2019년 춘계학술대회
Current Result Document :
| 한글제목(Korean Title) |
Wearable Sensor based Gait Pattern Analysis for detection of ON/OFF State in Parkinson’s Disease |
| 영문제목(English Title) |
Wearable Sensor based Gait Pattern Analysis for detection of ON/OFF State in Parkinson’s Disease |
| 저자(Author) |
Satyabrata Aich
Jinse Park
Moon-il Joo
Jong Seong Sim
Hee-Cheol Kim
|
| 원문수록처(Citation) |
VOL 23 NO. 01 PP. 0283 ~ 0284 (2019. 05) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
In the last decades patient’s suffering with Parkinson’s disease is increasing at a rapid rate and as per prediction it will grow more rapidly as old age population is increasing at a rapid rate through out the world. As the performance of wearable sensor based approach reached to a new height as well as powerful machine learning technique provides more accurate result these combination has been widely used for assessment of various neurological diseases. ON state is the state where the effect of medicine is present and OFF state the effect of medicine is reduced or not present at all. Classification of ON/OFF state for the Parkinson’s disease is important because the patients could injure them self due to freezing of gait and gait related problems in the OFF state. in this paper wearable sensor based approach has been used to collect the data in ON and OFF state and machine learning techniques are used to automate the classification based on the gait pattern. Supervised machine learning techniques able to provide 97.6% accuracy while classifying the ON/OFF state. |
| 키워드(Keyword) |
Wearable sensors
gait
pattern analysis
classification
Parkinson’s disease
|
| 파일첨부 |
PDF 다운로드
|
