TY - JOUR
T1 - Step Sequence and Direction Detection of Four Square Step Test
AU - Kong, Weisheng
AU - Wanning, Lauren
AU - Sessa, Salvatore
AU - Zecca, Massimiliano
AU - Magistro, Daniele
AU - Takeuchi, Hikaru
AU - Kawashima, Ryuta
AU - Takanishi, Atsuo
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/10
Y1 - 2017/10
N2 - Poor balance control and falls are big issues for older adults that due to aging decline have a lower postural balance and directional control in balance performance than younger age groups. The four square step test (FSST) was developed to evaluate rapid stepping that is often required when changing direction and avoiding obstacles while walking. However, previous researchers used only the total time as the assessment in the test. The aim of this letter is to objectively quantify the sequence and direction of the steps in FSST, by using two inertial sensors placed on both feet. An algorithm was developed to automatically segment the steps performed during the test, and calculate the stepping direction from the linear velocity of the foot. Experiments were conducted with 100 Japanese healthy older adults, where sensor data and video of 20 subjects were randomly subtracted for algorithm verification. The results showed that the algorithm succeeded for 71.7% trials in recognizing both the step sequence and step direction in FSST, while 90.2% of the detection failure could be excluded with an auto verification method.
AB - Poor balance control and falls are big issues for older adults that due to aging decline have a lower postural balance and directional control in balance performance than younger age groups. The four square step test (FSST) was developed to evaluate rapid stepping that is often required when changing direction and avoiding obstacles while walking. However, previous researchers used only the total time as the assessment in the test. The aim of this letter is to objectively quantify the sequence and direction of the steps in FSST, by using two inertial sensors placed on both feet. An algorithm was developed to automatically segment the steps performed during the test, and calculate the stepping direction from the linear velocity of the foot. Experiments were conducted with 100 Japanese healthy older adults, where sensor data and video of 20 subjects were randomly subtracted for algorithm verification. The results showed that the algorithm succeeded for 71.7% trials in recognizing both the step sequence and step direction in FSST, while 90.2% of the detection failure could be excluded with an auto verification method.
KW - Automation in life sciences: biotechnology
KW - health care management
KW - pharmaceutical and health care
KW - sensor fusion
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U2 - 10.1109/LRA.2017.2723929
DO - 10.1109/LRA.2017.2723929
M3 - Article
AN - SCOPUS:85059704493
SN - 2377-3766
VL - 2
SP - 2194
EP - 2200
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 4
M1 - 7970186
ER -