M
Mohsin I. Tiwana
Researcher at University of the Sciences
Publications - 54
Citations - 1013
Mohsin I. Tiwana is an academic researcher from University of the Sciences. The author has contributed to research in topics: Computer science & Tactile sensor. The author has an hindex of 8, co-authored 44 publications receiving 739 citations. Previous affiliations of Mohsin I. Tiwana include National University of Sciences and Technology & College of Electrical and Mechanical Engineering.
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A review of tactile sensing technologies with applications in biomedical engineering
TL;DR: The importance of tactile sensor technology was recognized in the 1980s, along with a realization of the importance of computers and robotics, despite this awareness, tactile sensors failed to be strongly adopted in industrial or consumer markets as discussed by the authors.
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Characterization of a capacitive tactile shear sensor for application in robotic and upper limb prostheses
TL;DR: In this article, the authors presented a tactile sensor designed to measure shear forces, which is targeted for use in robotic and prosthetic hands, where haptic feedback or ability to detect the mechanical deflection of the sensor element is critical.
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Improving classification performance of four class FNIRS-BCI using Mel Frequency Cepstral Coefficients (MFCC)
Muhammad Saad Bin Abdul Ghaffar,Umar Shahbaz Khan,Umar Shahbaz Khan,Javed Iqbal,Javed Iqbal,Nasir Rashid,Nasir Rashid,Amir Hamza,Amir Hamza,Waqar S. Qureshi,Waqar S. Qureshi,Mohsin I. Tiwana,Mohsin I. Tiwana,U. Izhar +13 more
TL;DR: This study was able to compare, differentiate and distinguish the brain signal activities captured while performing four different tasks using three different classifiers i.e. Linear Discriminant Analysis, Support Vector Machine and K Nearest Neighbor.
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Advancements, Trends and Future Prospects of Lower Limb Prosthesis
Muhammad Asif,Mohsin I. Tiwana,Umar Shahbaz Khan,Waqar S. Qureshi,Javaid Iqbal,Nasir Rashid,Noman Naseer +6 more
TL;DR: In this article, the authors present a review of lower limb prosthesis; the main aspects from causes of amputation to the psycho-social impact of the amputees after using the prosthetic device.
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Artificial Immune System-Negative Selection Classification Algorithm (NSCA) for Four Class Electroencephalogram (EEG) Signals.
TL;DR: Electroencephalography signals for four distinct motor movements of human limbs are detected and classified using a negative selection classification algorithm (NSCA) using a widely studied open source EEG signal database.