A System for Real-Time Feedback to Improve Gait and Posture in Parkinson's Disease. Jellish, J., Abbas, J., J., Ingalls, T., M., Mahant, P., Samanta, J., Ospina, M., C., & Krishnamurthi, N. IEEE Journal of Biomedical and Health Informatics, 19(6):1809-1819, IEEE, 11, 2015.
A System for Real-Time Feedback to Improve Gait and Posture in Parkinson's Disease [link]Website  abstract   bibtex   
For people with Parkinson's disease (PD), gait and postural impairments can significantly affect their ability to perform activities of daily living. Presentation of appropriate cues has been shown to improve gait in PD. Based on this, a treadmill-based system and experimental paradigm were developed to determine if people with PD can utilize real-time feedback (RTFB) of step length or back angle (uprightness) to improve gait and posture. Eleven subjects (mean age 67 ± 8 years) with mild-to-moderate PD (Hoehn and Yahr stage I–III) were evaluated regarding their ability to successfully utilize RTFB of back angle or step length during quiet standing and treadmill walking tasks during a single session in their medication-on state. Changes in back angle and step length due to feedback were compared using Friedman nonparametric tests with Wilcoxon Signed-Rank tests for post-hoc comparisons. Improvements in uprightness were observed as an increase in back angle during quiet standing ( p = 0.005 ) and during treadmill walking ( p = 0.005 ) with back angle feedback when compared to corresponding tasks without feedback. Improvements in gait were also observed as an increase in step length ( p = 0.005 ) during step length feedback compared to tasks without feedback. These results indicate that people with mild-to-moderate PD can utilize RTFB to improve upright posture and gait. Future work will investigate the long-term effects of this RTFB paradigm and the development of systems for clinical or home-based use.
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 title = {A System for Real-Time Feedback to Improve Gait and Posture in Parkinson's Disease},
 type = {article},
 year = {2015},
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 keywords = {gait,healthcare,mhealth,mhealth-examples,parkinson,wearable},
 pages = {1809-1819},
 volume = {19},
 websites = {http://dx.doi.org/10.1109/jbhi.2015.2472560},
 month = {11},
 publisher = {IEEE},
 institution = {Center for Adaptive Neural Systems and the College of Nursing and Health Innovation, Arizona State University, Tempe, AZ, USA},
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 abstract = {For people with Parkinson's disease (PD), gait and postural impairments can significantly affect their ability to perform activities of daily living. Presentation of appropriate cues has been shown to improve gait in PD. Based on this, a treadmill-based system and experimental paradigm were developed to determine if people with PD can utilize real-time feedback (RTFB) of step length or back angle (uprightness) to improve gait and posture. Eleven subjects (mean age 67 ± 8 years) with mild-to-moderate PD (Hoehn and Yahr stage I–III) were evaluated regarding their ability to successfully utilize RTFB of back angle or step length during quiet standing and treadmill walking tasks during a single session in their medication-on state. Changes in back angle and step length due to feedback were compared using Friedman nonparametric tests with Wilcoxon Signed-Rank tests for post-hoc comparisons. Improvements in uprightness were observed as an increase in back angle during quiet standing ( p = 0.005 ) and during treadmill walking ( p = 0.005 ) with back angle feedback when compared to corresponding tasks without feedback. Improvements in gait were also observed as an increase in step length ( p = 0.005 ) during step length feedback compared to tasks without feedback. These results indicate that people with mild-to-moderate PD can utilize RTFB to improve upright posture and gait. Future work will investigate the long-term effects of this RTFB paradigm and the development of systems for clinical or home-based use.},
 bibtype = {article},
 author = {Jellish, Jeremy and Abbas, James J and Ingalls, Todd M and Mahant, Padma and Samanta, Johan and Ospina, Maria C and Krishnamurthi, Narayanan},
 journal = {IEEE Journal of Biomedical and Health Informatics},
 number = {6}
}

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