title: A low-cost body inertial-sensing network for practical gait discrimination of hemiplegia patients.
abstract: Gait analysis is widely used in detecting human walking disorders. Current gait analysis methods like video- or optical-based systems are expensive and cause invasion of human privacy. This article presents a self-developed low-cost body inertial-sensing network, which contains a base station, three wearable inertial measurement nodes, and the affiliated wireless communication protocol, for practical gait discrimination between hemiplegia patients and asymptomatic subjects. Every sensing node contains one three-axis accelerometer, one three-axis magnetometer, and one three-axis gyroscope. Seven hemiplegia patients (all were abnormal on the right side) and 7 asymptomatic subjects were examined. The three measurement nodes were attached on the thigh, the shank, and the dorsum of the foot, respectively (all on the right side of the body). A new method, which does not need to obtain accurate positions of the sensors, was used to calculate angles of knee flexion/extension and foot in the gait cycle. The angle amplitudes of initial contact, toe off, and knee flexion/extension were extracted. The results showed that there were significant differences between the two groups in the three angle amplitudes examined (-0.52±0.98° versus 6.94±2.63°, 28.33±11.66° versus 47.34±7.90°, and 26.85±8.6° versus 50.91±6.60°, respectively). It was concluded that the body inertial-sensing network platform provided a practical approach for wearable biomotion acquisition and was effective for discriminating gait symptoms between hemiplegia and asymptomatic subjects.
authors.affiliation: Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Shenzhen, China.
authors.forename: Yanwei
authors.initials: Y
authors.lastname: Guo
authors.forename: Dan
authors.initials: D
authors.lastname: Wu
authors.forename: Guanzheng
authors.initials: G
authors.lastname: Liu
authors.forename: Guoru
authors.initials: G
authors.lastname: Zhao
authors.forename: Bangyu
authors.initials: B
authors.lastname: Huang
authors.forename: Lei
authors.initials: L
authors.lastname: Wang
mesh_terms: D003943:Diagnostic Techniques, Neurological / Q000191:economics* / Q000295:instrumentation; D056228:Feedback, Sensory / Q000502:physiology; D005260:Female; D005684:Gait / Q000502:physiology*; D006429:Hemiplegia / Q000175:diagnosis*; D006801:Humans; D008297:Male; D008875:Middle Aged