TY - JOUR
T1 - Assessing upper extremity motion
T2 - An innovative method to identify frailty
AU - Toosizadeh, Nima
AU - Mohler, Jane
AU - Najafi, Bijan
N1 - Publisher Copyright: © 2015, The American Geriatrics Society.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - Objectives To objectively identify frailty using wireless sensors and an innovative upper extremity motion assessment routine that does not rely on gait. Design Validation study. Setting Southwestern tertiary academic medical center, Tucson, Arizona. Participants Convenience subsample of the Arizona Frailty Cohort, a community-dwelling older adults (≥65; n = 117; 50 nonfrail, 51 prefrail, 16 frail). Measurements Wireless sensors were attached to the upper arm and forearm with bands, and subjects performed repetitive elbow flexion for 20 seconds on each side. Information was extracted on objective slowness, weakness, exhaustion, and flexibility measures, and associations between parameters and Fried frailty categories were determined. Results Speed of elbow flexion (slowness) was 29% less in prefrail and 59% less in frail than in nonfrail controls (P <.001), power of movement (weakness) was 61% less in prefrail and 89% less frail (P <.001), and speed variation (exhaustion) was 35% more in prefrail and 272% more in frail (P <.001). Using elbow flexion parameters in regression models, sensitivity and specificity of 100% were achieved in predicting frailty and sensitivity of 87% and specificity of 95% in predicting prefrailty compared to Fried frailty category. Conclusion The suggested innovative upper extremity frailty assessment method integrates low-cost sensors, and the physical assessment is easily performed in less than 1 minute. The uniqueness of the proposed technology is its applicability in older nonambulatory individuals, such as those in emergency settings. Further improvement is warrant to make it suitable for routine clinical applications.
AB - Objectives To objectively identify frailty using wireless sensors and an innovative upper extremity motion assessment routine that does not rely on gait. Design Validation study. Setting Southwestern tertiary academic medical center, Tucson, Arizona. Participants Convenience subsample of the Arizona Frailty Cohort, a community-dwelling older adults (≥65; n = 117; 50 nonfrail, 51 prefrail, 16 frail). Measurements Wireless sensors were attached to the upper arm and forearm with bands, and subjects performed repetitive elbow flexion for 20 seconds on each side. Information was extracted on objective slowness, weakness, exhaustion, and flexibility measures, and associations between parameters and Fried frailty categories were determined. Results Speed of elbow flexion (slowness) was 29% less in prefrail and 59% less in frail than in nonfrail controls (P <.001), power of movement (weakness) was 61% less in prefrail and 89% less frail (P <.001), and speed variation (exhaustion) was 35% more in prefrail and 272% more in frail (P <.001). Using elbow flexion parameters in regression models, sensitivity and specificity of 100% were achieved in predicting frailty and sensitivity of 87% and specificity of 95% in predicting prefrailty compared to Fried frailty category. Conclusion The suggested innovative upper extremity frailty assessment method integrates low-cost sensors, and the physical assessment is easily performed in less than 1 minute. The uniqueness of the proposed technology is its applicability in older nonambulatory individuals, such as those in emergency settings. Further improvement is warrant to make it suitable for routine clinical applications.
KW - frailty
KW - geriatric
KW - immobile
KW - kinematics
KW - upper limb
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U2 - 10.1111/jgs.13451
DO - 10.1111/jgs.13451
M3 - Article
C2 - 26096391
SN - 0002-8614
VL - 63
SP - 1181
EP - 1186
JO - Journal of the American Geriatrics Society
JF - Journal of the American Geriatrics Society
IS - 6
ER -