Farid Ghani

Papers

Total Citations

H-Index

About

Farid Ghani’s research lies at the intersection of neuroscience and assistive technology, focusing on non-invasive brain-computer interfaces (BCIs) and brain-machine interfaces (BMIs). His work aims to restore mobility and independence to individuals with neuromuscular disorders by translating neural signals into real-world actions. Ghani’s most cited study, “Detection of wrist movement using EEG signal for brain machine interface” (2013, 5 citations), explores how electroencephalographic (EEG) activity can decode wrist movements, offering a safer, non-invasive alternative to surgical implants like electrocorticography. In a related 2012 paper (2 citations), he demonstrated that simple time-domain statistical features—such as mean and variance—can effectively classify elbow movements from EEG data, enabling control of artificial actuators. These contributions highlight Ghani’s commitment to making assistive technologies more accessible and practical. While his citation counts are modest, his work addresses a critical gap in non-invasive BCI design, laying groundwork for affordable, user-friendly systems that could transform rehabilitation and daily living for patients with paralysis or motor impairments.