Blar i TKD - Institutt for informasjonsteknologi på forfatter "Mirtaheri, Peyman"
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Analysis of human gait using hybrid EEG-fNIRS-based BCI system: A review
Khan, Haroon; Naseer, Noman; Yazidi, Anis; Eide, Per Kristian; Hassan, Wajahat; Mirtaheri, Peyman (Peer reviewed; Journal article, 2021)Human gait is a complex activity that requires high coordination between the central nervous system, the limb, and the musculoskeletal system. More research is needed to understand the latter coordination's complexity in ... -
Feasibility study of multi-wavelength optical probe to analyze magnesium implant degradation effects
Hassan, Hafiz Wajahat; Mathew, Anna; Khan, Haroon; Korostynska, Olga; Mirtaheri, Peyman (Proceedings of IEEE Sensors;, Chapter, 2021)Near-infrared spectroscopy (NIRS) is a rapidly developing and promising technology with potential for spectrographic analysis. Understanding NIRS measurements on the implant-tissue interface for hydrogen gas formation as ... -
Single-leg stance on a challenging surface can enhance cortical activation in the right hemisphere – A case study
Khan, Haroon; Qureshi, Nauman Khalid; Yazidi, Anis; Engell, Håvard; Mirtaheri, Peyman (Peer reviewed; Journal article, 2023)Maintaining body balance, whether static or dynamic, is critical in performing everyday activities and developing and optimizing basic motor skills. This study investigates how a professional alpine skier’s brain activates ... -
Solving the Grand Challenges Together: A Brazil-Norway Approach to Teaching Collaborative Design and Prototyping of Assistive Technologies and Products for Independent Living
Sandnes, Frode Eika; Medola, Fausto Orsi; Berg, Arild; Rodrigues, Osmar Vicente; Mirtaheri, Peyman; Gjøvaag, Terje (Chapter; Peer reviewed, 2017)This paper describes the roadmap for a long term strategic internationalization project involving two key higher education institutions in Norway and Brazil. The project involves six different yet related ... -
Unleashing the potential of fNIRS with machine learning: classification of fine anatomical movements to empower future brain-computer interface
Khan, Haroon; Khadka, Rabindra; Sultan, Malik Shahid; Yazidi, Anis; Ombao, Hernando; Mirtaheri, Peyman (Peer reviewed; Journal article, 2024)In this study, we explore the potential of using functional near-infrared spectroscopy (fNIRS) signals in conjunction with modern machine-learning techniques to classify specific anatomical movements to increase the number ...