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• W2987142311 abstract "Gait signifies the walking pattern of an individual. It may be normal or abnormal, depending on the health condition of the individual. This paper considers the development of a gait sensor network system that uses a pair of wireless inertial measurement unit (IMU) sensors to monitor the gait cycle of a user. The sensor information is used for determining the normality of movement of the leg. The sensor system places the IMU sensors on one of the legs to extract the three-dimensional angular motions of the hip and knee joints while walking. The wearable sensor is custom-made at San Diego State University with wireless data transmission capability. The system enables the user to collect gait data at any site, including in a non-laboratory environment. The paper also presents the mathematical calculations to decompose movements experienced by a pair of IMUs into individual and relative three directional hip and knee joint motions. Further, a new approach of gait pattern classification based on the phase difference angles between hip and knee joints is presented. The experimental results show a potential application of the classification method in the areas of smart detection of abnormal gait patterns." @default.
• W2987142311 created "2019-11-22" @default.
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• W2987142311 date "2019-11-18" @default.
• W2987142311 modified "2023-10-06" @default.
• W2987142311 title "Identification of Gait Motion Patterns Using Wearable Inertial Sensor Network" @default.
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• W2987142311 doi "https://doi.org/10.3390/s19225024" @default.
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