Zhi Dou

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In this study, we developed an algorithm based on neuromuscular-mechanical fusion to continuously recognize a variety of locomotion modes performed by patients with transfemoral (TF) amputations. Electromyographic (EMG) signals recorded from gluteal and residual thigh muscles and ground reaction forces/moments measured from the prosthetic pylon were used as(More)
BACKGROUND Various studies have modeled the impact of test-and-treat policies on the HIV epidemics worldwide. However, few modeling studies have taken into account China's context. To understand the potential effect of test-and-treat on the HIV epidemic among men who have sex with men (MSM) in China, we developed a mathematical model to evaluate the impact(More)
OBJECTIVES To assess HIV incidence and its associated risk factors among young men who have sex with men (YMSM) in urban areas, China. DESIGN The study used a prospective cohort study design and standard diagnostic tests. METHODS A twelve-month prospective cohort study was conducted among YMSM (18-25 years old) in 8 large cities in China. The(More)
A previously developed neural-machine interface (NMI) based on neuromuscular-mechanical fusion has showed promise for recognizing user locomotion modes; however, errors of NMI during mode transitions were observed, which may challenge its real application. This study aimed to investigate whether or not the prior knowledge of walking environment could(More)
This paper presents a real-time implementation of an intent recognition system on one transfemoral (TF) amputee. Surface Electromyographic (EMG) signals recorded from residual thigh muscles and the ground reaction forces/moments collected from the prosthetic pylon were fused to identify three locomotion modes (level-ground walking, stair ascent, and stair(More)
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