Article Versions Notes

Rehman RZU, Zhou Y, Del Din S, Alcock L, Hansen C, Guan Y, Hortobágyi T, Maetzler W, Rochester L, Lamoth CJC. Gait Analysis with Wearables Can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders. Sensors. 2020; 20(23):6992. https://doi.org/10.3390/s20236992

Rehman, Rana Zia Ur, Yuhan Zhou, Silvia Del Din, Lisa Alcock, Clint Hansen, Yu Guan, Tibor Hortobágyi, Walter Maetzler, Lynn Rochester, and Claudine J. C. Lamoth. 2020. "Gait Analysis with Wearables Can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders" Sensors 20, no. 23: 6992. https://doi.org/10.3390/s20236992

Rehman, R. Z. U., Zhou, Y., Del Din, S., Alcock, L., Hansen, C., Guan, Y., Hortobágyi, T., Maetzler, W., Rochester, L., & Lamoth, C. J. C. (2020). Gait Analysis with Wearables Can Accurately Classify Fallers from Non-Fallers: A Step toward Better Management of Neurological Disorders. Sensors, 20(23), 6992. https://doi.org/10.3390/s20236992