Variable-stiffness joints with embedded force sensor for high-performance wearable gait exoskeletons

Soto, Manuel Cestari

doi:10.20868/upm.thesis.44653

Cited by 1 publication

(1 citation statement)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One gait cycle of human walking: ( a ) description of the hip and knee local coordinate system that are referenced to the anatomical position in three reference planes; ( b ) description of the phase difference motion of the hip and knee in the sagittal plane [17]. …”

Section: Figurementioning

confidence: 99%

Identification of Gait Motion Patterns Using Wearable Inertial Sensor Network

Moon

Lee

Öztürk

et al. 2019

Sensors

View full text Add to dashboard Cite

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.

show abstract

Section: Figurementioning

confidence: 99%