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Sensing strides using EMG signal for pedestrian navigation

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Abstract

Navigation applications and location-based services are now becoming standard features in smart phones. However, locating a mobile user anytime anywhere is still a challenging task, especially in GNSS (Global Navigation Satellite System) degraded and denied environments, such as urban canyons and indoor environments. To approach a seamless indoor/outdoor positioning solution, Micro-Electro-Mechanical System sensors such as accelerometers, digital compasses, gyros and pressure sensors are being adopted as augmentation technologies for a GNSS receiver. However, the GNSS degraded and denied environments are typically contaminated with significant sources of error, which disturb the measurements of these sensors. We introduce a new sensor, the electromyography (EMG) sensor, for stride detection and stride length estimation and apply these measurements, together with a digital compass, to a simple pedestrian dead reckoning (PDR) solution. Unlike the accelerometer, which senses the earth gravity field and the kinematic acceleration of the sensor, the EMG sensor senses action potentials generated by the muscle contractions of the human body. The EMG signal is independent of the ambient environment and its disturbance sources. Therefore, it is a good alternative sensor for stride detection and stride length estimation. For evaluating the performance of the EMG sensor, we carried out several field tests at a sports field and along a pedestrian path. The test results demonstrated that the accuracy of stride detection was better than 99.5%, the errors of the EMG-derived travelled distances were less than 1.5%, and the performance of the corresponding PDR solutions was comparable to that of the global positioning system solutions.

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References

  • Beauregard S, Haas H (2006) Pedestrian dead reckoning: a basis for personal positioning. In: Proceedings of the 3rd workshop on positioning, navigation and communication. Hannover, Germany, pp 27–35

  • Campanini I, Merlo A, Degola P, Merletti R, Vezzosi G, Farina D (2007) Effect of electrode location on EMG signal envelope in leg muscles during gait. J Electromyogr Kinesiol 17:515–526

    Article  Google Scholar 

  • Chen X, Zhang X, Zhao Z, Yang J, Lantz V, Wang K (2007) Hand gesture recognition research based on surface EMG sensors and 2D-accelerometers. In: Proceedings of the 11th IEEE international symposium on wearable computers, Boston, MA, USA, pp 11–14

  • Chen R, Chen Y, Pei L, Chen W, Kuusniemi H, Liu J, Leppäkoski H, Takala J (2009a) A DSP-based multi-sensor multi-network positioning platform. In: Proceedings of ION GNSS 2009, Savannah, Georgia, USA, pp 615–621

  • Chen W, Fu Z, Chen R, Chen Y, Andrei O, Kroger T, Wang J (2009b) An integrated GPS and multi-sensor pedestrian positioning system for 3D urban navigation. In: Proceedings of the joint urban remote sensing event 2009, Shanghai, China, pp 1–6

  • Chen R, Kuusniemi H, Hyyppä J, Zhang J, Takala J, Kuittinen R, Chen J, Pei L, Liu Z, Zhu L, Qin Y, Leppäkoski H, Wang J (2010a) Going 3D, Personal Nav and LBS. GPS World 21(2):14–18

    Google Scholar 

  • Chen W, Chen R, Chen Y, Kuusniemi H, Wang J, Fu Z (2010b) An effective pedestrian dead reckoning algorithm using a unified heading error model. In: Proceedings of the IEEE/ION position, location and navigation symposium (PLANS) 2010, Indian Wells, CA, USA, pp 1–8

  • Cho S, Park C, Yim H (2003) Sensor fusion and error compensation algorithm for pedestrian navigation system. In: Proceeding of ICCAS, Gyeongju, Korea, pp 1001–1006

  • Cram JR, Kasman GS, Holtz J (1998) Introduction to surface electromyography. Aspen Publishers, USA

    Google Scholar 

  • Duckworth J, Cyganski D, Makarov S et al. (2007) WPI precision personnel locator system: evaluation by first responders. In: Proceedings of ION GNSS 2007, Fort Worth, Texas, USA, pp 1427–1435

  • Fang L, Antsaklis P, Montestruque L, McMickell M, Lemmon M, Sun Y, Fang H, Koutroulis I, Haenggi M, Xie M, Xie X (2005) Design of a wireless assisted pedestrian dead reckoning system—the NavMote experience. IEEE Trans Instrum Meas 54:2342–2358

    Google Scholar 

  • Foxlin E (2005) Pedestrian tracking with shoe-mounted inertial sensors. IEEE Comput Graph Appl 25(6):38–46

    Article  Google Scholar 

  • Godha S, Lachapelle G, Cannon ME (2006) Integrated GPS/INS system for pedestrian navigation in a signal degraded environment. In: Proceedings of ION GNSS 2006, Fort Worth, TX, USA, pp 2151–2164

  • Grejner-Brzezinska D, Toth C, Moafipoor S (2007) Pedestrian tracking and navigation using an adaptive knowledge system based on neural networks. J Appl Geod 1:111–123

    Article  Google Scholar 

  • Käppi J, Syrjärinne J, Saarinen J (2001) MEMS-IMU based pedestrian navigator for handheld devices. In: Proceedings of ION GPS 2001, Salt Lake City, UT, USA, pp 1369–1373

  • Ladetto Q (2000) On foot navigation: continuous step calibration using both complementary recursive prediction and adaptive Kalman filtering. In: Proceedings of ION GPS 2000, Salt Lake City, UT, USA, pp 1735–1740

  • Levi R, Judd T (1999) Dead reckoning navigational system using accelerometer to measure foot impacts. US Patent 5,583,776

  • Mezentsev O (2005) Sensor aiding of HSGPS pedestrian navigation. Ph. D dissertation, University of Calgary

  • Moafipoor S, Grejner-Brzezinska D, Toth C (2008) A fuzzy dead reckoning algorithm for a personal navigator. J Inst Navig 55(4):241–254

    Google Scholar 

  • Reaz MBI, Hussain MS, Mohd-Yasin F (2006) Techniques of EMG signal analysis: detection, processing, classification and applications. Biol Proced Online 8(1):11–35

    Article  Google Scholar 

  • Retscher G (2007) Test and integration of location sensors for a multi-sensor personal navigator. J Navig 60:107–117

    Article  Google Scholar 

  • Weimann F, Abwerzger G, Hofman-Wellenhof B (2007) A pedestrian navigation system for urban and indoor environments. In: Proceedings of ION GNSS 2007, Fort Worth, TX, USA, pp 1380–1389

  • Zhang X, Chen X, Wang W, Yang J, Lantz V, Wang K (2009) Hand gesture recognition and virtual game control based on 3D accelerometer and EMG sensors. In: Proceedings of IUI’09, Sanibel Island, Florida, USA, pp 401–405

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Acknowledgments

The authors would like to thank Dr Heidi Kuusniemi for proofreading the manuscript.

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Authors and Affiliations

  1. Department of Navigation and Positioning, Finnish Geodetic Institute, 02431, Masala, Finland

    Ruizhi Chen, Wei Chen & Yuwei Chen

  2. Department of Electronic Science and Technology, University of Science and Technology of China, 230027, Hefei, China

    Wei Chen, Xiang Chen & Xu Zhang

  3. Department of Computer Systems, Tampere University of Technology, 33101, Tampere, Finland

    Ruizhi Chen

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  1. Ruizhi Chen
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  2. Wei Chen
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  3. Xiang Chen
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  4. Xu Zhang
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  5. Yuwei Chen
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Correspondence to Ruizhi Chen.

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Chen, R., Chen, W., Chen, X. et al. Sensing strides using EMG signal for pedestrian navigation. GPS Solut 15, 161–170 (2011). https://doi.org/10.1007/s10291-010-0180-x

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  • DOI: https://doi.org/10.1007/s10291-010-0180-x

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