AI Prediction of Brain Signals for Human Gait Using BCI Device and FBG Based Sensorial Platform for Plantar Pressure Measurements

Abstract

Artificial intelligence (AI) in developing modern solutions for biomedical problems such as the prediction of human gait for human rehabilitation is gaining ground. An attempt was made to use plantar pressure information through fiber Bragg grating (FBG) sensors mounted on an in-sole, in tandem with a brain-computer interface (BCI) device to predict brain signals corresponding to sitting, standing and walking postures of a person. Posture classification was attained with an accuracy range between 87–93% from FBG and BCI signals using machine learning models such as K-nearest neighbor (KNN), logistic regression (LR), support vector machine (SVM), and naïve Bayes (NB). These models were used to identify electrodes responding to sitting, standing and walking activities of four users from a 16 channel BCI device. Six electrode positions based on the 10–20 system for electroencephalography (EEG) were identified as the most sensitive to plantar activities and found to be consistent with clinical investigations of the sensorimotor cortex during foot movement. A prediction of brain EEG corresponding to given FBG data with lowest mean square error (MSE) values (0.065–0.109) was made with the selection of a long-short term memory (LSTM) machine learning model when compared to the recurrent neural network (RNN) and gated recurrent unit (GRU) models.

Translation, Cross-Cultural Adaptation, and Validation of the Foot Posture Index (FPI-6)—Italian Version

“…In a static position, observation of the loaded foot is a recurrent examination in medical offices and healthcare settings. The result of this observation is often unquantified, except when using generic terms, such as "flat foot" and "cavus foot", or when adding adjectives, such as "severe" or "mild", to describe the extent of the observed characteristics [27,28].…”

Prediction of Cognitive Load from Electroencephalography Signals Using Long Short-Term Memory Network

“…A typical BCI system utilizes data preprocessing processes to remove noise, extract features, and classify the data to reflect characteristics and extract meaningful data from unprocessed brainwaves [ 28 ]. The classified information may be used as an instruction for device control or provided to the user.…”

Design and analysis of a fiber Bragg grating‐based foot pressure assessment system

“…There was enough space to take various foot deformity disorders or foot fractures into consideration. Plantar pressure will vary for different types of insoles along with temperature elements [10]. Plantar pressure sensors also used in investigating the different types of walking activities and classifying them with machine learning algorithm methods.…”