Name
Abstract | ||
|---|---|---|
We present a novel statistical paradigm for modeling and analysis of gait variability which captures the natural point process structure of gait intervals and allows for definition of new measures instantaneous mean and standard deviation. We validate our model using two existing data sets from physionet.org. Results show an excellent model fit and yield insights into the underlying statistical structure behind human gait. Statistical analyses further corroborate previous findings of increased variability in gait at different speeds, both self-paced and metronome-paced, and reveal a significant increase in gait variability in Parkinson's subjects, as compared to young and elderly healthy subjects. These results indicate the validity of a point process approach to the analysis of gait, and the potential utility of incorporating instantaneous measures of gait into diagnostic or patient monitoring applications. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IEMBS.2011.6090475 | 2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Keywords | Field | DocType |
standard deviation,geriatrics,statistical analysis,patient monitoring,time measurement,point process,strontium,gait,algorithms,heart rate variability,correlation,gait analysis | Data set,Gait,Remote patient monitoring,Computer science,Point process,Effect of gait parameters on energetic cost,Gait analysis,Artificial intelligence,Physical medicine and rehabilitation,Computer vision,Pattern recognition,Gait (human),Standard deviation | Conference |
Volume | ISSN | Citations |
2011 | 1557-170X | 2 |
PageRank | References | Authors |
0.45 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert J Ellis | 1 | 2 | 0.45 |
| luca citi | 2 | 168 | 27.88 |
| Riccardo Barbieri | 3 | 460 | 70.50 |