal cord injury, World Health Organization & The International Spinal Cord Society, Malta: WHO, 2013, pp. 68–72.
 N. L. Mazwi, K. Adeletti, and R. E. Hirschberg, “Traumatic Spinal Cord Injury: Recovery, Rehabilitation, and Prognosis,” Current Trauma Reports, vol. 1, issue 3, Sept. 2015, pp. 182–192.
 M. P. LaPlante, H. S. Kaye, T. Kang, and C. Harrington, “Unmet need for personal assistance services: estimating the shortfall in hours of help and adverse consequences,” Journal of Gerontology: Social Sciences, vol. 59B, No. 2, 2004, pp. 98–108
 L. Floris, C. Dif, and M. A. Le Mouel, “The tetraplegic patient and the environment," in: Surgical rehabilitation of the upper limb in tetraplegia, London: W.B. Saunders, 2002, pp. 45–55.
 Dinging with Dignity. Flatware for the Grip Impaired. (accessed 18.10.2016) Available at: www.diningwithdignity.com.
 D. A. Craig, and H. T. Nguyen, “Wireless real-time head movement system using a personal digital assistant (PDA) for control of a power wheelchair”, IEEE, Jan. 2006, pp. 772-775 (27th Annual Conference on Engineering in Medicine and Biology).
 T. Guerreiro, and J. Jorge, “Assistive technologies for spinal cord injured individuals: Electromyographic mobile accessibility,” Proceedings of GW, 2007 (7th International Workshop on Gesture in Human-Computer Interaction and Simulation).
 J. Kim, H. Park, J. Bruce, D. Rowles, J. Holbrook, B. Nardone, D. P. West, L. Laumann, E. J. Roth, and M. Ghovanloo, “Assessment of the tongue-drive system using a computer, a smartphone, and a powered-wheelchair by people with tetraplegia,” IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 24, Issue 1, Jan. 2016, pp. 68-78.
 S. Guo, R. A. Cooper, M. L. Boninger, A. Kwarciak, and B. Ammer, “Development of power wheelchair chin-operated force-sensing joystick,” Engineering in Medicine and Biology, vol. 3, Oct. 2002, pp. 2373-2374 (24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002, Proceedings of the Second Joint).
 M. A. Eid, N. Giakoumidis, and A. El Saddik, A., “A Novel Eye-Gaze-Controlled Wheelchair System for Navigating Unknown Environments: Case Study With a Person With ALS,” IEEE, vol. 4, 28. Jan. 2016, pp. 558–573.
 C. Mandel, T. Lüth, T. Laue, T. Röfer, A. Gräser, & B. Krieg-Brückner (2009, October). Navigating a smart wheelchair with a brain-computer interface interpreting steady-state visual evoked potentials. In 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 1118-1125). IEEE
 J. Lobo-Prat, P. N. Kooren, A. H. Stienen, J. L. Herder, B. F. Koopman, and P. H. Veltink, „Non-invasive control interfaces for intention detection in active movement-assistive devices,” Journal of neuroengineering and rehabilitation, vol. 11, No. 2, 2014.
 A. Cunningham, W. Keddy-Hector, U. Sinha, D. Whalen, D. Kruse, J. Braasch, and J. T.Wen, “Jamster: A mobile dual-arm assistive robot with jamboxx control,” IEEE, Oct. 07, 2014, pp. 509-514 (IEEE 10th International Conference on Automation Science and Engineering, 2014).
 C. Leroux, I. Laffont, N. Biard, S. Schmutz, J. F. Desert, G. Chalubert, and Y. Measson, „Robot grasping of unknown objects, description and validation of the function with quadriplegic people,” IEEE, Jan. 14, 2008, pp. 35–42 (IEEE 10th International Conference on Rehabilitation Robotics, 2007).
 J. Nelles, S. Kohns, J. Spies, C. Brandl, A. Mertens and C. M. Schlick, “Analysis of Stress and Strain in Head Based Control of Collaborative Robots – A Literature Review,” in Advances in Physical Ergonomics and Human Factors, International Publishing: Springer, 2016, pp. 727-737.
 N. Rudigkeit, M. Gebhard, and A. Gräser, “Towards a user-friendly AHRS-based human-machine interface for a semi-autonomous robot,” IEE, Sept. 04, 2014 (IEEE/RSJ International Conference on Intelligent Robots and Systems, Workshop on Assistive Robotics for Individuals with Disabilities: HRI Issues and Beyond, 2014.
 N. Rudigkeit, M. Gebhard, & A. Gräser (2015). An analytical approach for head gesture recognition with motion sensors. In IEEE Ninth International Conference on Sensing Technology (pp. 720-725).
 A. Jackowski, M. Gebhard, & A. Gräser, (2016, May). A novel head gesture based interface for hands-free control of a robot. In Medical Measurements and Applications (MeMeA), 2016 IEEE International Symposium on (pp. 1-6). IEEE.
 Hillcrestlabs Experts in Motion. FSM-9. (accessed 18.10.2016) Available at: http://hillcrestlabs.com/product/fsm-9/
 J. Nelles, J., C. Bröhl, J. Spies, C. Brandl, A. Mertens, C. M. Schlick, „ELSI-Fragestellungen im Kontext der Mensch-Roboter-Kollaboration,“ in Arbeit in komplexen Systemen. Digital, vernetzt, human?! Bericht zum 62. Arbeitswissenschaftlichen, Kongress vom 03. - 05. März 2016, Gesellschaft für Arbeitswissenschaft e.V. (GfA), GfA-Press: Dortmund, 2016, pp. 1-6.
 F. R. H. Zijlstra, (1993). Efficiency in work behaviour: A design approach for modern tools. TU Delft, Delft University of Technology.
 W. Rohmert, & J. Rutenfranz (1975). Arbeitswissenschaftliche Beurteilung der Belastung und Beanspruchung an unterschiedlichen industriellen Arbeitsplätzen. Bonn: Bundesminister für Arbeit und Sozialordnung.
 W. Rohmert (1984). Das Belastungs-Beanspruchungs-Konzept. Zeitschrift für Arbeitswissenschaft, 38 (4), 193-200.
 W. Rohmert, & H. Luczak (1973). Zur ergonomischen Beurteilung informatorischer Arbeit. Internationale Zeitschrift für angewandte Physiologie einschließlich Arbeitsphysiologie, 31, 209-229.
 J. Dul, R. Bruder, P. Buckle, P. Carayon, P. Falzon, W. S. Marras, J. R. Wilson, & B. van der Doelen (2012). A strategy for human factors/ergonomics: developing the discipline and profession. Ergonomics, 55(4), 377-395.
 S. A. A. N. Bolink, H. Naisas, R. Senden, H. Essers, I. C. Heyligers, K. Meijer, & B. Grimm (2015). Validity of an inertial measurement unit to assess pelvic orientation angles during gait, sit–stand transfers and step-up transfers: Comparison with an optoelectronic motion capture system. Medical Engineering and Physics, 000, 1-7.
 K. Lebel, P. Boissy, H. Nguyen, & C. Duval (2016). Autonomous Quality Control of Joint Orientation Measured with Inertial Sensors. Sensors, 16 (7), doi: 10.3390/s16071037.
 G. Ligorio & A. M. Sabatini (2016) Dealing with Magnetic Disturbances in Human Motion Capture: A Survey of Techniques. Micromachines, 7, 43.
 E. R. Bachmann, X. Yun, & A. Brumfield (2007). Limitations of Attitude Estimation Algorithms for Inertial/Magnetic Sensor Modules. IEEE Robotics & Automation Magazine, 14, 76-87.
 D. Vlasic, R. Adelsberger, G. Vannucci, J. Barnwell, M. Gross, W. Matusik, & J. Popović (2007). Practical Motion Capture in Everyday Surroundings. ACM Transactions on Graphics, 26 (3), doi: 10.1145/1239451.1239486.
 S. Day (2002). Important Factors in Surface EMG Measurement. Calgary: Bortec Biomedical Ltd.
 M. Schünke, E. Schulte, & U. Schumacher (2007). PROMETHEUS Lernatlas der Anatomie. Allgemeine Anatomie und Bewegungssystem. Stuttgart, New York: Thieme Verlag.
 M. A. M. Benhamou, M. Revel, & C. Vallee (1995). Surface electrodes are not appropriate to record selective myoelectric activity of splenius capitis muscle in humans. Experimental Brain Research, 105, 432-438.
 F. Klimmer, J. Rutenfranz, & W. Rohmert (1979). Untersuchungen über physiologische und biochemische Indikatoren zur Differenzierung zwischen mentaler und emotionaler Beanspruchung bei psychischen Leistungen. International Archives of Occupational and Environmental Health, 44, 149-163.
 G. Sjøgaard, U. Lundberg, & R. Kadefors (2000). The role of muscle activity and mental load in the development of pain and degenerative processes at the muscle cell level during computer work. European Journal of Applied Physiology, 83, 99-105.
 U. Lundberg, R. Kadefors, B. Melin, G. Palmerud, P. Hassmén, M. Engström, & I. E. Dohns (1994). Psychophysiological Stress and EMG Activity of the Trapezius Muscle. International Journal of Behavioral Medicine, 1 (4), 354-370.
 Vicon. (accessed 09.12.2016) Available at: https://www.vicon.com/
 Noraxon. (accessed 09.12.2016) Available at: http://www.noraxon.com/products/emg-electromyography/
 DIN EN ISO 9241-110 (2008). Ergonomie der Mensch-System-Interaktion–Teil 110: Grundsätze der Dialoggestaltung (ISO 9241-110: 2006); Deutsche Fassung EN ISO 9241-110: 2006.
 Universal Robots (2015): UR 5 Technische Spezifikationen, (accessed 30.11.16) available at: http://www.universal-robots.com/de/produkte/ur5-roboter/
 A. Burden (2010). How should we normalize electromyograms obtained from healthy participants? What we have learned from over 25 years of research. Journal of Electromyography and Kinesiology, 20, 1023-1035.
 M. S. Conley, R. A. Meyer, J. J. Bloomberg, D. L. Feeback, & G. A. Dudley (1995). Noninvasive Analysis of Human Neck Muscle Function. Spine, 20 (23), 2505-2512.
 S. Kuz, H. Petruck, M. Heisterüber, H. Patel, B. Schumann, C. M. Schlick, & F. Binkofski (2015). Mirror neurons and human-robot interaction in assembly cells. Procedia Manufacturing 3, 402-408.
 B. R. Duffy (2003). Anthropomorphism and the social robot. Robotics and Autonomous Systems, 42, 177-190.