Abstract
Falls are among the most serious accidents among the elderly leading to increased injuries, reduced functioning and mortality. In 2009, about 2.2 million nonfatal fall injuries were reported among the elderly population (CDC, 2010). In this study, eleven community dwelling elderly (aged 65-84 years) participated in fall risk assessment camp at sterling senior center organized by Northern Virginia Fall Prevention Coalition (NVFPC). Three custom made wireless inertial measurement units (IMUs) were attached on trunk and both shanks. All participants performed postural and locomotor tasks such as sit-to-stand (STS) and timed up and go (TUG). Temporal and kinematic parameters were obtained. Raw signals obtained were denoised using ensemble empirical mode decomposition and savistzky-golay filtering. The mean and standard deviation of TUG time and STS completion time for participants were found to be 11.3±6.6 sec and 3.58±2.07 sec respectively. The high variation in the result may be due to the use of assistive devices (i.e., cane and walker) by two participants. The objective of this study is to classify fall prone community dwelling individuals using non-invasive system. Four participants were classified as fall prone, three without fall risk and four were at potential risk based on their objective assessment and task performance. This system provides a platform for identifying fall prone individuals and may be used for early fall interventions among the elderly.
| Original language | English (US) |
|---|---|
| Journal | Biomedical Sciences Instrumentation |
| Volume | 48 |
| State | Published - 2012 |
| Externally published | Yes |
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Keywords
- Community dwelling elderly
- Ensemble empirical mode decomposition
- Fall
- Inertial measurement units
- Timed up and go
ASJC Scopus subject areas
- Medical Laboratory Technology
- Biophysics
Cite this
Non-invasive fall risk assessment in community dwelling elderly with wireless inertial measurement units. / Lockhart, Thurmon; Yeoh, Han T.; Soangra, Rahul; Jongprasithporn, Manutchanok; Zhang, Jian; Wu, Xuefang; Ghosh, Arka.
In: Biomedical Sciences Instrumentation, Vol. 48, 2012.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Non-invasive fall risk assessment in community dwelling elderly with wireless inertial measurement units
AU - Lockhart, Thurmon
AU - Yeoh, Han T.
AU - Soangra, Rahul
AU - Jongprasithporn, Manutchanok
AU - Zhang, Jian
AU - Wu, Xuefang
AU - Ghosh, Arka
PY - 2012
Y1 - 2012
N2 - Falls are among the most serious accidents among the elderly leading to increased injuries, reduced functioning and mortality. In 2009, about 2.2 million nonfatal fall injuries were reported among the elderly population (CDC, 2010). In this study, eleven community dwelling elderly (aged 65-84 years) participated in fall risk assessment camp at sterling senior center organized by Northern Virginia Fall Prevention Coalition (NVFPC). Three custom made wireless inertial measurement units (IMUs) were attached on trunk and both shanks. All participants performed postural and locomotor tasks such as sit-to-stand (STS) and timed up and go (TUG). Temporal and kinematic parameters were obtained. Raw signals obtained were denoised using ensemble empirical mode decomposition and savistzky-golay filtering. The mean and standard deviation of TUG time and STS completion time for participants were found to be 11.3±6.6 sec and 3.58±2.07 sec respectively. The high variation in the result may be due to the use of assistive devices (i.e., cane and walker) by two participants. The objective of this study is to classify fall prone community dwelling individuals using non-invasive system. Four participants were classified as fall prone, three without fall risk and four were at potential risk based on their objective assessment and task performance. This system provides a platform for identifying fall prone individuals and may be used for early fall interventions among the elderly.
AB - Falls are among the most serious accidents among the elderly leading to increased injuries, reduced functioning and mortality. In 2009, about 2.2 million nonfatal fall injuries were reported among the elderly population (CDC, 2010). In this study, eleven community dwelling elderly (aged 65-84 years) participated in fall risk assessment camp at sterling senior center organized by Northern Virginia Fall Prevention Coalition (NVFPC). Three custom made wireless inertial measurement units (IMUs) were attached on trunk and both shanks. All participants performed postural and locomotor tasks such as sit-to-stand (STS) and timed up and go (TUG). Temporal and kinematic parameters were obtained. Raw signals obtained were denoised using ensemble empirical mode decomposition and savistzky-golay filtering. The mean and standard deviation of TUG time and STS completion time for participants were found to be 11.3±6.6 sec and 3.58±2.07 sec respectively. The high variation in the result may be due to the use of assistive devices (i.e., cane and walker) by two participants. The objective of this study is to classify fall prone community dwelling individuals using non-invasive system. Four participants were classified as fall prone, three without fall risk and four were at potential risk based on their objective assessment and task performance. This system provides a platform for identifying fall prone individuals and may be used for early fall interventions among the elderly.
KW - Community dwelling elderly
KW - Ensemble empirical mode decomposition
KW - Fall
KW - Inertial measurement units
KW - Timed up and go
UR - http://www.scopus.com/inward/record.url?scp=84888621385&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84888621385&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84888621385
VL - 48
JO - Biomedical Sciences Instrumentation
JF - Biomedical Sciences Instrumentation
SN - 0067-8856
ER -