Wearable electromyography sensor based outdoor-indoor seamless pedestrian navigation using motion recognition method

Navigation and position applications are now becoming standard built-in features in a smart phone. However, locating a mobile user in GNSS unfriendly and denied environments such as urban canyons and indoor environments ubiquitously is still a challenging task. Several self-contained sensors, such as accelerometer, digital compass, gyroscope and barometer, have been adapted as assistance augmentation technologies to a GPS receiver to make a seamless outdoor-indoor pedestrian navigation system. Since the indoor environment is more complex than an open-sky environment, such GNSS signal-degraded areas are typically also contaminated with disturbance sources that affect sensor measurements, a digital compass can be disturbed significantly by e.g. an elevator that bears magnetic perturbance. And a ventilation facility may cause inconsistencies in the barometer's measurements; not to mention that the indoor surrounding attenuates or blocks the GNSS signal. In this paper, a novel outdoor-indoor seamless solution for pedestrian navigation is introduced, which is based on Electromyography (EMG) sensors. The EMG sensor measures the electrical potentials generated by muscle contractions of human body. Therefore it is immune against the environment disturbance; moreover, it has potential capability to exploit the health situation of the pedestrian, since the EMG sensor has been applied on the biomedical field for decades. In the paper, five different motions are classified to estimate the stride length, including: walking horizontally, walking up along a slope, stepping upstairs/downstairs and standing still. The stride length estimation is based on a simple empirical module where fix stride length is donated to each classified motion. In order to evaluate the EMG-based pedestrian dead reckoning (PDR) solution developed in this study, an outdoor-indoor field test had been carried out in the Finnish Geodetic Institute. The test results demonstrated that the EMG-based PDR solutions are comparable to the commercial GPS stand-alone solutions for a period of 9 minutes outdoors, which is equivalent to a walking distance of 667 meters and also demonstrates its robustness for indoor navigation for a period of 3 minutes.