TY - GEN
T1 - An easy wearable gait assessment system for assessing stroke patients
AU - Tseng, Mu Hsun
AU - Chen, Tain Song
AU - Chang, Ya Ting
N1 - Publisher Copyright:
© 2020 IEEE
PY - 2020/11
Y1 - 2020/11
N2 - The aftereffects of stroke are numerous, and about 88% of patients show hemiplegia with different severity after stroke. Patients can improve their condition through long-term rehabilitation. The effectiveness of rehabilitation can be assessed by the gait characteristics between the feet. However, most of today's gait analysis systems can only be carried out in biomechanical laboratories or medical related institutions. It has been proven that the equipment is expensive and takes up a long time and is not suitable for home care applications. A simple rehabilitation assessment system has become an important clinical issue. In this study, two inertial measurement components are respectively fixed on the instep of the two feet, then the acceleration and angular velocity in the inertial component are extracted as the basis for quantifying the gait characteristics. Due to the limitations of the accelerometer and the gyroscope itself, this study allows the two components to be calibrated to each other through the sensor fusion technique, and integrates the algorithms developed in the study to estimate the correct gait characteristics as much as possible. It can be known from the experimental results that for a normal subject with both feet, the symmetrical ratio presented in the gait characteristics of both feet is about 1. For subjects with difficulty walking on one foot, the symmetrical ratio is greater than 1 or less than 1, indicating that any one foot will be significantly different from the other in some gait characteristics. It can be seen from the results that the correlation of gait characteristics between the normal and abnormal gait feet is consistent with the pre-experiment hypothesis.
AB - The aftereffects of stroke are numerous, and about 88% of patients show hemiplegia with different severity after stroke. Patients can improve their condition through long-term rehabilitation. The effectiveness of rehabilitation can be assessed by the gait characteristics between the feet. However, most of today's gait analysis systems can only be carried out in biomechanical laboratories or medical related institutions. It has been proven that the equipment is expensive and takes up a long time and is not suitable for home care applications. A simple rehabilitation assessment system has become an important clinical issue. In this study, two inertial measurement components are respectively fixed on the instep of the two feet, then the acceleration and angular velocity in the inertial component are extracted as the basis for quantifying the gait characteristics. Due to the limitations of the accelerometer and the gyroscope itself, this study allows the two components to be calibrated to each other through the sensor fusion technique, and integrates the algorithms developed in the study to estimate the correct gait characteristics as much as possible. It can be known from the experimental results that for a normal subject with both feet, the symmetrical ratio presented in the gait characteristics of both feet is about 1. For subjects with difficulty walking on one foot, the symmetrical ratio is greater than 1 or less than 1, indicating that any one foot will be significantly different from the other in some gait characteristics. It can be seen from the results that the correlation of gait characteristics between the normal and abnormal gait feet is consistent with the pre-experiment hypothesis.
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U2 - 10.1109/IS3C50286.2020.00061
DO - 10.1109/IS3C50286.2020.00061
M3 - Conference contribution
AN - SCOPUS:85104855627
T3 - Proceedings - 2020 International Symposium on Computer, Consumer and Control, IS3C 2020
SP - 209
EP - 211
BT - Proceedings - 2020 International Symposium on Computer, Consumer and Control, IS3C 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Symposium on Computer, Consumer and Control, IS3C 2020
Y2 - 13 November 2020 through 16 November 2020
ER -