Evaluating the performance of a face movement based wheelchair control interface in an indoor environment

Abstract

This paper presents a novel facial movement based human machine interface for an intelligent wheelchair to operate in an indoor environment. Five random selected intact subjects are designated to control a wheelchair by using the proposed control interface. The testing is carried out in a designed indoor environment. The system performance is evaluated by implementing same tasks ten times, with the criteria of control easiness and the time spent on each task. The experimental result shows that this new control strategy can assist disabled and elderly users for hands-free control of an electric powered wheelchair.

Jaw-Operated Human Computer Interface Based on EEG Signals via Artificial Neural Networks

“…Converting the higher dimensional data (Xi) into a lower dimensional one (St) is carried out by PCA determining the eigenvalues and eigenvectors of the covariance matrix (C). The equations of PCA is shown in (3)(4)(5).…”

“…In their next work they introduced a new control way to detect facial movements by using facial image processing together with EMG signals. By using a route following an experimental setup, they evaluate the performance of an electrical wheelchair [4]. Wei and Hu reported that they developed their previous studies on EMG and image processing by creating software simulation environment to extract brain intentions and declared high performance [5].…”

Movement intention detection using neural network for quadriplegic assistive machine

“…There is specific position where the motor and sensory cortex relates to the certain parts of the body. Frontal lobe is vital for controlling thoughts, reasoning and behavior [15] and [16]. This part also called Broca area, apart from that this part also controls motor functions of human .…”

Yatay Çene Hareketlerinin EEG Üzerinde Oluşturduğu Yönelimsel Etkilerin Değerlendirilmesi

“…Bu yolla yapılmış olan çalışmalar engelli kişilerin hayatlarını kolaylaştırmayı amaçlamakta olup, bu kişiler için bir bilgisayar imlecini yada bilgisayarı kontrol etme, beyin sinyalleri sayesinde elektrikli sandalye kullanabilme veya bilgisayarlı heceleyiciler ile istenilen kelimelerin ekrana yazdırılması yada mekanik bir kolun kontrol edilebilmesi ve hatta sinirsel protez cihazlarının etkin kullanılabilmesi gibi avantajlar oluşturmakla birlikte, onların rehabilite olmalarını sağlamayı da hedeflemektedir. Bu tür çalışmaların nerdeyse hepsinde, elektromiyogram (EMG) ya da elektrookülogram (EOG) sinyallerinden faydalanıldığı (1)(2)(3)(4), bazılarının da elektroesefalogram (EEG) ve EMG sinyallerini birlikte kullandığı görülmektedir (5)(6)(7). Bu çalışma ile yalnızca EEG sinyali üzerinde oluşan sağ/ sol çene hareketlerinin biyoelektrik sinyaller üzerinden çıkarılması amaçlanmıştır.…”