Park, Ji Su Koo, Sang-Mo Kim, Choong Hyun 2024-01-19T15:05:30Z 2024-01-19T15:05:30Z 2021-09-05 2021-03 1424-8220 https://pubs.kist.re.kr/handle/201004/117333 The operation of wearable robots, such as gait rehabilitation robots, requires real-time classification of the standing or walking state of the wearer. This report explains a technique that measures the ground reaction force (GRF) using an insole device equipped with force sensing resistors, and detects whether the insole wearer is standing or walking based on the measured results. The technique developed in the present study uses the waveform length that represents the sum of the changes in the center of pressure within an arbitrary time window as the determining factor, and applies this factor to a conventional threshold method and an artificial neural network (ANN) model for classification of the standing and walking states. The results showed that applying the newly developed technique could significantly reduce classification errors due to shuffling movements of the patient, typically noticed in the conventional threshold method using GRF, i.e., real-time classification of the standing and walking states is possible in the ANN model. The insole device used in the present study can be applied not only to gait analysis systems used in wearable robot operations, but also as a device for remotely monitoring the activities of daily living of the wearer. English Multidisciplinary Digital Publishing Institute (MDPI) Classification of Standing and Walking States Using Ground Reaction Forces Article 10.3390/s21062145 1 Sensors, v.21, no.6, pp.1 - 19 Sensors 21 6 1 19 Y scie scopus 000652715700001 2-s2.0-85102578001 Chemistry, Analytical Engineering, Electrical & Electronic Instruments & Instrumentation Chemistry Engineering Instruments & Instrumentation Article PHASE DETECTION GAIT EVENTS ACCELEROMETERS gait analysis wearable devices insole force sensing resistors ground reaction force center of pressure waveform length m-health activities of daily living