Name
Title | ||
|---|---|---|
Mechanisms for improving walking speed after longitudinal powered robotic exoskeleton training for individuals with spinal cord injury. |
Abstract | ||
|---|---|---|
The goal of this study was to establish strideparameter gait models correlated to speed on individuals with chronic SCI and able-bodied controls walking with a powered robotic exoskeleton (EksoGT $^{\mathrm{ TM}}$). Longitudinal exoskeleton training $( >100$ hours) across eight individuals with SCI resulted in a 30% increase in walking speed. A simple linear regression between step length, stride length for given speed were very tightly correlated along a line of best fit $( \mathrm {p}<$.001). The temporal parameters of stride time, stance time and double support time depicted a non-linear exponentially decaying relationship for given walking speed. The research findings indicate that although longitudinal exoskeleton training reduces the temporal parameters, increases in spatial parameters are only marginal. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/EMBC.2018.8512821 | EMBC |
Field | DocType | Volume |
Computer vision,Spinal cord injury,STRIDE,Gait,Computer science,Exoskeleton,Artificial intelligence,Physical medicine and rehabilitation,Powered exoskeleton,Preferred walking speed | Conference | 2018 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
10 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arvind Ramanujam | 1 | 0 | 1.01 |
| Kamyar Momeni | 2 | 0 | 1.35 |
| Syed R. Husain | 3 | 0 | 0.68 |
| Jonathan Augustine | 4 | 0 | 0.34 |
| Erica Garbarini | 5 | 0 | 1.01 |
| Peter Barrance | 6 | 0 | 0.34 |
| Ann Spungen | 7 | 0 | 0.34 |
| Pierre Asselin | 8 | 0 | 0.34 |
| Steven Knezevic | 9 | 0 | 0.34 |
| Gail Forrest | 10 | 0 | 1.35 |