TY - GEN
T1 - Portable, non-invasive fall risk assessment in end stage renal disease patients on hemodialysis
AU - Lockhart, Thurmon E.
AU - Barth, Adam T.
AU - Zhang, Xiaoyue
AU - Songra, Rahul
AU - Abdel-Rahman, Emaad
AU - Lach, John
PY - 2010
Y1 - 2010
N2 - Patients with end stage renal diseases (ESRD) on hemodialysis (HD) have high morbidity and mortality due to multiple causes, one of which is dramatically higher fall rates than the general population. The mobility mechanisms that contribute to falls in this population must be understood if adequate interventions for fall prevention are to be achieved. This study utilizes emerging non-invasive, portable gait, posture, strength, and stability assessment technologies to extract various mobility parameters that research has shown to be predictive of fall risk in the general population. As part of an ongoing human subjects study, mobility measures such as postural and locomotion profiles were obtained from five (5) ESRD patients undergoing HD treatments. To assess the effects of post-HD-fatigue on fall risk, both the pre- and post-HD measurements were obtained. Additionally, the effects of inter-HD periods (two days vs. three days) were investigated using the non-invasive, wireless, body-worn motion capture technology and novel signal processing algorithms. The results indicated that HD treatment influenced strength and mobility (i.e., weaker and slower after the dialysis, increasing the susceptibility to falls while returning home) and inter-dialysis period influenced pre-HD profiles (increasing the susceptibility to falls before they come in for a HD treatment). Methodology for early detection of increased fall risk - before a fall event occurs - using the portable mobility assessment technology for out-patient monitoring is further explored, including targeting interventions to identified individuals for fall prevention.
AB - Patients with end stage renal diseases (ESRD) on hemodialysis (HD) have high morbidity and mortality due to multiple causes, one of which is dramatically higher fall rates than the general population. The mobility mechanisms that contribute to falls in this population must be understood if adequate interventions for fall prevention are to be achieved. This study utilizes emerging non-invasive, portable gait, posture, strength, and stability assessment technologies to extract various mobility parameters that research has shown to be predictive of fall risk in the general population. As part of an ongoing human subjects study, mobility measures such as postural and locomotion profiles were obtained from five (5) ESRD patients undergoing HD treatments. To assess the effects of post-HD-fatigue on fall risk, both the pre- and post-HD measurements were obtained. Additionally, the effects of inter-HD periods (two days vs. three days) were investigated using the non-invasive, wireless, body-worn motion capture technology and novel signal processing algorithms. The results indicated that HD treatment influenced strength and mobility (i.e., weaker and slower after the dialysis, increasing the susceptibility to falls while returning home) and inter-dialysis period influenced pre-HD profiles (increasing the susceptibility to falls before they come in for a HD treatment). Methodology for early detection of increased fall risk - before a fall event occurs - using the portable mobility assessment technology for out-patient monitoring is further explored, including targeting interventions to identified individuals for fall prevention.
KW - Algorithms
KW - Experimentation
KW - Human Factors
KW - J.3 [Life and Medical Sciences]: Health
KW - Measurement
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U2 - 10.1145/1921081.1921092
DO - 10.1145/1921081.1921092
M3 - Conference contribution
AN - SCOPUS:79951667336
SN - 9781605589893
T3 - Proceedings - Wireless Health 2010, WH'10
SP - 84
EP - 93
BT - Proceedings - Wireless Health 2010, WH'10
T2 - 1st Wireless Health Conference, WH'10
Y2 - 5 October 2010 through 7 October 2010
ER -