&nbsp; Walking of a human is constituted by two main-phases (i.e., stance and swing), and the two main-phases consist of multiple sub-phases depending on the characteristics of ground contact and motion of a foot. Since the sub-phases of a human walking provide various useful information, such as the health-care status, the gait abnormality, the motion intention, etc., gait phase analysis systems have been widely developed and many of them have been commercialized already. Most of the gait analysis systems, however, should be used in a laboratory environment. Moreover, the existing systems detect the gait phases mainly based on the ground reaction pressures, and therefore the outcomes are limited to the sub-phases during stance. As the information of the sub-phases during swing (i.e., pre-swing, mid-swing, and terminal swing) are critical for the precise diagnosis of gait abnormality and for high-level applications of such systems (e.g., wearable assistive robotics), a new method is proposed in this paper. The proposed shoes-typed gait-phase detection system includes two time-of-flight (ToF) sensors and two conventional ground reaction pressure sensors. The two ToF sensors placed near the heel and metatarsal joints measure the distance between the ground and the sole of the foot. From the two distance measurements, it is possible to observe the motion of the foot, which enables the detection of sub-phases during swing. The proposed method can detect the full information on the sub-phases in both swing and stance in real time. Experimental gait analysis results for walking at various speeds will be introduced in the presentation. 
&nbsp; Keywords: Wearable sensor, Gait analysis, Wearable devices, Human robot interaction.

Detection of Full Phases in a Gait Using Multi-Modal Sensor-Integrated Shoes

Paper Proceedings: https://asmedigitalcollection.asme.org/ISPS/ISPS2021/volume/84799

ASME 2021 Information Storage and Processing Systems (ISPS2021)

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