Name
Title | ||
|---|---|---|
Deep learning for freezing of gait detection in Parkinson's disease patients in their homes using a waist-worn inertial measurement unit. |
Abstract | ||
|---|---|---|
Among Parkinson’s disease (PD) motor symptoms, freezing of gait (FOG) may be the most incapacitating. FOG episodes may result in falls and reduce patients’ quality of life. Accurate assessment of FOG would provide objective information to neurologists about the patient’s condition and the symptom’s characteristics, while it could enable non-pharmacologic support based on rhythmic cues. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.knosys.2017.10.017 | Knowledge-Based Systems |
Keywords | Field | DocType |
Deep learning,Signal processing,Freezing of gait,Parkinson’s disease,Wearable device | Gait,Waist,Computer science,Simulation,Spectral data,Inertial measurement unit,Artificial intelligence,Deep learning,Physical medicine and rehabilitation,Machine learning | Journal |
Volume | ISSN | Citations |
139 | 0950-7051 | 11 |
PageRank | References | Authors |
0.73 | 35 | 21 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Julià Camps | 1 | 12 | 1.75 |
| Albert Samà | 2 | 211 | 18.28 |
| Mario Martin | 3 | 14 | 3.23 |
| Daniel Rodríguez Martín | 4 | 82 | 9.53 |
| Carlos Pérez-López | 5 | 76 | 7.79 |
| Juan Manuel Moreno | 6 | 186 | 32.74 |
| J. Cabestany | 7 | 34 | 5.44 |
| Andreu Català | 8 | 234 | 26.75 |
| Sheila Alcaine | 9 | 46 | 4.67 |
| Berta Mestre | 10 | 46 | 5.01 |
| Anna Prats | 11 | 18 | 1.93 |
| Maria C. Crespo-Maraver | 12 | 11 | 0.73 |
| Timothy Counihan | 13 | 17 | 1.31 |
| Patrick Browne | 14 | 29 | 2.64 |
| Leo R. Quinlan | 15 | 29 | 2.98 |
| Gearóid ÓLaighin | 16 | 67 | 7.06 |
| Dean Sweeney | 17 | 29 | 2.98 |
| Hadas Lewy | 18 | 28 | 2.26 |
| Gabriel Vainstein | 19 | 22 | 1.68 |
| Alberto C. Costa | 20 | 28 | 2.60 |
| Roberta Annicchiarico | 21 | 28 | 2.60 |